This is module one of the Neural data science course. This modules gives an overview of population methods, i.e. methods for making sense of the simultaneous activity of many neurons. These technqiues are of increasing importance for system neuroscientists, due to the quickly increasing number of neurons simultaneously accessible with modern recording systems, and the importance of studying the collective behaviour of neural populations to understand their function.
- Neural decoding with bayesian methods - 60 minutes
- Neural decoding with Support Vector Machines - 60 minutes
- Dimensionality reduction - 60 minutes
To use material of this module profitably, you will need:
- Familiarity with python and jupyter
- Basic knowledge of calculus and linear algebra
- Basic knowledge of machine learning techniques
Install Pyhton and anaconda on your machine
If you don't have them already installed, install Pyhton and Anaconda on your machine.
Follow these instructions on how to install anaconda
Download the module folder
Clic on Code/Download Zip at the top of the page.
Move the zipped folder in the directory of your choice and decompress it.
Open the terminal and navigate to the module directory.
Create a conda environment
Create a conda virtual environment with the name you prefer, then activate it to work within it.
Run
conda create --name env_name
conda activate env_name
Install the module requirements
Run in the terminal
pip install -r requirements.txt
Open Jupyter
You can now open the lesson's notebooks in your favourite editor, or just type:
jupyter notebook
All set!
You're all set to go throrugh the lessons.
This module was created by:
- Davide Spalla
- Bryan Souza
- Federico Stella
Shield:
This work is licensed under a Creative Commons Attribution 4.0 International License.
If you want to cite this module, please use:
