This is module two of the Neural data science course. In this module we will overview techniques used to characterize the response and the selectivity of single neurons to different stimuli. These tools will be applied to paradigmatic examples in systems neuroscience: the selectivity for spatial location in the rodent hippocampus and the receptive fields in primary visual cortex.
- Tuning curves and spatial selectivity - 60 minutes
- Generalized linear models - 60 minutesx
To make the best out of the material of this module, you will need:
- Familiarity with python and jupyter
- Basic knowledge of calculus and linear algebra
If you don't have them already installed, install Pyhton and Anaconda on your machine. Follow these instructions on how to install anaconda
Create a conda virtual environment with the name you prefer, then activate it to work within it. Open a terminal, or open 'Anaconda Prompt' from Anaconda Navigator, in there run:
conda create --name env_name
conda activate env_name
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.
Run in the terminal
pip install -r requirements.txt
You can now open the lesson's notebooks in jupyter lab
jupyter lab
You're all set to go through the lessons.
This module was created by:
- Davide Spalla
- Francesco Battaglia
- Arne Meyer
Shield:
This work is licensed under a Creative Commons Attribution 4.0 International License.
If you want to cite this module, please use:
