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"),(0,n.kt)("p",null,(0,n.kt)("em",{parentName:"p"},"Neurosynth Compose")," provides a streamlined workflow to facilitate study selection and\ndata extraction. You can then easily specify a meta-analysis and execute it in the cloud,\nrapidly generating results that you can inspect and share."),(0,n.kt)("admonition",{type:"tip"},(0,n.kt)("p",{parentName:"admonition"},"We will perform a slimmed down replication of the following meta-analysis:\n",(0,n.kt)("a",{parentName:"p",href:"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4494985/"},"Neurobiological impact of nicotinic acetylcholine receptor agonists: An ALE meta-analysis of pharmacological neuroimaging studies"),"."),(0,n.kt)("p",{parentName:"admonition"},"For more guidance on how to choose a topic for meta-analysis, see the ",(0,n.kt)("a",{parentName:"p",href:"https://www.bmj.com/content/372/bmj.n71"},"PRISMA statement")," and the ",(0,n.kt)("a",{parentName:"p",href:"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5918306/"},"10 simple rules for neuroimaging meta-analyses"),".")),(0,n.kt)("h2",{id:"creating-a-new-project"},"Creating a new Project"),(0,n.kt)("p",null,(0,n.kt)("em",{parentName:"p"},"Projects")," contain all the Steps necessary to create a new meta-analysis in Neurosynth Compose.\nWe'll step through this process in detail."),(0,n.kt)("p",null,"To get started, ",(0,n.kt)("em",{parentName:"p"},"sign in"),", and select ",(0,n.kt)("strong",{parentName:"p"},"New Project"),". "),(0,n.kt)("p",null,"You'll now see the Project page, showing the three stages of a meta-analysis:\n",(0,n.kt)("strong",{parentName:"p"},"Search & Curate, Extract & Annotate")," and ",(0,n.kt)("strong",{parentName:"p"},"Specify Meta-Analyses"),"."),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"New Project",src:a(4819).Z,width:"1557",height:"501"}),". "),(0,n.kt)("h2",{id:"search--curate"},"Search & Curate"),(0,n.kt)("p",null,"The first step in a meta-analysis is to ",(0,n.kt)("em",{parentName:"p"},"Search")," for studies, and ",(0,n.kt)("em",{parentName:"p"},"Curate")," these studies into a\nfinal ",(0,n.kt)("em",{parentName:"p"},"StudySet")," that contains the studies we want to include in a Meta-Analysis."),(0,n.kt)("p",null,"To get started, we must choose a Curation workflow. There are three options: Simple, PRISMA and Custom. The main difference between these options is the number of review steps involved in creating a final list of studies. ",(0,n.kt)("strong",{parentName:"p"},'For a rigorous Manual Meta-Analysis, select "PRISMA".')),(0,n.kt)("admonition",{type:"tip"},(0,n.kt)("p",{parentName:"admonition"},"Reviewers typically require Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting\nfor gold-standard meta-analyses. The PRISMA guidelines ensure a systematic selection and reporting process.\nHowever, a Simple workflow may be useful for exploratory and automated meta-analyses. ")),(0,n.kt)("p",null,"Next, you will be presented with the Curation board, consisting of four columns representing\nthe steps of a PRISMA workflow:"),(0,n.kt)("ul",null,(0,n.kt)("li",{parentName:"ul"},(0,n.kt)("p",{parentName:"li"},(0,n.kt)("strong",{parentName:"p"},"Identification"),": Remove duplicate studies")),(0,n.kt)("li",{parentName:"ul"},(0,n.kt)("p",{parentName:"li"},(0,n.kt)("strong",{parentName:"p"},"Screening"),": Remove irrelevant studies")),(0,n.kt)("li",{parentName:"ul"},(0,n.kt)("p",{parentName:"li"},(0,n.kt)("strong",{parentName:"p"},"Elibility"),": Remove studies that do not meet inclusion criteria or do not have retrievable information")),(0,n.kt)("li",{parentName:"ul"},(0,n.kt)("p",{parentName:"li"},(0,n.kt)("strong",{parentName:"p"},"Included"),": Double check the studies and view which studies will be included in the meta-analysis"))),(0,n.kt)("p",null,"The overall goal is to go from a large number of studies from a broad search results, to only the\nstudies that are relevant to your research question. These steps should be completed in order!"),(0,n.kt)("h3",{id:"importing-studies"},"Importing studies"),(0,n.kt)("p",null,"But first, we must add studies to our Project. Click the ",(0,n.kt)("strong",{parentName:"p"},"Import Studies")," button. "),(0,n.kt)("p",null,"You can search for studies within the ",(0,n.kt)("em",{parentName:"p"},"NeuroStore")," database\u2014which we maintain and indexes over 20,000 pre-processed neuroimaging studies\u2014or from external sources, such as PubMed or a Ciation manager file. "),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"Import Studies",src:a(3569).Z,width:"622",height:"238"}),". "),(0,n.kt)("p",null,(0,n.kt)("em",{parentName:"p"},"Import via NeuroStore")," is simpler and faster, as these studies already exist on in our system\nand have pre-extracted imaging data (e.g. coordinates).\nAs a result, there will be fewer irrelevant studies to exclude, and less data extraction to complete."),(0,n.kt)("p",null,"However, ",(0,n.kt)("em",{parentName:"p"},"searching other sources")," is often recommended for a comprehensive literature search, as a single source can never index all possible studies."),(0,n.kt)("p",null,"To replicate the Nicotine meta-analysis, we will replicate the author's PubMed search."),(0,n.kt)("admonition",{type:"info"},(0,n.kt)("p",{parentName:"admonition"},"Searching NeuroStore is a valid option for a manual meta-analysis to balance rigor and efficiency. To learn more, see the ",(0,n.kt)("a",{parentName:"p",href:"/compose-docs/tutorial/automated"},"Automated Meta-Analysis tutorial"),". ")),(0,n.kt)("h4",{id:"searching-pubmed"},"Searching PubMed"),(0,n.kt)("p",null,"We can export any PubMed search result to file, and import that file into Neurosynth Compose.\nIn this example, we perform the following search which in the ",(0,n.kt)("a",{parentName:"p",href:"https://pubmed.ncbi.nlm.nih.gov/"},"PubMed")," search field:"),(0,n.kt)("pre",null,(0,n.kt)("code",{parentName:"pre"},'("fMRI" OR "PET" OR "neuroimaging" OR "Functional magnetic resonance imaging" OR "functional MRI") \nAND ("nicotine" OR "cigarette" OR "smok*" OR "DMXB-A")\n')),(0,n.kt)("p",null,"This results in over 3,000 studies that are potentially relevant for this meta-analysis."),(0,n.kt)("p",null,"Next, we save the results to ",(0,n.kt)("inlineCode",{parentName:"p"},"PMID")," format, with a PubMed ID on each line."),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"Download PubMed",src:a(6652).Z,width:"1053",height:"475"})),(0,n.kt)("admonition",{type:"info"},(0,n.kt)("p",{parentName:"admonition"},"Reviewing 3,000 studies can take a long time!\nOnly a small percentage of these studies will meet all inclusion criteria. For the sake of the tutorial, we provide a shortened list of ",(0,n.kt)(o.aBF,{size:20,mdxType:"FaDownload"})," ",(0,n.kt)("a",{target:"_blank",href:a(7555).Z},"PUBMED IDS"),".")),(0,n.kt)("p",null,"We can import this file into our Project by clicking ",(0,n.kt)("strong",{parentName:"p"},"Upload File"),". Give this import a name for future reference.\nAll studies imported from this search will be ",(0,n.kt)("strong",{parentName:"p"},"Tagged")," with the search name. "),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"Import name",src:a(212).Z,width:"1282",height:"354"})),(0,n.kt)("h3",{id:"identification"},"Identification"),(0,n.kt)("p",null,"All the imported studies are now visible in the first column of our PRISMA curation board. "),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"Identification",src:a(8665).Z,width:"3595",height:"939"})),(0,n.kt)("p",null,"The purpose ",(0,n.kt)("strong",{parentName:"p"},"Identification")," is to find ",(0,n.kt)("em",{parentName:"p"},"duplicate studies"),", which is common when importing from multiple sources.\n",(0,n.kt)("em",{parentName:"p"},"Neurosynth Compose")," will automatically find potential duplicates (based on the Title, DOI, and PMID).\nHowever, you can also manually review studies to identify any duplicates we might have missed."),(0,n.kt)("p",null,"To review studies, click on the ",(0,n.kt)("strong",{parentName:"p"},"Identification"),' column header, or an individual study.\nFor each study, you can choose to "Promote" it to the next phase, "Exclude" as a duplicate, or flag for later review.'),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"Identification review",src:a(3615).Z,width:"2251",height:"1211"})),(0,n.kt)("admonition",{type:"tip"},(0,n.kt)("p",{parentName:"admonition"},"To remain PRISMA compliant, you should only exclude studies for being a duplicate in the Identification step.")),(0,n.kt)("p",null,"In this example, there are no duplicates. To quickly advance, click ",(0,n.kt)("strong",{parentName:"p"},"Promote All Uncategorized Studies")," under ",(0,n.kt)("em",{parentName:"p"},"Identification"),"."),(0,n.kt)("h3",{id:"screening"},"Screening"),(0,n.kt)("p",null,"The goal of ",(0,n.kt)("em",{parentName:"p"},"Screening")," is to determine if imported studies are relevant to your research question, based on the the Tile\nand Abstract of each."),(0,n.kt)("p",null,"To begin, click on the Screening column header from the main Curation board. The interface is\nidentical to the previous phase, except the default Exclusion reason is now ",(0,n.kt)("strong",{parentName:"p"},"irrelevant"),". "),(0,n.kt)("p",null,"Go ahead and review all 13 studies to determine if they are relevant to the topic of ",(0,n.kt)("em",{parentName:"p"},'"Nicotime administration'),'".\nAny studies that are not relevant will remain in this column and not advance.'),(0,n.kt)("h3",{id:"eligibility"},"Eligibility"),(0,n.kt)("p",null,"The goal ",(0,n.kt)("em",{parentName:"p"},"Eligibility")," is to determine studies meet the eligibility criteria of your meta-analysis.\nYou will need to read the ",(0,n.kt)("strong",{parentName:"p"},"full text")," to make this determination. "),(0,n.kt)("admonition",{type:"note"},(0,n.kt)("p",{parentName:"admonition"},"The eligibility criteria depends on your research question!\nThis is where your expertise is most necessary, in order to create an interesting research question,\nand filter studies accordingly. The results of this step depends on the researcher, and there may be reasonable scientific disagrements.")),(0,n.kt)("p",null,'To begin, click on the "Eligibility" column header, or a study, as before.'),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"Custom Eligibility",src:a(940).Z,width:"2341",height:"1449"})),(0,n.kt)("p",null,"For this example, we will include studies that meet these criteria:"),(0,n.kt)("pre",null,(0,n.kt)("code",{parentName:"pre"},"* fMRI or PET\n* Reported brain activity in stereotaxic coordinates (Talairach or MNI space)\n* Reported a set of coordinates (i.e., foci) from a within-subjects or between-subjects contrast assessing the effects of nAChR agonist administration (i.e., pharmacological administration or cigarette smoking) relative to a baseline condition (i.e., placebo administration or smoking-abstinence condition)\n* Examined brain activity using a cognitive or affective task paradigm or at rest. \n* Studies examining functional connectivity, brain morphology, or neurochemistry are excluded.\n")),(0,n.kt)("p",null,"For this tutorial, go ahead and review all studies in this column, and Promote relevant studies to the next phase."),(0,n.kt)("admonition",{type:"tip"},(0,n.kt)("p",{parentName:"admonition"},"Given that this phase is more open-ended, there is no default Exclusion reason. We provide four default options for you, and\nyou may define custom Exclusion reasons if you see fit.")),(0,n.kt)("admonition",{type:"tip"},(0,n.kt)("p",{parentName:"admonition"},'For open source studies, we will link to the article full text (PDF). If not available, click\n"view article link" to view article\'s PubMed page, and access the full text using your credentials.')),(0,n.kt)("h3",{id:"included"},"Included"),(0,n.kt)("p",null,"Congratulations! Once you have reviewed all studies, you should have a set of studies that you want to include in your meta-analysis. "),(0,n.kt)("p",null,"At this point, you can review this final list, and view a PRISMA diagram visually outlining your review process:"),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"PRISMA",src:a(8718).Z,width:"1714",height:"1448"})),(0,n.kt)("p",null,"To finish ",(0,n.kt)("em",{parentName:"p"},"Curation"),", and create a final StudySet, click ",(0,n.kt)("em",{parentName:"p"},"Move on to Extraction")," at the top right. "),(0,n.kt)("h2",{id:"extract-and-annotation"},"Extract and Annotation"),(0,n.kt)("p",null,"The goal of this phase is to ",(0,n.kt)("strong",{parentName:"p"},"extract data")," from the text of studies (such as coordinates)\nthat will be used in the meta-analysis. You will also want to ",(0,n.kt)("strong",{parentName:"p"},"annotate")," relevant Study meta-data.\nMost commonly, for each Study you will designate which Analyses (i.e. Contrasts) to included in your meta-analysis."),(0,n.kt)("admonition",{type:"tip"},(0,n.kt)("p",{parentName:"admonition"},"Studies that are already indexed by NeuroStore will have automatically extracted data (such as coordinates)\nsaving you a lot of time and effort. However, you may want to verify and improve this information.")),(0,n.kt)("h3",{id:"ingestion"},"Ingestion"),(0,n.kt)("p",null,"But first, we must create a StudySet containing your studies! "),(0,n.kt)("p",null,"New studies not in the NeuroStore database will be created, and studies that match existing studies will be added to a newly created StudySet."),(0,n.kt)("admonition",{type:"info"},(0,n.kt)("p",{parentName:"admonition"},"Studies in NeuroStore have multiple Versions, including those created by other users, as well as the original copy."),(0,n.kt)("p",{parentName:"admonition"},"If you ingest a study that is already indexed in the database, we will match to the newest possible Version, by default.\nIdeally, this will be a Version that another user has already improved, saving you even more time!"),(0,n.kt)("p",{parentName:"admonition"},"You can switch Study Versions at anytime (including to the original automate copy) by clicking ",(0,n.kt)("em",{parentName:"p"},"Switch Study Version")," at the bottom\nof Study's page. Any edits you make will automatically be saved as a new Version.")),(0,n.kt)("h3",{id:"editing-studies"},"Editing studies"),(0,n.kt)("p",null,"Once your StudySet is created, it's time to edit studies. You will see a list of your studies:"),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"Extraction",src:a(9774).Z,width:"1655",height:"799"})),(0,n.kt)("p",null,"Click on any Study to edit:"),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"Extraction study view",src:a(5362).Z,width:"2418",height:"856"})),(0,n.kt)("h4",{id:"analysis-data"},"Analysis Data"),(0,n.kt)("p",null,"Let's start by editing a Study's Analyses."),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"Extraction study view",src:a(369).Z,width:"2128",height:"923"})),(0,n.kt)("admonition",{type:"info"},(0,n.kt)("p",{parentName:"admonition"},(0,n.kt)("em",{parentName:"p"},"Analyses"),' are groups of images or coordinates reported in a given study fir a specific analysis. This is often referred to as "Contrasts", but we use the more general term "Analyses" to accomodate a wider range of fMRI models. ')),(0,n.kt)("p",null,"For new studies, we will not have any data, and it is necessary to manually enter these data from the text of a study.\nWe can create a new Analysis for each group of Coordinates, and input the data from the text:"),(0,n.kt)("p",null,"For studies already indexed by NeuroStore, we will already have pre-extracted Coordinates. You can use this same interface to verify and correct these data. "),(0,n.kt)("admonition",{type:"caution"},(0,n.kt)("p",{parentName:"admonition"},"Automatically extracted coordinates can contain a number of errors. Mostly commonly, several distinct Analyses (i.e. contrasts), will get grouped into a single Analyses. You will want to create new Analyses to split up the Coordinates into distinct units. "),(0,n.kt)("p",{parentName:"admonition"},"Another common error is that Analyses are duplicated, meaning you may want to delete extra Analyses. ")),(0,n.kt)("admonition",{type:"tip"},(0,n.kt)("p",{parentName:"admonition"},"You can copy and paste coordinates from Microsoft Excel or Google Sheets.")),(0,n.kt)("h4",{id:"annotations"},"Annotations"),(0,n.kt)("p",null,"A key goal of the Extraction phase, is to add Annotations that can help us distinguish Analyses, and include/exclude specific Analyses from a meta-analysis. Annotations are simply columns of data with a value for all Analyses within a StudySet."),(0,n.kt)("p",null,"Annotations can be explained as a way to categorize analyses within each study. For example, they can be categorized by task (e.g., Stroop, N-back, etc.), by modality (e.g., fMRI, PET, etc.), or by any other category that you want to use to filter the analyses. "),(0,n.kt)("admonition",{type:"tip"},(0,n.kt)("p",{parentName:"admonition"},'By default, a single Annotation called "included" is created, which includes all Analyses.\nYou can modify this Annotation to select the relevant Analyses of interest to your research question')),(0,n.kt)("p",null,"For this replication, we are interested in the effects of nAChR agonists on the brain, which can either be excitatory or inhibitory, so we add both an \u201cactivation\u201d and \u201cdeactivation\u201d column. "),(0,n.kt)("p",null,'First create an Annotation. From the main Extraction page, click "View Annoations" on the top right. Here you can view all annotations and the value for each Analyses, as well as create new Annotations. You can choose the data type of each column as either a Number, String, or Boolean. Selected a Boolean data type for the \u201cactivation\u201d and \u201cdeactivation\u201d columns, which will allow you to filter the analyses by whether they are excitatory or inhibitory. By default you will have an \u201cinclude\u201d column to help get you started.'),(0,n.kt)("p",null,'Below, I am creating a new Annotation for "deactivations"'),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"annotation for a study",src:a(8669).Z,width:"1795",height:"758"})),(0,n.kt)("p",null,'Now, when I look at a study, I can edit the value for Analyses, assigning each group of coordinates as "activations" or "deactivations":'),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"annotation for a study",src:a(4235).Z,width:"850",height:"128"})),(0,n.kt)("h2",{id:"meta-analysis-specification"},"Meta-analysis specification"),(0,n.kt)("p",null,"You are finally ready to specify a meta-analysis! "),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"start meta-analysis specification",src:a(234).Z,width:"834",height:"308"})),(0,n.kt)("p",null,"After clicking ",(0,n.kt)("strong",{parentName:"p"},'"+ Meta-Analysis Specification"'),", you'll see the following dialog:"),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"Meta-analysis wizard",src:a(588).Z,width:"1762",height:"1014"})),(0,n.kt)("p",null,'For each Meta-Analysis, you will select an Annotation to filter the Analyses to include.\nRemember, by default, the "included" column will be created and include ',(0,n.kt)("em",{parentName:"p"},"all")," Analyses. "),(0,n.kt)("p",null,"Next, you will ",(0,n.kt)("strong",{parentName:"p"},"select a meta-analysis Algorithm and Corrector"),":"),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"Meta-analysis algorithm",src:a(3556).Z,width:"1762",height:"1014"})),(0,n.kt)("p",null,'A variety of common meta-analysis algirithms such as "ALE" and "MKDA" are available, as well as two\nstrategies for controling for multiple comparisons: FDR (false detection rate) and FWE (family wise error).'),(0,n.kt)("p",null,'For this example, we\'ll choose "MKDADensity" and and "FDRCorrection". You can modify the parameters for each, if you want,\nbut we provide sane defaults for all. '),(0,n.kt)("admonition",{type:"tip"},(0,n.kt)("p",{parentName:"admonition"},"Learn more about meta-analysis algorithms in the ",(0,n.kt)("a",{parentName:"p",href:"https://nimare.readthedocs.io/en/stable/index.html"},"NiMARE Documentation"))),(0,n.kt)("p",null,"Next, you'll give your meta-analysis a name, and review the details of your specification. "),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"Meta-analysis review",src:a(7832).Z,width:"1771",height:"1575"})),(0,n.kt)("admonition",{type:"tip"},(0,n.kt)("p",{parentName:"admonition"},"You can define multiple Meta-Analysis specifications in a Project, paired to the same StudySet")),(0,n.kt)("h2",{id:"run-your-meta-analysis"},"Run your meta-analysis!"),(0,n.kt)("p",null,"Congratulations! You now have a Meta-Analysis specification that is ready to run."),(0,n.kt)("p",null,"You can execute your Meta-Analysis for free in the cloud on Google Colab by copying the unique ",(0,n.kt)("em",{parentName:"p"},"meta-analysis id"),"\nand pasting it into our Google Colab notebook."),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"Meta-analysis run",src:a(3349).Z,width:"2994",height:"1030"})))}m.isMDXComponent=!0},7555:(e,t,a)=>{a.d(t,{Z:()=>i});const i=a.p+"assets/files/tutorial_pmids-434d072c0087956ffdef61013ba6d0da.txt"},369:(e,t,a)=>{a.d(t,{Z:()=>i});const i=a.p+"assets/images/add_coordinates-8bea486d4904648bcafa7ea0aa3ccf05.png"},5362:(e,t,a)=>{a.d(t,{Z:()=>i});const i=a.p+"assets/images/annotate_and_extract_study-ca3e4d3930ebf9dc60ad23185a36eefc.png"},8669:(e,t,a)=>{a.d(t,{Z:()=>i});const i=a.p+"assets/images/annotation_create-1b42a849c3fa25379a4492e899c883bd.png"},4235:(e,t,a)=>{a.d(t,{Z:()=>i});const i=a.p+"assets/images/annotation_view-bb152fb9777b96fa48ecf95ada750d97.png"},940:(e,t,a)=>{a.d(t,{Z:()=>i});const i=a.p+"assets/images/custom_exclusion-16ad73f8fbab6041651f04bf3deb4f80.png"},6652:(e,t,a)=>{a.d(t,{Z:()=>i});const i=a.p+"assets/images/download_search_results-d5ec087db9b8527d9891715d987540a0.png"},9774:(e,t,a)=>{a.d(t,{Z:()=>i});const i=a.p+"assets/images/extraction_and_annotation-3f2588aa81794ea975ca13e54b3ae968.png"},8665:(e,t,a)=>{a.d(t,{Z:()=>i});const i=a.p+"assets/images/identification-7f834ceb21aa8027ee29b527ead7700d.png"},3615:(e,t,a)=>{a.d(t,{Z:()=>i});const i=a.p+"assets/images/identification_review-95da15912e8e3b0ecd45612d88ce8ae7.png"},212:(e,t,a)=>{a.d(t,{Z:()=>i});const i=a.p+"assets/images/import_name-47b2b52fb0476898def227448666b9c9.png"},3569:(e,t,a)=>{a.d(t,{Z:()=>i});const i=a.p+"assets/images/import_studies_options-d58951af444810f76b35e77050c7deb4.png"},3556:(e,t,a)=>{a.d(t,{Z:()=>i});const i=a.p+"assets/images/ma_algorithm-76b551077f36af384173d025dd8d39cb.png"},7832:(e,t,a)=>{a.d(t,{Z:()=>i});const i=a.p+"assets/images/ma_review-dca9072320631a4c2b7bd8a3939763bf.png"},3349:(e,t,a)=>{a.d(t,{Z:()=>i});const i=a.p+"assets/images/ma_run-21ff60898e902524975d8fc965d4a08c.png"},588:(e,t,a)=>{a.d(t,{Z:()=>i});const i=a.p+"assets/images/ma_wizard-94f17423e2d4a4df7e23f88cb26c4595.png"},4819:(e,t,a)=>{a.d(t,{Z:()=>i});const i=a.p+"assets/images/new_project_view-865234e6c83825dde8320121d1d9c773.png"},8718:(e,t,a)=>{a.d(t,{Z:()=>i});const i=a.p+"assets/images/prisma_diagram-399aba8441e1b00d3ffb3cdc7b5c6d9c.png"},234:(e,t,a)=>{a.d(t,{Z:()=>i});const i=a.p+"assets/images/proceed_meta_analysis-ccd673905b3f5425823cc947b282bd48.png"}}]); \ No newline at end of file diff --git a/assets/js/2367c334.2e68a327.js b/assets/js/2367c334.2e68a327.js new file mode 100644 index 0000000..d9d6d20 --- /dev/null +++ b/assets/js/2367c334.2e68a327.js @@ -0,0 +1 @@ +"use strict";(self.webpackChunkns_compose_docs=self.webpackChunkns_compose_docs||[]).push([[7068],{4894:(e,t,a)=>{a.r(t),a.d(t,{assets:()=>d,contentTitle:()=>r,default:()=>m,frontMatter:()=>s,metadata:()=>l,toc:()=>c});var i=a(7462),n=(a(7294),a(3905)),o=a(5154);const s={sidebar_label:"Manual Meta-Analysis",sidebar_position:2},r="Manual Meta-Analysis",l={unversionedId:"tutorial/manual",id:"tutorial/manual",title:"Manual Meta-Analysis",description:"This is a condensed adaptation of a course taught at OHBM 2023.",source:"@site/docs/tutorial/manual.md",sourceDirName:"tutorial",slug:"/tutorial/manual",permalink:"/compose-docs/tutorial/manual",draft:!1,editUrl:"https://github.com/neurostuff/compose-docs/edit/master/docs/tutorial/manual.md",tags:[],version:"current",lastUpdatedBy:"Alejandro de la Vega",lastUpdatedAt:1701130832,formattedLastUpdatedAt:"Nov 28, 2023",sidebarPosition:2,frontMatter:{sidebar_label:"Manual Meta-Analysis",sidebar_position:2},sidebar:"tutorialSidebar",previous:{title:"Tutorials",permalink:"/compose-docs/tutorial/"},next:{title:"Automated Meta-Analysis",permalink:"/compose-docs/tutorial/automated"}},d={},c=[{value:"Creating a new Project",id:"creating-a-new-project",level:2},{value:"Search & Curate",id:"search--curate",level:2},{value:"Importing studies",id:"importing-studies",level:3},{value:"Searching PubMed",id:"searching-pubmed",level:4},{value:"Identification",id:"identification",level:3},{value:"Screening",id:"screening",level:3},{value:"Eligibility",id:"eligibility",level:3},{value:"Included",id:"included",level:3},{value:"Extract and Annotation",id:"extract-and-annotation",level:2},{value:"Ingestion",id:"ingestion",level:3},{value:"Editing studies",id:"editing-studies",level:3},{value:"Analysis Data",id:"analysis-data",level:4},{value:"Annotations",id:"annotations",level:4},{value:"Meta-analysis specification",id:"meta-analysis-specification",level:2},{value:"Run your meta-analysis!",id:"run-your-meta-analysis",level:2}],u={toc:c},p="wrapper";function m(e){let{components:t,...s}=e;return(0,n.kt)(p,(0,i.Z)({},u,s,{components:t,mdxType:"MDXLayout"}),(0,n.kt)("h1",{id:"manual-meta-analysis"},"Manual Meta-Analysis"),(0,n.kt)("admonition",{type:"info"},(0,n.kt)("p",{parentName:"admonition"},"This is a condensed adaptation of a course taught at OHBM 2023.\nSee the ",(0,n.kt)("a",{parentName:"p",href:"https://neurostuff.github.io/meta-analysis-book/ohbm_course_intro.html"},"course materials")," for a complete overview.")),(0,n.kt)("p",null,"In this tutorial, we demonstrate how to create a custom, manual meta-analysis. "),(0,n.kt)("p",null,(0,n.kt)("em",{parentName:"p"},"Neurosynth Compose")," provides a streamlined workflow to facilitate study selection and\ndata extraction. You can then easily specify a meta-analysis and execute it in the cloud,\nrapidly generating results that you can inspect and share."),(0,n.kt)("admonition",{type:"tip"},(0,n.kt)("p",{parentName:"admonition"},"We will perform a slimmed down replication of the following meta-analysis:\n",(0,n.kt)("a",{parentName:"p",href:"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4494985/"},"Neurobiological impact of nicotinic acetylcholine receptor agonists: An ALE meta-analysis of pharmacological neuroimaging studies"),"."),(0,n.kt)("p",{parentName:"admonition"},"For more guidance on how to choose a topic for meta-analysis, see the ",(0,n.kt)("a",{parentName:"p",href:"https://www.bmj.com/content/372/bmj.n71"},"PRISMA statement")," and the ",(0,n.kt)("a",{parentName:"p",href:"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5918306/"},"10 simple rules for neuroimaging meta-analyses"),".")),(0,n.kt)("h2",{id:"creating-a-new-project"},"Creating a new Project"),(0,n.kt)("p",null,(0,n.kt)("em",{parentName:"p"},"Projects")," contain all the Steps necessary to create a new meta-analysis in Neurosynth Compose.\nWe'll step through this process in detail."),(0,n.kt)("p",null,"To get started, ",(0,n.kt)("em",{parentName:"p"},"sign in"),", and select ",(0,n.kt)("strong",{parentName:"p"},"New Project"),". "),(0,n.kt)("p",null,"You'll now see the Project page, showing the three stages of a meta-analysis:\n",(0,n.kt)("strong",{parentName:"p"},"Search & Curate, Extract & Annotate")," and ",(0,n.kt)("strong",{parentName:"p"},"Specify Meta-Analyses"),"."),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"New Project",src:a(4819).Z,width:"1557",height:"501"}),". "),(0,n.kt)("h2",{id:"search--curate"},"Search & Curate"),(0,n.kt)("p",null,"The first step in a meta-analysis is to ",(0,n.kt)("em",{parentName:"p"},"Search")," for studies, and ",(0,n.kt)("em",{parentName:"p"},"Curate")," these studies into a\nfinal ",(0,n.kt)("em",{parentName:"p"},"StudySet")," that contains the studies we want to include in a Meta-Analysis."),(0,n.kt)("p",null,"To get started, we must choose a Curation workflow. There are three options: Simple, PRISMA and Custom. The main difference between these options is the number of review steps involved in creating a final list of studies. ",(0,n.kt)("strong",{parentName:"p"},'For a rigorous Manual Meta-Analysis, select "PRISMA".')),(0,n.kt)("admonition",{type:"tip"},(0,n.kt)("p",{parentName:"admonition"},"Reviewers typically require Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting\nfor gold-standard meta-analyses. The PRISMA guidelines ensure a systematic selection and reporting process.\nHowever, a Simple workflow may be useful for exploratory and automated meta-analyses. ")),(0,n.kt)("p",null,"Next, you will be presented with the Curation board, consisting of four columns representing\nthe steps of a PRISMA workflow:"),(0,n.kt)("ul",null,(0,n.kt)("li",{parentName:"ul"},(0,n.kt)("p",{parentName:"li"},(0,n.kt)("strong",{parentName:"p"},"Identification"),": Remove duplicate studies")),(0,n.kt)("li",{parentName:"ul"},(0,n.kt)("p",{parentName:"li"},(0,n.kt)("strong",{parentName:"p"},"Screening"),": Remove irrelevant studies")),(0,n.kt)("li",{parentName:"ul"},(0,n.kt)("p",{parentName:"li"},(0,n.kt)("strong",{parentName:"p"},"Elibility"),": Remove studies that do not meet inclusion criteria or do not have retrievable information")),(0,n.kt)("li",{parentName:"ul"},(0,n.kt)("p",{parentName:"li"},(0,n.kt)("strong",{parentName:"p"},"Included"),": Double check the studies and view which studies will be included in the meta-analysis"))),(0,n.kt)("p",null,"The overall goal is to go from a large number of studies from a broad search results, to only the\nstudies that are relevant to your research question. These steps should be completed in order!"),(0,n.kt)("h3",{id:"importing-studies"},"Importing studies"),(0,n.kt)("p",null,"But first, we must add studies to our Project. Click the ",(0,n.kt)("strong",{parentName:"p"},"Import Studies")," button. "),(0,n.kt)("p",null,"You can search for studies within the ",(0,n.kt)("em",{parentName:"p"},"NeuroStore")," database\u2014which we maintain and indexes over 20,000 pre-processed neuroimaging studies\u2014or from external sources, such as PubMed or a Citation manager file. "),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"Import Studies",src:a(3569).Z,width:"622",height:"238"}),". "),(0,n.kt)("p",null,(0,n.kt)("em",{parentName:"p"},"Import via NeuroStore")," is simpler and faster, as these studies already exist on in our system\nand have pre-extracted imaging data (e.g. coordinates).\nAs a result, there will be fewer irrelevant studies to exclude, and less data extraction to complete."),(0,n.kt)("p",null,"However, ",(0,n.kt)("em",{parentName:"p"},"searching other sources")," is often recommended for a comprehensive literature search, as a single source can never index all possible studies."),(0,n.kt)("p",null,"To replicate the Nicotine meta-analysis, we will replicate the author's PubMed search."),(0,n.kt)("admonition",{type:"info"},(0,n.kt)("p",{parentName:"admonition"},"Searching NeuroStore is a valid option for a manual meta-analysis to balance rigor and efficiency. To learn more, see the ",(0,n.kt)("a",{parentName:"p",href:"/compose-docs/tutorial/automated"},"Automated Meta-Analysis tutorial"),". ")),(0,n.kt)("h4",{id:"searching-pubmed"},"Searching PubMed"),(0,n.kt)("p",null,"We can export any PubMed search result to file, and import that file into Neurosynth Compose.\nIn this example, we perform the following search which in the ",(0,n.kt)("a",{parentName:"p",href:"https://pubmed.ncbi.nlm.nih.gov/"},"PubMed")," search field:"),(0,n.kt)("pre",null,(0,n.kt)("code",{parentName:"pre"},'("fMRI" OR "PET" OR "neuroimaging" OR "Functional magnetic resonance imaging" OR "functional MRI") \nAND ("nicotine" OR "cigarette" OR "smok*" OR "DMXB-A")\n')),(0,n.kt)("p",null,"This results in over 3,000 studies that are potentially relevant for this meta-analysis."),(0,n.kt)("p",null,"Next, we save the results to ",(0,n.kt)("inlineCode",{parentName:"p"},"PMID")," format, with a PubMed ID on each line."),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"Download PubMed",src:a(6652).Z,width:"1053",height:"475"})),(0,n.kt)("admonition",{type:"info"},(0,n.kt)("p",{parentName:"admonition"},"Reviewing 3,000 studies can take a long time!\nOnly a small percentage of these studies will meet all inclusion criteria. For the sake of the tutorial, we provide a shortened list of ",(0,n.kt)(o.aBF,{size:20,mdxType:"FaDownload"})," ",(0,n.kt)("a",{target:"_blank",href:a(7555).Z},"PUBMED IDS"),".")),(0,n.kt)("p",null,"We can import this file into our Project by clicking ",(0,n.kt)("strong",{parentName:"p"},"Upload File"),". Give this import a name for future reference.\nAll studies imported from this search will be ",(0,n.kt)("strong",{parentName:"p"},"Tagged")," with the search name. "),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"Import name",src:a(212).Z,width:"1282",height:"354"})),(0,n.kt)("h3",{id:"identification"},"Identification"),(0,n.kt)("p",null,"All the imported studies are now visible in the first column of our PRISMA curation board. "),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"Identification",src:a(8665).Z,width:"3595",height:"939"})),(0,n.kt)("p",null,"The purpose ",(0,n.kt)("strong",{parentName:"p"},"Identification")," is to find ",(0,n.kt)("em",{parentName:"p"},"duplicate studies"),", which is common when importing from multiple sources.\n",(0,n.kt)("em",{parentName:"p"},"Neurosynth Compose")," will automatically find potential duplicates (based on the Title, DOI, and PMID).\nHowever, you can also manually review studies to identify any duplicates we might have missed."),(0,n.kt)("p",null,"To review studies, click on the ",(0,n.kt)("strong",{parentName:"p"},"Identification"),' column header, or an individual study.\nFor each study, you can choose to "Promote" it to the next phase, "Exclude" as a duplicate, or flag for later review.'),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"Identification review",src:a(3615).Z,width:"2251",height:"1211"})),(0,n.kt)("admonition",{type:"tip"},(0,n.kt)("p",{parentName:"admonition"},"To remain PRISMA compliant, you should only exclude studies for being a duplicate in the Identification step.")),(0,n.kt)("p",null,"In this example, there are no duplicates. To quickly advance, click ",(0,n.kt)("strong",{parentName:"p"},"Promote All Uncategorized Studies")," under ",(0,n.kt)("em",{parentName:"p"},"Identification"),"."),(0,n.kt)("h3",{id:"screening"},"Screening"),(0,n.kt)("p",null,"The goal of ",(0,n.kt)("em",{parentName:"p"},"Screening")," is to determine if imported studies are relevant to your research question, based on the the Tile\nand Abstract of each."),(0,n.kt)("p",null,"To begin, click on the Screening column header from the main Curation board. The interface is\nidentical to the previous phase, except the default Exclusion reason is now ",(0,n.kt)("strong",{parentName:"p"},"irrelevant"),". "),(0,n.kt)("p",null,"Go ahead and review all 13 studies to determine if they are relevant to the topic of ",(0,n.kt)("em",{parentName:"p"},'"Nicotime administration'),'".\nAny studies that are not relevant will remain in this column and not advance.'),(0,n.kt)("h3",{id:"eligibility"},"Eligibility"),(0,n.kt)("p",null,"The goal ",(0,n.kt)("em",{parentName:"p"},"Eligibility")," is to determine studies meet the eligibility criteria of your meta-analysis.\nYou will need to read the ",(0,n.kt)("strong",{parentName:"p"},"full text")," to make this determination. "),(0,n.kt)("admonition",{type:"note"},(0,n.kt)("p",{parentName:"admonition"},"The eligibility criteria depends on your research question!\nThis is where your expertise is most necessary, in order to create an interesting research question,\nand filter studies accordingly. The results of this step depends on the researcher, and there may be reasonable scientific disagreements.")),(0,n.kt)("p",null,'To begin, click on the "Eligibility" column header, or a study, as before.'),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"Custom Eligibility",src:a(940).Z,width:"2341",height:"1449"})),(0,n.kt)("p",null,"For this example, we will include studies that meet these criteria:"),(0,n.kt)("pre",null,(0,n.kt)("code",{parentName:"pre"},"* fMRI or PET\n* Reported brain activity in stereotaxic coordinates (Talairach or MNI space)\n* Reported a set of coordinates (i.e., foci) from a within-subjects or between-subjects contrast assessing the effects of nAChR agonist administration (i.e., pharmacological administration or cigarette smoking) relative to a baseline condition (i.e., placebo administration or smoking-abstinence condition)\n* Examined brain activity using a cognitive or affective task paradigm or at rest. \n* Studies examining functional connectivity, brain morphology, or neurochemistry are excluded.\n")),(0,n.kt)("p",null,"For this tutorial, go ahead and review all studies in this column, and Promote relevant studies to the next phase."),(0,n.kt)("admonition",{type:"tip"},(0,n.kt)("p",{parentName:"admonition"},"Given that this phase is more open-ended, there is no default Exclusion reason. We provide four default options for you, and\nyou may define custom Exclusion reasons if you see fit.")),(0,n.kt)("admonition",{type:"tip"},(0,n.kt)("p",{parentName:"admonition"},'For open source studies, we will link to the article full text (PDF). If not available, click\n"view article link" to view article\'s PubMed page, and access the full text using your credentials.')),(0,n.kt)("h3",{id:"included"},"Included"),(0,n.kt)("p",null,"Congratulations! Once you have reviewed all studies, you should have a set of studies that you want to include in your meta-analysis. "),(0,n.kt)("p",null,"At this point, you can review this final list, and view a PRISMA diagram visually outlining your review process:"),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"PRISMA",src:a(8718).Z,width:"1714",height:"1448"})),(0,n.kt)("p",null,"To finish ",(0,n.kt)("em",{parentName:"p"},"Curation"),", and create a final StudySet, click ",(0,n.kt)("em",{parentName:"p"},"Move on to Extraction")," at the top right. "),(0,n.kt)("h2",{id:"extract-and-annotation"},"Extract and Annotation"),(0,n.kt)("p",null,"The goal of this phase is to ",(0,n.kt)("strong",{parentName:"p"},"extract data")," from the text of studies (such as coordinates)\nthat will be used in the meta-analysis. You will also want to ",(0,n.kt)("strong",{parentName:"p"},"annotate")," relevant Study meta-data.\nMost commonly, for each Study you will designate which Analyses (i.e. Contrasts) to included in your meta-analysis."),(0,n.kt)("admonition",{type:"tip"},(0,n.kt)("p",{parentName:"admonition"},"Studies that are already indexed by NeuroStore will have automatically extracted data (such as coordinates)\nsaving you a lot of time and effort. However, you may want to verify and improve this information.")),(0,n.kt)("h3",{id:"ingestion"},"Ingestion"),(0,n.kt)("p",null,"But first, we must create a StudySet containing your studies! "),(0,n.kt)("p",null,"New studies not in the NeuroStore database will be created, and studies that match existing studies will be added to a newly created StudySet."),(0,n.kt)("admonition",{type:"info"},(0,n.kt)("p",{parentName:"admonition"},"Studies in NeuroStore have multiple Versions, including those created by other users, as well as the original copy."),(0,n.kt)("p",{parentName:"admonition"},"If you ingest a study that is already indexed in the database, we will match to the newest possible Version, by default.\nIdeally, this will be a Version that another user has already improved, saving you even more time!"),(0,n.kt)("p",{parentName:"admonition"},"You can switch Study Versions at anytime (including to the original automate copy) by clicking ",(0,n.kt)("em",{parentName:"p"},"Switch Study Version")," at the bottom\nof Study's page. Any edits you make will automatically be saved as a new Version.")),(0,n.kt)("h3",{id:"editing-studies"},"Editing studies"),(0,n.kt)("p",null,"Once your StudySet is created, it's time to edit studies. You will see a list of your studies:"),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"Extraction",src:a(9774).Z,width:"1655",height:"799"})),(0,n.kt)("p",null,"Click on any Study to edit:"),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"Extraction study view",src:a(5362).Z,width:"2418",height:"856"})),(0,n.kt)("h4",{id:"analysis-data"},"Analysis Data"),(0,n.kt)("p",null,"Let's start by editing a Study's Analyses."),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"Extraction study view",src:a(369).Z,width:"2128",height:"923"})),(0,n.kt)("admonition",{type:"info"},(0,n.kt)("p",{parentName:"admonition"},(0,n.kt)("em",{parentName:"p"},"Analyses"),' are groups of images or coordinates reported in a given study fir a specific analysis. This is often referred to as "Contrasts", but we use the more general term "Analyses" to accommodate a wider range of fMRI models. ')),(0,n.kt)("p",null,"For new studies, we will not have any data, and it is necessary to manually enter these data from the text of a study.\nWe can create a new Analysis for each group of Coordinates, and input the data from the text:"),(0,n.kt)("p",null,"For studies already indexed by NeuroStore, we will already have pre-extracted Coordinates. You can use this same interface to verify and correct these data. "),(0,n.kt)("admonition",{type:"caution"},(0,n.kt)("p",{parentName:"admonition"},"Automatically extracted coordinates can contain a number of errors. Mostly commonly, several distinct Analyses (i.e. contrasts), will get grouped into a single Analyses. You will want to create new Analyses to split up the Coordinates into distinct units. "),(0,n.kt)("p",{parentName:"admonition"},"Another common error is that Analyses are duplicated, meaning you may want to delete extra Analyses. ")),(0,n.kt)("admonition",{type:"tip"},(0,n.kt)("p",{parentName:"admonition"},"You can copy and paste coordinates from Microsoft Excel or Google Sheets.")),(0,n.kt)("h4",{id:"annotations"},"Annotations"),(0,n.kt)("p",null,"A key goal of the Extraction phase, is to add Annotations that can help us distinguish Analyses, and include/exclude specific Analyses from a meta-analysis. Annotations are simply columns of data with a value for all Analyses within a StudySet."),(0,n.kt)("p",null,"Annotations can be explained as a way to categorize analyses within each study. For example, they can be categorized by task (e.g., Stroop, N-back, etc.), by modality (e.g., fMRI, PET, etc.), or by any other category that you want to use to filter the analyses. "),(0,n.kt)("admonition",{type:"tip"},(0,n.kt)("p",{parentName:"admonition"},'By default, a single Annotation called "included" is created, which includes all Analyses.\nYou can modify this Annotation to select the relevant Analyses of interest to your research question')),(0,n.kt)("p",null,"For this replication, we are interested in the effects of nAChR agonists on the brain, which can either be excitatory or inhibitory, so we add both an \u201cactivation\u201d and \u201cdeactivation\u201d column. "),(0,n.kt)("p",null,'First create an Annotation. From the main Extraction page, click "View Annotations" on the top right. Here you can view all annotations and the value for each Analyses, as well as create new Annotations. You can choose the data type of each column as either a Number, String, or Boolean. Selected a Boolean data type for the \u201cactivation\u201d and \u201cdeactivation\u201d columns, which will allow you to filter the analyses by whether they are excitatory or inhibitory. By default you will have an \u201cinclude\u201d column to help get you started.'),(0,n.kt)("p",null,'Below, I am creating a new Annotation for "deactivations"'),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"annotation for a study",src:a(8669).Z,width:"1795",height:"758"})),(0,n.kt)("p",null,'Now, when I look at a study, I can edit the value for Analyses, assigning each group of coordinates as "activations" or "deactivations":'),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"annotation for a study",src:a(4235).Z,width:"850",height:"128"})),(0,n.kt)("h2",{id:"meta-analysis-specification"},"Meta-analysis specification"),(0,n.kt)("p",null,"You are finally ready to specify a meta-analysis! "),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"start meta-analysis specification",src:a(234).Z,width:"834",height:"308"})),(0,n.kt)("p",null,"After clicking ",(0,n.kt)("strong",{parentName:"p"},'"+ Meta-Analysis Specification"'),", you'll see the following dialog:"),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"Meta-analysis wizard",src:a(588).Z,width:"1762",height:"1014"})),(0,n.kt)("p",null,'For each Meta-Analysis, you will select an Annotation to filter the Analyses to include.\nRemember, by default, the "included" column will be created and include ',(0,n.kt)("em",{parentName:"p"},"all")," Analyses. "),(0,n.kt)("p",null,"Next, you will ",(0,n.kt)("strong",{parentName:"p"},"select a meta-analysis Algorithm and Corrector"),":"),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"Meta-analysis algorithm",src:a(3556).Z,width:"1762",height:"1014"})),(0,n.kt)("p",null,'A variety of common meta-analysis algorithms such as "ALE" and "MKDA" are available, as well as two\nstrategies for controlling for multiple comparisons: FDR (false detection rate) and FWE (family wise error).'),(0,n.kt)("p",null,'For this example, we\'ll choose "MKDADensity" and and "FDRCorrection". You can modify the parameters for each, if you want,\nbut we provide sane defaults for all. '),(0,n.kt)("admonition",{type:"tip"},(0,n.kt)("p",{parentName:"admonition"},"Learn more about meta-analysis algorithms in the ",(0,n.kt)("a",{parentName:"p",href:"https://nimare.readthedocs.io/en/stable/index.html"},"NiMARE Documentation"))),(0,n.kt)("p",null,"Next, you'll give your meta-analysis a name, and review the details of your specification. "),(0,n.kt)("p",null,(0,n.kt)("img",{alt:"Meta-analysis review",src:a(7832).Z,width:"1771",height:"1575"})),(0,n.kt)("admonition",{type:"tip"},(0,n.kt)("p",{parentName:"admonition"},"You can define multiple Meta-Analysis specifications in a Project, paired to the same StudySet")),(0,n.kt)("h2",{id:"run-your-meta-analysis"},"Run your meta-analysis!"),(0,n.kt)("p",null,"Congratulations! 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"),(0,r.kt)("p",null,"Although this approach was surprsingly successful, there were several major limitations to Neurosynth 1.0:"),(0,r.kt)("ul",null,(0,r.kt)("li",{parentName:"ul"},(0,r.kt)("p",{parentName:"li"},"Meta-analyses were limited by ",(0,r.kt)("strong",{parentName:"p"},"concepts that can be inferred from large scale text mining")," (i.e. frequency of terms in the text).\nAlthough these features proved to be surprsingly useful for well-powered and broad cognitive constructs (e.g. 'emotion'), Neurosynth was not able\nto capture the fine-grained details of the neuroimaging literature, or allow users to define their own grouping of studies. ")),(0,r.kt)("li",{parentName:"ul"},(0,r.kt)("p",{parentName:"li"},"The database is not curated, and therefore contains many ",(0,r.kt)("strong",{parentName:"p"},"inaccuracies and incomplete")," data at both the study and coordinate level.\nAside from obvious extraction erors, automated coordinate extraction lacks the ability to determine critical information, such as whether the activation is positive or negative.\nIn addition, it's not possible to segregate the coordinates into distinct contrast, conditions, or studies without manual curation.")),(0,r.kt)("li",{parentName:"ul"},(0,r.kt)("p",{parentName:"li"},"Coordinate-based analyses are inherently ",(0,r.kt)("strong",{parentName:"p"},"inferior to image-based")," meta-analysis, which is becoming increasingly possible with sharing of unthresholded statisical maps in repositories like ",(0,r.kt)("a",{parentName:"p",href:"https://neurovault.org/"},"NeuroVault"),"."))),(0,r.kt)("p",null,(0,r.kt)("em",{parentName:"p"},"Neurosynth Compose")," aims to address these limitations:"),(0,r.kt)("ul",null,(0,r.kt)("li",{parentName:"ul"},(0,r.kt)("p",{parentName:"li"},"Provides a web-based platform for meta-analytic neuroimaging research, allowing users to ",(0,r.kt)("strong",{parentName:"p"},"curate studies"),", and ",(0,r.kt)("strong",{parentName:"p"},"specify meta-analytic models"),". ")),(0,r.kt)("li",{parentName:"ul"},(0,r.kt)("p",{parentName:"li"},(0,r.kt)("strong",{parentName:"p"},"Flexible and easy to use"),", allowing users to perform both large-scale ",(0,r.kt)("strong",{parentName:"p"},"exploratory")," meta-analyses, as well as ",(0,r.kt)("strong",{parentName:"p"},"targeted, hypothesis-driven")," meta-analyses that conform to stringent standards such as the ","[PRISMA][https://prisma-statement.org]"," statement.")),(0,r.kt)("li",{parentName:"ul"},(0,r.kt)("p",{parentName:"li"},"Allows users to perfom ",(0,r.kt)("strong",{parentName:"p"},"image-based meta-analysis")," using unthresholded images from NeuroVault (in progress).")),(0,r.kt)("li",{parentName:"ul"},(0,r.kt)("p",{parentName:"li"},"Quick, reproducible and transparent ",(0,r.kt)("strong",{parentName:"p"},"sharing of results"),".")),(0,r.kt)("li",{parentName:"ul"},(0,r.kt)("p",{parentName:"li"},"Incentivizes ",(0,r.kt)("strong",{parentName:"p"},"collaborative curation")," of neuroimaging studies in a accesible ",(0,r.kt)("strong",{parentName:"p"},"centralized repository")," (NeuroStore, see below)."))),(0,r.kt)("h2",{id:"neurostore"},"NeuroStore"),(0,r.kt)("p",null,"NeuroStore is the centralized repository for neuroimaging data amenable to meta-analysis, including coordinates, images, and metadata.\nNeuroStore serves as the data backend for Neurosynth Compose, but is also designed to be a standalone interoperable resource for the neuroimaging community."),(0,r.kt)("p",null,"NeuroStore ingests data from a number of sources, including NeuroVault, NeuroQuery, and Neurosynth (ACE), and provides a unified API for querying the database."),(0,r.kt)("p",null,"Importantly, data on NeuroStore can be ",(0,r.kt)("strong",{parentName:"p"},"curated")," the community, allowing users to correct errors in coordinate extraction, and add new studies and coordinates. 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i={sidebar_label:"Automated Meta-Analysis",sidebar_position:3},r="Automated Meta-Analysis",s={unversionedId:"tutorial/automated",id:"tutorial/automated",title:"Automated Meta-Analysis",description:"This tutorial, and the functionality for automated meta-analysis, is under construction.",source:"@site/docs/tutorial/automated.md",sourceDirName:"tutorial",slug:"/tutorial/automated",permalink:"/compose-docs/tutorial/automated",draft:!1,editUrl:"https://github.com/neurostuff/compose-docs/edit/master/docs/tutorial/automated.md",tags:[],version:"current",lastUpdatedBy:"Alejandro de la Vega",lastUpdatedAt:1701130832,formattedLastUpdatedAt:"Nov 28, 2023",sidebarPosition:3,frontMatter:{sidebar_label:"Automated Meta-Analysis",sidebar_position:3},sidebar:"tutorialSidebar",previous:{title:"Manual Meta-Analysis",permalink:"/compose-docs/tutorial/manual"}},l={},u=[{value:"Why automated meta-analysis?",id:"why-automated-meta-analysis",level:2},{value:"Flexible automated meta-analysis in Neurosynth Compose",id:"flexible-automated-meta-analysis-in-neurosynth-compose",level:3},{value:"Tutorial",id:"tutorial",level:2},{value:"Search & Curate",id:"search--curate",level:3},{value:"Import from Neurostore",id:"import-from-neurostore",level:4},{value:"Promote studies",id:"promote-studies",level:4},{value:"Extraction and Annotation",id:"extraction-and-annotation",level:3},{value:"Specify Meta-Analyses",id:"specify-meta-analyses",level:3},{value:"Execute",id:"execute",level:3}],m={toc:u},d="wrapper";function c(e){let{components:t,...i}=e;return(0,o.kt)(d,(0,n.Z)({},m,i,{components:t,mdxType:"MDXLayout"}),(0,o.kt)("h1",{id:"automated-meta-analysis"},"Automated Meta-Analysis"),(0,o.kt)("admonition",{type:"caution"},(0,o.kt)("p",{parentName:"admonition"},"This tutorial, and the functionality for automated meta-analysis, is under construction.\nTo view existing automated meta-analyses, you can use ",(0,o.kt)("a",{parentName:"p",href:"https://neurosynth.org"},"Neurosynth Original"))),(0,o.kt)("h2",{id:"why-automated-meta-analysis"},"Why automated meta-analysis?"),(0,o.kt)("p",null,"The principal difference between an automated and a ",(0,o.kt)("a",{parentName:"p",href:"/compose-docs/tutorial/manual"},"manual meta-analysis")," is ",(0,o.kt)("em",{parentName:"p"},"the process used to select the final set of Studies and Analyses to include")," into your meta-analysis. "),(0,o.kt)("p",null,"In a ",(0,o.kt)("strong",{parentName:"p"},"manual meta-analysis"),", researchers cast a wide net to find a wide range of potentially relevant articles, and use their expertise (read: painstakingly review hundreds of articles) to decide which of articles are relevant to their research question. Our platform seeks streamline this process through a user-friendly interface and pre-extracted data for over 20,000 neuroimaging studies. Yet, ",(0,o.kt)("strong",{parentName:"p"},"a gold standard meta-analysis still requires a significant time investment"),", limiting their application in routine scientific practice."),(0,o.kt)("p",null,"In an ",(0,o.kt)("strong",{parentName:"p"},"automated meta-analysis"),", we instead use data-driven text mining metrics to ",(0,o.kt)("em",{parentName:"p"},"select")," articles. The original ",(0,o.kt)("em",{parentName:"p"},"Neurosynth")," pioneered this approach by developing text mining techniques to automatically extract brain coordinates and semantic text features from thousands of articles. "),(0,o.kt)("p",null,"Surprisingly, this works! For example, by meta-analyzing all studies that mention the term ",(0,o.kt)("a",{parentName:"p",href:"https://neurosynth.org/analyses/terms/emotional/"},'"emotional"')," above a certain frequency, we observe a strong association with activity in the amygdala. By and large, the sheer number of studies overcomes the inherent noisiness of automated data extraction and study selection. "),(0,o.kt)("h3",{id:"flexible-automated-meta-analysis-in-neurosynth-compose"},"Flexible automated meta-analysis in Neurosynth Compose"),(0,o.kt)("p",null,"Although automated meta-analyses have proved to be a useful tool, there are several limitations. The overall goal of ",(0,o.kt)("em",{parentName:"p"},"Neurosynth Compose")," is to give users a flexible data curation platform, to overcome these limitations using their expert knowledge. For example:"),(0,o.kt)("ul",null,(0,o.kt)("li",{parentName:"ul"},(0,o.kt)("em",{parentName:"li"},"Flexible selection criteria.")," The original Neurosynth has a fixed number of terms and meta-analyses. With",(0,o.kt)("em",{parentName:"li"},"Neurosynth Compose")," you can flexibly search the NeuroStore database using a powerful and flexible search to precisely define your search criteria. "),(0,o.kt)("li",{parentName:"ul"},(0,o.kt)("em",{parentName:"li"},"Combine expert knowledge with automated selection.")," Automated study selection is inherently an noisy and imperfect measure. With ",(0,o.kt)("em",{parentName:"li"},"Neurosynth Compose"),", you can use automated study selection as a first pass, and later apply your own expert criteria to refine study inclusion criteria. "),(0,o.kt)("li",{parentName:"ul"},(0,o.kt)("em",{parentName:"li"},"Correct data extraction errors.")," Automated extraction can miss entire tables of coordinates (e.g. supplementary materials), duplicate coordinates, and groups distinct sets of Analyses (e.g. Contrasts) into a single group. Now, you can correct these data to make your meta-analysis more precise. ")),(0,o.kt)("h2",{id:"tutorial"},"Tutorial"),(0,o.kt)("p",null,"An automated meta-analysis in ",(0,o.kt)("em",{parentName:"p"},"Neurosynth Compose")," looks a lot like a manual one, except data curation is optional. 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")),(0,o.kt)("h4",{id:"import-from-neurostore"},"Import from Neurostore"),(0,o.kt)("p",null,"Let's add studies to our curation board by clicking ",(0,o.kt)("strong",{parentName:"p"},"Import Studies"),".\nIn an automated meta-analysis, you'll want to select ",(0,o.kt)("em",{parentName:"p"},"Import via NeuroStore"),", as all indexed studies are guaranteed to contain imaging data (saving you from manual data extraction)."),(0,o.kt)("admonition",{type:"caution"},(0,o.kt)("p",{parentName:"admonition"},"Although the NeuroStore database is continuously growing, it is necessarily an incomplete snapshot of the neuroimaging literature")),(0,o.kt)("p",null,"Input any search term to narrow down studies. This will search the Title and Abstract fields. You may also add additional search filters using the ",(0,o.kt)("strong",{parentName:"p"},"+ Add Filter")," button, and ",(0,o.kt)("em",{parentName:"p"},"select the desired modality of the imaging data"),". "),(0,o.kt)("p",null,(0,o.kt)("img",{alt:"Neurostore Search",src:a(8506).Z,width:"1849",height:"1523"}),". "),(0,o.kt)("p",null,'To import your search, click "Import Studies From Neurostore" at the bottom right. Give your import a name to Tag all imported studies, and continue back to your Curation board. '),(0,o.kt)("admonition",{type:"note"},(0,o.kt)("p",{parentName:"admonition"},"You must import an entire set of search results into your curation board. If you want to exclude any specific studies, you will do so on your board. This allows the Search & Curate process to be fully reproducible.")),(0,o.kt)("h4",{id:"promote-studies"},"Promote studies"),(0,o.kt)("p",null,"Back to your Curation board, you will now see all studies from your NeuroStore search on the left most column."),(0,o.kt)("p",null,(0,o.kt)("img",{alt:"Curation board",src:a(761).Z,width:"2583",height:"1604"}),". "),(0,o.kt)("p",null,"At this point, you have two options: manually review the search results and select which studies to include, or perform a fully automated meta-analysis by including all search results. "),(0,o.kt)("p",null,"For this tutorial, we'll skip manual curation and ",(0,o.kt)("strong",{parentName:"p"},"Promote All Uncategorized Studies"),' to the right-most "Included" column. '),(0,o.kt)("p",null,"We can now click ",(0,o.kt)("em",{parentName:"p"},"Move to Extraction Phase"),"."),(0,o.kt)("h3",{id:"extraction-and-annotation"},"Extraction and Annotation"),(0,o.kt)("p",null,"At this point, you will create a StudySet containing all of your Studies. Advance through the dialog to begin ",(0,o.kt)("em",{parentName:"p"},"Extraction"),"."),(0,o.kt)("p",null,"The goal of this phase is to add or correct imaging data (e.g. Coordinates) in imported studies, and create Annotations to determine which Analyses (e.g. Contrasts), should be included in your meta-analysis."),(0,o.kt)("p",null,"Since we are performing a manual meta-analysis, we're going to skip these steps!"),(0,o.kt)("p",null,"From the main ",(0,o.kt)("em",{parentName:"p"},"Project"),' page, we can click "Mark All as Complete".'),(0,o.kt)("p",null,(0,o.kt)("img",{alt:"Skip Extraction",src:a(1599).Z,width:"1263",height:"855"}),". "),(0,o.kt)("admonition",{type:"tip"},(0,o.kt)("p",{parentName:"admonition"},"It's up to you if you want to skip this step. The validity of your meta-analysis is highly dependant on input data, so we only recommend skipping all curation for exploratory analyses.")),(0,o.kt)("h3",{id:"specify-meta-analyses"},"Specify Meta-Analyses"),(0,o.kt)("p",null,"You can now specify your meta-analysis. This step will be identical between automated and manual meta-analyses."),(0,o.kt)("p",null,'First, we select the "included" column, which by default includes ',(0,o.kt)("em",{parentName:"p"},"all")," Study Analyses as inputs."),(0,o.kt)("p",null,(0,o.kt)("img",{alt:"Inclusion column",src:a(8376).Z,width:"1368",height:"1715"}),". "),(0,o.kt)("p",null,"Next, we select a meta-analysis algorithm. This time, we'll select MKDA Chi-Squared (",(0,o.kt)("inlineCode",{parentName:"p"},"MKDAChi2"),") with ",(0,o.kt)("inlineCode",{parentName:"p"},"FDRCorrector"),". "),(0,o.kt)("p",null,"MKDA Chi-Square compares your StudySet to a reference set of studies (all the studies in NeuroStore that you did ",(0,o.kt)("em",{parentName:"p"},"not")," select), allowing you to identify areas of stronger association with your selected studies. This is the algorithm used in the original Neurosynth Platform."),(0,o.kt)("h3",{id:"execute"},"Execute"),(0,o.kt)("p",null,"Once you specify your meta-analysis, you can execute it in the cloud using Google Colab using your unique meta-analysis id. "),(0,o.kt)("p",null,(0,o.kt)("img",{alt:"Automated execute",src:a(2770).Z,width:"1551",height:"1098"}),". 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"),(0,o.kt)("p",null,"In a ",(0,o.kt)("strong",{parentName:"p"},"manual meta-analysis"),", researchers cast a wide net to find a wide range of potentially relevant articles, and use their expertise (read: painstakingly review hundreds of articles) to decide which of articles are relevant to their research question. Our platform seeks streamline this process through a user-friendly interface and pre-extracted data for over 20,000 neuroimaging studies. Yet, ",(0,o.kt)("strong",{parentName:"p"},"a gold standard meta-analysis still requires a significant time investment"),", limiting their application in routine scientific practice."),(0,o.kt)("p",null,"In an ",(0,o.kt)("strong",{parentName:"p"},"automated meta-analysis"),", we instead use data-driven text mining metrics to ",(0,o.kt)("em",{parentName:"p"},"select")," articles. The original ",(0,o.kt)("em",{parentName:"p"},"Neurosynth")," pioneered this approach by developing text mining techniques to automatically extract brain coordinates and semantic text features from thousands of articles. "),(0,o.kt)("p",null,"Surprisingly, this works! For example, by meta-analyzing all studies that mention the term ",(0,o.kt)("a",{parentName:"p",href:"https://neurosynth.org/analyses/terms/emotional/"},'"emotional"')," above a certain frequency, we observe a strong association with activity in the amygdala. By and large, the sheer number of studies overcomes the inherent noisiness of automated data extraction and study selection. "),(0,o.kt)("h3",{id:"flexible-automated-meta-analysis-in-neurosynth-compose"},"Flexible automated meta-analysis in Neurosynth Compose"),(0,o.kt)("p",null,"Although automated meta-analyses have proved to be a useful tool, there are several limitations. The overal goal of ",(0,o.kt)("em",{parentName:"p"},"Neurosynth Compose")," is to give users a flexible data curation platform, to overcome these limitations using their expert knowledge. For example:"),(0,o.kt)("ul",null,(0,o.kt)("li",{parentName:"ul"},(0,o.kt)("em",{parentName:"li"},"Flexible selection criteria.")," The original Neurosynth has a fixed number of terms and meta-analyses. With",(0,o.kt)("em",{parentName:"li"},"Neurosynth Compose")," you can flexibly search the NeuroStore database using a powerful and flexible search to precisely define your search criteria. "),(0,o.kt)("li",{parentName:"ul"},(0,o.kt)("em",{parentName:"li"},"Combine expert knowledge with automated selection.")," Automated study selection is inherently an noisy and imperfect measure. With ",(0,o.kt)("em",{parentName:"li"},"Neurosynth Compose"),", you can use automated study selection as a first pass, and later apply your own expert criteria to refine study inclusion criteria. "),(0,o.kt)("li",{parentName:"ul"},(0,o.kt)("em",{parentName:"li"},"Correct data extraction errors.")," Automated extraction can miss entire tables of coordinates (e.g. supplementary materials), duplicate coordinates, and groups distinct sets of Analyses (e.g. Contrasts) into a single group. Now, you can correct these data to make your meta-analysis more precise. ")),(0,o.kt)("h2",{id:"tutorial"},"Tutorial"),(0,o.kt)("p",null,"An automated meta-analysis in ",(0,o.kt)("em",{parentName:"p"},"Neurosynth Compose")," looks a lot like a manual one, except data curation is optional. 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")),(0,o.kt)("h4",{id:"import-from-neurostore"},"Import from Neurostore"),(0,o.kt)("p",null,"Let's add studies to our curation board by clicking ",(0,o.kt)("strong",{parentName:"p"},"Import Studies"),".\nIn an automated meta-analysis, you'll want to select ",(0,o.kt)("em",{parentName:"p"},"Import via NeuroStore"),", as all indexed studies are guaranteed to contain imaging data (saving you from manual data extraction)."),(0,o.kt)("admonition",{type:"caution"},(0,o.kt)("p",{parentName:"admonition"},"Although the NeuroStore database is continously growing, it is necessarily an incomplete snapshot of the neuroimaging literature")),(0,o.kt)("p",null,"Input any search term to narrow down studies. This will search the Title and Abstract fields. You may also add additional search filters using the ",(0,o.kt)("strong",{parentName:"p"},"+ Add Filter")," button, and ",(0,o.kt)("em",{parentName:"p"},"select the desired modality of the imaging data"),". "),(0,o.kt)("p",null,(0,o.kt)("img",{alt:"Neurostore Search",src:a(8506).Z,width:"1849",height:"1523"}),". "),(0,o.kt)("p",null,'To import your search, click "Import Studies From Neurostore" at the bottom right. Give your import a name to Tag all imported studies, and continue back to your Curation board. '),(0,o.kt)("admonition",{type:"note"},(0,o.kt)("p",{parentName:"admonition"},"You must import an entire set of search results into your curation board. If you want to exclude any specific studies, you will do so on your board. This allows the Search & Curate process to be fully reproducible.")),(0,o.kt)("h4",{id:"promote-studies"},"Promote studies"),(0,o.kt)("p",null,"Back to your Curation board, you will now see all studies from your NeuroStore search on the left most column."),(0,o.kt)("p",null,(0,o.kt)("img",{alt:"Curation board",src:a(761).Z,width:"2583",height:"1604"}),". "),(0,o.kt)("p",null,"At this point, you have two options: manually review the search results and select which studies to include, or perform a fully automated meta-analysis by including all search results. "),(0,o.kt)("p",null,"For this tutorial, we'll skip manual curation and ",(0,o.kt)("strong",{parentName:"p"},"Promote All Uncategorized Studies"),' to the right-most "Included" column. '),(0,o.kt)("p",null,"We can now click ",(0,o.kt)("em",{parentName:"p"},"Move to Extraction Phase"),"."),(0,o.kt)("h3",{id:"extraction-and-annotation"},"Extraction and Annotation"),(0,o.kt)("p",null,"At this point, you will create a StudySet containing all of your Studies. Advance through the dialog to begin ",(0,o.kt)("em",{parentName:"p"},"Extraction"),"."),(0,o.kt)("p",null,"The goal of this phase is to add or correct imaging data (e.g. Coordinates) in imported studies, and create Annotations to determine which Analyses (e.g. Contrasts), should be included in your meta-analysis."),(0,o.kt)("p",null,"Since we are perfomring a manual meta-analysis, we're going to skip these steps!"),(0,o.kt)("p",null,"From the main ",(0,o.kt)("em",{parentName:"p"},"Project"),' page, we can click "Mark All as Complete".'),(0,o.kt)("p",null,(0,o.kt)("img",{alt:"Skip Extraction",src:a(1599).Z,width:"1263",height:"855"}),". "),(0,o.kt)("admonition",{type:"tip"},(0,o.kt)("p",{parentName:"admonition"},"It's up to you if you want to skip this step. The validity of your meta-analysis is highly dependant on input data, so we only reccomend skipping all curation for exploratory analyses.")),(0,o.kt)("h3",{id:"specify-meta-analyses"},"Specify Meta-Analyses"),(0,o.kt)("p",null,"You can now specify your meta-analysis. This step will be identical between automated and manual meta-analyses."),(0,o.kt)("p",null,'First, we select the "included" column, which by default includes ',(0,o.kt)("em",{parentName:"p"},"all")," Study Analyses as inputs."),(0,o.kt)("p",null,(0,o.kt)("img",{alt:"Inclusion column",src:a(8376).Z,width:"1368",height:"1715"}),". "),(0,o.kt)("p",null,"Next, we select a meta-analysis algorithm. This time, we'll select MKDA Chi-Squared (",(0,o.kt)("inlineCode",{parentName:"p"},"MKDAChi2"),") with ",(0,o.kt)("inlineCode",{parentName:"p"},"FDRCorrector"),". "),(0,o.kt)("p",null,"MKDA Chi-Square compares your StudySet to a reference set of studies (all the studies in NeuroStore that you did ",(0,o.kt)("em",{parentName:"p"},"not")," select), allowing you to identify areas of stronger association with your selected studies. This is the algorithm used in the original Neurosynth Platform."),(0,o.kt)("h3",{id:"execute"},"Execute"),(0,o.kt)("p",null,"Once you specify your meta-analysis, you can execute it in the cloud using Google Colab using your unique meta-analysis id. "),(0,o.kt)("p",null,(0,o.kt)("img",{alt:"Automated execute",src:a(2770).Z,width:"1551",height:"1098"}),". 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The\n",(0,i.kt)("a",{parentName:"p",href:"http://www.prisma-statement.org/?AspxAutoDetectCookieSupport=1"},"PRISMA guidelines")," are a set of rules for reporting a\nsystematic review, and are the gold standard for producing a proper, rigorous, and transparent meta-analysis."),(0,i.kt)("p",null,"If you are trying to create a rigorous ",(0,i.kt)("a",{parentName:"p",href:"/compose-docs/tutorial/manual"},"PRISMA compliant manual meta-analysis")," you will want to select this option."),(0,i.kt)("p",null,"When you select this option, neurosynth-compose will automatically initialize the curation step with 4 distinct columns as\ndictated by PRISMA guidelines: ",(0,i.kt)("strong",{parentName:"p"},"Identification, Screening, Eligibility, Included"),"."),(0,i.kt)("p",null,"After importing studies into neurosynth, they will be placed into the identification column and studies are triaged from there."),(0,i.kt)("admonition",{title:"PRISMA Summary",type:"info"},(0,i.kt)("p",{parentName:"admonition"},"The ",(0,i.kt)("strong",{parentName:"p"},"Identification")," column is where all imported studies are deposited into initially. As alluded to by the name, the identification\ncolumn is where you identify all records yielded from your search. In this column, you wil exclude studies purely based on whether they are\nduplicates of existing studies. All other studies are promoted."),(0,i.kt)("p",{parentName:"admonition"},"The ",(0,i.kt)("strong",{parentName:"p"},"Screening")," column consists of all records that have been screened for duplicates. In this column, you want to review the titles/abstracts of studies\nand exclude purely based on whether they are irrelevant to your research question or domain. All other studies are promoted. "),(0,i.kt)("p",{parentName:"admonition"},"The ",(0,i.kt)("strong",{parentName:"p"},"Eligibility")," column consists of all records that have been screened for duplicates and irrelevant content. In this column, you want to\nreview the full text of studies and exclude based on whether the study described aligns with the standards of the meta-analysis itself. Reasons\nfor exclusion may include wrong setting, wrong patient population, wrong intervention, wrong paragdigm, etc."),(0,i.kt)("p",{parentName:"admonition"},"The ",(0,i.kt)("strong",{parentName:"p"},"Included")," column consists of all records that have passed previous levels of exclusion and can be considered for the next step of the project."),(0,i.kt)("p",{parentName:"admonition"},"For more information, consult the ",(0,i.kt)("a",{parentName:"p",href:"http://www.prisma-statement.org/?AspxAutoDetectCookieSupport=1"},"PRISMA guidelines"),".")),(0,i.kt)("h3",{id:"simple-workflow"},"Simple Workflow"),(0,i.kt)("p",null,"If you want to create a semi-automated meta-analysis (i.e. perform manual review on a large-scale study search), you'll want to select this option."),(0,i.kt)("p",null,"This workflow is initalized with only two columns. As before, the left most column is where studies will be placed when they are imported. However, unlike a full PRISMA workflow, all exclusion occurs in this column. All studies not excluded are then promoted to the right most column for inclusion into the meta-analysis."),(0,i.kt)("h2",{id:"importing"},"Importing"),(0,i.kt)("p",null,"To begin importing studies into your project clicking the ",(0,i.kt)("strong",{parentName:"p"},"IMPORT STUDIES")," button."),(0,i.kt)("p",null,"You will be asked to choose a source, name your import, and address\nany potential duplicate studies."),(0,i.kt)("admonition",{type:"tip"},(0,i.kt)("p",{parentName:"admonition"},"We recommend giving each import a meaningful name. This will be useful when you come back\nand want to know where a certain study was imported from.")),(0,i.kt)("h3",{id:"import-from-neurostore"},"Import from Neurostore"),(0,i.kt)("p",null,"Neurostore indexes a large number of neuroimaging studies which are ready for meta-analysis. Studies in Neurostore have been pre-processed, including extracting peak activation coordinates from Tables in the text, and computing semantic features from the abstract/full text. Neurostore also indexes studies which other users have annotated and made available to others for re-use."),(0,i.kt)("p",null,"Importing from Neurostore utilizes the Study search UI similar to the ",(0,i.kt)("a",{parentName:"p",href:"https://compose.neurosynth.org/studies"},"Study Page"),".\nAfter entering your search, click the bottom right button to import the searched studies into your project."),(0,i.kt)("admonition",{type:"tip"},(0,i.kt)("p",{parentName:"admonition"},"Importing from Neurostore can save you a lot of time, as these studies are much more likely to be amenable to meta-analysis, and have pre-extracted coordinates. However, note that some manual annotation may still be required to verify the coordinate extraction, and choose the relevant Analysis (i.e. contrast) for final inclusion.")),(0,i.kt)("h3",{id:"import-from-pubmed"},"Import from PubMed"),(0,i.kt)("p",null,"Use this option to import studies directly from PubMed. To start, you need to go to the ",(0,i.kt)("a",{parentName:"p",href:"https://pubmed.ncbi.nlm.nih.gov/"},"PubMed Site"),"\nand either enter in a search or navigate to a previously created collection. "),(0,i.kt)("p",null,"To import the search or collection from PubMed into neurosynth-compose, you will need a text file containing a list of PMIDs.\nYou can obtain this by going to your collection/search and clicking the ",(0,i.kt)("strong",{parentName:"p"},"Save")," button. Set ",(0,i.kt)("strong",{parentName:"p"},"Selection")," to ",(0,i.kt)("strong",{parentName:"p"},"All results"),"\nand set ",(0,i.kt)("strong",{parentName:"p"},"Format")," to ",(0,i.kt)("strong",{parentName:"p"},"PMID"),". Click ",(0,i.kt)("strong",{parentName:"p"},"Create file")," and your text file containing the PMIDs will be generated and downloaded."),(0,i.kt)("admonition",{type:"caution"},(0,i.kt)("p",{parentName:"admonition"},"Neurosynth-Compose uses the PubMed API to import studies. As a result, the maximum number of PMIDs that can be imported at once is 1,500.\nIf your collection has more than 1,500 PMIDs, split the import into multiple files.")),(0,i.kt)("h3",{id:"import-from-bibtexrisendnote"},"Import from BibTex/RIS/endnote"),(0,i.kt)("p",null,"Use this option to import studies via a .bib, .RIS, or .enw file. This may be useful if you want to import from a citation manager like Zotero."),(0,i.kt)("h3",{id:"custom-studies"},"Custom Studies"),(0,i.kt)("p",null,"If there is any record that cannot be easily imported using one of the methods listed above, you can also manually create a study. This may be necessary\nto include resources like unpublished studies."),(0,i.kt)("h3",{id:"duplicates"},"Duplicates"),(0,i.kt)("p",null,'If duplicates are detected in your import, you will be asked how to re-concile them by choosing which of the studies to keep by choosing "KEEP THIS STUDY". Matching duplicates will be automatically marked for exclusion. Note that as a user, you can over-ride any of these selection at any time, and choose which studies to keep or exclude. '),(0,i.kt)("admonition",{type:"info"},(0,i.kt)("p",{parentName:"admonition"},(0,i.kt)("em",{parentName:"p"},"Neurosynth Compose")," does not delete studies. If a study is marked as a duplicate, it is marked as ",(0,i.kt)("strong",{parentName:"p"},"excluded")," but it is not discarded to ensure complete provenance. ")),(0,i.kt)("p",null,"There are two potential ways that duplicates can occur:"),(0,i.kt)("h4",{id:"duplicates-are-detected-between-the-studies-being-imported-and-the-studies-already-in-the-project"},"Duplicates are detected between the studies being imported and the studies already in the project"),(0,i.kt)("p",null,"If any study being important has the same title, PMID, or DOI is the same as\none already in the project, you will be asked reconcile these duplicates."),(0,i.kt)("p",null,'Note that if you mark a study that is already promoted as a duplicate, it will be "demoted" back to the first column and marked as "duplicate". It is reccomended to mark as duplicate the incoming study to avoid this. '),(0,i.kt)("h4",{id:"duplicates-are-detected-within-the-file-you-are-importing"},"Duplicates are detected within the file you are importing"),(0,i.kt)("p",null,"Although rare, it is possible to have duplicates within a given import. For example, if within a RIS file there are duplicate entries. In this case, you will be asked to select which study to keep. Studies marked as duplicates will still be imported but marked as excluded. "),(0,i.kt)("h2",{id:"excluding-and-promoting-studies"},"Excluding and Promoting Studies"),(0,i.kt)("p",null,"Once studies have been imported into the first column of the curation phase, they need to be reviewed for inclusion into your meta-analysis.\nAll studies must be either excluded or moved to the inclusion column in order to progress to the extraction phase."),(0,i.kt)("p",null,"To begin, either click on the button at the top of the column or click on any study in the column. This will open up a page which will show the study\nalong with the following options: ",(0,i.kt)("strong",{parentName:"p"},"PROMOTE, NEEDS REVIEW"),", and ",(0,i.kt)("strong",{parentName:"p"},"EXCLUDE"),". There is also a button to ",(0,i.kt)("strong",{parentName:"p"},"ADD TAGS")," which will assign an informational tag to the study."),(0,i.kt)("h3",{id:"exclude"},"Exclude"),(0,i.kt)("p",null,"To exclude a study, click the ",(0,i.kt)("strong",{parentName:"p"},"EXCLUDE")," button and select the exclusion reason. You can either choose from the preset exclusion reasons or you can begin\ntyping to create a new one."),(0,i.kt)("admonition",{type:"tip"},(0,i.kt)("p",{parentName:"admonition"},"For the PRISMA workflow, the default exclusion reason wil depend on the phase you are in (identification vs screening vs eligibility), to match the PRISMA guidelines. While we do not recommend it, you can click the arrow button and start typing in the input to create a new exclusion reason.\nRevisit the ",(0,i.kt)("a",{parentName:"p",href:"./Curation#prisma-workflow"},"PRISMA workflow")," to review reccomended exclusion criteria.")),(0,i.kt)("h3",{id:"promote"},"Promote"),(0,i.kt)("p",null,"If a study meets inclusion critera (for the current phase), click ",(0,i.kt)("strong",{parentName:"p"},"PROMOTE")," to move the study forward to the next curation column. If it is moved into the right most inclusion column, then it will be included in the meta-analysis."),(0,i.kt)("admonition",{type:"tip"},(0,i.kt)("p",{parentName:"admonition"},"For the first column (especially in a PRISMA workflow) it can be tedious to promote non-duplicates to the next column. If all duplicates have been resolved, you can exit the dialog and click ",(0,i.kt)("strong",{parentName:"p"},"PROMOTE ALL UNCATEGORIZED STUDIES")," to advance all non-duplicate studies to the next column.")),(0,i.kt)("h2",{id:"on-to-extraction"},"On to Extraction"),(0,i.kt)("p",null,"When you have categorized all imported studies by either excluding them or moving them to the inclusion column, then you have\nsuccessfully completed the curation portion of the meta-analysis."),(0,i.kt)("p",null,(0,i.kt)("em",{parentName:"p"},"Neurosynth Compose")," will detect this and reveal a new button: ",(0,i.kt)("strong",{parentName:"p"},"MOVE TO EXTRACTION PHASE"),". This will move you back to the project page and get you started on the next major component to building your meta-analysis: ",(0,i.kt)("a",{parentName:"p",href:"./Extraction"},"extraction"),"."))}p.isMDXComponent=!0}}]); \ No newline at end of file +"use strict";(self.webpackChunkns_compose_docs=self.webpackChunkns_compose_docs||[]).push([[657],{3905:(e,t,o)=>{o.d(t,{Zo:()=>d,kt:()=>h});var n=o(7294);function i(e,t,o){return t in e?Object.defineProperty(e,t,{value:o,enumerable:!0,configurable:!0,writable:!0}):e[t]=o,e}function a(e,t){var o=Object.keys(e);if(Object.getOwnPropertySymbols){var n=Object.getOwnPropertySymbols(e);t&&(n=n.filter((function(t){return Object.getOwnPropertyDescriptor(e,t).enumerable}))),o.push.apply(o,n)}return o}function r(e){for(var t=1;t<arguments.length;t++){var o=null!=arguments[t]?arguments[t]:{};t%2?a(Object(o),!0).forEach((function(t){i(e,t,o[t])})):Object.getOwnPropertyDescriptors?Object.defineProperties(e,Object.getOwnPropertyDescriptors(o)):a(Object(o)).forEach((function(t){Object.defineProperty(e,t,Object.getOwnPropertyDescriptor(o,t))}))}return e}function s(e,t){if(null==e)return{};var o,n,i=function(e,t){if(null==e)return{};var o,n,i={},a=Object.keys(e);for(n=0;n<a.length;n++)o=a[n],t.indexOf(o)>=0||(i[o]=e[o]);return i}(e,t);if(Object.getOwnPropertySymbols){var a=Object.getOwnPropertySymbols(e);for(n=0;n<a.length;n++)o=a[n],t.indexOf(o)>=0||Object.prototype.propertyIsEnumerable.call(e,o)&&(i[o]=e[o])}return i}var l=n.createContext({}),u=function(e){var t=n.useContext(l),o=t;return e&&(o="function"==typeof e?e(t):r(r({},t),e)),o},d=function(e){var t=u(e.components);return n.createElement(l.Provider,{value:t},e.children)},c="mdxType",p={inlineCode:"code",wrapper:function(e){var t=e.children;return n.createElement(n.Fragment,{},t)}},m=n.forwardRef((function(e,t){var o=e.components,i=e.mdxType,a=e.originalType,l=e.parentName,d=s(e,["components","mdxType","originalType","parentName"]),c=u(o),m=i,h=c["".concat(l,".").concat(m)]||c[m]||p[m]||a;return o?n.createElement(h,r(r({ref:t},d),{},{components:o})):n.createElement(h,r({ref:t},d))}));function h(e,t){var o=arguments,i=t&&t.mdxType;if("string"==typeof e||i){var a=o.length,r=new Array(a);r[0]=m;var s={};for(var l in t)hasOwnProperty.call(t,l)&&(s[l]=t[l]);s.originalType=e,s[c]="string"==typeof e?e:i,r[1]=s;for(var u=2;u<a;u++)r[u]=o[u];return n.createElement.apply(null,r)}return n.createElement.apply(null,o)}m.displayName="MDXCreateElement"},7979:(e,t,o)=>{o.r(t),o.d(t,{assets:()=>l,contentTitle:()=>r,default:()=>p,frontMatter:()=>a,metadata:()=>s,toc:()=>u});var n=o(7462),i=(o(7294),o(3905));const a={title:"Curation",sidebar_position:0},r="Curation",s={unversionedId:"guide/walkthrough/Project/Curation",id:"guide/walkthrough/Project/Curation",title:"Curation",description:"Curation is the first step in creating a meta-analysis, and begins by searching for and importing studies into the project. 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Next, you will ",(0,i.kt)("em",{parentName:"p"},"review")," studies for inclusion based on their relevancy to your research question. This involves ",(0,i.kt)("strong",{parentName:"p"},"excluding")," irrelevant studies, and ",(0,i.kt)("strong",{parentName:"p"},"including")," relevant ones. "),(0,i.kt)("p",null,"At the end of the process, you will be ready to create a ",(0,i.kt)("a",{parentName:"p",href:"/compose-docs/guide/glossary#studyset"},(0,i.kt)("strong",{parentName:"a"},"Studyset"))," of related studies that are amenable for neuroimaging meta-analysis"),(0,i.kt)("h2",{id:"getting-started"},"Getting Started"),(0,i.kt)("p",null,"The curation interface uses columns as a way to label studies based on their current status.\nThe left most column is the starting point and all studies imported into the project will begin there.\nThe right most column is the ",(0,i.kt)("strong",{parentName:"p"},"inclusion column")," and is the place where studies will go to be included in the meta-analysis. "),(0,i.kt)("p",null,'The goal is to get studies from the left most starting column, and narrow them down to a final subset of included studies in the right most column.\nIf a study is not eligible for inclusion at any point, it should be marked as "excluded" before reaching the inclusion column.'),(0,i.kt)("p",null,"The curation step is complete when all studies have been categorized, either by being included or excluded."),(0,i.kt)("p",null,"When you first begin ",(0,i.kt)("em",{parentName:"p"},"Curation"),", you will choose between different workflows, which vary in how rigorous or systematic the selection of studies will be."),(0,i.kt)("admonition",{title:"How specific to be?",type:"tip"},(0,i.kt)("p",{parentName:"admonition"},"Performing a systematic meta-analysis involves a substantial amount of effort. It is up to you, the researcher, how rigorous to be in this process. We reccomend thinking about your ",(0,i.kt)("em",{parentName:"p"},"goals")," prior to starting this process so that you can have clear inclusion guidelines. If you are looking for an exploratory analysis, we reccomend following the tutorial for ",(0,i.kt)("em",{parentName:"p"},"automated meta-analysis"),", which replaces manual curation with an automated selection of studies. Note that automated meta-analyses are not a replacement for a careful systematic meta-analysis.")),(0,i.kt)("h3",{id:"prisma-workflow"},"PRISMA Workflow"),(0,i.kt)("p",null,"PRISMA stands for the ",(0,i.kt)("strong",{parentName:"p"},"Preferred Reporting Items for Systematic Review and Meta-Analyses"),". The\n",(0,i.kt)("a",{parentName:"p",href:"http://www.prisma-statement.org/?AspxAutoDetectCookieSupport=1"},"PRISMA guidelines")," are a set of rules for reporting a\nsystematic review, and are the gold standard for producing a proper, rigorous, and transparent meta-analysis."),(0,i.kt)("p",null,"If you are trying to create a rigorous ",(0,i.kt)("a",{parentName:"p",href:"/compose-docs/tutorial/manual"},"PRISMA compliant manual meta-analysis")," you will want to select this option."),(0,i.kt)("p",null,"When you select this option, neurosynth-compose will automatically initialize the curation step with 4 distinct columns as\ndictated by PRISMA guidelines: ",(0,i.kt)("strong",{parentName:"p"},"Identification, Screening, Eligibility, Included"),"."),(0,i.kt)("p",null,"After importing studies into neurosynth, they will be placed into the identification column and studies are triaged from there."),(0,i.kt)("admonition",{title:"PRISMA Summary",type:"info"},(0,i.kt)("p",{parentName:"admonition"},"The ",(0,i.kt)("strong",{parentName:"p"},"Identification")," column is where all imported studies are deposited into initially. As alluded to by the name, the identification\ncolumn is where you identify all records yielded from your search. In this column, you wil exclude studies purely based on whether they are\nduplicates of existing studies. All other studies are promoted."),(0,i.kt)("p",{parentName:"admonition"},"The ",(0,i.kt)("strong",{parentName:"p"},"Screening")," column consists of all records that have been screened for duplicates. In this column, you want to review the titles/abstracts of studies\nand exclude purely based on whether they are irrelevant to your research question or domain. All other studies are promoted. "),(0,i.kt)("p",{parentName:"admonition"},"The ",(0,i.kt)("strong",{parentName:"p"},"Eligibility")," column consists of all records that have been screened for duplicates and irrelevant content. In this column, you want to\nreview the full text of studies and exclude based on whether the study described aligns with the standards of the meta-analysis itself. Reasons\nfor exclusion may include wrong setting, wrong patient population, wrong intervention, wrong paragdigm, etc."),(0,i.kt)("p",{parentName:"admonition"},"The ",(0,i.kt)("strong",{parentName:"p"},"Included")," column consists of all records that have passed previous levels of exclusion and can be considered for the next step of the project."),(0,i.kt)("p",{parentName:"admonition"},"For more information, consult the ",(0,i.kt)("a",{parentName:"p",href:"http://www.prisma-statement.org/?AspxAutoDetectCookieSupport=1"},"PRISMA guidelines"),".")),(0,i.kt)("h3",{id:"simple-workflow"},"Simple Workflow"),(0,i.kt)("p",null,"If you want to create a semi-automated meta-analysis (i.e. perform manual review on a large-scale study search), you'll want to select this option."),(0,i.kt)("p",null,"This workflow is initalized with only two columns. As before, the left most column is where studies will be placed when they are imported. However, unlike a full PRISMA workflow, all exclusion occurs in this column. All studies not excluded are then promoted to the right most column for inclusion into the meta-analysis."),(0,i.kt)("h2",{id:"importing"},"Importing"),(0,i.kt)("p",null,"To begin importing studies into your project clicking the ",(0,i.kt)("strong",{parentName:"p"},"IMPORT STUDIES")," button."),(0,i.kt)("p",null,"You will be asked to choose a source, name your import, and address\nany potential duplicate studies."),(0,i.kt)("admonition",{type:"tip"},(0,i.kt)("p",{parentName:"admonition"},"We recommend giving each import a meaningful name. This will be useful when you come back\nand want to know where a certain study was imported from.")),(0,i.kt)("h3",{id:"import-from-neurostore"},"Import from Neurostore"),(0,i.kt)("p",null,"Neurostore indexes a large number of neuroimaging studies which are ready for meta-analysis. Studies in Neurostore have been pre-processed, including extracting peak activation coordinates from Tables in the text, and computing semantic features from the abstract/full text. Neurostore also indexes studies which other users have annotated and made available to others for re-use."),(0,i.kt)("p",null,"Importing from Neurostore utilizes the Study search UI similar to the ",(0,i.kt)("a",{parentName:"p",href:"https://compose.neurosynth.org/studies"},"Study Page"),".\nAfter entering your search, click the bottom right button to import the searched studies into your project."),(0,i.kt)("admonition",{type:"tip"},(0,i.kt)("p",{parentName:"admonition"},"Importing from Neurostore can save you a lot of time, as these studies are much more likely to be amenable to meta-analysis, and have pre-extracted coordinates. However, note that some manual annotation may still be required to verify the coordinate extraction, and choose the relevant Analysis (i.e. contrast) for final inclusion.")),(0,i.kt)("h3",{id:"import-from-pubmed"},"Import from PubMed"),(0,i.kt)("p",null,"Use this option to import studies directly from PubMed. To start, you need to go to the ",(0,i.kt)("a",{parentName:"p",href:"https://pubmed.ncbi.nlm.nih.gov/"},"PubMed Site"),"\nand either enter in a search or navigate to a previously created collection. "),(0,i.kt)("p",null,"To import the search or collection from PubMed into neurosynth-compose, you will need a text file containing a list of PMIDs.\nYou can obtain this by going to your collection/search and clicking the ",(0,i.kt)("strong",{parentName:"p"},"Save")," button. 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margin-vert--lg"><div class="row"><aside class="col col--3"><nav class="sidebar_re4s thin-scrollbar" aria-label="Blog recent posts navigation"><div class="sidebarItemTitle_pO2u margin-bottom--md">Recent posts</div><ul class="sidebarItemList_Yudw clean-list"><li class="sidebarItem__DBe"><a class="sidebarItemLink_mo7H" href="/compose-docs/blog/announcing-ns-compose">Announcing Neurosynth Compose!</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="title_f1Hy" itemprop="headline"><a itemprop="url" href="/compose-docs/blog/announcing-ns-compose">Announcing Neurosynth Compose!</a></h2><div class="container_mt6G margin-vert--md"><time datetime="2023-08-13T00:00:00.000Z" itemprop="datePublished">August 13, 2023</time> · <!-- -->3 min read</div><div class="margin-top--md margin-bottom--sm row"><div class="col col--6 authorCol_Hf19"><div class="avatar margin-bottom--sm"><a href="https://github.com/adelavega" target="_blank" rel="noopener noreferrer" class="avatar__photo-link"><img class="avatar__photo" src="https://github.com/adelavega.png" alt="Alejandro de la Vega"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://github.com/adelavega" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Alejandro de la Vega</span></a></div><small class="avatar__subtitle" itemprop="description">Research Scientist</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Dear Neurosynth Community,</p><p>My name is Alejandro, and I am the current project leader of the Neurosynth project.</p><p>I am very excited to announce to you that the Neurosynth project lives on, and we are officially announcing the (beta) release of the latest member of the ecosystem: Neurosynth Compose.</p><p><em>Neurosynth Compose</em> enables users to easily perform custom neuroimaging meta-analyses using a web-based platform, with no programming experience required. This project addresses one of the most commonly request features, which is the ability to customize large-scale meta-analyses using you own expert knowledge.</p><p><em>Neurosynth Compose</em> is <em>free to use</em> and helps users:</p><ul><li>🔎 <strong>Search</strong> across over 20,000 studies in the Neurosynth database, or import from external databses such as PubMed.</li><li>🗃️ <strong>Curate</strong> your StudySet using systematic review tools conforming to the <a href="https://www.prisma-statement.org/" target="_blank" rel="noopener noreferrer">PRISMA</a> guidelines.</li><li>📝 <strong>Extract</strong> coordinates and metadata for each study, leveraging thousands of pre-extracted studies to minimize effort.</li><li>📊 <strong>Analyze</strong> by specifying a reproducible <a href="https://readthedocs.org/projects/nimare/" target="_blank" rel="noopener noreferrer">NiMARE</a> workflow, and execute it locally or in the cloud.</li><li>🔗 <strong>Share</strong> with the community with complete provenance and reproducibility.</li></ul><p>The goal of <em>Neurosynth Compose</em> is to enable researchers to go beyond the finite set of automatically generated meta-analyses from the original platform and overcome limitations from automated coordinate and semantic extraction. The end result is a gold standard meta-analysis, in much less time than a manual workflow, and with much greater reproducible. </p><p>Currently, <em>Neurosynth Compose</em> is in beta, and under active development. We welcome feedback to ensure our platform meets the needs of the community. Please leave us feedback using the button on the bottom right corner of the screen!</p><p>We are working on several upcoming features that will make the platform even better. Many of these features are already available in our Python meta-analysis library, NiMARE, and we are actively working on the user facing online interfaces.</p><ul><li><strong>Image-based Meta-Analysis (IBMA)</strong>. We have developed algorithms in NiMARE for using whole-brain statistical maps as inputs to meta-analysis. This is more powerful and sensitive technique compared to Coordinate-base Meta-Analysis. Soon, you will be able to use NeuroVault data as inputs for your meta-analyses.</li><li><strong>MKDA Chi-squared / Association test</strong>. A hallmark feature of Neurosynth is the ability to relate meta-analytic findings to the rest of the literature, to determine the strength and specificity of an association (this was previously called "reverse inference"). This will soon be possible on your custom meta-analyses.</li><li><strong>A wide range of improvements to the user experience</strong>. We are in the process of re-working parts of the online interface to decrease friction when creating a StudySet, making study utilization, and editing more intuitive. </li></ul><p>I would like to thank everyone involved in this highly-collaborative project, but especially James Kent, a postdoctoral fellow, and Nick Lee, a software engineer, who did the lion's share of the work.</p><p>We are excited for you to try it and let us know what you think.</p><p>-Alejandro</p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><ul class="tags_jXut padding--none margin-left--sm"><li class="tag_QGVx"><a class="tag_zVej tagRegular_sFm0" href="/compose-docs/blog/tags/hello">hello</a></li><li class="tag_QGVx"><a class="tag_zVej tagRegular_sFm0" href="/compose-docs/blog/tags/neurosynth">neurosynth</a></li></ul></div></footer></article><nav class="pagination-nav" aria-label="Blog list page navigation"></nav></main></div></div></div><footer class="footer footer--dark"><div 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margin-vert--lg"><div class="row"><aside class="col col--3"><nav class="sidebar_re4s thin-scrollbar" aria-label="Blog recent posts navigation"><div class="sidebarItemTitle_pO2u margin-bottom--md">Recent posts</div><ul class="sidebarItemList_Yudw clean-list"><li class="sidebarItem__DBe"><a aria-current="page" class="sidebarItemLink_mo7H sidebarItemLinkActive_I1ZP" href="/compose-docs/blog/announcing-ns-compose">Announcing Neurosynth Compose!</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><article itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h1 class="title_f1Hy" itemprop="headline">Announcing Neurosynth Compose!</h1><div class="container_mt6G margin-vert--md"><time datetime="2023-08-13T00:00:00.000Z" itemprop="datePublished">August 13, 2023</time> · <!-- -->3 min read</div><div class="margin-top--md margin-bottom--sm row"><div class="col col--6 authorCol_Hf19"><div class="avatar margin-bottom--sm"><a href="https://github.com/adelavega" target="_blank" rel="noopener noreferrer" class="avatar__photo-link"><img class="avatar__photo" src="https://github.com/adelavega.png" alt="Alejandro de la Vega"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://github.com/adelavega" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Alejandro de la Vega</span></a></div><small class="avatar__subtitle" itemprop="description">Research Scientist</small></div></div></div></div></header><div id="post-content" class="markdown" itemprop="articleBody"><p>Dear Neurosynth Community,</p><p>My name is Alejandro, and I am the current project leader of the Neurosynth project.</p><p>I am very excited to announce to you that the Neurosynth project lives on, and we are officially announcing the (beta) release of the latest member of the ecosystem: Neurosynth Compose.</p><p><em>Neurosynth Compose</em> enables users to easily perform custom neuroimaging meta-analyses using a web-based platform, with no programming experience required. This project addresses one of the most commonly request features, which is the ability to customize large-scale meta-analyses using you own expert knowledge.</p><p><em>Neurosynth Compose</em> is <em>free to use</em> and helps users:</p><ul><li>🔎 <strong>Search</strong> across over 20,000 studies in the Neurosynth database, or import from external databses such as PubMed.</li><li>🗃️ <strong>Curate</strong> your StudySet using systematic review tools conforming to the <a href="https://www.prisma-statement.org/" target="_blank" rel="noopener noreferrer">PRISMA</a> guidelines.</li><li>📝 <strong>Extract</strong> coordinates and metadata for each study, leveraging thousands of pre-extracted studies to minimize effort.</li><li>📊 <strong>Analyze</strong> by specifying a reproducible <a href="https://readthedocs.org/projects/nimare/" target="_blank" rel="noopener noreferrer">NiMARE</a> workflow, and execute it locally or in the cloud.</li><li>🔗 <strong>Share</strong> with the community with complete provenance and reproducibility.</li></ul><p>The goal of <em>Neurosynth Compose</em> is to enable researchers to go beyond the finite set of automatically generated meta-analyses from the original platform and overcome limitations from automated coordinate and semantic extraction. The end result is a gold standard meta-analysis, in much less time than a manual workflow, and with much greater reproducible. </p><p>Currently, <em>Neurosynth Compose</em> is in beta, and under active development. We welcome feedback to ensure our platform meets the needs of the community. Please leave us feedback using the button on the bottom right corner of the screen!</p><p>We are working on several upcoming features that will make the platform even better. Many of these features are already available in our Python meta-analysis library, NiMARE, and we are actively working on the user facing online interfaces.</p><ul><li><strong>Image-based Meta-Analysis (IBMA)</strong>. We have developed algorithms in NiMARE for using whole-brain statistical maps as inputs to meta-analysis. This is more powerful and sensitive technique compared to Coordinate-base Meta-Analysis. Soon, you will be able to use NeuroVault data as inputs for your meta-analyses.</li><li><strong>MKDA Chi-squared / Association test</strong>. A hallmark feature of Neurosynth is the ability to relate meta-analytic findings to the rest of the literature, to determine the strength and specificity of an association (this was previously called "reverse inference"). This will soon be possible on your custom meta-analyses.</li><li><strong>A wide range of improvements to the user experience</strong>. We are in the process of re-working parts of the online interface to decrease friction when creating a StudySet, making study utilization, and editing more intuitive. </li></ul><p>I would like to thank everyone involved in this highly-collaborative project, but especially James Kent, a postdoctoral fellow, and Nick Lee, a software engineer, who did the lion's share of the work.</p><p>We are excited for you to try it and let us know what you think.</p><p>-Alejandro</p></div><footer class="row docusaurus-mt-lg blogPostFooterDetailsFull_mRVl"><div class="col"><b>Tags:</b><ul class="tags_jXut padding--none margin-left--sm"><li class="tag_QGVx"><a class="tag_zVej tagRegular_sFm0" href="/compose-docs/blog/tags/hello">hello</a></li><li class="tag_QGVx"><a class="tag_zVej tagRegular_sFm0" href="/compose-docs/blog/tags/neurosynth">neurosynth</a></li></ul></div><div class="col margin-top--sm"><a href="https://github.com/neurostuff/compose-docs/edit/master/blog/2023-08-13-announcing.md" 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Compose!