karnigili / computational-neuroscience

Using computational tools to explore the networks underlying cognitive neuroscience

Computational Neuroscience

This repo showcases some work I have done using computational tools to explore the networks underlying cognitive neuroscience.

Utils

1. A Docker image to run NetPyNE with python3 here
2. A Docker image to run NetPyNE on jupyter notebook here

Tutorials

1. This tutorial discusses rs-fMRI preprocessing using mriQC, fMRIprep, and freesurfer & feature exctraction using nilearn and python. Read more on medium at my post Identifying resting-state networks from fMRI data using ICAs. Or find the python notebook here.

2. This tutorial, following the previous one, explores using LSTMs for classifying preprocessed rs-fMRI data of ADHD patients from healthy controls. Read more on medium at my post Classifying ADHD from healthy controls using LSTMs with rs-fMRI data. Or find the python notebook here.

3. This tutorial presents exploring biological neural netwrok via a simple simulation using NEURUON and NetPyNE. I present a docker image that runs the software in an isolated environment (See here) and an example of how to use it. Read more on medium at my post Simulating Biological Neural Networks with NetPyNE. Find the full code here.

computational-neuroscience's Issues

ICA-lstm

Hello, the ROC curve I drew with your code is very strange. Do you have time to tell me your code principle in detail? How did you draw it？Thank you very much