</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><header class="margin-bottom--xl"><h1>One post tagged with "hello"</h1><a href="/compose-docs/blog/tags">View All Tags</a></header><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="title_f1Hy" itemprop="headline"><a itemprop="url" href="/compose-docs/blog/announcing-ns-compose">Announcing Neurosynth Compose!</a></h2><div class="container_mt6G margin-vert--md"><time datetime="2023-08-13T00:00:00.000Z" itemprop="datePublished">August 13, 2023</time> · <!-- -->3 min read</div><div class="margin-top--md margin-bottom--sm row"><div class="col col--6 authorCol_Hf19"><div class="avatar margin-bottom--sm"><a href="https://github.com/adelavega" target="_blank" rel="noopener noreferrer" class="avatar__photo-link"><img class="avatar__photo" src="https://github.com/adelavega.png" alt="Alejandro de la Vega"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://github.com/adelavega" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Alejandro de la Vega</span></a></div><small class="avatar__subtitle" itemprop="description">Research Scientist</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Dear Neurosynth Community,</p><p>My name is Alejandro, and I am the current project leader of the Neurosynth project.</p><p>I am very excited to announce to you that the Neurosynth project lives on, and we are officially announcing the (beta) release of the latest member of the ecosystem: Neurosynth Compose.</p><p><em>Neurosynth Compose</em> enables users to easily perform custom neuroimaging meta-analyses using a web-based platform, with no programming experience required. This project addresses one of the most commonly request features, which is the ability to customize large-scale meta-analyses using you own expert knowledge.</p><p><em>Neurosynth Compose</em> is <em>free to use</em> and helps users:</p><ul><li>🔎 <strong>Search</strong> across over 20,000 studies in the Neurosynth database, or import from external databses such as PubMed.</li><li>🗃️ <strong>Curate</strong> your StudySet using systematic review tools conforming to the <a href="https://www.prisma-statement.org/" target="_blank" rel="noopener noreferrer">PRISMA</a> guidelines.</li><li>📝 <strong>Extract</strong> coordinates and metadata for each study, leveraging thousands of pre-extracted studies to minimize effort.</li><li>📊 <strong>Analyze</strong> by specifying a reproducible <a href="https://readthedocs.org/projects/nimare/" target="_blank" rel="noopener noreferrer">NiMARE</a> workflow, and execute it locally or in the cloud.</li><li>🔗 <strong>Share</strong> with the community with complete provenance and reproducibility.</li></ul><p>The goal of <em>Neurosynth Compose</em> is to enable researchers to go beyond the finite set of automatically generated meta-analyses from the original platform and overcome limitations from automated coordinate and semantic extraction. The end result is a gold standard meta-analysis, in much less time than a manual workflow, and with much greater reproducible. </p><p>Currently, <em>Neurosynth Compose</em> is in beta, and under active development. We welcome feedback to ensure our platform meets the needs of the community. Please leave us feedback using the button on the bottom right corner of the screen!</p><p>We are working on several upcoming features that will make the platform even better. Many of these features are already available in our Python meta-analysis library, NiMARE, and we are actively working on the user facing online interfaces.</p><ul><li><strong>Image-based Meta-Analysis (IBMA)</strong>. We have developed algorithms in NiMARE for using whole-brain statistical maps as inputs to meta-analysis. This is more powerful and sensitive technique compared to Coordinate-base Meta-Analysis. Soon, you will be able to use NeuroVault data as inputs for your meta-analyses.</li><li><strong>MKDA Chi-squared / Association test</strong>. A hallmark feature of Neurosynth is the ability to relate meta-analytic findings to the rest of the literature, to determine the strength and specificity of an association (this was previously called "reverse inference"). This will soon be possible on your custom meta-analyses.</li><li><strong>A wide range of improvements to the user experience</strong>. We are in the process of re-working parts of the online interface to decrease friction when creating a StudySet, making study utilization, and editing more intuitive. </li></ul><p>I would like to thank everyone involved in this highly-collaborative project, but especially James Kent, a postdoctoral fellow, and Nick Lee, a software engineer, who did the lion's share of the work.</p><p>We are excited for you to try it and let us know what you think.</p><p>-Alejandro</p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><ul class="tags_jXut padding--none margin-left--sm"><li class="tag_QGVx"><a class="tag_zVej tagRegular_sFm0" href="/compose-docs/blog/tags/hello">hello</a></li><li class="tag_QGVx"><a class="tag_zVej tagRegular_sFm0" href="/compose-docs/blog/tags/neurosynth">neurosynth</a></li></ul></div></footer></article><nav class="pagination-nav" aria-label="Blog list page navigation"></nav></main></div></div></div><footer class="footer footer--dark"><div 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Compose!</a></li></ul></nav></aside><main class="col col--7" itemscope="" itemtype="http://schema.org/Blog"><header class="margin-bottom--xl"><h1>One post tagged with "neurosynth"</h1><a href="/compose-docs/blog/tags">View All Tags</a></header><article class="margin-bottom--xl" itemprop="blogPost" itemscope="" itemtype="http://schema.org/BlogPosting"><header><h2 class="title_f1Hy" itemprop="headline"><a itemprop="url" href="/compose-docs/blog/announcing-ns-compose">Announcing Neurosynth Compose!</a></h2><div class="container_mt6G margin-vert--md"><time datetime="2023-08-13T00:00:00.000Z" itemprop="datePublished">August 13, 2023</time> · <!-- -->3 min read</div><div class="margin-top--md margin-bottom--sm row"><div class="col col--6 authorCol_Hf19"><div class="avatar margin-bottom--sm"><a href="https://github.com/adelavega" target="_blank" rel="noopener noreferrer" class="avatar__photo-link"><img class="avatar__photo" src="https://github.com/adelavega.png" alt="Alejandro de la Vega"></a><div class="avatar__intro" itemprop="author" itemscope="" itemtype="https://schema.org/Person"><div class="avatar__name"><a href="https://github.com/adelavega" target="_blank" rel="noopener noreferrer" itemprop="url"><span itemprop="name">Alejandro de la Vega</span></a></div><small class="avatar__subtitle" itemprop="description">Research Scientist</small></div></div></div></div></header><div class="markdown" itemprop="articleBody"><p>Dear Neurosynth Community,</p><p>My name is Alejandro, and I am the current project leader of the Neurosynth project.</p><p>I am very excited to announce to you that the Neurosynth project lives on, and we are officially announcing the (beta) release of the latest member of the ecosystem: Neurosynth Compose.</p><p><em>Neurosynth Compose</em> enables users to easily perform custom neuroimaging meta-analyses using a web-based platform, with no programming experience required. This project addresses one of the most commonly request features, which is the ability to customize large-scale meta-analyses using you own expert knowledge.</p><p><em>Neurosynth Compose</em> is <em>free to use</em> and helps users:</p><ul><li>🔎 <strong>Search</strong> across over 20,000 studies in the Neurosynth database, or import from external databses such as PubMed.</li><li>🗃️ <strong>Curate</strong> your StudySet using systematic review tools conforming to the <a href="https://www.prisma-statement.org/" target="_blank" rel="noopener noreferrer">PRISMA</a> guidelines.</li><li>📝 <strong>Extract</strong> coordinates and metadata for each study, leveraging thousands of pre-extracted studies to minimize effort.</li><li>📊 <strong>Analyze</strong> by specifying a reproducible <a href="https://readthedocs.org/projects/nimare/" target="_blank" rel="noopener noreferrer">NiMARE</a> workflow, and execute it locally or in the cloud.</li><li>🔗 <strong>Share</strong> with the community with complete provenance and reproducibility.</li></ul><p>The goal of <em>Neurosynth Compose</em> is to enable researchers to go beyond the finite set of automatically generated meta-analyses from the original platform and overcome limitations from automated coordinate and semantic extraction. The end result is a gold standard meta-analysis, in much less time than a manual workflow, and with much greater reproducible. </p><p>Currently, <em>Neurosynth Compose</em> is in beta, and under active development. We welcome feedback to ensure our platform meets the needs of the community. Please leave us feedback using the button on the bottom right corner of the screen!</p><p>We are working on several upcoming features that will make the platform even better. Many of these features are already available in our Python meta-analysis library, NiMARE, and we are actively working on the user facing online interfaces.</p><ul><li><strong>Image-based Meta-Analysis (IBMA)</strong>. We have developed algorithms in NiMARE for using whole-brain statistical maps as inputs to meta-analysis. This is more powerful and sensitive technique compared to Coordinate-base Meta-Analysis. Soon, you will be able to use NeuroVault data as inputs for your meta-analyses.</li><li><strong>MKDA Chi-squared / Association test</strong>. A hallmark feature of Neurosynth is the ability to relate meta-analytic findings to the rest of the literature, to determine the strength and specificity of an association (this was previously called "reverse inference"). This will soon be possible on your custom meta-analyses.</li><li><strong>A wide range of improvements to the user experience</strong>. We are in the process of re-working parts of the online interface to decrease friction when creating a StudySet, making study utilization, and editing more intuitive. </li></ul><p>I would like to thank everyone involved in this highly-collaborative project, but especially James Kent, a postdoctoral fellow, and Nick Lee, a software engineer, who did the lion's share of the work.</p><p>We are excited for you to try it and let us know what you think.</p><p>-Alejandro</p></div><footer class="row docusaurus-mt-lg"><div class="col"><b>Tags:</b><ul class="tags_jXut padding--none margin-left--sm"><li class="tag_QGVx"><a class="tag_zVej tagRegular_sFm0" href="/compose-docs/blog/tags/hello">hello</a></li><li class="tag_QGVx"><a class="tag_zVej tagRegular_sFm0" href="/compose-docs/blog/tags/neurosynth">neurosynth</a></li></ul></div></footer></article><nav class="pagination-nav" aria-label="Blog list page navigation"></nav></main></div></div></div><footer class="footer footer--dark"><div 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An analysis also contains the results of the statistical contrast either with an image and/or a table -indicating significant results </p><h2 class="anchor anchorWithStickyNavbar_LWe7" id="condition">Condition<a href="#condition" class="hash-link" aria-label="Direct link to Condition" title="Direct link to Condition"></a></h2><h3 class="anchor anchorWithStickyNavbar_LWe7" id="overview-4">Overview<a href="#overview-4" class="hash-link" aria-label="Direct link to Overview" title="Direct link to Overview"></a></h3><p>A condition is term/word that represents a psychological (e.g., 2-back), physical (e.g., biking)</p><h2 class="anchor anchorWithStickyNavbar_LWe7" id="weights">Weights<a href="#weights" class="hash-link" aria-label="Direct link to Weights" title="Direct link to Weights"></a></h2><h2 class="anchor anchorWithStickyNavbar_LWe7" id="point">Point<a href="#point" class="hash-link" aria-label="Direct link to Point" title="Direct link to Point"></a></h2><h3 class="anchor 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padding-bottom--lg"><div class="row"><div class="col docItemCol_VOVn"><div class="docItemContainer_Djhp"><article><nav class="theme-doc-breadcrumbs breadcrumbsContainer_Z_bl" aria-label="Breadcrumbs"><ul class="breadcrumbs" itemscope="" itemtype="https://schema.org/BreadcrumbList"><li class="breadcrumbs__item"><a aria-label="Home page" class="breadcrumbs__link" href="/compose-docs/"><svg viewBox="0 0 24 24" class="breadcrumbHomeIcon_YNFT"><path d="M10 19v-5h4v5c0 .55.45 1 1 1h3c.55 0 1-.45 1-1v-7h1.7c.46 0 .68-.57.33-.87L12.67 3.6c-.38-.34-.96-.34-1.34 0l-8.36 7.53c-.34.3-.13.87.33.87H5v7c0 .55.45 1 1 1h3c.55 0 1-.45 1-1z" fill="currentColor"></path></svg></a></li><li itemscope="" itemprop="itemListElement" itemtype="https://schema.org/ListItem" class="breadcrumbs__item"><a class="breadcrumbs__link" itemprop="item" href="/compose-docs/guide"><span itemprop="name">User Guide</span></a><meta itemprop="position" content="1"></li><li itemscope="" itemprop="itemListElement" 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.68-.57.33-.87L12.67 3.6c-.38-.34-.96-.34-1.34 0l-8.36 7.53c-.34.3-.13.87.33.87H5v7c0 .55.45 1 1 1h3c.55 0 1-.45 1-1z" fill="currentColor"></path></svg></a></li><li itemscope="" itemprop="itemListElement" itemtype="https://schema.org/ListItem" class="breadcrumbs__item"><a class="breadcrumbs__link" itemprop="item" href="/compose-docs/guide"><span itemprop="name">User Guide</span></a><meta itemprop="position" content="1"></li><li itemscope="" itemprop="itemListElement" itemtype="https://schema.org/ListItem" class="breadcrumbs__item breadcrumbs__item--active"><span class="breadcrumbs__link" itemprop="name">Walkthrough</span><meta itemprop="position" content="2"></li></ul></nav><div class="theme-doc-markdown markdown"><h1>Walkthrough</h1><p>This is a comprehensive walkthrough and reference for each page of Neurosynth Compose.</p><p>If you're looking for a quickstart, check out our <a href="/compose-docs/tutorial">Tutorials</a>.</p><section class="row"><article class="col col--6 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class="breadcrumbHomeIcon_YNFT"><path d="M10 19v-5h4v5c0 .55.45 1 1 1h3c.55 0 1-.45 1-1v-7h1.7c.46 0 .68-.57.33-.87L12.67 3.6c-.38-.34-.96-.34-1.34 0l-8.36 7.53c-.34.3-.13.87.33.87H5v7c0 .55.45 1 1 1h3c.55 0 1-.45 1-1z" fill="currentColor"></path></svg></a></li><li itemscope="" itemprop="itemListElement" itemtype="https://schema.org/ListItem" class="breadcrumbs__item"><a class="breadcrumbs__link" itemprop="item" href="/compose-docs/guide"><span itemprop="name">User Guide</span></a><meta itemprop="position" content="1"></li><li itemscope="" itemprop="itemListElement" itemtype="https://schema.org/ListItem" class="breadcrumbs__item"><a class="breadcrumbs__link" itemprop="item" href="/compose-docs/guide/walkthrough"><span itemprop="name">Walkthrough</span></a><meta itemprop="position" content="2"></li><li itemscope="" itemprop="itemListElement" itemtype="https://schema.org/ListItem" class="breadcrumbs__item breadcrumbs__item--active"><span class="breadcrumbs__link" itemprop="name">Project</span><meta itemprop="position" content="3"></li></ul></nav><div class="theme-doc-markdown markdown"><h1>Project</h1><p>A project organizes the the various steps needed to create a meta-analysis from start to finish.</p><p>Within a project you will be able to:</p><ol><li><strong><a href="/compose-docs/guide/walkthrough/Project/Curation">Curate</a></strong> studies of interest and select the ones to be included in the meta-analysis </li><li><strong><a href="/compose-docs/guide/walkthrough/Project/Extraction">Extract</a></strong> the relevant data such as activation coordinates and other meta-data</li><li><strong><a href="/compose-docs/guide/walkthrough/Project/Specification">Specify</a></strong> the algorithm and corrector you would like to use</li><li><strong>Run</strong> the meta-analysis and <strong>View</strong> the results</li></ol><p>In each project, you can define a define a single StudySe (i.e. a collection of related studies), and one or more MetaAnalysis specifications.</p><p>You can open a specific project by logging in, navigating to the <a href="https://compose.neurosynth.org/projects" target="_blank" rel="noopener noreferrer">My Projects</a> page, and selecting a project you've created. </p><p>When you view a project for the first time, you'll notice that you'll default to the "Edit Project" tab. The "View Meta-Analyses" tab will be disabled and will become enabled when you have created the first meta-analysis specification -for the project.</p></div><footer class="theme-doc-footer docusaurus-mt-lg"><div class="theme-doc-footer-edit-meta-row row"><div class="col"><a href="https://github.com/neurostuff/compose-docs/edit/master/docs/guide/walkthrough/Project/index.mdx" target="_blank" rel="noreferrer noopener" class="theme-edit-this-page"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_Z9Sw" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col lastUpdated_vwxv"><span class="theme-last-updated">Last updated<!-- --> on <b><time datetime="2023-11-27T23:56:16.000Z">Nov 27, 2023</time></b> by <b>Alejandro de la Vega</b></span></div></div></footer></article><nav 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4.172v-11z"></path></svg></a></li></ul></div></div><div class="footer__bottom text--center"><div class="footer__copyright">Copyright © 2023 Neuroinformatics Lab, Inc.</div></div></div></footer></div> +<script src="/compose-docs/assets/js/runtime~main.710cc351.js"></script> <script src="/compose-docs/assets/js/main.660f8467.js"></script> </body> </html> \ No newline at end of file diff --git a/guide/walkthrough/Project/Curation.html b/guide/walkthrough/Project/Curation.html index 3c2b655..cb616ee 100644 --- a/guide/walkthrough/Project/Curation.html +++ b/guide/walkthrough/Project/Curation.html @@ -5,7 +5,7 @@ <meta name="generator" content="Docusaurus v2.3.1"> <title data-rh="true">Curation | Neurosynth Compose Docs</title><meta data-rh="true" name="viewport" content="width=device-width,initial-scale=1"><meta data-rh="true" name="twitter:card" content="summary_large_image"><meta data-rh="true" property="og:image" content="https://neurostuff.github.io/compose-docs/img/docusaurus-social-card.jpg"><meta data-rh="true" name="twitter:image" content="https://neurostuff.github.io/compose-docs/img/docusaurus-social-card.jpg"><meta data-rh="true" property="og:url" content="https://neurostuff.github.io/compose-docs/guide/walkthrough/Project/Curation"><meta data-rh="true" name="docusaurus_locale" content="en"><meta data-rh="true" name="docsearch:language" content="en"><meta data-rh="true" name="docusaurus_version" content="current"><meta data-rh="true" name="docusaurus_tag" content="docs-default-current"><meta data-rh="true" name="docsearch:version" content="current"><meta data-rh="true" name="docsearch:docusaurus_tag" content="docs-default-current"><meta data-rh="true" property="og:title" content="Curation | Neurosynth Compose Docs"><meta data-rh="true" name="description" content="Curation is the first step in creating a meta-analysis, and begins by searching for and importing studies into the project. Next, you will review studies for inclusion based on their relevancy to your research question. This involves excluding irrelevant studies, and including relevant ones."><meta data-rh="true" property="og:description" content="Curation is the first step in creating a meta-analysis, and begins by searching for and importing studies into the project. Next, you will review studies for inclusion based on their relevancy to your research question. This involves excluding irrelevant studies, and including relevant ones."><link data-rh="true" rel="icon" href="/compose-docs/img/favicon.ico"><link data-rh="true" rel="canonical" href="https://neurostuff.github.io/compose-docs/guide/walkthrough/Project/Curation"><link data-rh="true" rel="alternate" href="https://neurostuff.github.io/compose-docs/guide/walkthrough/Project/Curation" hreflang="en"><link data-rh="true" rel="alternate" href="https://neurostuff.github.io/compose-docs/guide/walkthrough/Project/Curation" hreflang="x-default"><link rel="alternate" type="application/rss+xml" href="/compose-docs/blog/rss.xml" title="Neurosynth Compose Docs RSS Feed"> <link rel="alternate" type="application/atom+xml" href="/compose-docs/blog/atom.xml" title="Neurosynth Compose Docs Atom Feed"><link rel="stylesheet" href="/compose-docs/assets/css/styles.cce6c2a6.css"> -<link rel="preload" href="/compose-docs/assets/js/runtime~main.7d2821c4.js" as="script"> +<link rel="preload" href="/compose-docs/assets/js/runtime~main.710cc351.js" as="script"> <link rel="preload" href="/compose-docs/assets/js/main.660f8467.js" as="script"> </head> <body class="navigation-with-keyboard"> @@ -35,8 +35,8 @@ along with the following options: <strong>PROMOTE, NEEDS REVIEW</strong>, and <strong>EXCLUDE</strong>. There is also a button to <strong>ADD TAGS</strong> which will assign an informational tag to the study.</p><h3 class="anchor anchorWithStickyNavbar_LWe7" id="exclude">Exclude<a href="#exclude" class="hash-link" aria-label="Direct link to Exclude" title="Direct link to Exclude"></a></h3><p>To exclude a study, click the <strong>EXCLUDE</strong> button and select the exclusion reason. You can either choose from the preset exclusion reasons or you can begin typing to create a new one.</p><div class="theme-admonition theme-admonition-tip alert alert--success admonition_LlT9"><div class="admonitionHeading_tbUL"><span class="admonitionIcon_kALy"><svg viewBox="0 0 12 16"><path fill-rule="evenodd" d="M6.5 0C3.48 0 1 2.19 1 5c0 .92.55 2.25 1 3 1.34 2.25 1.78 2.78 2 4v1h5v-1c.22-1.22.66-1.75 2-4 .45-.75 1-2.08 1-3 0-2.81-2.48-5-5.5-5zm3.64 7.48c-.25.44-.47.8-.67 1.11-.86 1.41-1.25 2.06-1.45 3.23-.02.05-.02.11-.02.17H5c0-.06 0-.13-.02-.17-.2-1.17-.59-1.83-1.45-3.23-.2-.31-.42-.67-.67-1.11C2.44 6.78 2 5.65 2 5c0-2.2 2.02-4 4.5-4 1.22 0 2.36.42 3.22 1.19C10.55 2.94 11 3.94 11 5c0 .66-.44 1.78-.86 2.48zM4 14h5c-.23 1.14-1.3 2-2.5 2s-2.27-.86-2.5-2z"></path></svg></span>tip</div><div class="admonitionContent_S0QG"><p>For the PRISMA workflow, the default exclusion reason wil depend on the phase you are in (identification vs screening vs eligibility), to match the PRISMA guidelines. While we do not recommend it, you can click the arrow button and start typing in the input to create a new exclusion reason. Revisit the <a href="/compose-docs/guide/walkthrough/Project/Curation#prisma-workflow">PRISMA workflow</a> to review reccomended exclusion criteria.</p></div></div><h3 class="anchor anchorWithStickyNavbar_LWe7" id="promote">Promote<a href="#promote" class="hash-link" aria-label="Direct link to Promote" title="Direct link to Promote"></a></h3><p>If a study meets inclusion critera (for the current phase), click <strong>PROMOTE</strong> to move the study forward to the next curation column. If it is moved into the right most inclusion column, then it will be included in the meta-analysis.</p><div class="theme-admonition theme-admonition-tip alert alert--success admonition_LlT9"><div class="admonitionHeading_tbUL"><span class="admonitionIcon_kALy"><svg viewBox="0 0 12 16"><path fill-rule="evenodd" d="M6.5 0C3.48 0 1 2.19 1 5c0 .92.55 2.25 1 3 1.34 2.25 1.78 2.78 2 4v1h5v-1c.22-1.22.66-1.75 2-4 .45-.75 1-2.08 1-3 0-2.81-2.48-5-5.5-5zm3.64 7.48c-.25.44-.47.8-.67 1.11-.86 1.41-1.25 2.06-1.45 3.23-.02.05-.02.11-.02.17H5c0-.06 0-.13-.02-.17-.2-1.17-.59-1.83-1.45-3.23-.2-.31-.42-.67-.67-1.11C2.44 6.78 2 5.65 2 5c0-2.2 2.02-4 4.5-4 1.22 0 2.36.42 3.22 1.19C10.55 2.94 11 3.94 11 5c0 .66-.44 1.78-.86 2.48zM4 14h5c-.23 1.14-1.3 2-2.5 2s-2.27-.86-2.5-2z"></path></svg></span>tip</div><div class="admonitionContent_S0QG"><p>For the first column (especially in a PRISMA workflow) it can be tedious to promote non-duplicates to the next column. If all duplicates have been resolved, you can exit the dialog and click <strong>PROMOTE ALL UNCATEGORIZED STUDIES</strong> to advance all non-duplicate studies to the next column.</p></div></div><h2 class="anchor anchorWithStickyNavbar_LWe7" id="on-to-extraction">On to Extraction<a href="#on-to-extraction" class="hash-link" aria-label="Direct link to On to Extraction" title="Direct link to On to Extraction"></a></h2><p>When you have categorized all imported studies by either excluding them or moving them to the inclusion column, then you have -successfully completed the curation portion of the meta-analysis.</p><p><em>Neurosynth Compose</em> will detect this and reveal a new button: <strong>MOVE TO EXTRACTION PHASE</strong>. This will move you back to the project page and get you started on the next major component to building your meta-analysis: <a href="/compose-docs/guide/walkthrough/Project/Extraction">extraction</a>.</p></div><footer class="theme-doc-footer docusaurus-mt-lg"><div class="theme-doc-footer-edit-meta-row row"><div class="col"><a href="https://github.com/neurostuff/compose-docs/edit/master/docs/guide/walkthrough/Project/Curation.md" target="_blank" rel="noreferrer noopener" class="theme-edit-this-page"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_Z9Sw" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col lastUpdated_vwxv"><span class="theme-last-updated">Last updated<!-- --> on <b><time datetime="2023-11-27T23:56:16.000Z">Nov 27, 2023</time></b> by <b>Alejandro de la 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toc-highlight">Promote</a></li></ul></li><li><a href="#on-to-extraction" class="table-of-contents__link toc-highlight">On to Extraction</a></li></ul></div></div></div></div></main></div></div><footer class="footer footer--dark"><div class="container container-fluid"><div class="row footer__links"><div class="col footer__col"><div class="footer__title">Docs</div><ul class="footer__items clean-list"><li class="footer__item"><a class="footer__link-item" href="/compose-docs/">Docs</a></li></ul></div><div class="col footer__col"><div class="footer__title">Community</div><ul class="footer__items clean-list"><li class="footer__item"><a href="https://neurostars.org/tag/neuroscout" target="_blank" rel="noopener noreferrer" class="footer__link-item">NeuroStars<svg width="13.5" height="13.5" aria-hidden="true" viewBox="0 0 24 24" class="iconExternalLink_nPIU"><path fill="currentColor" d="M21 13v10h-21v-19h12v2h-10v15h17v-8h2zm3-12h-10.988l4.035 4-6.977 7.07 2.828 2.828 6.977-7.07 4.125 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2.828 2.828 6.977-7.07 4.125 4.172v-11z"></path></svg></a></li></ul></div></div><div class="footer__bottom text--center"><div class="footer__copyright">Copyright © 2023 Neuroinformatics Lab, Inc.</div></div></div></footer></div> -<script src="/compose-docs/assets/js/runtime~main.7d2821c4.js"></script> +successfully completed the curation portion of the meta-analysis.</p><p><em>Neurosynth Compose</em> will detect this and reveal a new button: <strong>MOVE TO EXTRACTION PHASE</strong>. This will move you back to the project page and get you started on the next major component to building your meta-analysis: <a href="/compose-docs/guide/walkthrough/Project/Extraction">extraction</a>.</p></div><footer class="theme-doc-footer docusaurus-mt-lg"><div class="theme-doc-footer-edit-meta-row row"><div class="col"><a href="https://github.com/neurostuff/compose-docs/edit/master/docs/guide/walkthrough/Project/Curation.md" target="_blank" rel="noreferrer noopener" class="theme-edit-this-page"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_Z9Sw" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col lastUpdated_vwxv"><span class="theme-last-updated">Last updated<!-- --> on <b><time datetime="2023-11-28T00:20:32.000Z">Nov 28, 2023</time></b> by <b>Alejandro de la Vega</b></span></div></div></footer></article><nav class="pagination-nav docusaurus-mt-lg" aria-label="Docs pages navigation"><a class="pagination-nav__link pagination-nav__link--prev" href="/compose-docs/guide/walkthrough/Project"><div class="pagination-nav__sublabel">Previous</div><div class="pagination-nav__label">Project</div></a><a class="pagination-nav__link pagination-nav__link--next" href="/compose-docs/guide/walkthrough/Project/Extraction"><div class="pagination-nav__sublabel">Next</div><div class="pagination-nav__label">Extraction</div></a></nav></div></div><div class="col col--3"><div class="tableOfContents_bqdL thin-scrollbar theme-doc-toc-desktop"><ul class="table-of-contents table-of-contents__left-border"><li><a href="#getting-started" class="table-of-contents__link toc-highlight">Getting Started</a><ul><li><a href="#prisma-workflow" class="table-of-contents__link toc-highlight">PRISMA Workflow</a></li><li><a href="#simple-workflow" class="table-of-contents__link toc-highlight">Simple Workflow</a></li></ul></li><li><a href="#importing" class="table-of-contents__link toc-highlight">Importing</a><ul><li><a href="#import-from-neurostore" class="table-of-contents__link toc-highlight">Import from Neurostore</a></li><li><a href="#import-from-pubmed" class="table-of-contents__link toc-highlight">Import from PubMed</a></li><li><a href="#import-from-bibtexrisendnote" class="table-of-contents__link toc-highlight">Import from BibTex/RIS/endnote</a></li><li><a href="#custom-studies" class="table-of-contents__link toc-highlight">Custom Studies</a></li><li><a href="#duplicates" class="table-of-contents__link toc-highlight">Duplicates</a></li></ul></li><li><a href="#excluding-and-promoting-studies" class="table-of-contents__link toc-highlight">Excluding and Promoting Studies</a><ul><li><a href="#exclude" class="table-of-contents__link toc-highlight">Exclude</a></li><li><a href="#promote" class="table-of-contents__link 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It involves taking the"><meta data-rh="true" property="og:description" content="Extraction is the second step in creating a meta-analysis. It involves taking the"><link data-rh="true" rel="icon" href="/compose-docs/img/favicon.ico"><link data-rh="true" rel="canonical" href="https://neurostuff.github.io/compose-docs/guide/walkthrough/Project/Extraction"><link data-rh="true" rel="alternate" href="https://neurostuff.github.io/compose-docs/guide/walkthrough/Project/Extraction" hreflang="en"><link data-rh="true" rel="alternate" href="https://neurostuff.github.io/compose-docs/guide/walkthrough/Project/Extraction" hreflang="x-default"><link rel="alternate" type="application/rss+xml" href="/compose-docs/blog/rss.xml" title="Neurosynth Compose Docs RSS Feed"> <link rel="alternate" type="application/atom+xml" href="/compose-docs/blog/atom.xml" title="Neurosynth Compose Docs Atom Feed"><link rel="stylesheet" href="/compose-docs/assets/css/styles.cce6c2a6.css"> -<link rel="preload" href="/compose-docs/assets/js/runtime~main.7d2821c4.js" as="script"> +<link rel="preload" href="/compose-docs/assets/js/runtime~main.710cc351.js" as="script"> <link rel="preload" href="/compose-docs/assets/js/main.660f8467.js" as="script"> </head> <body class="navigation-with-keyboard"> @@ -24,8 +24,8 @@ are imported into the curation phase are excluded during the curation process. Inserting these studies into the database would clutter it and create a lot of empty entries which don't have coordinates and might not even be used. By waiting until we have our finalized included subset of studies, we reduce the number of empty, useless studies in the database.</p></div></div><h2 class="anchor anchorWithStickyNavbar_LWe7" id="annotations">Annotations<a href="#annotations" class="hash-link" aria-label="Direct link to Annotations" title="Direct link to Annotations"></a></h2><h2 class="anchor anchorWithStickyNavbar_LWe7" id="study-editing">Study Editing<a href="#study-editing" class="hash-link" aria-label="Direct link to Study Editing" title="Direct link to Study Editing"></a></h2><p>Studies in the extraction phase are filtered and categorized to help better organize and facilitate the process. Initially, all studies -start as <strong>Uncategorized</strong>. The user can then decide to mark them as <strong>Save For Later</strong> if they want to revisit the study, or <strong>Completed</strong>.</p><h3 class="anchor anchorWithStickyNavbar_LWe7" id="read-only-studies">Read Only Studies<a href="#read-only-studies" class="hash-link" aria-label="Direct link to Read Only Studies" title="Direct link to Read Only Studies"></a></h3><h3 class="anchor anchorWithStickyNavbar_LWe7" id="study-annotations">Study Annotations<a href="#study-annotations" class="hash-link" aria-label="Direct link to Study Annotations" title="Direct link to Study Annotations"></a></h3><h3 class="anchor anchorWithStickyNavbar_LWe7" id="study-edit-interface">Study Edit Interface<a href="#study-edit-interface" class="hash-link" aria-label="Direct link to Study Edit Interface" title="Direct link to Study Edit Interface"></a></h3><h2 class="anchor anchorWithStickyNavbar_LWe7" id="syncing-between-curation-and-extraction">Syncing Between Curation and Extraction<a href="#syncing-between-curation-and-extraction" class="hash-link" aria-label="Direct link to Syncing Between Curation and Extraction" title="Direct link to Syncing Between Curation and Extraction"></a></h2></div><footer class="theme-doc-footer docusaurus-mt-lg"><div class="theme-doc-footer-edit-meta-row row"><div class="col"><a href="https://github.com/neurostuff/compose-docs/edit/master/docs/guide/walkthrough/Project/Extraction.md" target="_blank" rel="noreferrer noopener" class="theme-edit-this-page"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_Z9Sw" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col lastUpdated_vwxv"><span class="theme-last-updated">Last updated<!-- --> on <b><time datetime="2023-11-27T23:56:16.000Z">Nov 27, 2023</time></b> by <b>Alejandro de la 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The user can then decide to mark them as <strong>Save For Later</strong> if they want to revisit the study, or <strong>Completed</strong>.</p><h3 class="anchor anchorWithStickyNavbar_LWe7" id="read-only-studies">Read Only Studies<a href="#read-only-studies" class="hash-link" aria-label="Direct link to Read Only Studies" title="Direct link to Read Only Studies"></a></h3><h3 class="anchor anchorWithStickyNavbar_LWe7" id="study-annotations">Study Annotations<a href="#study-annotations" class="hash-link" aria-label="Direct link to Study Annotations" title="Direct link to Study Annotations"></a></h3><h3 class="anchor anchorWithStickyNavbar_LWe7" id="study-edit-interface">Study Edit Interface<a href="#study-edit-interface" class="hash-link" aria-label="Direct link to Study Edit Interface" title="Direct link to Study Edit Interface"></a></h3><h2 class="anchor anchorWithStickyNavbar_LWe7" id="syncing-between-curation-and-extraction">Syncing Between Curation and Extraction<a 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b/guide/walkthrough/Studies/Searching.html index dce6484..4f9591d 100644 --- a/guide/walkthrough/Studies/Searching.html +++ b/guide/walkthrough/Studies/Searching.html @@ -5,7 +5,7 @@ <meta name="generator" content="Docusaurus v2.3.1"> <title data-rh="true">Searching | Neurosynth Compose Docs</title><meta data-rh="true" name="viewport" content="width=device-width,initial-scale=1"><meta data-rh="true" name="twitter:card" content="summary_large_image"><meta data-rh="true" property="og:image" content="https://neurostuff.github.io/compose-docs/img/docusaurus-social-card.jpg"><meta data-rh="true" name="twitter:image" content="https://neurostuff.github.io/compose-docs/img/docusaurus-social-card.jpg"><meta data-rh="true" property="og:url" content="https://neurostuff.github.io/compose-docs/guide/walkthrough/Studies/Searching"><meta data-rh="true" name="docusaurus_locale" content="en"><meta data-rh="true" name="docsearch:language" content="en"><meta data-rh="true" name="docusaurus_version" content="current"><meta data-rh="true" name="docusaurus_tag" content="docs-default-current"><meta data-rh="true" name="docsearch:version" content="current"><meta data-rh="true" name="docsearch:docusaurus_tag" content="docs-default-current"><meta data-rh="true" property="og:title" content="Searching | Neurosynth Compose Docs"><meta data-rh="true" name="description" content="Neurosynth-Compose works with the neurostore database to provide a convenient and functional interface to search for studies."><meta data-rh="true" property="og:description" content="Neurosynth-Compose works with the neurostore database to provide a convenient and functional interface to search for studies."><link data-rh="true" rel="icon" href="/compose-docs/img/favicon.ico"><link data-rh="true" rel="canonical" href="https://neurostuff.github.io/compose-docs/guide/walkthrough/Studies/Searching"><link data-rh="true" rel="alternate" href="https://neurostuff.github.io/compose-docs/guide/walkthrough/Studies/Searching" hreflang="en"><link data-rh="true" rel="alternate" href="https://neurostuff.github.io/compose-docs/guide/walkthrough/Studies/Searching" hreflang="x-default"><link rel="alternate" type="application/rss+xml" href="/compose-docs/blog/rss.xml" title="Neurosynth Compose Docs RSS Feed"> <link rel="alternate" type="application/atom+xml" href="/compose-docs/blog/atom.xml" title="Neurosynth Compose Docs Atom Feed"><link rel="stylesheet" href="/compose-docs/assets/css/styles.cce6c2a6.css"> -<link rel="preload" href="/compose-docs/assets/js/runtime~main.7d2821c4.js" as="script"> +<link rel="preload" href="/compose-docs/assets/js/runtime~main.710cc351.js" as="script"> <link rel="preload" href="/compose-docs/assets/js/main.660f8467.js" as="script"> </head> <body class="navigation-with-keyboard"> @@ -15,8 +15,8 @@ certain <code>AND</code> or <code>NOT</code> operators amongst multiple clauses.</p><p>For example, consider the search: <code>nicotine OR smoking -marijuana</code>. In this example, the search results returned to you will be all the results yielded from <code>nicotine</code> unioned with all the results of <code>smoking -marijuana</code>. Having <code>-marijuana</code> here does not relate to the entire search term - just <code>smoking</code>.</p><p>To ensure that you do not have any mention of marijuana in your returned papers, you must search: <code>nicotine -marijuana or smoking -marijuana</code>.</p><p>The same case applies for <code>AND</code> operations. In general, <code>OR</code> unions between various search groups consisting of <code>and</code>, <code>not</code>, and quoted search terms. </p></div></div><h3 class="anchor anchorWithStickyNavbar_LWe7" id="study-data-type">Study Data Type<a href="#study-data-type" class="hash-link" aria-label="Direct link to Study Data Type" title="Direct link to Study Data Type"></a></h3><p>Studies can either report their findings as coordinate data, image data, or in some cases, both. Using the Study Data Type button, you can filter the results so that only coordinate or image data appears. For example, if you are doing a coordinate based meta-analysis, you -will want to filter the results to show only studies that report coordinates.</p><h3 class="anchor anchorWithStickyNavbar_LWe7" id="sorting-results">Sorting Results<a href="#sorting-results" class="hash-link" aria-label="Direct link to Sorting Results" title="Direct link to Sorting Results"></a></h3><p>Use the Sort By feature to sort the results based on a given property. You can also set this to be ascending or descending.</p><h3 class="anchor anchorWithStickyNavbar_LWe7" id="filtering">Filtering<a href="#filtering" class="hash-link" aria-label="Direct link to Filtering" title="Direct link to Filtering"></a></h3><p>To filter the results of the search, click on the orange <span style="font-weight:bold;color:orange">Add Filter</span> button. You have the option of filtering by title, description, author, or publication. Enter the string you want to filter by and click add to apply the filter.</p><p>Only one filter can be applied for each field. In order to remove a filter, simply click on the delete button on the given filter.</p></div><footer class="theme-doc-footer docusaurus-mt-lg"><div class="theme-doc-footer-edit-meta-row row"><div class="col"><a href="https://github.com/neurostuff/compose-docs/edit/master/docs/guide/walkthrough/Studies/Searching.md" target="_blank" rel="noreferrer noopener" class="theme-edit-this-page"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_Z9Sw" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col lastUpdated_vwxv"><span class="theme-last-updated">Last updated<!-- --> on <b><time datetime="2023-11-27T23:56:16.000Z">Nov 27, 2023</time></b> by <b>Alejandro de la Vega</b></span></div></div></footer></article><nav class="pagination-nav docusaurus-mt-lg" aria-label="Docs pages navigation"><a class="pagination-nav__link pagination-nav__link--prev" href="/compose-docs/guide/walkthrough/Studies"><div class="pagination-nav__sublabel">Previous</div><div class="pagination-nav__label">Studies Page</div></a><a class="pagination-nav__link pagination-nav__link--next" href="/compose-docs/guide/walkthrough/studysets"><div class="pagination-nav__sublabel">Next</div><div class="pagination-nav__label">Studysets Page</div></a></nav></div></div><div class="col col--3"><div class="tableOfContents_bqdL thin-scrollbar theme-doc-toc-desktop"><ul class="table-of-contents table-of-contents__left-border"><li><a href="#search-mechanics" class="table-of-contents__link toc-highlight">Search Mechanics</a></li><li><a href="#study-data-type" class="table-of-contents__link toc-highlight">Study Data Type</a></li><li><a href="#sorting-results" class="table-of-contents__link toc-highlight">Sorting Results</a></li><li><a href="#filtering" class="table-of-contents__link toc-highlight">Filtering</a></li></ul></div></div></div></div></main></div></div><footer class="footer footer--dark"><div class="container container-fluid"><div class="row footer__links"><div class="col footer__col"><div class="footer__title">Docs</div><ul class="footer__items clean-list"><li class="footer__item"><a class="footer__link-item" href="/compose-docs/">Docs</a></li></ul></div><div class="col footer__col"><div class="footer__title">Community</div><ul class="footer__items clean-list"><li class="footer__item"><a href="https://neurostars.org/tag/neuroscout" target="_blank" rel="noopener noreferrer" class="footer__link-item">NeuroStars<svg width="13.5" height="13.5" aria-hidden="true" viewBox="0 0 24 24" class="iconExternalLink_nPIU"><path fill="currentColor" d="M21 13v10h-21v-19h12v2h-10v15h17v-8h2zm3-12h-10.988l4.035 4-6.977 7.07 2.828 2.828 6.977-7.07 4.125 4.172v-11z"></path></svg></a></li><li class="footer__item"><a href="https://twitter.com/neurosynth" target="_blank" rel="noopener noreferrer" class="footer__link-item">Twitter<svg width="13.5" height="13.5" aria-hidden="true" viewBox="0 0 24 24" class="iconExternalLink_nPIU"><path fill="currentColor" d="M21 13v10h-21v-19h12v2h-10v15h17v-8h2zm3-12h-10.988l4.035 4-6.977 7.07 2.828 2.828 6.977-7.07 4.125 4.172v-11z"></path></svg></a></li></ul></div><div class="col footer__col"><div class="footer__title">More</div><ul class="footer__items clean-list"><li class="footer__item"><a class="footer__link-item" href="/compose-docs/blog">Blog</a></li><li class="footer__item"><a href="https://github.com/neurostuff/neurostore" target="_blank" rel="noopener noreferrer" class="footer__link-item">GitHub<svg width="13.5" height="13.5" aria-hidden="true" viewBox="0 0 24 24" class="iconExternalLink_nPIU"><path fill="currentColor" d="M21 13v10h-21v-19h12v2h-10v15h17v-8h2zm3-12h-10.988l4.035 4-6.977 7.07 2.828 2.828 6.977-7.07 4.125 4.172v-11z"></path></svg></a></li></ul></div></div><div class="footer__bottom text--center"><div class="footer__copyright">Copyright © 2023 Neuroinformatics Lab, Inc.</div></div></div></footer></div> -<script src="/compose-docs/assets/js/runtime~main.7d2821c4.js"></script> +will want to filter the results to show only studies that report coordinates.</p><h3 class="anchor anchorWithStickyNavbar_LWe7" id="sorting-results">Sorting Results<a href="#sorting-results" class="hash-link" aria-label="Direct link to Sorting Results" title="Direct link to Sorting Results"></a></h3><p>Use the Sort By feature to sort the results based on a given property. You can also set this to be ascending or descending.</p><h3 class="anchor anchorWithStickyNavbar_LWe7" id="filtering">Filtering<a href="#filtering" class="hash-link" aria-label="Direct link to Filtering" title="Direct link to Filtering"></a></h3><p>To filter the results of the search, click on the orange <span style="font-weight:bold;color:orange">Add Filter</span> button. You have the option of filtering by title, description, author, or publication. Enter the string you want to filter by and click add to apply the filter.</p><p>Only one filter can be applied for each field. In order to remove a filter, simply click on the delete button on the given filter.</p></div><footer class="theme-doc-footer docusaurus-mt-lg"><div class="theme-doc-footer-edit-meta-row row"><div class="col"><a href="https://github.com/neurostuff/compose-docs/edit/master/docs/guide/walkthrough/Studies/Searching.md" target="_blank" rel="noreferrer noopener" class="theme-edit-this-page"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_Z9Sw" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col lastUpdated_vwxv"><span class="theme-last-updated">Last updated<!-- --> on <b><time datetime="2023-11-28T00:20:32.000Z">Nov 28, 2023</time></b> by <b>Alejandro de la Vega</b></span></div></div></footer></article><nav class="pagination-nav docusaurus-mt-lg" aria-label="Docs pages 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page</button></div><div class="theme-doc-markdown markdown"><h1>What is Neurosynth Compose?</h1><p><em>Neurosynth Compose</em> is the next-generation of Neurosynth, enabling users to easily perform custom neuroimaging meta-analyses using a fully web-based platform, with no programming experience required. </p><p><em>Neurosynth Compose</em> is <em>free to use</em> and helps users:</p><ul><li>🔎 <strong>Search</strong> across over 20,000 studies in the Neurosynth database, or import from external databases such as PubMed.</li><li>🗃️ <strong>Curate</strong> your StudySet using systematic review tools conforming to the <a href="https://www.prisma-statement.org/" target="_blank" rel="noopener noreferrer">PRISMA</a> guidelines.</li><li>📝 <strong>Extract</strong> coordinates and metadata for each study, leveraging thousands of pre-extracted studies to minimize effort.</li><li>📊 <strong>Analyze</strong> by specifying a reproducible <a href="https://readthedocs.org/projects/nimare/" target="_blank" rel="noopener noreferrer">NiMARE</a> workflow, and execute it locally or in the cloud. </li><li>🔗 <strong>Share</strong> with the community with complete provenance and reproducibility.</li></ul><h2 class="anchor anchorWithStickyNavbar_LWe7" id="get-started-">Get started! 🚀<a href="#get-started-" class="hash-link" aria-label="Direct link to Get started! 🚀" title="Direct link to Get started! 🚀"></a></h2><div style="display:flex"><style data-emotion="css i6bazn">.css-i6bazn{overflow:hidden;}</style><style data-emotion="css s18byi">.css-s18byi{background-color:#fff;color:rgba(0, 0, 0, 0.87);-webkit-transition:box-shadow 300ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;transition:box-shadow 300ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;border-radius:4px;box-shadow:0px 2px 1px -1px rgba(0,0,0,0.2),0px 1px 1px 0px rgba(0,0,0,0.14),0px 1px 3px 0px rgba(0,0,0,0.12);overflow:hidden;}</style><div class="MuiPaper-root MuiPaper-elevation MuiPaper-rounded MuiPaper-elevation1 MuiCard-root css-s18byi" 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0ms;border-radius:4px;box-shadow:0px 2px 1px -1px rgba(0,0,0,0.2),0px 1px 1px 0px rgba(0,0,0,0.14),0px 1px 3px 0px rgba(0,0,0,0.12);overflow:hidden;}</style><div class="MuiPaper-root MuiPaper-elevation MuiPaper-rounded MuiPaper-elevation1 MuiCard-root css-s18byi" style="width:100%;display:flex"><style data-emotion="css 1qw96cp">.css-1qw96cp{padding:16px;}.css-1qw96cp:last-child{padding-bottom:24px;}</style><div class="MuiCardContent-root css-1qw96cp"><style data-emotion="css t1nuxs">.css-t1nuxs{margin:0;font-family:"Roboto","Helvetica","Arial",sans-serif;font-weight:400;font-size:1.5rem;line-height:1.334;letter-spacing:0em;margin-bottom:0.35em;}</style><h2 class="MuiTypography-root MuiTypography-h5 MuiTypography-gutterBottom css-t1nuxs">User Guide</h2><style data-emotion="css 1tqv6h6">.css-1tqv6h6{margin:0;font-family:"Roboto","Helvetica","Arial",sans-serif;font-weight:400;font-size:1rem;line-height:1.5;letter-spacing:0.00938em;margin-bottom:0.35em;}</style><p class="MuiTypography-root 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itemprop="itemListElement" itemtype="https://schema.org/ListItem" class="breadcrumbs__item breadcrumbs__item--active"><span class="breadcrumbs__link" itemprop="name">Introduction</span><meta itemprop="position" content="1"></li></ul></nav><div class="tocCollapsible_ETCw theme-doc-toc-mobile tocMobile_ITEo"><button type="button" class="clean-btn tocCollapsibleButton_TO0P">On this page</button></div><div class="theme-doc-markdown markdown"><h1>What is Neurosynth Compose?</h1><p><em>Neurosynth Compose</em> is the next-generation of Neurosynth, enabling users to easily perform custom neuroimaging meta-analyses using a fully web-based platform, with no programming experience required. </p><p><em>Neurosynth Compose</em> is <em>free to use</em> and helps users:</p><ul><li>🔎 <strong>Search</strong> across over 20,000 studies in the Neurosynth database, or import from external databases such as PubMed.</li><li>🗃️ <strong>Curate</strong> your StudySet using systematic review tools conforming to the <a href="https://www.prisma-statement.org/" target="_blank" rel="noopener noreferrer">PRISMA</a> guidelines.</li><li>📝 <strong>Extract</strong> coordinates and metadata for each study, leveraging thousands of pre-extracted studies to minimize effort.</li><li>📊 <strong>Analyze</strong> by specifying a reproducible <a href="https://readthedocs.org/projects/nimare/" target="_blank" rel="noopener noreferrer">NiMARE</a> workflow, and execute it locally or in the cloud. </li><li>🔗 <strong>Share</strong> with the community with complete provenance and reproducibility.</li></ul><h2 class="anchor anchorWithStickyNavbar_LWe7" id="get-started-">Get started! 🚀<a href="#get-started-" class="hash-link" aria-label="Direct link to Get started! 🚀" title="Direct link to Get started! 🚀"></a></h2><div style="display:flex"><style data-emotion="css i6bazn">.css-i6bazn{overflow:hidden;}</style><style data-emotion="css s18byi">.css-s18byi{background-color:#fff;color:rgba(0, 0, 0, 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0ms;border-radius:4px;box-shadow:0px 2px 1px -1px rgba(0,0,0,0.2),0px 1px 1px 0px rgba(0,0,0,0.14),0px 1px 3px 0px rgba(0,0,0,0.12);overflow:hidden;}</style><div class="MuiPaper-root MuiPaper-elevation MuiPaper-rounded MuiPaper-elevation1 MuiCard-root css-s18byi" style="width:100%;display:flex"><style data-emotion="css 1qw96cp">.css-1qw96cp{padding:16px;}.css-1qw96cp:last-child{padding-bottom:24px;}</style><div class="MuiCardContent-root css-1qw96cp"><style data-emotion="css t1nuxs">.css-t1nuxs{margin:0;font-family:"Roboto","Helvetica","Arial",sans-serif;font-weight:400;font-size:1.5rem;line-height:1.334;letter-spacing:0em;margin-bottom:0.35em;}</style><h2 class="MuiTypography-root MuiTypography-h5 MuiTypography-gutterBottom css-t1nuxs">User Guide</h2><style data-emotion="css 1tqv6h6">.css-1tqv6h6{margin:0;font-family:"Roboto","Helvetica","Arial",sans-serif;font-weight:400;font-size:1rem;line-height:1.5;letter-spacing:0.00938em;margin-bottom:0.35em;}</style><p class="MuiTypography-root 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href="https://neurostuff.github.io/compose-docs/introduction/ecosystem" hreflang="x-default"><link rel="alternate" type="application/rss+xml" href="/compose-docs/blog/rss.xml" title="Neurosynth Compose Docs RSS Feed"> <link rel="alternate" type="application/atom+xml" href="/compose-docs/blog/atom.xml" title="Neurosynth Compose Docs Atom Feed"><link rel="stylesheet" href="/compose-docs/assets/css/styles.cce6c2a6.css"> -<link rel="preload" href="/compose-docs/assets/js/runtime~main.7d2821c4.js" as="script"> +<link rel="preload" href="/compose-docs/assets/js/runtime~main.710cc351.js" as="script"> <link rel="preload" href="/compose-docs/assets/js/main.660f8467.js" as="script"> </head> <body class="navigation-with-keyboard"> @@ -28,8 +28,8 @@ Additionally, the NeuroQuery database will feed directly into NeuroStore as a source of coordinates.</p><h2 class="anchor anchorWithStickyNavbar_LWe7" id="neurovault">NeuroVault<a href="#neurovault" class="hash-link" aria-label="Direct link to NeuroVault" title="Direct link to NeuroVault"></a></h2><p><a href="https://neurovault.org/" target="_blank" rel="noopener noreferrer">NeuroVault</a> is a repository for unthresholded statistical maps from neuroimaging studies.</p><p>As of early 2023, NeuroVault contains over 8,000 collections of statistical images, with over 100,000 images in total. It is the largest repository of unthresholded statistical maps in the world, and is the primary source of data for image-based meta-analyses using Neurosynth Compose.</p><p>Currently, NeuroVault supports some basic meta-analytic functionality. However, as other tools in this ecosystem are developed, -it is planned that NeuroVault will focus exclusively on image storage and sharing, and will rely on other tools for meta-analysis.</p></div><footer class="theme-doc-footer docusaurus-mt-lg"><div class="theme-doc-footer-edit-meta-row row"><div class="col"><a href="https://github.com/neurostuff/compose-docs/edit/master/docs/introduction/ecosystem.md" target="_blank" rel="noreferrer noopener" class="theme-edit-this-page"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_Z9Sw" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col lastUpdated_vwxv"><span class="theme-last-updated">Last updated<!-- --> on <b><time datetime="2023-11-27T23:56:16.000Z">Nov 27, 2023</time></b> by <b>Alejandro de la 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padding-bottom--lg"><div class="row"><div class="col docItemCol_VOVn"><div class="docItemContainer_Djhp"><article><nav class="theme-doc-breadcrumbs breadcrumbsContainer_Z_bl" aria-label="Breadcrumbs"><ul class="breadcrumbs" itemscope="" itemtype="https://schema.org/BreadcrumbList"><li class="breadcrumbs__item"><a aria-label="Home page" class="breadcrumbs__link" href="/compose-docs/"><svg viewBox="0 0 24 24" class="breadcrumbHomeIcon_YNFT"><path d="M10 19v-5h4v5c0 .55.45 1 1 1h3c.55 0 1-.45 1-1v-7h1.7c.46 0 .68-.57.33-.87L12.67 3.6c-.38-.34-.96-.34-1.34 0l-8.36 7.53c-.34.3-.13.87.33.87H5v7c0 .55.45 1 1 1h3c.55 0 1-.45 1-1z" fill="currentColor"></path></svg></a></li><li itemscope="" itemprop="itemListElement" itemtype="https://schema.org/ListItem" class="breadcrumbs__item"><a class="breadcrumbs__link" itemprop="item" href="/compose-docs/"><span itemprop="name">Introduction</span></a><meta itemprop="position" content="1"></li><li itemscope="" itemprop="itemListElement" itemtype="https://schema.org/ListItem" class="breadcrumbs__item breadcrumbs__item--active"><span class="breadcrumbs__link" itemprop="name">FAQ</span><meta itemprop="position" content="2"></li></ul></nav><div class="theme-doc-markdown markdown"><h1>Frequently Asked Questions</h1><details class="details_lb9f alert alert--info details_b_Ee" data-collapsed="true"><summary>Is this service free to use?</summary><div><div class="collapsibleContent_i85q">Yes! Note, however, that NS-Compose is a web-based engine for neuroimaging meta-analysis specification; at the moment, we don’t (yet?) provide free computing resources for the execution of the resulting meta-analysis specifications. However, you can easily run your meta-analysis in the cloud using Google Colab, or locally using Python. Instructions are provided after you complete a meta-analysis.</div></div></details><details class="details_lb9f alert alert--info details_b_Ee" data-collapsed="true"><summary>Are there any restrictions on meta-analyses created?</summary><div><div class="collapsibleContent_i85q">Yes. Once a meta-analysis specification is executed and results are uploaded to our platform, you will no longer be able to <em>delete or edit</em> the analysis specification. A complete copy of the StudySet and Analysis is kept on our system to ensure complete provenance. You can, however, keep the analysis as private to ensure it is unlisted in the public search.<br>If you wish to make any edits, you can edit the StudySet and create a new Analysis specification, which will receive a new unique ID.<br><br>In the event that you publish any results generated using the Neurosynth Compose, you MUST provide a link to the corresponding meta-analysis specification ID on the platform.</div></div></details><details class="details_lb9f alert alert--info details_b_Ee" data-collapsed="true"><summary>I've noticed that a study on your platform contains errors or is incomplete, can I fix them?</summary><div><div class="collapsibleContent_i85q">Yes! We welcome user contributions. You can correct or add details on a study, including meta-data and peak activation coordinates. A key piece of information that you may want to correct is how Activation coordinates are grouped into distinct Analyses (i.e., Contrasts). Please ensure that any edits you make are as objective as possible and reflect what is represented in the original Study, and *not* the goals of your meta-analysis.<br><br>To avoid debates about the ground truth of a Study, when you make edits a new Version of the study is created, which is associated with your User.</div></div></details><details class="details_lb9f alert alert--info details_b_Ee" data-collapsed="true"><summary>If I contribute new studies to the platform, or edit existing studies, will other users be able to see them?</summary><div><div class="collapsibleContent_i85q">Yes! Although a new Version of the study is created when you make any edits, we default to displaying user edited Versions over the automatically extracted versions. This is because we assume that any edits made by users will be improvements on the extraction algorithm. Please ensure any changes you make reflect this. You may also make a Version private if you don't want to share your edits with others.</div></div></details><details class="details_lb9f alert alert--info details_b_Ee" data-collapsed="true"><summary>How does this project relate to the original Neurosynth?</summary><div><div class="collapsibleContent_i85q">Neurosynth 1.0 was an online platform for browsing automatically generated large-scale neuroimaging meta-analyses. However, because all analyses were pre-generated, users were unable to define custom meta-analyses using the Neurosynth database. Instead, Neurosynth 1.0 used text mining techniques to automatically group studies based on the frequency of the terms mentioned in the text. Neurosynth Compose is focused on allowing users to overcome the limitations of automated large-scale meta-analysis, by enabling users to annotate studies, and curate sets of studies amenable for meta-analysis. This way, users can systematically define meta-analyses using their own expertise, while still leveraging the Neurosynth database, and an easy-to-use web-based analysis builder to accelerate the meta-analysis process.<br></div></div></details></div><footer class="theme-doc-footer docusaurus-mt-lg"><div class="theme-doc-footer-edit-meta-row row"><div class="col"><a href="https://github.com/neurostuff/compose-docs/edit/master/docs/introduction/faq.md" target="_blank" rel="noreferrer noopener" class="theme-edit-this-page"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_Z9Sw" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col lastUpdated_vwxv"><span class="theme-last-updated">Last updated<!-- --> on <b><time datetime="2023-11-27T23:56:16.000Z">Nov 27, 2023</time></b> by 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itemprop="position" content="2"></li></ul></nav><div class="theme-doc-markdown markdown"><h1>Frequently Asked Questions</h1><details class="details_lb9f alert alert--info details_b_Ee" data-collapsed="true"><summary>Is this service free to use?</summary><div><div class="collapsibleContent_i85q">Yes! Note, however, that NS-Compose is a web-based engine for neuroimaging meta-analysis specification; at the moment, we don’t (yet?) provide free computing resources for the execution of the resulting meta-analysis specifications. However, you can easily run your meta-analysis in the cloud using Google Colab, or locally using Python. Instructions are provided after you complete a meta-analysis.</div></div></details><details class="details_lb9f alert alert--info details_b_Ee" data-collapsed="true"><summary>Are there any restrictions on meta-analyses created?</summary><div><div class="collapsibleContent_i85q">Yes. Once a meta-analysis specification is executed and results are uploaded to our platform, you will no longer be able to <em>delete or edit</em> the analysis specification. A complete copy of the StudySet and Analysis is kept on our system to ensure complete provenance. You can, however, keep the analysis as private to ensure it is unlisted in the public search.<br>If you wish to make any edits, you can edit the StudySet and create a new Analysis specification, which will receive a new unique ID.<br><br>In the event that you publish any results generated using the Neurosynth Compose, you MUST provide a link to the corresponding meta-analysis specification ID on the platform.</div></div></details><details class="details_lb9f alert alert--info details_b_Ee" data-collapsed="true"><summary>I've noticed that a study on your platform contains errors or is incomplete, can I fix them?</summary><div><div class="collapsibleContent_i85q">Yes! We welcome user contributions. You can correct or add details on a study, including meta-data and peak activation coordinates. A key piece of information that you may want to correct is how Activation coordinates are grouped into distinct Analyses (i.e., Contrasts). Please ensure that any edits you make are as objective as possible and reflect what is represented in the original Study, and *not* the goals of your meta-analysis.<br><br>To avoid debates about the ground truth of a Study, when you make edits a new Version of the study is created, which is associated with your User.</div></div></details><details class="details_lb9f alert alert--info details_b_Ee" data-collapsed="true"><summary>If I contribute new studies to the platform, or edit existing studies, will other users be able to see them?</summary><div><div class="collapsibleContent_i85q">Yes! Although a new Version of the study is created when you make any edits, we default to displaying user edited Versions over the automatically extracted versions. This is because we assume that any edits made by users will be improvements on the extraction algorithm. Please ensure any changes you make reflect this. You may also make a Version private if you don't want to share your edits with others.</div></div></details><details class="details_lb9f alert alert--info details_b_Ee" data-collapsed="true"><summary>How does this project relate to the original Neurosynth?</summary><div><div class="collapsibleContent_i85q">Neurosynth 1.0 was an online platform for browsing automatically generated large-scale neuroimaging meta-analyses. However, because all analyses were pre-generated, users were unable to define custom meta-analyses using the Neurosynth database. Instead, Neurosynth 1.0 used text mining techniques to automatically group studies based on the frequency of the terms mentioned in the text. Neurosynth Compose is focused on allowing users to overcome the limitations of automated large-scale meta-analysis, by enabling users to annotate studies, and curate sets of studies amenable for meta-analysis. This way, users can systematically define meta-analyses using their own expertise, while still leveraging the Neurosynth database, and an easy-to-use web-based analysis builder to accelerate the meta-analysis process.<br></div></div></details></div><footer class="theme-doc-footer docusaurus-mt-lg"><div class="theme-doc-footer-edit-meta-row row"><div class="col"><a href="https://github.com/neurostuff/compose-docs/edit/master/docs/introduction/faq.md" target="_blank" rel="noreferrer noopener" class="theme-edit-this-page"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_Z9Sw" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col lastUpdated_vwxv"><span class="theme-last-updated">Last updated<!-- --> on <b><time datetime="2023-11-28T00:20:32.000Z">Nov 28, 2023</time></b> by 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padding-bottom--lg"><div class="row"><div class="col docItemCol_VOVn"><div class="docItemContainer_Djhp"><article><nav class="theme-doc-breadcrumbs breadcrumbsContainer_Z_bl" aria-label="Breadcrumbs"><ul class="breadcrumbs" itemscope="" itemtype="https://schema.org/BreadcrumbList"><li class="breadcrumbs__item"><a aria-label="Home page" class="breadcrumbs__link" href="/compose-docs/"><svg viewBox="0 0 24 24" class="breadcrumbHomeIcon_YNFT"><path d="M10 19v-5h4v5c0 .55.45 1 1 1h3c.55 0 1-.45 1-1v-7h1.7c.46 0 .68-.57.33-.87L12.67 3.6c-.38-.34-.96-.34-1.34 0l-8.36 7.53c-.34.3-.13.87.33.87H5v7c0 .55.45 1 1 1h3c.55 0 1-.45 1-1z" fill="currentColor"></path></svg></a></li><li itemscope="" itemprop="itemListElement" itemtype="https://schema.org/ListItem" class="breadcrumbs__item"><a class="breadcrumbs__link" itemprop="item" href="/compose-docs/"><span itemprop="name">Introduction</span></a><meta itemprop="position" content="1"></li><li itemscope="" itemprop="itemListElement" itemtype="https://schema.org/ListItem" class="breadcrumbs__item breadcrumbs__item--active"><span class="breadcrumbs__link" itemprop="name">Our Team</span><meta itemprop="position" content="2"></li></ul></nav><div class="theme-doc-markdown markdown"><h1>Our Team</h1><p>Neurosynth-Compose is collaborative effort across several laboratories, and is supported by the <a href="http://www.nimh.nih.gov/" target="_blank" rel="noopener noreferrer">National Institute of Mental Health</a> award 5R01MH096906. -Together, we developed Neurosynth-Compose, and related tools, such as NiMARE and Neurostore.</p><div class="team-grid"><div class="team-member-card"><img src="/compose-docs/team/delavega.jpg" alt="Alejandro de la Vega" class="team-member-image"><div class="team-member-info"><h3>Alejandro de la Vega</h3><p>Principal Investigator<br>University of Texas at Austin</p><div class="team-member-links"><a href="https://adelavega.github.io/" target="_blank" rel="noopener noreferrer"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 496 512" height="20" width="20" xmlns="http://www.w3.org/2000/svg"><path d="M336.5 160C322 70.7 287.8 8 248 8s-74 62.7-88.5 152h177zM152 256c0 22.2 1.2 43.5 3.3 64h185.3c2.1-20.5 3.3-41.8 3.3-64s-1.2-43.5-3.3-64H155.3c-2.1 20.5-3.3 41.8-3.3 64zm324.7-96c-28.6-67.9-86.5-120.4-158-141.6 24.4 33.8 41.2 84.7 50 141.6h108zM177.2 18.4C105.8 39.6 47.8 92.1 19.3 160h108c8.7-56.9 25.5-107.8 49.9-141.6zM487.4 192H372.7c2.1 21 3.3 42.5 3.3 64s-1.2 43-3.3 64h114.6c5.5-20.5 8.6-41.8 8.6-64s-3.1-43.5-8.5-64zM120 256c0-21.5 1.2-43 3.3-64H8.6C3.2 212.5 0 233.8 0 256s3.2 43.5 8.6 64h114.6c-2-21-3.2-42.5-3.2-64zm39.5 96c14.5 89.3 48.7 152 88.5 152s74-62.7 88.5-152h-177zm159.3 141.6c71.4-21.2 129.4-73.7 158-141.6h-108c-8.8 56.9-25.6 107.8-50 141.6zM19.3 352c28.6 67.9 86.5 120.4 158 141.6-24.4-33.8-41.2-84.7-50-141.6h-108z"></path></svg></a><span> </span><a href="https://github.com/adelavega" target="_blank" rel="noopener noreferrer" class="github-link"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 496 512" height="20" width="20" xmlns="http://www.w3.org/2000/svg"><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"></path></svg></a></div></div></div><div class="team-member-card"><img src="/compose-docs/team/kent.jpg" alt="James Kent" class="team-member-image"><div class="team-member-info"><h3>James Kent</h3><p>Postdoctoral Fellow & Principal Engineer<br>University of Texas at Austin</p><div class="team-member-links"><span> </span><a href="https://github.com/jdkent" target="_blank" rel="noopener noreferrer" class="github-link"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 496 512" height="20" width="20" xmlns="http://www.w3.org/2000/svg"><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"></path></svg></a></div></div></div><div class="team-member-card"><img src="/compose-docs/team/lee.jpg" alt="Nicholas Lee" class="team-member-image"><div class="team-member-info"><h3>Nicholas Lee</h3><p>Frontend Engineer<br>McGill University</p><div class="team-member-links"><span> </span><a href="https://github.com/nicoalee" target="_blank" rel="noopener noreferrer" class="github-link"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 496 512" height="20" width="20" xmlns="http://www.w3.org/2000/svg"><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"></path></svg></a></div></div></div><div class="team-member-card"><img src="/compose-docs/team/salo.png" alt="Taylor Salo" class="team-member-image"><div class="team-member-info"><h3>Taylor Salo</h3><p>Postdoctoral fellow<br>University of Pennsylvania</p><div class="team-member-links"><a href="tsalo.github.io" target="_blank" rel="noopener noreferrer"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 496 512" height="20" width="20" xmlns="http://www.w3.org/2000/svg"><path d="M336.5 160C322 70.7 287.8 8 248 8s-74 62.7-88.5 152h177zM152 256c0 22.2 1.2 43.5 3.3 64h185.3c2.1-20.5 3.3-41.8 3.3-64s-1.2-43.5-3.3-64H155.3c-2.1 20.5-3.3 41.8-3.3 64zm324.7-96c-28.6-67.9-86.5-120.4-158-141.6 24.4 33.8 41.2 84.7 50 141.6h108zM177.2 18.4C105.8 39.6 47.8 92.1 19.3 160h108c8.7-56.9 25.5-107.8 49.9-141.6zM487.4 192H372.7c2.1 21 3.3 42.5 3.3 64s-1.2 43-3.3 64h114.6c5.5-20.5 8.6-41.8 8.6-64s-3.1-43.5-8.5-64zM120 256c0-21.5 1.2-43 3.3-64H8.6C3.2 212.5 0 233.8 0 256s3.2 43.5 8.6 64h114.6c-2-21-3.2-42.5-3.2-64zm39.5 96c14.5 89.3 48.7 152 88.5 152s74-62.7 88.5-152h-177zm159.3 141.6c71.4-21.2 129.4-73.7 158-141.6h-108c-8.8 56.9-25.6 107.8-50 141.6zM19.3 352c28.6 67.9 86.5 120.4 158 141.6-24.4-33.8-41.2-84.7-50-141.6h-108z"></path></svg></a><span> </span><a href="https://github.com/tsalo" target="_blank" rel="noopener noreferrer" class="github-link"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 496 512" height="20" width="20" xmlns="http://www.w3.org/2000/svg"><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"></path></svg></a></div></div></div><div class="team-member-card"><img src="/compose-docs/team/bottenhorn.jpg" alt="Katie Bottenhorn" class="team-member-image"><div class="team-member-info"><h3>Katie Bottenhorn</h3><p>Postdoctoral Fellow<br>University of Southern California</p><div class="team-member-links"><a href="katherinebottenhorn.com" target="_blank" rel="noopener noreferrer"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 496 512" height="20" width="20" xmlns="http://www.w3.org/2000/svg"><path d="M336.5 160C322 70.7 287.8 8 248 8s-74 62.7-88.5 152h177zM152 256c0 22.2 1.2 43.5 3.3 64h185.3c2.1-20.5 3.3-41.8 3.3-64s-1.2-43.5-3.3-64H155.3c-2.1 20.5-3.3 41.8-3.3 64zm324.7-96c-28.6-67.9-86.5-120.4-158-141.6 24.4 33.8 41.2 84.7 50 141.6h108zM177.2 18.4C105.8 39.6 47.8 92.1 19.3 160h108c8.7-56.9 25.5-107.8 49.9-141.6zM487.4 192H372.7c2.1 21 3.3 42.5 3.3 64s-1.2 43-3.3 64h114.6c5.5-20.5 8.6-41.8 8.6-64s-3.1-43.5-8.5-64zM120 256c0-21.5 1.2-43 3.3-64H8.6C3.2 212.5 0 233.8 0 256s3.2 43.5 8.6 64h114.6c-2-21-3.2-42.5-3.2-64zm39.5 96c14.5 89.3 48.7 152 88.5 152s74-62.7 88.5-152h-177zm159.3 141.6c71.4-21.2 129.4-73.7 158-141.6h-108c-8.8 56.9-25.6 107.8-50 141.6zM19.3 352c28.6 67.9 86.5 120.4 158 141.6-24.4-33.8-41.2-84.7-50-141.6h-108z"></path></svg></a><span> </span><a href="https://github.com/62442katieb" target="_blank" rel="noopener noreferrer" class="github-link"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 496 512" height="20" width="20" xmlns="http://www.w3.org/2000/svg"><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"></path></svg></a></div></div></div><div class="team-member-card"><img src="/compose-docs/team/poline.png" alt="Jean-Baptiste Poline" class="team-member-image"><div class="team-member-info"><h3>Jean-Baptiste Poline</h3><p>Associate Professor<br>McGill University</p><div class="team-member-links"><a href="https://www.mcgill.ca/neuro/jean-baptiste-poline-phd" target="_blank" rel="noopener noreferrer"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 496 512" height="20" width="20" xmlns="http://www.w3.org/2000/svg"><path d="M336.5 160C322 70.7 287.8 8 248 8s-74 62.7-88.5 152h177zM152 256c0 22.2 1.2 43.5 3.3 64h185.3c2.1-20.5 3.3-41.8 3.3-64s-1.2-43.5-3.3-64H155.3c-2.1 20.5-3.3 41.8-3.3 64zm324.7-96c-28.6-67.9-86.5-120.4-158-141.6 24.4 33.8 41.2 84.7 50 141.6h108zM177.2 18.4C105.8 39.6 47.8 92.1 19.3 160h108c8.7-56.9 25.5-107.8 49.9-141.6zM487.4 192H372.7c2.1 21 3.3 42.5 3.3 64s-1.2 43-3.3 64h114.6c5.5-20.5 8.6-41.8 8.6-64s-3.1-43.5-8.5-64zM120 256c0-21.5 1.2-43 3.3-64H8.6C3.2 212.5 0 233.8 0 256s3.2 43.5 8.6 64h114.6c-2-21-3.2-42.5-3.2-64zm39.5 96c14.5 89.3 48.7 152 88.5 152s74-62.7 88.5-152h-177zm159.3 141.6c71.4-21.2 129.4-73.7 158-141.6h-108c-8.8 56.9-25.6 107.8-50 141.6zM19.3 352c28.6 67.9 86.5 120.4 158 141.6-24.4-33.8-41.2-84.7-50-141.6h-108z"></path></svg></a><span> </span></div></div></div><div class="team-member-card"><img src="/compose-docs/team/laird.jpg" alt="Angela Laird" class="team-member-image"><div class="team-member-info"><h3>Angela Laird</h3><p>Professor<br>Florida International University</p><div class="team-member-links"><a href="https://case.fiu.edu/about/directory/profiles/laird-angela.html" target="_blank" rel="noopener noreferrer"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 496 512" height="20" width="20" xmlns="http://www.w3.org/2000/svg"><path d="M336.5 160C322 70.7 287.8 8 248 8s-74 62.7-88.5 152h177zM152 256c0 22.2 1.2 43.5 3.3 64h185.3c2.1-20.5 3.3-41.8 3.3-64s-1.2-43.5-3.3-64H155.3c-2.1 20.5-3.3 41.8-3.3 64zm324.7-96c-28.6-67.9-86.5-120.4-158-141.6 24.4 33.8 41.2 84.7 50 141.6h108zM177.2 18.4C105.8 39.6 47.8 92.1 19.3 160h108c8.7-56.9 25.5-107.8 49.9-141.6zM487.4 192H372.7c2.1 21 3.3 42.5 3.3 64s-1.2 43-3.3 64h114.6c5.5-20.5 8.6-41.8 8.6-64s-3.1-43.5-8.5-64zM120 256c0-21.5 1.2-43 3.3-64H8.6C3.2 212.5 0 233.8 0 256s3.2 43.5 8.6 64h114.6c-2-21-3.2-42.5-3.2-64zm39.5 96c14.5 89.3 48.7 152 88.5 152s74-62.7 88.5-152h-177zm159.3 141.6c71.4-21.2 129.4-73.7 158-141.6h-108c-8.8 56.9-25.6 107.8-50 141.6zM19.3 352c28.6 67.9 86.5 120.4 158 141.6-24.4-33.8-41.2-84.7-50-141.6h-108z"></path></svg></a><span> </span></div></div></div><div class="team-member-card"><img src="/compose-docs/team/pedraza.jpg" alt="Julio Peraza" class="team-member-image"><div class="team-member-info"><h3>Julio Peraza</h3><p>Graduate Student<br>Florida International University</p><div class="team-member-links"><span> </span><a href="https://github.com/julioAPeraza" target="_blank" rel="noopener noreferrer" class="github-link"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 496 512" height="20" width="20" xmlns="http://www.w3.org/2000/svg"><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"></path></svg></a></div></div></div><div class="team-member-card"><img src="/compose-docs/team/poldrack.jpg" alt="Russ Poldrack" class="team-member-image"><div class="team-member-info"><h3>Russ Poldrack</h3><p>Professor<br>Stanford University</p><div class="team-member-links"><a href="http://poldracklab.org/" target="_blank" rel="noopener noreferrer"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 496 512" height="20" width="20" xmlns="http://www.w3.org/2000/svg"><path d="M336.5 160C322 70.7 287.8 8 248 8s-74 62.7-88.5 152h177zM152 256c0 22.2 1.2 43.5 3.3 64h185.3c2.1-20.5 3.3-41.8 3.3-64s-1.2-43.5-3.3-64H155.3c-2.1 20.5-3.3 41.8-3.3 64zm324.7-96c-28.6-67.9-86.5-120.4-158-141.6 24.4 33.8 41.2 84.7 50 141.6h108zM177.2 18.4C105.8 39.6 47.8 92.1 19.3 160h108c8.7-56.9 25.5-107.8 49.9-141.6zM487.4 192H372.7c2.1 21 3.3 42.5 3.3 64s-1.2 43-3.3 64h114.6c5.5-20.5 8.6-41.8 8.6-64s-3.1-43.5-8.5-64zM120 256c0-21.5 1.2-43 3.3-64H8.6C3.2 212.5 0 233.8 0 256s3.2 43.5 8.6 64h114.6c-2-21-3.2-42.5-3.2-64zm39.5 96c14.5 89.3 48.7 152 88.5 152s74-62.7 88.5-152h-177zm159.3 141.6c71.4-21.2 129.4-73.7 158-141.6h-108c-8.8 56.9-25.6 107.8-50 141.6zM19.3 352c28.6 67.9 86.5 120.4 158 141.6-24.4-33.8-41.2-84.7-50-141.6h-108z"></path></svg></a><span> </span><a href="https://github.com/poldrack" target="_blank" rel="noopener noreferrer" class="github-link"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 496 512" height="20" width="20" xmlns="http://www.w3.org/2000/svg"><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"></path></svg></a></div></div></div><div class="team-member-card"><img src="/compose-docs/team/nichols.jpg" alt="Tom Nichols" class="team-member-image"><div class="team-member-info"><h3>Tom Nichols</h3><p>Professor<br>Oxford University</p><div class="team-member-links"><a href="https://www.bdi.ox.ac.uk/Team/t-e-nichols" target="_blank" rel="noopener noreferrer"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 496 512" height="20" width="20" xmlns="http://www.w3.org/2000/svg"><path d="M336.5 160C322 70.7 287.8 8 248 8s-74 62.7-88.5 152h177zM152 256c0 22.2 1.2 43.5 3.3 64h185.3c2.1-20.5 3.3-41.8 3.3-64s-1.2-43.5-3.3-64H155.3c-2.1 20.5-3.3 41.8-3.3 64zm324.7-96c-28.6-67.9-86.5-120.4-158-141.6 24.4 33.8 41.2 84.7 50 141.6h108zM177.2 18.4C105.8 39.6 47.8 92.1 19.3 160h108c8.7-56.9 25.5-107.8 49.9-141.6zM487.4 192H372.7c2.1 21 3.3 42.5 3.3 64s-1.2 43-3.3 64h114.6c5.5-20.5 8.6-41.8 8.6-64s-3.1-43.5-8.5-64zM120 256c0-21.5 1.2-43 3.3-64H8.6C3.2 212.5 0 233.8 0 256s3.2 43.5 8.6 64h114.6c-2-21-3.2-42.5-3.2-64zm39.5 96c14.5 89.3 48.7 152 88.5 152s74-62.7 88.5-152h-177zm159.3 141.6c71.4-21.2 129.4-73.7 158-141.6h-108c-8.8 56.9-25.6 107.8-50 141.6zM19.3 352c28.6 67.9 86.5 120.4 158 141.6-24.4-33.8-41.2-84.7-50-141.6h-108z"></path></svg></a><span> </span></div></div></div><div class="team-member-card"><img src="/compose-docs/team/yu.jpg" alt="Yifan Yu" class="team-member-image"><div class="team-member-info"><h3>Yifan Yu</h3><p>Graduate Student<br>Oxford University</p><div class="team-member-links"><span> </span><a href="https://github.com/yifan0330" target="_blank" rel="noopener noreferrer" class="github-link"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 496 512" height="20" width="20" xmlns="http://www.w3.org/2000/svg"><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"></path></svg></a></div></div></div></div></div><footer class="theme-doc-footer docusaurus-mt-lg"><div class="theme-doc-footer-edit-meta-row row"><div class="col"><a href="https://github.com/neurostuff/compose-docs/edit/master/docs/introduction/team.md" target="_blank" rel="noreferrer noopener" class="theme-edit-this-page"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_Z9Sw" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 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4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"></path></svg></a></div></div></div><div class="team-member-card"><img src="/compose-docs/team/kent.jpg" alt="James Kent" class="team-member-image"><div class="team-member-info"><h3>James Kent</h3><p>Postdoctoral Fellow & Principal Engineer<br>University of Texas at Austin</p><div class="team-member-links"><span> </span><a href="https://github.com/jdkent" target="_blank" rel="noopener noreferrer" class="github-link"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 496 512" height="20" width="20" xmlns="http://www.w3.org/2000/svg"><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"></path></svg></a></div></div></div><div class="team-member-card"><img src="/compose-docs/team/lee.jpg" alt="Nicholas Lee" class="team-member-image"><div class="team-member-info"><h3>Nicholas Lee</h3><p>Frontend Engineer<br>McGill University</p><div class="team-member-links"><span> </span><a href="https://github.com/nicoalee" target="_blank" rel="noopener noreferrer" class="github-link"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 496 512" height="20" width="20" xmlns="http://www.w3.org/2000/svg"><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"></path></svg></a></div></div></div><div class="team-member-card"><img src="/compose-docs/team/salo.png" alt="Taylor Salo" class="team-member-image"><div class="team-member-info"><h3>Taylor Salo</h3><p>Postdoctoral fellow<br>University of Pennsylvania</p><div class="team-member-links"><a href="tsalo.github.io" target="_blank" rel="noopener noreferrer"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 496 512" height="20" width="20" xmlns="http://www.w3.org/2000/svg"><path d="M336.5 160C322 70.7 287.8 8 248 8s-74 62.7-88.5 152h177zM152 256c0 22.2 1.2 43.5 3.3 64h185.3c2.1-20.5 3.3-41.8 3.3-64s-1.2-43.5-3.3-64H155.3c-2.1 20.5-3.3 41.8-3.3 64zm324.7-96c-28.6-67.9-86.5-120.4-158-141.6 24.4 33.8 41.2 84.7 50 141.6h108zM177.2 18.4C105.8 39.6 47.8 92.1 19.3 160h108c8.7-56.9 25.5-107.8 49.9-141.6zM487.4 192H372.7c2.1 21 3.3 42.5 3.3 64s-1.2 43-3.3 64h114.6c5.5-20.5 8.6-41.8 8.6-64s-3.1-43.5-8.5-64zM120 256c0-21.5 1.2-43 3.3-64H8.6C3.2 212.5 0 233.8 0 256s3.2 43.5 8.6 64h114.6c-2-21-3.2-42.5-3.2-64zm39.5 96c14.5 89.3 48.7 152 88.5 152s74-62.7 88.5-152h-177zm159.3 141.6c71.4-21.2 129.4-73.7 158-141.6h-108c-8.8 56.9-25.6 107.8-50 141.6zM19.3 352c28.6 67.9 86.5 120.4 158 141.6-24.4-33.8-41.2-84.7-50-141.6h-108z"></path></svg></a><span> </span><a href="https://github.com/tsalo" target="_blank" rel="noopener noreferrer" class="github-link"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 496 512" height="20" width="20" xmlns="http://www.w3.org/2000/svg"><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"></path></svg></a></div></div></div><div class="team-member-card"><img src="/compose-docs/team/bottenhorn.jpg" alt="Katie Bottenhorn" class="team-member-image"><div class="team-member-info"><h3>Katie Bottenhorn</h3><p>Postdoctoral Fellow<br>University of Southern California</p><div class="team-member-links"><a href="katherinebottenhorn.com" target="_blank" rel="noopener noreferrer"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 496 512" height="20" width="20" xmlns="http://www.w3.org/2000/svg"><path d="M336.5 160C322 70.7 287.8 8 248 8s-74 62.7-88.5 152h177zM152 256c0 22.2 1.2 43.5 3.3 64h185.3c2.1-20.5 3.3-41.8 3.3-64s-1.2-43.5-3.3-64H155.3c-2.1 20.5-3.3 41.8-3.3 64zm324.7-96c-28.6-67.9-86.5-120.4-158-141.6 24.4 33.8 41.2 84.7 50 141.6h108zM177.2 18.4C105.8 39.6 47.8 92.1 19.3 160h108c8.7-56.9 25.5-107.8 49.9-141.6zM487.4 192H372.7c2.1 21 3.3 42.5 3.3 64s-1.2 43-3.3 64h114.6c5.5-20.5 8.6-41.8 8.6-64s-3.1-43.5-8.5-64zM120 256c0-21.5 1.2-43 3.3-64H8.6C3.2 212.5 0 233.8 0 256s3.2 43.5 8.6 64h114.6c-2-21-3.2-42.5-3.2-64zm39.5 96c14.5 89.3 48.7 152 88.5 152s74-62.7 88.5-152h-177zm159.3 141.6c71.4-21.2 129.4-73.7 158-141.6h-108c-8.8 56.9-25.6 107.8-50 141.6zM19.3 352c28.6 67.9 86.5 120.4 158 141.6-24.4-33.8-41.2-84.7-50-141.6h-108z"></path></svg></a><span> </span><a href="https://github.com/62442katieb" target="_blank" rel="noopener noreferrer" class="github-link"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 496 512" height="20" width="20" xmlns="http://www.w3.org/2000/svg"><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"></path></svg></a></div></div></div><div class="team-member-card"><img src="/compose-docs/team/poline.png" alt="Jean-Baptiste Poline" class="team-member-image"><div class="team-member-info"><h3>Jean-Baptiste Poline</h3><p>Associate Professor<br>McGill University</p><div class="team-member-links"><a href="https://www.mcgill.ca/neuro/jean-baptiste-poline-phd" target="_blank" rel="noopener noreferrer"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 496 512" height="20" width="20" xmlns="http://www.w3.org/2000/svg"><path d="M336.5 160C322 70.7 287.8 8 248 8s-74 62.7-88.5 152h177zM152 256c0 22.2 1.2 43.5 3.3 64h185.3c2.1-20.5 3.3-41.8 3.3-64s-1.2-43.5-3.3-64H155.3c-2.1 20.5-3.3 41.8-3.3 64zm324.7-96c-28.6-67.9-86.5-120.4-158-141.6 24.4 33.8 41.2 84.7 50 141.6h108zM177.2 18.4C105.8 39.6 47.8 92.1 19.3 160h108c8.7-56.9 25.5-107.8 49.9-141.6zM487.4 192H372.7c2.1 21 3.3 42.5 3.3 64s-1.2 43-3.3 64h114.6c5.5-20.5 8.6-41.8 8.6-64s-3.1-43.5-8.5-64zM120 256c0-21.5 1.2-43 3.3-64H8.6C3.2 212.5 0 233.8 0 256s3.2 43.5 8.6 64h114.6c-2-21-3.2-42.5-3.2-64zm39.5 96c14.5 89.3 48.7 152 88.5 152s74-62.7 88.5-152h-177zm159.3 141.6c71.4-21.2 129.4-73.7 158-141.6h-108c-8.8 56.9-25.6 107.8-50 141.6zM19.3 352c28.6 67.9 86.5 120.4 158 141.6-24.4-33.8-41.2-84.7-50-141.6h-108z"></path></svg></a><span> </span></div></div></div><div class="team-member-card"><img src="/compose-docs/team/laird.jpg" alt="Angela Laird" class="team-member-image"><div class="team-member-info"><h3>Angela Laird</h3><p>Professor<br>Florida International University</p><div class="team-member-links"><a href="https://case.fiu.edu/about/directory/profiles/laird-angela.html" target="_blank" rel="noopener noreferrer"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 496 512" height="20" width="20" xmlns="http://www.w3.org/2000/svg"><path d="M336.5 160C322 70.7 287.8 8 248 8s-74 62.7-88.5 152h177zM152 256c0 22.2 1.2 43.5 3.3 64h185.3c2.1-20.5 3.3-41.8 3.3-64s-1.2-43.5-3.3-64H155.3c-2.1 20.5-3.3 41.8-3.3 64zm324.7-96c-28.6-67.9-86.5-120.4-158-141.6 24.4 33.8 41.2 84.7 50 141.6h108zM177.2 18.4C105.8 39.6 47.8 92.1 19.3 160h108c8.7-56.9 25.5-107.8 49.9-141.6zM487.4 192H372.7c2.1 21 3.3 42.5 3.3 64s-1.2 43-3.3 64h114.6c5.5-20.5 8.6-41.8 8.6-64s-3.1-43.5-8.5-64zM120 256c0-21.5 1.2-43 3.3-64H8.6C3.2 212.5 0 233.8 0 256s3.2 43.5 8.6 64h114.6c-2-21-3.2-42.5-3.2-64zm39.5 96c14.5 89.3 48.7 152 88.5 152s74-62.7 88.5-152h-177zm159.3 141.6c71.4-21.2 129.4-73.7 158-141.6h-108c-8.8 56.9-25.6 107.8-50 141.6zM19.3 352c28.6 67.9 86.5 120.4 158 141.6-24.4-33.8-41.2-84.7-50-141.6h-108z"></path></svg></a><span> </span></div></div></div><div class="team-member-card"><img src="/compose-docs/team/pedraza.jpg" alt="Julio Peraza" class="team-member-image"><div class="team-member-info"><h3>Julio Peraza</h3><p>Graduate Student<br>Florida International University</p><div class="team-member-links"><span> </span><a href="https://github.com/julioAPeraza" target="_blank" rel="noopener noreferrer" class="github-link"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 496 512" height="20" width="20" xmlns="http://www.w3.org/2000/svg"><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"></path></svg></a></div></div></div><div class="team-member-card"><img src="/compose-docs/team/poldrack.jpg" alt="Russ Poldrack" class="team-member-image"><div class="team-member-info"><h3>Russ Poldrack</h3><p>Professor<br>Stanford University</p><div class="team-member-links"><a href="http://poldracklab.org/" target="_blank" rel="noopener noreferrer"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 496 512" height="20" width="20" xmlns="http://www.w3.org/2000/svg"><path d="M336.5 160C322 70.7 287.8 8 248 8s-74 62.7-88.5 152h177zM152 256c0 22.2 1.2 43.5 3.3 64h185.3c2.1-20.5 3.3-41.8 3.3-64s-1.2-43.5-3.3-64H155.3c-2.1 20.5-3.3 41.8-3.3 64zm324.7-96c-28.6-67.9-86.5-120.4-158-141.6 24.4 33.8 41.2 84.7 50 141.6h108zM177.2 18.4C105.8 39.6 47.8 92.1 19.3 160h108c8.7-56.9 25.5-107.8 49.9-141.6zM487.4 192H372.7c2.1 21 3.3 42.5 3.3 64s-1.2 43-3.3 64h114.6c5.5-20.5 8.6-41.8 8.6-64s-3.1-43.5-8.5-64zM120 256c0-21.5 1.2-43 3.3-64H8.6C3.2 212.5 0 233.8 0 256s3.2 43.5 8.6 64h114.6c-2-21-3.2-42.5-3.2-64zm39.5 96c14.5 89.3 48.7 152 88.5 152s74-62.7 88.5-152h-177zm159.3 141.6c71.4-21.2 129.4-73.7 158-141.6h-108c-8.8 56.9-25.6 107.8-50 141.6zM19.3 352c28.6 67.9 86.5 120.4 158 141.6-24.4-33.8-41.2-84.7-50-141.6h-108z"></path></svg></a><span> </span><a href="https://github.com/poldrack" target="_blank" rel="noopener noreferrer" class="github-link"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 496 512" height="20" width="20" xmlns="http://www.w3.org/2000/svg"><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"></path></svg></a></div></div></div><div class="team-member-card"><img src="/compose-docs/team/nichols.jpg" alt="Tom Nichols" class="team-member-image"><div class="team-member-info"><h3>Tom Nichols</h3><p>Professor<br>Oxford University</p><div class="team-member-links"><a href="https://www.bdi.ox.ac.uk/Team/t-e-nichols" target="_blank" rel="noopener noreferrer"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 496 512" height="20" width="20" xmlns="http://www.w3.org/2000/svg"><path d="M336.5 160C322 70.7 287.8 8 248 8s-74 62.7-88.5 152h177zM152 256c0 22.2 1.2 43.5 3.3 64h185.3c2.1-20.5 3.3-41.8 3.3-64s-1.2-43.5-3.3-64H155.3c-2.1 20.5-3.3 41.8-3.3 64zm324.7-96c-28.6-67.9-86.5-120.4-158-141.6 24.4 33.8 41.2 84.7 50 141.6h108zM177.2 18.4C105.8 39.6 47.8 92.1 19.3 160h108c8.7-56.9 25.5-107.8 49.9-141.6zM487.4 192H372.7c2.1 21 3.3 42.5 3.3 64s-1.2 43-3.3 64h114.6c5.5-20.5 8.6-41.8 8.6-64s-3.1-43.5-8.5-64zM120 256c0-21.5 1.2-43 3.3-64H8.6C3.2 212.5 0 233.8 0 256s3.2 43.5 8.6 64h114.6c-2-21-3.2-42.5-3.2-64zm39.5 96c14.5 89.3 48.7 152 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aria-label="Home page" class="breadcrumbs__link" href="/compose-docs/"><svg viewBox="0 0 24 24" class="breadcrumbHomeIcon_YNFT"><path d="M10 19v-5h4v5c0 .55.45 1 1 1h3c.55 0 1-.45 1-1v-7h1.7c.46 0 .68-.57.33-.87L12.67 3.6c-.38-.34-.96-.34-1.34 0l-8.36 7.53c-.34.3-.13.87.33.87H5v7c0 .55.45 1 1 1h3c.55 0 1-.45 1-1z" fill="currentColor"></path></svg></a></li><li itemscope="" itemprop="itemListElement" itemtype="https://schema.org/ListItem" class="breadcrumbs__item breadcrumbs__item--active"><span class="breadcrumbs__link" itemprop="name">Tutorials</span><meta itemprop="position" content="1"></li></ul></nav><div class="theme-doc-markdown markdown"><h1>Tutorials</h1><p>Neurosynth Compose supports a range of different workflows, from exploratory large-scale automated analyses to highly curated and rigorous manual analyses.</p><p>The choice of workflow depends on the research question and the available resources. Note that you can choose to blend approaches from these two -ends of the spectrum, depending on your needs. Learn more about the different workflows by following the tutorials below.</p><div style="display:flex"><a style="width:100%;display:flex;margin-right:30px;cursor:pointer" href="/compose-docs/tutorial/manual"><style data-emotion="css i6bazn">.css-i6bazn{overflow:hidden;}</style><style data-emotion="css s18byi">.css-s18byi{background-color:#fff;color:rgba(0, 0, 0, 0.87);-webkit-transition:box-shadow 300ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;transition:box-shadow 300ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;border-radius:4px;box-shadow:0px 2px 1px -1px rgba(0,0,0,0.2),0px 1px 1px 0px rgba(0,0,0,0.14),0px 1px 3px 0px rgba(0,0,0,0.12);overflow:hidden;}</style><div class="MuiPaper-root MuiPaper-elevation MuiPaper-rounded MuiPaper-elevation1 MuiCard-root css-s18byi" style="border-radius:8px"><style data-emotion="css 1qw96cp">.css-1qw96cp{padding:16px;}.css-1qw96cp:last-child{padding-bottom:24px;}</style><div class="MuiCardContent-root css-1qw96cp"><style data-emotion="css t1nuxs">.css-t1nuxs{margin:0;font-family:"Roboto","Helvetica","Arial",sans-serif;font-weight:400;font-size:1.5rem;line-height:1.334;letter-spacing:0em;margin-bottom:0.35em;}</style><h2 class="MuiTypography-root MuiTypography-h5 MuiTypography-gutterBottom css-t1nuxs">Manual</h2><style data-emotion="css 1tqv6h6">.css-1tqv6h6{margin:0;font-family:"Roboto","Helvetica","Arial",sans-serif;font-weight:400;font-size:1rem;line-height:1.5;letter-spacing:0.00938em;margin-bottom:0.35em;}</style><p class="MuiTypography-root MuiTypography-body1 MuiTypography-gutterBottom css-1tqv6h6"><em>Most stringent and rigorous.</em><br><br></p><ul><li>Search across multiple sources, such as: PubMed, Web of Science, NeuroStore</li><li>Careful curation for inclusion/exclusion criteria</li><li>Extract coordinates from studies not already indexed</li><li>Meets PRISMA guidelines</li></ul><p></p></div></div></a><a style="width:100%;display:flex;margin-right:30px;cursor:pointer" href="/compose-docs/tutorial/automated"><style data-emotion="css i6bazn">.css-i6bazn{overflow:hidden;}</style><style data-emotion="css s18byi">.css-s18byi{background-color:#fff;color:rgba(0, 0, 0, 0.87);-webkit-transition:box-shadow 300ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;transition:box-shadow 300ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;border-radius:4px;box-shadow:0px 2px 1px -1px rgba(0,0,0,0.2),0px 1px 1px 0px rgba(0,0,0,0.14),0px 1px 3px 0px rgba(0,0,0,0.12);overflow:hidden;}</style><div class="MuiPaper-root MuiPaper-elevation MuiPaper-rounded MuiPaper-elevation1 MuiCard-root css-s18byi" style="border-radius:8px"><style data-emotion="css 1qw96cp">.css-1qw96cp{padding:16px;}.css-1qw96cp:last-child{padding-bottom:24px;}</style><div class="MuiCardContent-root css-1qw96cp"><style data-emotion="css t1nuxs">.css-t1nuxs{margin:0;font-family:"Roboto","Helvetica","Arial",sans-serif;font-weight:400;font-size:1.5rem;line-height:1.334;letter-spacing:0em;margin-bottom:0.35em;}</style><h2 class="MuiTypography-root MuiTypography-h5 MuiTypography-gutterBottom css-t1nuxs">Automated</h2><style data-emotion="css 1tqv6h6">.css-1tqv6h6{margin:0;font-family:"Roboto","Helvetica","Arial",sans-serif;font-weight:400;font-size:1rem;line-height:1.5;letter-spacing:0.00938em;margin-bottom:0.35em;}</style><p class="MuiTypography-root MuiTypography-body1 MuiTypography-gutterBottom css-1tqv6h6"><em>Fast exploratory analysis.</em><br><br></p><ul><li>Query studies at scale</li><li>Search using terms, topics or activation coordinates</li><li>Replicate results from original Neurosynth</li><li>Immediate results, ideal for a exploratory analysis</li></ul><p></p></div></div></a></div></div><footer class="theme-doc-footer docusaurus-mt-lg"><div class="theme-doc-footer-edit-meta-row row"><div class="col"><a href="https://github.com/neurostuff/compose-docs/edit/master/docs/tutorial/index.mdx" target="_blank" rel="noreferrer noopener" class="theme-edit-this-page"><svg fill="currentColor" height="20" 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class="footer__copyright">Copyright © 2023 Neuroinformatics Lab, Inc.</div></div></div></footer></div> -<script src="/compose-docs/assets/js/runtime~main.7d2821c4.js"></script> +ends of the spectrum, depending on your needs. Learn more about the different workflows by following the tutorials below.</p><div style="display:flex"><a style="width:100%;display:flex;margin-right:30px;cursor:pointer" href="/compose-docs/tutorial/manual"><style data-emotion="css i6bazn">.css-i6bazn{overflow:hidden;}</style><style data-emotion="css s18byi">.css-s18byi{background-color:#fff;color:rgba(0, 0, 0, 0.87);-webkit-transition:box-shadow 300ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;transition:box-shadow 300ms cubic-bezier(0.4, 0, 0.2, 1) 0ms;border-radius:4px;box-shadow:0px 2px 1px -1px rgba(0,0,0,0.2),0px 1px 1px 0px rgba(0,0,0,0.14),0px 1px 3px 0px rgba(0,0,0,0.12);overflow:hidden;}</style><div class="MuiPaper-root MuiPaper-elevation MuiPaper-rounded MuiPaper-elevation1 MuiCard-root css-s18byi" style="border-radius:8px"><style data-emotion="css 1qw96cp">.css-1qw96cp{padding:16px;}.css-1qw96cp:last-child{padding-bottom:24px;}</style><div class="MuiCardContent-root css-1qw96cp"><style data-emotion="css 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class="MuiTypography-root MuiTypography-h5 MuiTypography-gutterBottom css-t1nuxs">Automated</h2><style data-emotion="css 1tqv6h6">.css-1tqv6h6{margin:0;font-family:"Roboto","Helvetica","Arial",sans-serif;font-weight:400;font-size:1rem;line-height:1.5;letter-spacing:0.00938em;margin-bottom:0.35em;}</style><p class="MuiTypography-root MuiTypography-body1 MuiTypography-gutterBottom css-1tqv6h6"><em>Fast exploratory analysis.</em><br><br></p><ul><li>Query studies at scale</li><li>Search using terms, topics or activation coordinates</li><li>Replicate results from original Neurosynth</li><li>Immediate results, ideal for a exploratory analysis</li></ul><p></p></div></div></a></div></div><footer class="theme-doc-footer docusaurus-mt-lg"><div class="theme-doc-footer-edit-meta-row row"><div class="col"><a href="https://github.com/neurostuff/compose-docs/edit/master/docs/tutorial/index.mdx" target="_blank" rel="noreferrer noopener" class="theme-edit-this-page"><svg fill="currentColor" height="20" 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menu__link--active" aria-current="page" tabindex="0" href="/compose-docs/tutorial/automated">Automated Meta-Analysis</a></li></ul></li></ul></nav></div></div></aside><main class="docMainContainer_gTbr"><div class="container padding-top--md padding-bottom--lg"><div class="row"><div class="col docItemCol_VOVn"><div class="docItemContainer_Djhp"><article><nav class="theme-doc-breadcrumbs breadcrumbsContainer_Z_bl" aria-label="Breadcrumbs"><ul class="breadcrumbs" itemscope="" itemtype="https://schema.org/BreadcrumbList"><li class="breadcrumbs__item"><a aria-label="Home page" class="breadcrumbs__link" href="/compose-docs/"><svg viewBox="0 0 24 24" class="breadcrumbHomeIcon_YNFT"><path d="M10 19v-5h4v5c0 .55.45 1 1 1h3c.55 0 1-.45 1-1v-7h1.7c.46 0 .68-.57.33-.87L12.67 3.6c-.38-.34-.96-.34-1.34 0l-8.36 7.53c-.34.3-.13.87.33.87H5v7c0 .55.45 1 1 1h3c.55 0 1-.45 1-1z" fill="currentColor"></path></svg></a></li><li itemscope="" itemprop="itemListElement" itemtype="https://schema.org/ListItem" class="breadcrumbs__item"><a class="breadcrumbs__link" itemprop="item" href="/compose-docs/tutorial"><span itemprop="name">Tutorials</span></a><meta itemprop="position" content="1"></li><li itemscope="" itemprop="itemListElement" itemtype="https://schema.org/ListItem" class="breadcrumbs__item breadcrumbs__item--active"><span class="breadcrumbs__link" itemprop="name">Automated Meta-Analysis</span><meta itemprop="position" content="2"></li></ul></nav><div class="tocCollapsible_ETCw theme-doc-toc-mobile tocMobile_ITEo"><button type="button" class="clean-btn tocCollapsibleButton_TO0P">On this page</button></div><div class="theme-doc-markdown markdown"><h1>Automated Meta-Analysis</h1><div class="theme-admonition theme-admonition-caution alert alert--warning admonition_LlT9"><div class="admonitionHeading_tbUL"><span class="admonitionIcon_kALy"><svg viewBox="0 0 16 16"><path fill-rule="evenodd" d="M8.893 1.5c-.183-.31-.52-.5-.887-.5s-.703.19-.886.5L.138 13.499a.98.98 0 0 0 0 1.001c.193.31.53.501.886.501h13.964c.367 0 .704-.19.877-.5a1.03 1.03 0 0 0 .01-1.002L8.893 1.5zm.133 11.497H6.987v-2.003h2.039v2.003zm0-3.004H6.987V5.987h2.039v4.006z"></path></svg></span>caution</div><div class="admonitionContent_S0QG"><p>This tutorial, and the functionality for automated meta-analysis, is under construction. -To view existing automated meta-analyses, you can use <a href="https://neurosynth.org" target="_blank" rel="noopener noreferrer">Neurosynth Original</a></p></div></div><h2 class="anchor anchorWithStickyNavbar_LWe7" id="why-automated-meta-analysis">Why automated meta-analysis?<a href="#why-automated-meta-analysis" class="hash-link" aria-label="Direct link to Why automated meta-analysis?" title="Direct link to Why automated meta-analysis?"></a></h2><p>The principal difference between an automated and a <a href="/compose-docs/tutorial/manual">manual meta-analysis</a> is <em>the process used to select the final set of Studies and Analyses to include</em> into your meta-analysis. </p><p>In a <strong>manual meta-analysis</strong>, researchers cast a wide net to find a wide range of potentially relevant articles, and use their expertise (read: painstakingly review hundreds of articles) to decide which of articles are relevant to their research question. Our platform seeks streamline this process through a user-friendly interface and pre-extracted data for over 20,000 neuroimaging studies. Yet, <strong>a gold standard meta-analysis still requires a significant time investment</strong>, limiting their application in routine scientific practice.</p><p>In an <strong>automated meta-analysis</strong>, we instead use data-driven text mining metrics to <em>select</em> articles. The original <em>Neurosynth</em> pioneered this approach by developing text mining techniques to automatically extract brain coordinates and semantic text features from thousands of articles. </p><p>Surprisingly, this works! For example, by meta-analyzing all studies that mention the term <a href="https://neurosynth.org/analyses/terms/emotional/" target="_blank" rel="noopener noreferrer">"emotional"</a> above a certain frequency, we observe a strong association with activity in the amygdala. By and large, the sheer number of studies overcomes the inherent noisiness of automated data extraction and study selection. </p><h3 class="anchor anchorWithStickyNavbar_LWe7" id="flexible-automated-meta-analysis-in-neurosynth-compose">Flexible automated meta-analysis in Neurosynth Compose<a href="#flexible-automated-meta-analysis-in-neurosynth-compose" class="hash-link" aria-label="Direct link to Flexible automated meta-analysis in Neurosynth Compose" title="Direct link to Flexible automated meta-analysis in Neurosynth Compose"></a></h3><p>Although automated meta-analyses have proved to be a useful tool, there are several limitations. The overal goal of <em>Neurosynth Compose</em> is to give users a flexible data curation platform, to overcome these limitations using their expert knowledge. For example:</p><ul><li><em>Flexible selection criteria.</em> The original Neurosynth has a fixed number of terms and meta-analyses. With<em>Neurosynth Compose</em> you can flexibly search the NeuroStore database using a powerful and flexible search to precisely define your search criteria. </li><li><em>Combine expert knowledge with automated selection.</em> Automated study selection is inherently an noisy and imperfect measure. With <em>Neurosynth Compose</em>, you can use automated study selection as a first pass, and later apply your own expert criteria to refine study inclusion criteria. </li><li><em>Correct data extraction errors.</em> Automated extraction can miss entire tables of coordinates (e.g. supplementary materials), duplicate coordinates, and groups distinct sets of Analyses (e.g. Contrasts) into a single group. Now, you can correct these data to make your meta-analysis more precise. </li></ul><h2 class="anchor anchorWithStickyNavbar_LWe7" id="tutorial">Tutorial<a href="#tutorial" class="hash-link" aria-label="Direct link to Tutorial" title="Direct link to Tutorial"></a></h2><p>An automated meta-analysis in <em>Neurosynth Compose</em> looks a lot like a manual one, except data curation is optional. We reccomend following the <a href="/compose-docs/tutorial/manual">manual meta-analysis</a> tutorial to learn in depth about our platform.</p><h3 class="anchor anchorWithStickyNavbar_LWe7" id="search--curate">Search & Curate<a href="#search--curate" class="hash-link" aria-label="Direct link to Search & Curate" title="Direct link to Search & Curate"></a></h3><p>One of the main differences between a <em>manual</em> and <em>automated</em> meta-analysis, is the steps required to select studies. As such, we reccomend selecting the "Simple" curation workflow, which only consists of a single data curation step (which is optional). </p><p><img loading="lazy" alt="Simple Workflow" src="/compose-docs/assets/images/automated_workflow-8bea486d4904648bcafa7ea0aa3ccf05.png" width="2128" height="923" class="img_ev3q">. </p><div class="theme-admonition theme-admonition-tip alert alert--success admonition_LlT9"><div class="admonitionHeading_tbUL"><span class="admonitionIcon_kALy"><svg viewBox="0 0 12 16"><path fill-rule="evenodd" d="M6.5 0C3.48 0 1 2.19 1 5c0 .92.55 2.25 1 3 1.34 2.25 1.78 2.78 2 4v1h5v-1c.22-1.22.66-1.75 2-4 .45-.75 1-2.08 1-3 0-2.81-2.48-5-5.5-5zm3.64 7.48c-.25.44-.47.8-.67 1.11-.86 1.41-1.25 2.06-1.45 3.23-.02.05-.02.11-.02.17H5c0-.06 0-.13-.02-.17-.2-1.17-.59-1.83-1.45-3.23-.2-.31-.42-.67-.67-1.11C2.44 6.78 2 5.65 2 5c0-2.2 2.02-4 4.5-4 1.22 0 2.36.42 3.22 1.19C10.55 2.94 11 3.94 11 5c0 .66-.44 1.78-.86 2.48zM4 14h5c-.23 1.14-1.3 2-2.5 2s-2.27-.86-2.5-2z"></path></svg></span>tip</div><div class="admonitionContent_S0QG"><p>Decide ahead of time if you want to perform a Coordinate or an Image based meta-analysis. Image-based Meta-Analysis (IBMA) is more precise and powerful, but there are much fewer studies available. </p></div></div><h4 class="anchor anchorWithStickyNavbar_LWe7" id="import-from-neurostore">Import from Neurostore<a href="#import-from-neurostore" class="hash-link" aria-label="Direct link to Import from Neurostore" title="Direct link to Import from Neurostore"></a></h4><p>Let's add studies to our curation board by clicking <strong>Import Studies</strong>. -In an automated meta-analysis, you'll want to select <em>Import via NeuroStore</em>, as all indexed studies are guaranteed to contain imaging data (saving you from manual data extraction).</p><div class="theme-admonition theme-admonition-caution alert alert--warning admonition_LlT9"><div class="admonitionHeading_tbUL"><span class="admonitionIcon_kALy"><svg viewBox="0 0 16 16"><path fill-rule="evenodd" d="M8.893 1.5c-.183-.31-.52-.5-.887-.5s-.703.19-.886.5L.138 13.499a.98.98 0 0 0 0 1.001c.193.31.53.501.886.501h13.964c.367 0 .704-.19.877-.5a1.03 1.03 0 0 0 .01-1.002L8.893 1.5zm.133 11.497H6.987v-2.003h2.039v2.003zm0-3.004H6.987V5.987h2.039v4.006z"></path></svg></span>caution</div><div class="admonitionContent_S0QG"><p>Although the NeuroStore database is continously growing, it is necessarily an incomplete snapshot of the neuroimaging literature</p></div></div><p>Input any search term to narrow down studies. This will search the Title and Abstract fields. You may also add additional search filters using the <strong>+ Add Filter</strong> button, and <em>select the desired modality of the imaging data</em>. </p><p><img loading="lazy" alt="Neurostore Search" src="/compose-docs/assets/images/automated_search_neurostore-8727f551752008b51b8d58e99a652605.png" width="1849" height="1523" class="img_ev3q">. </p><p>To import your search, click "Import Studies From Neurostore" at the bottom right. Give your import a name to Tag all imported studies, and continue back to your Curation board. </p><div class="theme-admonition theme-admonition-note alert alert--secondary admonition_LlT9"><div class="admonitionHeading_tbUL"><span class="admonitionIcon_kALy"><svg viewBox="0 0 14 16"><path fill-rule="evenodd" d="M6.3 5.69a.942.942 0 0 1-.28-.7c0-.28.09-.52.28-.7.19-.18.42-.28.7-.28.28 0 .52.09.7.28.18.19.28.42.28.7 0 .28-.09.52-.28.7a1 1 0 0 1-.7.3c-.28 0-.52-.11-.7-.3zM8 7.99c-.02-.25-.11-.48-.31-.69-.2-.19-.42-.3-.69-.31H6c-.27.02-.48.13-.69.31-.2.2-.3.44-.31.69h1v3c.02.27.11.5.31.69.2.2.42.31.69.31h1c.27 0 .48-.11.69-.31.2-.19.3-.42.31-.69H8V7.98v.01zM7 2.3c-3.14 0-5.7 2.54-5.7 5.68 0 3.14 2.56 5.7 5.7 5.7s5.7-2.55 5.7-5.7c0-3.15-2.56-5.69-5.7-5.69v.01zM7 .98c3.86 0 7 3.14 7 7s-3.14 7-7 7-7-3.12-7-7 3.14-7 7-7z"></path></svg></span>note</div><div class="admonitionContent_S0QG"><p>You must import an entire set of search results into your curation board. If you want to exclude any specific studies, you will do so on your board. This allows the Search & Curate process to be fully reproducible.</p></div></div><h4 class="anchor anchorWithStickyNavbar_LWe7" id="promote-studies">Promote studies<a href="#promote-studies" class="hash-link" aria-label="Direct link to Promote studies" title="Direct link to Promote studies"></a></h4><p>Back to your Curation board, you will now see all studies from your NeuroStore search on the left most column.</p><p><img loading="lazy" alt="Curation board" src="/compose-docs/assets/images/automated_curation-371eefa2a58043457c9b63a79728b217.png" width="2583" height="1604" class="img_ev3q">. </p><p>At this point, you have two options: manually review the search results and select which studies to include, or perform a fully automated meta-analysis by including all search results. </p><p>For this tutorial, we'll skip manual curation and <strong>Promote All Uncategorized Studies</strong> to the right-most "Included" column. </p><p>We can now click <em>Move to Extraction Phase</em>.</p><h3 class="anchor anchorWithStickyNavbar_LWe7" id="extraction-and-annotation">Extraction and Annotation<a href="#extraction-and-annotation" class="hash-link" aria-label="Direct link to Extraction and Annotation" title="Direct link to Extraction and Annotation"></a></h3><p>At this point, you will create a StudySet containing all of your Studies. Advance through the dialog to begin <em>Extraction</em>.</p><p>The goal of this phase is to add or correct imaging data (e.g. Coordinates) in imported studies, and create Annotations to determine which Analyses (e.g. Contrasts), should be included in your meta-analysis.</p><p>Since we are perfomring a manual meta-analysis, we're going to skip these steps!</p><p>From the main <em>Project</em> page, we can click "Mark All as Complete".</p><p><img loading="lazy" alt="Skip Extraction" src="/compose-docs/assets/images/automated_skip_extraction-a686288de267f089b546b703f315f5f0.png" width="1263" height="855" class="img_ev3q">. </p><div class="theme-admonition theme-admonition-tip alert alert--success admonition_LlT9"><div class="admonitionHeading_tbUL"><span class="admonitionIcon_kALy"><svg viewBox="0 0 12 16"><path fill-rule="evenodd" d="M6.5 0C3.48 0 1 2.19 1 5c0 .92.55 2.25 1 3 1.34 2.25 1.78 2.78 2 4v1h5v-1c.22-1.22.66-1.75 2-4 .45-.75 1-2.08 1-3 0-2.81-2.48-5-5.5-5zm3.64 7.48c-.25.44-.47.8-.67 1.11-.86 1.41-1.25 2.06-1.45 3.23-.02.05-.02.11-.02.17H5c0-.06 0-.13-.02-.17-.2-1.17-.59-1.83-1.45-3.23-.2-.31-.42-.67-.67-1.11C2.44 6.78 2 5.65 2 5c0-2.2 2.02-4 4.5-4 1.22 0 2.36.42 3.22 1.19C10.55 2.94 11 3.94 11 5c0 .66-.44 1.78-.86 2.48zM4 14h5c-.23 1.14-1.3 2-2.5 2s-2.27-.86-2.5-2z"></path></svg></span>tip</div><div class="admonitionContent_S0QG"><p>It's up to you if you want to skip this step. The validity of your meta-analysis is highly dependant on input data, so we only reccomend skipping all curation for exploratory analyses.</p></div></div><h3 class="anchor anchorWithStickyNavbar_LWe7" id="specify-meta-analyses">Specify Meta-Analyses<a href="#specify-meta-analyses" class="hash-link" aria-label="Direct link to Specify Meta-Analyses" title="Direct link to Specify Meta-Analyses"></a></h3><p>You can now specify your meta-analysis. This step will be identical between automated and manual meta-analyses.</p><p>First, we select the "included" column, which by default includes <em>all</em> Study Analyses as inputs.</p><p><img loading="lazy" alt="Inclusion column" src="/compose-docs/assets/images/automated_included_column-d2edd791b32654783c43877948de76f5.png" width="1368" height="1715" class="img_ev3q">. </p><p>Next, we select a meta-analysis algorithm. This time, we'll select MKDA Chi-Squared (<code>MKDAChi2</code>) with <code>FDRCorrector</code>. </p><p>MKDA Chi-Square compares your StudySet to a reference set of studies (all the studies in NeuroStore that you did <em>not</em> select), allowing you to identify areas of stronger association with your selected studies. This is the algorithm used in the original Neurosynth Platform.</p><h3 class="anchor anchorWithStickyNavbar_LWe7" id="execute">Execute<a href="#execute" class="hash-link" aria-label="Direct link to Execute" title="Direct link to Execute"></a></h3><p>Once you specify your meta-analysis, you can execute it in the cloud using Google Colab using your unique meta-analysis id. </p><p><img loading="lazy" alt="Automated execute" src="/compose-docs/assets/images/automated_execute-a020e8de9a3379dddedca4d00e04f3a6.png" width="1551" height="1098" class="img_ev3q">. </p><p>Congratulations, you have now run an automated meta-analysis!</p><p>Remember, just because it is easy to run a meta-analysis and get results, does not mean the results are valid. -It is important to think about the validity of your study selection process, for both manual and automated meta-analyses.</p></div><footer class="theme-doc-footer docusaurus-mt-lg"><div class="theme-doc-footer-edit-meta-row row"><div class="col"><a href="https://github.com/neurostuff/compose-docs/edit/master/docs/tutorial/automated.md" target="_blank" rel="noreferrer noopener" class="theme-edit-this-page"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_Z9Sw" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col lastUpdated_vwxv"><span class="theme-last-updated">Last updated<!-- --> on <b><time datetime="2023-11-27T23:56:16.000Z">Nov 27, 2023</time></b> by <b>Alejandro de la Vega</b></span></div></div></footer></article><nav class="pagination-nav docusaurus-mt-lg" aria-label="Docs pages navigation"><a class="pagination-nav__link pagination-nav__link--prev" href="/compose-docs/tutorial/manual"><div class="pagination-nav__sublabel">Previous</div><div class="pagination-nav__label">Manual Meta-Analysis</div></a></nav></div></div><div class="col col--3"><div class="tableOfContents_bqdL thin-scrollbar theme-doc-toc-desktop"><ul class="table-of-contents table-of-contents__left-border"><li><a href="#why-automated-meta-analysis" class="table-of-contents__link toc-highlight">Why automated meta-analysis?</a><ul><li><a href="#flexible-automated-meta-analysis-in-neurosynth-compose" class="table-of-contents__link toc-highlight">Flexible automated meta-analysis in Neurosynth Compose</a></li></ul></li><li><a href="#tutorial" class="table-of-contents__link toc-highlight">Tutorial</a><ul><li><a href="#search--curate" class="table-of-contents__link toc-highlight">Search & Curate</a></li><li><a href="#extraction-and-annotation" class="table-of-contents__link toc-highlight">Extraction and Annotation</a></li><li><a href="#specify-meta-analyses" class="table-of-contents__link toc-highlight">Specify Meta-Analyses</a></li><li><a href="#execute" class="table-of-contents__link toc-highlight">Execute</a></li></ul></li></ul></div></div></div></div></main></div></div><footer class="footer footer--dark"><div class="container container-fluid"><div class="row footer__links"><div class="col footer__col"><div class="footer__title">Docs</div><ul class="footer__items clean-list"><li class="footer__item"><a class="footer__link-item" href="/compose-docs/">Docs</a></li></ul></div><div class="col footer__col"><div class="footer__title">Community</div><ul class="footer__items clean-list"><li class="footer__item"><a href="https://neurostars.org/tag/neuroscout" target="_blank" rel="noopener noreferrer" class="footer__link-item">NeuroStars<svg width="13.5" height="13.5" aria-hidden="true" viewBox="0 0 24 24" class="iconExternalLink_nPIU"><path fill="currentColor" d="M21 13v10h-21v-19h12v2h-10v15h17v-8h2zm3-12h-10.988l4.035 4-6.977 7.07 2.828 2.828 6.977-7.07 4.125 4.172v-11z"></path></svg></a></li><li class="footer__item"><a href="https://twitter.com/neurosynth" 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class="footer__bottom text--center"><div class="footer__copyright">Copyright © 2023 Neuroinformatics Lab, Inc.</div></div></div></footer></div> -<script src="/compose-docs/assets/js/runtime~main.7d2821c4.js"></script> +To view existing automated meta-analyses, you can use <a href="https://neurosynth.org" target="_blank" rel="noopener noreferrer">Neurosynth Original</a></p></div></div><h2 class="anchor anchorWithStickyNavbar_LWe7" id="why-automated-meta-analysis">Why automated meta-analysis?<a href="#why-automated-meta-analysis" class="hash-link" aria-label="Direct link to Why automated meta-analysis?" title="Direct link to Why automated meta-analysis?"></a></h2><p>The principal difference between an automated and a <a href="/compose-docs/tutorial/manual">manual meta-analysis</a> is <em>the process used to select the final set of Studies and Analyses to include</em> into your meta-analysis. </p><p>In a <strong>manual meta-analysis</strong>, researchers cast a wide net to find a wide range of potentially relevant articles, and use their expertise (read: painstakingly review hundreds of articles) to decide which of articles are relevant to their research question. Our platform seeks streamline this process through a user-friendly interface and pre-extracted data for over 20,000 neuroimaging studies. Yet, <strong>a gold standard meta-analysis still requires a significant time investment</strong>, limiting their application in routine scientific practice.</p><p>In an <strong>automated meta-analysis</strong>, we instead use data-driven text mining metrics to <em>select</em> articles. The original <em>Neurosynth</em> pioneered this approach by developing text mining techniques to automatically extract brain coordinates and semantic text features from thousands of articles. </p><p>Surprisingly, this works! For example, by meta-analyzing all studies that mention the term <a href="https://neurosynth.org/analyses/terms/emotional/" target="_blank" rel="noopener noreferrer">"emotional"</a> above a certain frequency, we observe a strong association with activity in the amygdala. By and large, the sheer number of studies overcomes the inherent noisiness of automated data extraction and study selection. </p><h3 class="anchor anchorWithStickyNavbar_LWe7" id="flexible-automated-meta-analysis-in-neurosynth-compose">Flexible automated meta-analysis in Neurosynth Compose<a href="#flexible-automated-meta-analysis-in-neurosynth-compose" class="hash-link" aria-label="Direct link to Flexible automated meta-analysis in Neurosynth Compose" title="Direct link to Flexible automated meta-analysis in Neurosynth Compose"></a></h3><p>Although automated meta-analyses have proved to be a useful tool, there are several limitations. The overall goal of <em>Neurosynth Compose</em> is to give users a flexible data curation platform, to overcome these limitations using their expert knowledge. For example:</p><ul><li><em>Flexible selection criteria.</em> The original Neurosynth has a fixed number of terms and meta-analyses. With<em>Neurosynth Compose</em> you can flexibly search the NeuroStore database using a powerful and flexible search to precisely define your search criteria. </li><li><em>Combine expert knowledge with automated selection.</em> Automated study selection is inherently an noisy and imperfect measure. With <em>Neurosynth Compose</em>, you can use automated study selection as a first pass, and later apply your own expert criteria to refine study inclusion criteria. </li><li><em>Correct data extraction errors.</em> Automated extraction can miss entire tables of coordinates (e.g. supplementary materials), duplicate coordinates, and groups distinct sets of Analyses (e.g. Contrasts) into a single group. Now, you can correct these data to make your meta-analysis more precise. </li></ul><h2 class="anchor anchorWithStickyNavbar_LWe7" id="tutorial">Tutorial<a href="#tutorial" class="hash-link" aria-label="Direct link to Tutorial" title="Direct link to Tutorial"></a></h2><p>An automated meta-analysis in <em>Neurosynth Compose</em> looks a lot like a manual one, except data curation is optional. We reccomeend following the <a href="/compose-docs/tutorial/manual">manual meta-analysis</a> tutorial to learn in depth about our platform.</p><h3 class="anchor anchorWithStickyNavbar_LWe7" id="search--curate">Search & Curate<a href="#search--curate" class="hash-link" aria-label="Direct link to Search & Curate" title="Direct link to Search & Curate"></a></h3><p>One of the main differences between a <em>manual</em> and <em>automated</em> meta-analysis, is the steps required to select studies. As such, we reccomeend selecting the "Simple" curation workflow, which only consists of a single data curation step (which is optional). </p><p><img loading="lazy" alt="Simple Workflow" src="/compose-docs/assets/images/automated_workflow-8bea486d4904648bcafa7ea0aa3ccf05.png" width="2128" height="923" class="img_ev3q">. </p><div class="theme-admonition theme-admonition-tip alert alert--success admonition_LlT9"><div class="admonitionHeading_tbUL"><span class="admonitionIcon_kALy"><svg viewBox="0 0 12 16"><path fill-rule="evenodd" d="M6.5 0C3.48 0 1 2.19 1 5c0 .92.55 2.25 1 3 1.34 2.25 1.78 2.78 2 4v1h5v-1c.22-1.22.66-1.75 2-4 .45-.75 1-2.08 1-3 0-2.81-2.48-5-5.5-5zm3.64 7.48c-.25.44-.47.8-.67 1.11-.86 1.41-1.25 2.06-1.45 3.23-.02.05-.02.11-.02.17H5c0-.06 0-.13-.02-.17-.2-1.17-.59-1.83-1.45-3.23-.2-.31-.42-.67-.67-1.11C2.44 6.78 2 5.65 2 5c0-2.2 2.02-4 4.5-4 1.22 0 2.36.42 3.22 1.19C10.55 2.94 11 3.94 11 5c0 .66-.44 1.78-.86 2.48zM4 14h5c-.23 1.14-1.3 2-2.5 2s-2.27-.86-2.5-2z"></path></svg></span>tip</div><div class="admonitionContent_S0QG"><p>Decide ahead of time if you want to perform a Coordinate or an Image based meta-analysis. Image-based Meta-Analysis (IBMA) is more precise and powerful, but there are much fewer studies available. </p></div></div><h4 class="anchor anchorWithStickyNavbar_LWe7" id="import-from-neurostore">Import from Neurostore<a href="#import-from-neurostore" class="hash-link" aria-label="Direct link to Import from Neurostore" title="Direct link to Import from Neurostore"></a></h4><p>Let's add studies to our curation board by clicking <strong>Import Studies</strong>. +In an automated meta-analysis, you'll want to select <em>Import via NeuroStore</em>, as all indexed studies are guaranteed to contain imaging data (saving you from manual data extraction).</p><div class="theme-admonition theme-admonition-caution alert alert--warning admonition_LlT9"><div class="admonitionHeading_tbUL"><span class="admonitionIcon_kALy"><svg viewBox="0 0 16 16"><path fill-rule="evenodd" d="M8.893 1.5c-.183-.31-.52-.5-.887-.5s-.703.19-.886.5L.138 13.499a.98.98 0 0 0 0 1.001c.193.31.53.501.886.501h13.964c.367 0 .704-.19.877-.5a1.03 1.03 0 0 0 .01-1.002L8.893 1.5zm.133 11.497H6.987v-2.003h2.039v2.003zm0-3.004H6.987V5.987h2.039v4.006z"></path></svg></span>caution</div><div class="admonitionContent_S0QG"><p>Although the NeuroStore database is continuously growing, it is necessarily an incomplete snapshot of the neuroimaging literature</p></div></div><p>Input any search term to narrow down studies. This will search the Title and Abstract fields. You may also add additional search filters using the <strong>+ Add Filter</strong> button, and <em>select the desired modality of the imaging data</em>. </p><p><img loading="lazy" alt="Neurostore Search" src="/compose-docs/assets/images/automated_search_neurostore-8727f551752008b51b8d58e99a652605.png" width="1849" height="1523" class="img_ev3q">. </p><p>To import your search, click "Import Studies From Neurostore" at the bottom right. Give your import a name to Tag all imported studies, and continue back to your Curation board. </p><div class="theme-admonition theme-admonition-note alert alert--secondary admonition_LlT9"><div class="admonitionHeading_tbUL"><span class="admonitionIcon_kALy"><svg viewBox="0 0 14 16"><path fill-rule="evenodd" d="M6.3 5.69a.942.942 0 0 1-.28-.7c0-.28.09-.52.28-.7.19-.18.42-.28.7-.28.28 0 .52.09.7.28.18.19.28.42.28.7 0 .28-.09.52-.28.7a1 1 0 0 1-.7.3c-.28 0-.52-.11-.7-.3zM8 7.99c-.02-.25-.11-.48-.31-.69-.2-.19-.42-.3-.69-.31H6c-.27.02-.48.13-.69.31-.2.2-.3.44-.31.69h1v3c.02.27.11.5.31.69.2.2.42.31.69.31h1c.27 0 .48-.11.69-.31.2-.19.3-.42.31-.69H8V7.98v.01zM7 2.3c-3.14 0-5.7 2.54-5.7 5.68 0 3.14 2.56 5.7 5.7 5.7s5.7-2.55 5.7-5.7c0-3.15-2.56-5.69-5.7-5.69v.01zM7 .98c3.86 0 7 3.14 7 7s-3.14 7-7 7-7-3.12-7-7 3.14-7 7-7z"></path></svg></span>note</div><div class="admonitionContent_S0QG"><p>You must import an entire set of search results into your curation board. If you want to exclude any specific studies, you will do so on your board. This allows the Search & Curate process to be fully reproducible.</p></div></div><h4 class="anchor anchorWithStickyNavbar_LWe7" id="promote-studies">Promote studies<a href="#promote-studies" class="hash-link" aria-label="Direct link to Promote studies" title="Direct link to Promote studies"></a></h4><p>Back to your Curation board, you will now see all studies from your NeuroStore search on the left most column.</p><p><img loading="lazy" alt="Curation board" src="/compose-docs/assets/images/automated_curation-371eefa2a58043457c9b63a79728b217.png" width="2583" height="1604" class="img_ev3q">. </p><p>At this point, you have two options: manually review the search results and select which studies to include, or perform a fully automated meta-analysis by including all search results. </p><p>For this tutorial, we'll skip manual curation and <strong>Promote All Uncategorized Studies</strong> to the right-most "Included" column. </p><p>We can now click <em>Move to Extraction Phase</em>.</p><h3 class="anchor anchorWithStickyNavbar_LWe7" id="extraction-and-annotation">Extraction and Annotation<a href="#extraction-and-annotation" class="hash-link" aria-label="Direct link to Extraction and Annotation" title="Direct link to Extraction and Annotation"></a></h3><p>At this point, you will create a StudySet containing all of your Studies. Advance through the dialog to begin <em>Extraction</em>.</p><p>The goal of this phase is to add or correct imaging data (e.g. Coordinates) in imported studies, and create Annotations to determine which Analyses (e.g. Contrasts), should be included in your meta-analysis.</p><p>Since we are performing a manual meta-analysis, we're going to skip these steps!</p><p>From the main <em>Project</em> page, we can click "Mark All as Complete".</p><p><img loading="lazy" alt="Skip Extraction" src="/compose-docs/assets/images/automated_skip_extraction-a686288de267f089b546b703f315f5f0.png" width="1263" height="855" class="img_ev3q">. </p><div class="theme-admonition theme-admonition-tip alert alert--success admonition_LlT9"><div class="admonitionHeading_tbUL"><span class="admonitionIcon_kALy"><svg viewBox="0 0 12 16"><path fill-rule="evenodd" d="M6.5 0C3.48 0 1 2.19 1 5c0 .92.55 2.25 1 3 1.34 2.25 1.78 2.78 2 4v1h5v-1c.22-1.22.66-1.75 2-4 .45-.75 1-2.08 1-3 0-2.81-2.48-5-5.5-5zm3.64 7.48c-.25.44-.47.8-.67 1.11-.86 1.41-1.25 2.06-1.45 3.23-.02.05-.02.11-.02.17H5c0-.06 0-.13-.02-.17-.2-1.17-.59-1.83-1.45-3.23-.2-.31-.42-.67-.67-1.11C2.44 6.78 2 5.65 2 5c0-2.2 2.02-4 4.5-4 1.22 0 2.36.42 3.22 1.19C10.55 2.94 11 3.94 11 5c0 .66-.44 1.78-.86 2.48zM4 14h5c-.23 1.14-1.3 2-2.5 2s-2.27-.86-2.5-2z"></path></svg></span>tip</div><div class="admonitionContent_S0QG"><p>It's up to you if you want to skip this step. The validity of your meta-analysis is highly dependant on input data, so we only recommend skipping all curation for exploratory analyses.</p></div></div><h3 class="anchor anchorWithStickyNavbar_LWe7" id="specify-meta-analyses">Specify Meta-Analyses<a href="#specify-meta-analyses" class="hash-link" aria-label="Direct link to Specify Meta-Analyses" title="Direct link to Specify Meta-Analyses"></a></h3><p>You can now specify your meta-analysis. This step will be identical between automated and manual meta-analyses.</p><p>First, we select the "included" column, which by default includes <em>all</em> Study Analyses as inputs.</p><p><img loading="lazy" alt="Inclusion column" src="/compose-docs/assets/images/automated_included_column-d2edd791b32654783c43877948de76f5.png" width="1368" height="1715" class="img_ev3q">. </p><p>Next, we select a meta-analysis algorithm. This time, we'll select MKDA Chi-Squared (<code>MKDAChi2</code>) with <code>FDRCorrector</code>. </p><p>MKDA Chi-Square compares your StudySet to a reference set of studies (all the studies in NeuroStore that you did <em>not</em> select), allowing you to identify areas of stronger association with your selected studies. This is the algorithm used in the original Neurosynth Platform.</p><h3 class="anchor anchorWithStickyNavbar_LWe7" id="execute">Execute<a href="#execute" class="hash-link" aria-label="Direct link to Execute" title="Direct link to Execute"></a></h3><p>Once you specify your meta-analysis, you can execute it in the cloud using Google Colab using your unique meta-analysis id. </p><p><img loading="lazy" alt="Automated execute" src="/compose-docs/assets/images/automated_execute-a020e8de9a3379dddedca4d00e04f3a6.png" width="1551" height="1098" class="img_ev3q">. </p><p>Congratulations, you have now run an automated meta-analysis!</p><p>Remember, just because it is easy to run a meta-analysis and get results, does not mean the results are valid. +It is important to think about the validity of your study selection process, for both manual and automated meta-analyses.</p></div><footer class="theme-doc-footer docusaurus-mt-lg"><div class="theme-doc-footer-edit-meta-row row"><div class="col"><a 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Meta-Analysis</div></a></nav></div></div><div class="col col--3"><div class="tableOfContents_bqdL thin-scrollbar theme-doc-toc-desktop"><ul class="table-of-contents table-of-contents__left-border"><li><a href="#why-automated-meta-analysis" class="table-of-contents__link toc-highlight">Why automated meta-analysis?</a><ul><li><a href="#flexible-automated-meta-analysis-in-neurosynth-compose" class="table-of-contents__link toc-highlight">Flexible automated meta-analysis in Neurosynth Compose</a></li></ul></li><li><a href="#tutorial" class="table-of-contents__link toc-highlight">Tutorial</a><ul><li><a href="#search--curate" class="table-of-contents__link toc-highlight">Search & Curate</a></li><li><a href="#extraction-and-annotation" class="table-of-contents__link toc-highlight">Extraction and Annotation</a></li><li><a href="#specify-meta-analyses" class="table-of-contents__link toc-highlight">Specify Meta-Analyses</a></li><li><a href="#execute" class="table-of-contents__link 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class="navigation-with-keyboard"> @@ -21,7 +21,7 @@ for gold-standard meta-analyses. The PRISMA guidelines ensure a systematic selection and reporting process. However, a Simple workflow may be useful for exploratory and automated meta-analyses. </p></div></div><p>Next, you will be presented with the Curation board, consisting of four columns representing the steps of a PRISMA workflow:</p><ul><li><p><strong>Identification</strong>: Remove duplicate studies</p></li><li><p><strong>Screening</strong>: Remove irrelevant studies</p></li><li><p><strong>Elibility</strong>: Remove studies that do not meet inclusion criteria or do not have retrievable information</p></li><li><p><strong>Included</strong>: Double check the studies and view which studies will be included in the meta-analysis</p></li></ul><p>The overall goal is to go from a large number of studies from a broad search results, to only the -studies that are relevant to your research question. These steps should be completed in order!</p><h3 class="anchor anchorWithStickyNavbar_LWe7" id="importing-studies">Importing studies<a href="#importing-studies" class="hash-link" aria-label="Direct link to Importing studies" title="Direct link to Importing studies"></a></h3><p>But first, we must add studies to our Project. Click the <strong>Import Studies</strong> button. </p><p>You can search for studies within the <em>NeuroStore</em> database—which we maintain and indexes over 20,000 pre-processed neuroimaging studies—or from external sources, such as PubMed or a Ciation manager file. </p><p><img loading="lazy" alt="Import Studies" src="/compose-docs/assets/images/import_studies_options-d58951af444810f76b35e77050c7deb4.png" width="622" height="238" class="img_ev3q">. </p><p><em>Import via NeuroStore</em> is simpler and faster, as these studies already exist on in our system +studies that are relevant to your research question. These steps should be completed in order!</p><h3 class="anchor anchorWithStickyNavbar_LWe7" id="importing-studies">Importing studies<a href="#importing-studies" class="hash-link" aria-label="Direct link to Importing studies" title="Direct link to Importing studies"></a></h3><p>But first, we must add studies to our Project. Click the <strong>Import Studies</strong> button. </p><p>You can search for studies within the <em>NeuroStore</em> database—which we maintain and indexes over 20,000 pre-processed neuroimaging studies—or from external sources, such as PubMed or a Citation manager file. </p><p><img loading="lazy" alt="Import Studies" src="/compose-docs/assets/images/import_studies_options-d58951af444810f76b35e77050c7deb4.png" width="622" height="238" class="img_ev3q">. </p><p><em>Import via NeuroStore</em> is simpler and faster, as these studies already exist on in our system and have pre-extracted imaging data (e.g. coordinates). As a result, there will be fewer irrelevant studies to exclude, and less data extraction to complete.</p><p>However, <em>searching other sources</em> is often recommended for a comprehensive literature search, as a single source can never index all possible studies.</p><p>To replicate the Nicotine meta-analysis, we will replicate the author's PubMed search.</p><div class="theme-admonition theme-admonition-info alert alert--info admonition_LlT9"><div class="admonitionHeading_tbUL"><span class="admonitionIcon_kALy"><svg viewBox="0 0 14 16"><path fill-rule="evenodd" d="M7 2.3c3.14 0 5.7 2.56 5.7 5.7s-2.56 5.7-5.7 5.7A5.71 5.71 0 0 1 1.3 8c0-3.14 2.56-5.7 5.7-5.7zM7 1C3.14 1 0 4.14 0 8s3.14 7 7 7 7-3.14 7-7-3.14-7-7-7zm1 3H6v5h2V4zm0 6H6v2h2v-2z"></path></svg></span>info</div><div class="admonitionContent_S0QG"><p>Searching NeuroStore is a valid option for a manual meta-analysis to balance rigor and efficiency. To learn more, see the <a href="/compose-docs/tutorial/automated">Automated Meta-Analysis tutorial</a>. </p></div></div><h4 class="anchor anchorWithStickyNavbar_LWe7" id="searching-pubmed">Searching PubMed<a href="#searching-pubmed" class="hash-link" aria-label="Direct link to Searching PubMed" title="Direct link to Searching PubMed"></a></h4><p>We can export any PubMed search result to file, and import that file into Neurosynth Compose. In this example, we perform the following search which in the <a href="https://pubmed.ncbi.nlm.nih.gov/" target="_blank" rel="noopener noreferrer">PubMed</a> search field:</p><div class="codeBlockContainer_Ckt0 theme-code-block" style="--prism-color:#393A34;--prism-background-color:#f6f8fa"><div class="codeBlockContent_biex"><pre tabindex="0" class="prism-code language-text codeBlock_bY9V thin-scrollbar"><code class="codeBlockLines_e6Vv"><span class="token-line" style="color:#393A34"><span class="token plain">("fMRI" OR "PET" OR "neuroimaging" OR "Functional magnetic resonance imaging" OR "functional MRI") </span><br></span><span class="token-line" style="color:#393A34"><span class="token plain">AND ("nicotine" OR "cigarette" OR "smok*" OR "DMXB-A")</span><br></span></code></pre><div class="buttonGroup__atx"><button type="button" aria-label="Copy code to clipboard" title="Copy" class="clean-btn"><span class="copyButtonIcons_eSgA" aria-hidden="true"><svg class="copyButtonIcon_y97N" viewBox="0 0 24 24"><path d="M19,21H8V7H19M19,5H8A2,2 0 0,0 6,7V21A2,2 0 0,0 8,23H19A2,2 0 0,0 21,21V7A2,2 0 0,0 19,5M16,1H4A2,2 0 0,0 2,3V17H4V3H16V1Z"></path></svg><svg class="copyButtonSuccessIcon_LjdS" viewBox="0 0 24 24"><path d="M21,7L9,19L3.5,13.5L4.91,12.09L9,16.17L19.59,5.59L21,7Z"></path></svg></span></button></div></div></div><p>This results in over 3,000 studies that are potentially relevant for this meta-analysis.</p><p>Next, we save the results to <code>PMID</code> format, with a PubMed ID on each line.</p><p><img loading="lazy" alt="Download PubMed" src="/compose-docs/assets/images/download_search_results-d5ec087db9b8527d9891715d987540a0.png" width="1053" height="475" class="img_ev3q"></p><div class="theme-admonition theme-admonition-info alert alert--info admonition_LlT9"><div class="admonitionHeading_tbUL"><span class="admonitionIcon_kALy"><svg viewBox="0 0 14 16"><path fill-rule="evenodd" d="M7 2.3c3.14 0 5.7 2.56 5.7 5.7s-2.56 5.7-5.7 5.7A5.71 5.71 0 0 1 1.3 8c0-3.14 2.56-5.7 5.7-5.7zM7 1C3.14 1 0 4.14 0 8s3.14 7 7 7 7-3.14 7-7-3.14-7-7-7zm1 3H6v5h2V4zm0 6H6v2h2v-2z"></path></svg></span>info</div><div class="admonitionContent_S0QG"><p>Reviewing 3,000 studies can take a long time! @@ -35,21 +35,21 @@ Any studies that are not relevant will remain in this column and not advance.</p><h3 class="anchor anchorWithStickyNavbar_LWe7" id="eligibility">Eligibility<a href="#eligibility" class="hash-link" aria-label="Direct link to Eligibility" title="Direct link to Eligibility"></a></h3><p>The goal <em>Eligibility</em> is to determine studies meet the eligibility criteria of your meta-analysis. You will need to read the <strong>full text</strong> to make this determination. </p><div class="theme-admonition theme-admonition-note alert alert--secondary admonition_LlT9"><div class="admonitionHeading_tbUL"><span class="admonitionIcon_kALy"><svg viewBox="0 0 14 16"><path fill-rule="evenodd" d="M6.3 5.69a.942.942 0 0 1-.28-.7c0-.28.09-.52.28-.7.19-.18.42-.28.7-.28.28 0 .52.09.7.28.18.19.28.42.28.7 0 .28-.09.52-.28.7a1 1 0 0 1-.7.3c-.28 0-.52-.11-.7-.3zM8 7.99c-.02-.25-.11-.48-.31-.69-.2-.19-.42-.3-.69-.31H6c-.27.02-.48.13-.69.31-.2.2-.3.44-.31.69h1v3c.02.27.11.5.31.69.2.2.42.31.69.31h1c.27 0 .48-.11.69-.31.2-.19.3-.42.31-.69H8V7.98v.01zM7 2.3c-3.14 0-5.7 2.54-5.7 5.68 0 3.14 2.56 5.7 5.7 5.7s5.7-2.55 5.7-5.7c0-3.15-2.56-5.69-5.7-5.69v.01zM7 .98c3.86 0 7 3.14 7 7s-3.14 7-7 7-7-3.12-7-7 3.14-7 7-7z"></path></svg></span>note</div><div class="admonitionContent_S0QG"><p>The eligibility criteria depends on your research question! This is where your expertise is most necessary, in order to create an interesting research question, -and filter studies accordingly. The results of this step depends on the researcher, and there may be reasonable scientific disagrements.</p></div></div><p>To begin, click on the "Eligibility" column header, or a study, as before.</p><p><img loading="lazy" alt="Custom Eligibility" src="/compose-docs/assets/images/custom_exclusion-16ad73f8fbab6041651f04bf3deb4f80.png" width="2341" height="1449" class="img_ev3q"></p><p>For this example, we will include studies that meet these criteria:</p><div class="codeBlockContainer_Ckt0 theme-code-block" style="--prism-color:#393A34;--prism-background-color:#f6f8fa"><div class="codeBlockContent_biex"><pre tabindex="0" class="prism-code language-text codeBlock_bY9V thin-scrollbar"><code class="codeBlockLines_e6Vv"><span class="token-line" style="color:#393A34"><span class="token plain">* fMRI or PET</span><br></span><span class="token-line" style="color:#393A34"><span class="token plain">* Reported brain activity in stereotaxic coordinates (Talairach or MNI space)</span><br></span><span class="token-line" style="color:#393A34"><span class="token plain">* Reported a set of coordinates (i.e., foci) from a within-subjects or between-subjects contrast assessing the effects of nAChR agonist administration (i.e., pharmacological administration or cigarette smoking) relative to a baseline condition (i.e., placebo administration or smoking-abstinence condition)</span><br></span><span class="token-line" style="color:#393A34"><span class="token plain">* Examined brain activity using a cognitive or affective task paradigm or at rest. </span><br></span><span class="token-line" style="color:#393A34"><span class="token plain">* Studies examining functional connectivity, brain morphology, or neurochemistry are excluded.</span><br></span></code></pre><div class="buttonGroup__atx"><button type="button" aria-label="Copy code to clipboard" title="Copy" class="clean-btn"><span class="copyButtonIcons_eSgA" aria-hidden="true"><svg class="copyButtonIcon_y97N" viewBox="0 0 24 24"><path d="M19,21H8V7H19M19,5H8A2,2 0 0,0 6,7V21A2,2 0 0,0 8,23H19A2,2 0 0,0 21,21V7A2,2 0 0,0 19,5M16,1H4A2,2 0 0,0 2,3V17H4V3H16V1Z"></path></svg><svg class="copyButtonSuccessIcon_LjdS" viewBox="0 0 24 24"><path d="M21,7L9,19L3.5,13.5L4.91,12.09L9,16.17L19.59,5.59L21,7Z"></path></svg></span></button></div></div></div><p>For this tutorial, go ahead and review all studies in this column, and Promote relevant studies to the next phase.</p><div class="theme-admonition theme-admonition-tip alert alert--success admonition_LlT9"><div class="admonitionHeading_tbUL"><span class="admonitionIcon_kALy"><svg viewBox="0 0 12 16"><path fill-rule="evenodd" d="M6.5 0C3.48 0 1 2.19 1 5c0 .92.55 2.25 1 3 1.34 2.25 1.78 2.78 2 4v1h5v-1c.22-1.22.66-1.75 2-4 .45-.75 1-2.08 1-3 0-2.81-2.48-5-5.5-5zm3.64 7.48c-.25.44-.47.8-.67 1.11-.86 1.41-1.25 2.06-1.45 3.23-.02.05-.02.11-.02.17H5c0-.06 0-.13-.02-.17-.2-1.17-.59-1.83-1.45-3.23-.2-.31-.42-.67-.67-1.11C2.44 6.78 2 5.65 2 5c0-2.2 2.02-4 4.5-4 1.22 0 2.36.42 3.22 1.19C10.55 2.94 11 3.94 11 5c0 .66-.44 1.78-.86 2.48zM4 14h5c-.23 1.14-1.3 2-2.5 2s-2.27-.86-2.5-2z"></path></svg></span>tip</div><div class="admonitionContent_S0QG"><p>Given that this phase is more open-ended, there is no default Exclusion reason. We provide four default options for you, and +and filter studies accordingly. The results of this step depends on the researcher, and there may be reasonable scientific disagreements.</p></div></div><p>To begin, click on the "Eligibility" column header, or a study, as before.</p><p><img loading="lazy" alt="Custom Eligibility" src="/compose-docs/assets/images/custom_exclusion-16ad73f8fbab6041651f04bf3deb4f80.png" width="2341" height="1449" class="img_ev3q"></p><p>For this example, we will include studies that meet these criteria:</p><div class="codeBlockContainer_Ckt0 theme-code-block" style="--prism-color:#393A34;--prism-background-color:#f6f8fa"><div class="codeBlockContent_biex"><pre tabindex="0" class="prism-code language-text codeBlock_bY9V thin-scrollbar"><code class="codeBlockLines_e6Vv"><span class="token-line" style="color:#393A34"><span class="token plain">* fMRI or PET</span><br></span><span class="token-line" style="color:#393A34"><span class="token plain">* Reported brain activity in stereotaxic coordinates (Talairach or MNI space)</span><br></span><span class="token-line" style="color:#393A34"><span class="token plain">* Reported a set of coordinates (i.e., foci) from a within-subjects or between-subjects contrast assessing the effects of nAChR agonist administration (i.e., pharmacological administration or cigarette smoking) relative to a baseline condition (i.e., placebo administration or smoking-abstinence condition)</span><br></span><span class="token-line" style="color:#393A34"><span class="token plain">* Examined brain activity using a cognitive or affective task paradigm or at rest. </span><br></span><span class="token-line" style="color:#393A34"><span class="token plain">* Studies examining functional connectivity, brain morphology, or neurochemistry are excluded.</span><br></span></code></pre><div class="buttonGroup__atx"><button type="button" aria-label="Copy code to clipboard" title="Copy" class="clean-btn"><span class="copyButtonIcons_eSgA" aria-hidden="true"><svg class="copyButtonIcon_y97N" viewBox="0 0 24 24"><path d="M19,21H8V7H19M19,5H8A2,2 0 0,0 6,7V21A2,2 0 0,0 8,23H19A2,2 0 0,0 21,21V7A2,2 0 0,0 19,5M16,1H4A2,2 0 0,0 2,3V17H4V3H16V1Z"></path></svg><svg class="copyButtonSuccessIcon_LjdS" viewBox="0 0 24 24"><path d="M21,7L9,19L3.5,13.5L4.91,12.09L9,16.17L19.59,5.59L21,7Z"></path></svg></span></button></div></div></div><p>For this tutorial, go ahead and review all studies in this column, and Promote relevant studies to the next phase.</p><div class="theme-admonition theme-admonition-tip alert alert--success admonition_LlT9"><div class="admonitionHeading_tbUL"><span class="admonitionIcon_kALy"><svg viewBox="0 0 12 16"><path fill-rule="evenodd" d="M6.5 0C3.48 0 1 2.19 1 5c0 .92.55 2.25 1 3 1.34 2.25 1.78 2.78 2 4v1h5v-1c.22-1.22.66-1.75 2-4 .45-.75 1-2.08 1-3 0-2.81-2.48-5-5.5-5zm3.64 7.48c-.25.44-.47.8-.67 1.11-.86 1.41-1.25 2.06-1.45 3.23-.02.05-.02.11-.02.17H5c0-.06 0-.13-.02-.17-.2-1.17-.59-1.83-1.45-3.23-.2-.31-.42-.67-.67-1.11C2.44 6.78 2 5.65 2 5c0-2.2 2.02-4 4.5-4 1.22 0 2.36.42 3.22 1.19C10.55 2.94 11 3.94 11 5c0 .66-.44 1.78-.86 2.48zM4 14h5c-.23 1.14-1.3 2-2.5 2s-2.27-.86-2.5-2z"></path></svg></span>tip</div><div class="admonitionContent_S0QG"><p>Given that this phase is more open-ended, there is no default Exclusion reason. We provide four default options for you, and you may define custom Exclusion reasons if you see fit.</p></div></div><div class="theme-admonition theme-admonition-tip alert alert--success admonition_LlT9"><div class="admonitionHeading_tbUL"><span class="admonitionIcon_kALy"><svg viewBox="0 0 12 16"><path fill-rule="evenodd" d="M6.5 0C3.48 0 1 2.19 1 5c0 .92.55 2.25 1 3 1.34 2.25 1.78 2.78 2 4v1h5v-1c.22-1.22.66-1.75 2-4 .45-.75 1-2.08 1-3 0-2.81-2.48-5-5.5-5zm3.64 7.48c-.25.44-.47.8-.67 1.11-.86 1.41-1.25 2.06-1.45 3.23-.02.05-.02.11-.02.17H5c0-.06 0-.13-.02-.17-.2-1.17-.59-1.83-1.45-3.23-.2-.31-.42-.67-.67-1.11C2.44 6.78 2 5.65 2 5c0-2.2 2.02-4 4.5-4 1.22 0 2.36.42 3.22 1.19C10.55 2.94 11 3.94 11 5c0 .66-.44 1.78-.86 2.48zM4 14h5c-.23 1.14-1.3 2-2.5 2s-2.27-.86-2.5-2z"></path></svg></span>tip</div><div class="admonitionContent_S0QG"><p>For open source studies, we will link to the article full text (PDF). If not available, click "view article link" to view article's PubMed page, and access the full text using your credentials.</p></div></div><h3 class="anchor anchorWithStickyNavbar_LWe7" id="included">Included<a href="#included" class="hash-link" aria-label="Direct link to Included" title="Direct link to Included"></a></h3><p>Congratulations! Once you have reviewed all studies, you should have a set of studies that you want to include in your meta-analysis. </p><p>At this point, you can review this final list, and view a PRISMA diagram visually outlining your review process:</p><p><img loading="lazy" alt="PRISMA" src="/compose-docs/assets/images/prisma_diagram-399aba8441e1b00d3ffb3cdc7b5c6d9c.png" width="1714" height="1448" class="img_ev3q"></p><p>To finish <em>Curation</em>, and create a final StudySet, click <em>Move on to Extraction</em> at the top right. </p><h2 class="anchor anchorWithStickyNavbar_LWe7" id="extract-and-annotation">Extract and Annotation<a href="#extract-and-annotation" class="hash-link" aria-label="Direct link to Extract and Annotation" title="Direct link to Extract and Annotation"></a></h2><p>The goal of this phase is to <strong>extract data</strong> from the text of studies (such as coordinates) that will be used in the meta-analysis. You will also want to <strong>annotate</strong> relevant Study meta-data. Most commonly, for each Study you will designate which Analyses (i.e. Contrasts) to included in your meta-analysis.</p><div class="theme-admonition theme-admonition-tip alert alert--success admonition_LlT9"><div class="admonitionHeading_tbUL"><span class="admonitionIcon_kALy"><svg viewBox="0 0 12 16"><path fill-rule="evenodd" d="M6.5 0C3.48 0 1 2.19 1 5c0 .92.55 2.25 1 3 1.34 2.25 1.78 2.78 2 4v1h5v-1c.22-1.22.66-1.75 2-4 .45-.75 1-2.08 1-3 0-2.81-2.48-5-5.5-5zm3.64 7.48c-.25.44-.47.8-.67 1.11-.86 1.41-1.25 2.06-1.45 3.23-.02.05-.02.11-.02.17H5c0-.06 0-.13-.02-.17-.2-1.17-.59-1.83-1.45-3.23-.2-.31-.42-.67-.67-1.11C2.44 6.78 2 5.65 2 5c0-2.2 2.02-4 4.5-4 1.22 0 2.36.42 3.22 1.19C10.55 2.94 11 3.94 11 5c0 .66-.44 1.78-.86 2.48zM4 14h5c-.23 1.14-1.3 2-2.5 2s-2.27-.86-2.5-2z"></path></svg></span>tip</div><div class="admonitionContent_S0QG"><p>Studies that are already indexed by NeuroStore will have automatically extracted data (such as coordinates) saving you a lot of time and effort. However, you may want to verify and improve this information.</p></div></div><h3 class="anchor anchorWithStickyNavbar_LWe7" id="ingestion">Ingestion<a href="#ingestion" class="hash-link" aria-label="Direct link to Ingestion" title="Direct link to Ingestion"></a></h3><p>But first, we must create a StudySet containing your studies! </p><p>New studies not in the NeuroStore database will be created, and studies that match existing studies will be added to a newly created StudySet.</p><div class="theme-admonition theme-admonition-info alert alert--info admonition_LlT9"><div class="admonitionHeading_tbUL"><span class="admonitionIcon_kALy"><svg viewBox="0 0 14 16"><path fill-rule="evenodd" d="M7 2.3c3.14 0 5.7 2.56 5.7 5.7s-2.56 5.7-5.7 5.7A5.71 5.71 0 0 1 1.3 8c0-3.14 2.56-5.7 5.7-5.7zM7 1C3.14 1 0 4.14 0 8s3.14 7 7 7 7-3.14 7-7-3.14-7-7-7zm1 3H6v5h2V4zm0 6H6v2h2v-2z"></path></svg></span>info</div><div class="admonitionContent_S0QG"><p>Studies in NeuroStore have multiple Versions, including those created by other users, as well as the original copy.</p><p>If you ingest a study that is already indexed in the database, we will match to the newest possible Version, by default. Ideally, this will be a Version that another user has already improved, saving you even more time!</p><p>You can switch Study Versions at anytime (including to the original automate copy) by clicking <em>Switch Study Version</em> at the bottom -of Study's page. Any edits you make will automatically be saved as a new Version.</p></div></div><h3 class="anchor anchorWithStickyNavbar_LWe7" id="editing-studies">Editing studies<a href="#editing-studies" class="hash-link" aria-label="Direct link to Editing studies" title="Direct link to Editing studies"></a></h3><p>Once your StudySet is created, it's time to edit studies. You will see a list of your studies:</p><p><img loading="lazy" alt="Extraction" src="/compose-docs/assets/images/extraction_and_annotation-3f2588aa81794ea975ca13e54b3ae968.png" width="1655" height="799" class="img_ev3q"></p><p>Click on any Study to edit:</p><p><img loading="lazy" alt="Extraction study view" src="/compose-docs/assets/images/annotate_and_extract_study-ca3e4d3930ebf9dc60ad23185a36eefc.png" width="2418" height="856" class="img_ev3q"></p><h4 class="anchor anchorWithStickyNavbar_LWe7" id="analysis-data">Analysis Data<a href="#analysis-data" class="hash-link" aria-label="Direct link to Analysis Data" title="Direct link to Analysis Data"></a></h4><p>Let's start by editing a Study's Analyses.</p><p><img loading="lazy" alt="Extraction study view" src="/compose-docs/assets/images/add_coordinates-8bea486d4904648bcafa7ea0aa3ccf05.png" width="2128" height="923" class="img_ev3q"></p><div class="theme-admonition theme-admonition-info alert alert--info admonition_LlT9"><div class="admonitionHeading_tbUL"><span class="admonitionIcon_kALy"><svg viewBox="0 0 14 16"><path fill-rule="evenodd" d="M7 2.3c3.14 0 5.7 2.56 5.7 5.7s-2.56 5.7-5.7 5.7A5.71 5.71 0 0 1 1.3 8c0-3.14 2.56-5.7 5.7-5.7zM7 1C3.14 1 0 4.14 0 8s3.14 7 7 7 7-3.14 7-7-3.14-7-7-7zm1 3H6v5h2V4zm0 6H6v2h2v-2z"></path></svg></span>info</div><div class="admonitionContent_S0QG"><p><em>Analyses</em> are groups of images or coordinates reported in a given study fir a specific analysis. This is often referred to as "Contrasts", but we use the more general term "Analyses" to accomodate a wider range of fMRI models. </p></div></div><p>For new studies, we will not have any data, and it is necessary to manually enter these data from the text of a study. +of Study's page. Any edits you make will automatically be saved as a new Version.</p></div></div><h3 class="anchor anchorWithStickyNavbar_LWe7" id="editing-studies">Editing studies<a href="#editing-studies" class="hash-link" aria-label="Direct link to Editing studies" title="Direct link to Editing studies"></a></h3><p>Once your StudySet is created, it's time to edit studies. You will see a list of your studies:</p><p><img loading="lazy" alt="Extraction" src="/compose-docs/assets/images/extraction_and_annotation-3f2588aa81794ea975ca13e54b3ae968.png" width="1655" height="799" class="img_ev3q"></p><p>Click on any Study to edit:</p><p><img loading="lazy" alt="Extraction study view" src="/compose-docs/assets/images/annotate_and_extract_study-ca3e4d3930ebf9dc60ad23185a36eefc.png" width="2418" height="856" class="img_ev3q"></p><h4 class="anchor anchorWithStickyNavbar_LWe7" id="analysis-data">Analysis Data<a href="#analysis-data" class="hash-link" aria-label="Direct link to Analysis Data" title="Direct link to Analysis Data"></a></h4><p>Let's start by editing a Study's Analyses.</p><p><img loading="lazy" alt="Extraction study view" src="/compose-docs/assets/images/add_coordinates-8bea486d4904648bcafa7ea0aa3ccf05.png" width="2128" height="923" class="img_ev3q"></p><div class="theme-admonition theme-admonition-info alert alert--info admonition_LlT9"><div class="admonitionHeading_tbUL"><span class="admonitionIcon_kALy"><svg viewBox="0 0 14 16"><path fill-rule="evenodd" d="M7 2.3c3.14 0 5.7 2.56 5.7 5.7s-2.56 5.7-5.7 5.7A5.71 5.71 0 0 1 1.3 8c0-3.14 2.56-5.7 5.7-5.7zM7 1C3.14 1 0 4.14 0 8s3.14 7 7 7 7-3.14 7-7-3.14-7-7-7zm1 3H6v5h2V4zm0 6H6v2h2v-2z"></path></svg></span>info</div><div class="admonitionContent_S0QG"><p><em>Analyses</em> are groups of images or coordinates reported in a given study fir a specific analysis. This is often referred to as "Contrasts", but we use the more general term "Analyses" to accommodate a wider range of fMRI models. </p></div></div><p>For new studies, we will not have any data, and it is necessary to manually enter these data from the text of a study. We can create a new Analysis for each group of Coordinates, and input the data from the text:</p><p>For studies already indexed by NeuroStore, we will already have pre-extracted Coordinates. You can use this same interface to verify and correct these data. </p><div class="theme-admonition theme-admonition-caution alert alert--warning admonition_LlT9"><div class="admonitionHeading_tbUL"><span class="admonitionIcon_kALy"><svg viewBox="0 0 16 16"><path fill-rule="evenodd" d="M8.893 1.5c-.183-.31-.52-.5-.887-.5s-.703.19-.886.5L.138 13.499a.98.98 0 0 0 0 1.001c.193.31.53.501.886.501h13.964c.367 0 .704-.19.877-.5a1.03 1.03 0 0 0 .01-1.002L8.893 1.5zm.133 11.497H6.987v-2.003h2.039v2.003zm0-3.004H6.987V5.987h2.039v4.006z"></path></svg></span>caution</div><div class="admonitionContent_S0QG"><p>Automatically extracted coordinates can contain a number of errors. Mostly commonly, several distinct Analyses (i.e. contrasts), will get grouped into a single Analyses. You will want to create new Analyses to split up the Coordinates into distinct units. </p><p>Another common error is that Analyses are duplicated, meaning you may want to delete extra Analyses. </p></div></div><div class="theme-admonition theme-admonition-tip alert alert--success admonition_LlT9"><div class="admonitionHeading_tbUL"><span class="admonitionIcon_kALy"><svg viewBox="0 0 12 16"><path fill-rule="evenodd" d="M6.5 0C3.48 0 1 2.19 1 5c0 .92.55 2.25 1 3 1.34 2.25 1.78 2.78 2 4v1h5v-1c.22-1.22.66-1.75 2-4 .45-.75 1-2.08 1-3 0-2.81-2.48-5-5.5-5zm3.64 7.48c-.25.44-.47.8-.67 1.11-.86 1.41-1.25 2.06-1.45 3.23-.02.05-.02.11-.02.17H5c0-.06 0-.13-.02-.17-.2-1.17-.59-1.83-1.45-3.23-.2-.31-.42-.67-.67-1.11C2.44 6.78 2 5.65 2 5c0-2.2 2.02-4 4.5-4 1.22 0 2.36.42 3.22 1.19C10.55 2.94 11 3.94 11 5c0 .66-.44 1.78-.86 2.48zM4 14h5c-.23 1.14-1.3 2-2.5 2s-2.27-.86-2.5-2z"></path></svg></span>tip</div><div class="admonitionContent_S0QG"><p>You can copy and paste coordinates from Microsoft Excel or Google Sheets.</p></div></div><h4 class="anchor anchorWithStickyNavbar_LWe7" id="annotations">Annotations<a href="#annotations" class="hash-link" aria-label="Direct link to Annotations" title="Direct link to Annotations"></a></h4><p>A key goal of the Extraction phase, is to add Annotations that can help us distinguish Analyses, and include/exclude specific Analyses from a meta-analysis. Annotations are simply columns of data with a value for all Analyses within a StudySet.</p><p>Annotations can be explained as a way to categorize analyses within each study. For example, they can be categorized by task (e.g., Stroop, N-back, etc.), by modality (e.g., fMRI, PET, etc.), or by any other category that you want to use to filter the analyses. </p><div class="theme-admonition theme-admonition-tip alert alert--success admonition_LlT9"><div class="admonitionHeading_tbUL"><span class="admonitionIcon_kALy"><svg viewBox="0 0 12 16"><path fill-rule="evenodd" d="M6.5 0C3.48 0 1 2.19 1 5c0 .92.55 2.25 1 3 1.34 2.25 1.78 2.78 2 4v1h5v-1c.22-1.22.66-1.75 2-4 .45-.75 1-2.08 1-3 0-2.81-2.48-5-5.5-5zm3.64 7.48c-.25.44-.47.8-.67 1.11-.86 1.41-1.25 2.06-1.45 3.23-.02.05-.02.11-.02.17H5c0-.06 0-.13-.02-.17-.2-1.17-.59-1.83-1.45-3.23-.2-.31-.42-.67-.67-1.11C2.44 6.78 2 5.65 2 5c0-2.2 2.02-4 4.5-4 1.22 0 2.36.42 3.22 1.19C10.55 2.94 11 3.94 11 5c0 .66-.44 1.78-.86 2.48zM4 14h5c-.23 1.14-1.3 2-2.5 2s-2.27-.86-2.5-2z"></path></svg></span>tip</div><div class="admonitionContent_S0QG"><p>By default, a single Annotation called "included" is created, which includes all Analyses. -You can modify this Annotation to select the relevant Analyses of interest to your research question</p></div></div><p>For this replication, we are interested in the effects of nAChR agonists on the brain, which can either be excitatory or inhibitory, so we add both an “activation” and “deactivation” column. </p><p>First create an Annotation. From the main Extraction page, click "View Annoations" on the top right. Here you can view all annotations and the value for each Analyses, as well as create new Annotations. You can choose the data type of each column as either a Number, String, or Boolean. Selected a Boolean data type for the “activation” and “deactivation” columns, which will allow you to filter the analyses by whether they are excitatory or inhibitory. By default you will have an “include” column to help get you started.</p><p>Below, I am creating a new Annotation for "deactivations"</p><p><img loading="lazy" alt="annotation for a study" src="/compose-docs/assets/images/annotation_create-1b42a849c3fa25379a4492e899c883bd.png" width="1795" height="758" class="img_ev3q"></p><p>Now, when I look at a study, I can edit the value for Analyses, assigning each group of coordinates as "activations" or "deactivations":</p><p><img loading="lazy" alt="annotation for a study" src="/compose-docs/assets/images/annotation_view-bb152fb9777b96fa48ecf95ada750d97.png" width="850" height="128" class="img_ev3q"></p><h2 class="anchor anchorWithStickyNavbar_LWe7" id="meta-analysis-specification">Meta-analysis specification<a href="#meta-analysis-specification" class="hash-link" aria-label="Direct link to Meta-analysis specification" title="Direct link to Meta-analysis specification"></a></h2><p>You are finally ready to specify a meta-analysis! </p><p><img loading="lazy" alt="start meta-analysis specification" src="/compose-docs/assets/images/proceed_meta_analysis-ccd673905b3f5425823cc947b282bd48.png" width="834" height="308" class="img_ev3q"></p><p>After clicking <strong>"+ Meta-Analysis Specification"</strong>, you'll see the following dialog:</p><p><img loading="lazy" alt="Meta-analysis wizard" src="/compose-docs/assets/images/ma_wizard-94f17423e2d4a4df7e23f88cb26c4595.png" width="1762" height="1014" class="img_ev3q"></p><p>For each Meta-Analysis, you will select an Annotation to filter the Analyses to include. -Remember, by default, the "included" column will be created and include <em>all</em> Analyses. </p><p>Next, you will <strong>select a meta-analysis Algorithm and Corrector</strong>:</p><p><img loading="lazy" alt="Meta-analysis algorithm" src="/compose-docs/assets/images/ma_algorithm-76b551077f36af384173d025dd8d39cb.png" width="1762" height="1014" class="img_ev3q"></p><p>A variety of common meta-analysis algirithms such as "ALE" and "MKDA" are available, as well as two -strategies for controling for multiple comparisons: FDR (false detection rate) and FWE (family wise error).</p><p>For this example, we'll choose "MKDADensity" and and "FDRCorrection". You can modify the parameters for each, if you want, +You can modify this Annotation to select the relevant Analyses of interest to your research question</p></div></div><p>For this replication, we are interested in the effects of nAChR agonists on the brain, which can either be excitatory or inhibitory, so we add both an “activation” and “deactivation” column. </p><p>First create an Annotation. From the main Extraction page, click "View Annotations" on the top right. Here you can view all annotations and the value for each Analyses, as well as create new Annotations. You can choose the data type of each column as either a Number, String, or Boolean. Selected a Boolean data type for the “activation” and “deactivation” columns, which will allow you to filter the analyses by whether they are excitatory or inhibitory. By default you will have an “include” column to help get you started.</p><p>Below, I am creating a new Annotation for "deactivations"</p><p><img loading="lazy" alt="annotation for a study" src="/compose-docs/assets/images/annotation_create-1b42a849c3fa25379a4492e899c883bd.png" width="1795" height="758" class="img_ev3q"></p><p>Now, when I look at a study, I can edit the value for Analyses, assigning each group of coordinates as "activations" or "deactivations":</p><p><img loading="lazy" alt="annotation for a study" src="/compose-docs/assets/images/annotation_view-bb152fb9777b96fa48ecf95ada750d97.png" width="850" height="128" class="img_ev3q"></p><h2 class="anchor anchorWithStickyNavbar_LWe7" id="meta-analysis-specification">Meta-analysis specification<a href="#meta-analysis-specification" class="hash-link" aria-label="Direct link to Meta-analysis specification" title="Direct link to Meta-analysis specification"></a></h2><p>You are finally ready to specify a meta-analysis! </p><p><img loading="lazy" alt="start meta-analysis specification" src="/compose-docs/assets/images/proceed_meta_analysis-ccd673905b3f5425823cc947b282bd48.png" width="834" height="308" class="img_ev3q"></p><p>After clicking <strong>"+ Meta-Analysis Specification"</strong>, you'll see the following dialog:</p><p><img loading="lazy" alt="Meta-analysis wizard" src="/compose-docs/assets/images/ma_wizard-94f17423e2d4a4df7e23f88cb26c4595.png" width="1762" height="1014" class="img_ev3q"></p><p>For each Meta-Analysis, you will select an Annotation to filter the Analyses to include. +Remember, by default, the "included" column will be created and include <em>all</em> Analyses. </p><p>Next, you will <strong>select a meta-analysis Algorithm and Corrector</strong>:</p><p><img loading="lazy" alt="Meta-analysis algorithm" src="/compose-docs/assets/images/ma_algorithm-76b551077f36af384173d025dd8d39cb.png" width="1762" height="1014" class="img_ev3q"></p><p>A variety of common meta-analysis algorithms such as "ALE" and "MKDA" are available, as well as two +strategies for controlling for multiple comparisons: FDR (false detection rate) and FWE (family wise error).</p><p>For this example, we'll choose "MKDADensity" and and "FDRCorrection". You can modify the parameters for each, if you want, but we provide sane defaults for all. </p><div class="theme-admonition theme-admonition-tip alert alert--success admonition_LlT9"><div class="admonitionHeading_tbUL"><span class="admonitionIcon_kALy"><svg viewBox="0 0 12 16"><path fill-rule="evenodd" d="M6.5 0C3.48 0 1 2.19 1 5c0 .92.55 2.25 1 3 1.34 2.25 1.78 2.78 2 4v1h5v-1c.22-1.22.66-1.75 2-4 .45-.75 1-2.08 1-3 0-2.81-2.48-5-5.5-5zm3.64 7.48c-.25.44-.47.8-.67 1.11-.86 1.41-1.25 2.06-1.45 3.23-.02.05-.02.11-.02.17H5c0-.06 0-.13-.02-.17-.2-1.17-.59-1.83-1.45-3.23-.2-.31-.42-.67-.67-1.11C2.44 6.78 2 5.65 2 5c0-2.2 2.02-4 4.5-4 1.22 0 2.36.42 3.22 1.19C10.55 2.94 11 3.94 11 5c0 .66-.44 1.78-.86 2.48zM4 14h5c-.23 1.14-1.3 2-2.5 2s-2.27-.86-2.5-2z"></path></svg></span>tip</div><div class="admonitionContent_S0QG"><p>Learn more about meta-analysis algorithms in the <a href="https://nimare.readthedocs.io/en/stable/index.html" target="_blank" rel="noopener noreferrer">NiMARE Documentation</a></p></div></div><p>Next, you'll give your meta-analysis a name, and review the details of your specification. </p><p><img loading="lazy" alt="Meta-analysis review" src="/compose-docs/assets/images/ma_review-dca9072320631a4c2b7bd8a3939763bf.png" width="1771" height="1575" class="img_ev3q"></p><div class="theme-admonition theme-admonition-tip alert alert--success admonition_LlT9"><div class="admonitionHeading_tbUL"><span class="admonitionIcon_kALy"><svg viewBox="0 0 12 16"><path fill-rule="evenodd" d="M6.5 0C3.48 0 1 2.19 1 5c0 .92.55 2.25 1 3 1.34 2.25 1.78 2.78 2 4v1h5v-1c.22-1.22.66-1.75 2-4 .45-.75 1-2.08 1-3 0-2.81-2.48-5-5.5-5zm3.64 7.48c-.25.44-.47.8-.67 1.11-.86 1.41-1.25 2.06-1.45 3.23-.02.05-.02.11-.02.17H5c0-.06 0-.13-.02-.17-.2-1.17-.59-1.83-1.45-3.23-.2-.31-.42-.67-.67-1.11C2.44 6.78 2 5.65 2 5c0-2.2 2.02-4 4.5-4 1.22 0 2.36.42 3.22 1.19C10.55 2.94 11 3.94 11 5c0 .66-.44 1.78-.86 2.48zM4 14h5c-.23 1.14-1.3 2-2.5 2s-2.27-.86-2.5-2z"></path></svg></span>tip</div><div class="admonitionContent_S0QG"><p>You can define multiple Meta-Analysis specifications in a Project, paired to the same StudySet</p></div></div><h2 class="anchor anchorWithStickyNavbar_LWe7" id="run-your-meta-analysis">Run your meta-analysis!<a href="#run-your-meta-analysis" class="hash-link" aria-label="Direct link to Run your meta-analysis!" title="Direct link to Run your meta-analysis!"></a></h2><p>Congratulations! You now have a Meta-Analysis specification that is ready to run.</p><p>You can execute your Meta-Analysis for free in the cloud on Google Colab by copying the unique <em>meta-analysis id</em> -and pasting it into our Google Colab notebook.</p><p><img loading="lazy" alt="Meta-analysis run" src="/compose-docs/assets/images/ma_run-21ff60898e902524975d8fc965d4a08c.png" width="2994" height="1030" class="img_ev3q"></p></div><footer class="theme-doc-footer docusaurus-mt-lg"><div class="theme-doc-footer-edit-meta-row row"><div class="col"><a href="https://github.com/neurostuff/compose-docs/edit/master/docs/tutorial/manual.md" target="_blank" rel="noreferrer noopener" class="theme-edit-this-page"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_Z9Sw" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col lastUpdated_vwxv"><span class="theme-last-updated">Last updated<!-- --> on <b><time datetime="2023-11-27T23:56:16.000Z">Nov 27, 2023</time></b> by <b>Alejandro de la Vega</b></span></div></div></footer></article><nav class="pagination-nav docusaurus-mt-lg" aria-label="Docs pages navigation"><a class="pagination-nav__link pagination-nav__link--prev" href="/compose-docs/tutorial"><div class="pagination-nav__sublabel">Previous</div><div class="pagination-nav__label">Tutorials</div></a><a class="pagination-nav__link pagination-nav__link--next" href="/compose-docs/tutorial/automated"><div class="pagination-nav__sublabel">Next</div><div class="pagination-nav__label">Automated Meta-Analysis</div></a></nav></div></div><div class="col col--3"><div class="tableOfContents_bqdL thin-scrollbar theme-doc-toc-desktop"><ul class="table-of-contents table-of-contents__left-border"><li><a href="#creating-a-new-project" class="table-of-contents__link toc-highlight">Creating a new Project</a></li><li><a href="#search--curate" class="table-of-contents__link toc-highlight">Search & Curate</a><ul><li><a href="#importing-studies" class="table-of-contents__link toc-highlight">Importing studies</a></li><li><a href="#identification" class="table-of-contents__link toc-highlight">Identification</a></li><li><a href="#screening" class="table-of-contents__link toc-highlight">Screening</a></li><li><a href="#eligibility" class="table-of-contents__link toc-highlight">Eligibility</a></li><li><a href="#included" class="table-of-contents__link toc-highlight">Included</a></li></ul></li><li><a href="#extract-and-annotation" class="table-of-contents__link toc-highlight">Extract and Annotation</a><ul><li><a href="#ingestion" class="table-of-contents__link toc-highlight">Ingestion</a></li><li><a href="#editing-studies" class="table-of-contents__link toc-highlight">Editing studies</a></li></ul></li><li><a href="#meta-analysis-specification" class="table-of-contents__link toc-highlight">Meta-analysis specification</a></li><li><a href="#run-your-meta-analysis" class="table-of-contents__link toc-highlight">Run your meta-analysis!</a></li></ul></div></div></div></div></main></div></div><footer class="footer footer--dark"><div class="container container-fluid"><div class="row footer__links"><div class="col footer__col"><div class="footer__title">Docs</div><ul class="footer__items clean-list"><li class="footer__item"><a class="footer__link-item" href="/compose-docs/">Docs</a></li></ul></div><div class="col footer__col"><div class="footer__title">Community</div><ul class="footer__items clean-list"><li class="footer__item"><a href="https://neurostars.org/tag/neuroscout" target="_blank" rel="noopener noreferrer" class="footer__link-item">NeuroStars<svg width="13.5" height="13.5" aria-hidden="true" viewBox="0 0 24 24" class="iconExternalLink_nPIU"><path fill="currentColor" d="M21 13v10h-21v-19h12v2h-10v15h17v-8h2zm3-12h-10.988l4.035 4-6.977 7.07 2.828 2.828 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0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col lastUpdated_vwxv"><span class="theme-last-updated">Last updated<!-- --> on <b><time datetime="2023-11-28T00:20:32.000Z">Nov 28, 2023</time></b> by <b>Alejandro de la Vega</b></span></div></div></footer></article><nav class="pagination-nav docusaurus-mt-lg" aria-label="Docs pages navigation"><a class="pagination-nav__link pagination-nav__link--prev" href="/compose-docs/tutorial"><div class="pagination-nav__sublabel">Previous</div><div class="pagination-nav__label">Tutorials</div></a><a class="pagination-nav__link pagination-nav__link--next" href="/compose-docs/tutorial/automated"><div class="pagination-nav__sublabel">Next</div><div class="pagination-nav__label">Automated Meta-Analysis</div></a></nav></div></div><div class="col col--3"><div class="tableOfContents_bqdL thin-scrollbar theme-doc-toc-desktop"><ul class="table-of-contents table-of-contents__left-border"><li><a href="#creating-a-new-project" class="table-of-contents__link toc-highlight">Creating a new Project</a></li><li><a href="#search--curate" class="table-of-contents__link toc-highlight">Search & Curate</a><ul><li><a href="#importing-studies" class="table-of-contents__link toc-highlight">Importing studies</a></li><li><a href="#identification" class="table-of-contents__link toc-highlight">Identification</a></li><li><a href="#screening" class="table-of-contents__link toc-highlight">Screening</a></li><li><a href="#eligibility" class="table-of-contents__link toc-highlight">Eligibility</a></li><li><a href="#included" class="table-of-contents__link toc-highlight">Included</a></li></ul></li><li><a href="#extract-and-annotation" class="table-of-contents__link toc-highlight">Extract and Annotation</a><ul><li><a href="#ingestion" class="table-of-contents__link toc-highlight">Ingestion</a></li><li><a href="#editing-studies" class="table-of-contents__link 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