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This project was done in the Computational Neuroscience Lab (CNS Lab) at Stanford. The main goal of the project is to predict sex and age from resting state functional MRI (f-MRI) scans using a Spatio-Temporal Graph Convolutional Network. The accepted paper can be found at https://arxiv.org/abs/2003.10613

This is a simplified version of the ST-GCN module: https://github.com/yysijie/st-gcn

The previous version of this module implementation for f-MRI scans can be found at https://github.com/ericksiavichay/cs230-final-project

DATA USAGE

For HCP, the the data "Resting State fMRI 1 Preprocessed" was downloaded from https://db.humanconnectome.org/. The GIFTI images were then parcellated using https://balsa.wustl.edu/QnXj

Here are the final processed BOLD signal files: https://drive.google.com/file/d/1c4UYvp089KwqAllAHdHMHGjq8y5x882D/view.

If you need the NCANDA data, you should directly contact last author Dr. Kilian Pohl (kilian.pohl@stanford.edu) for data usage.

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CNS (Computational Neuroscience) Lab project for age/sex classification of fMRI scans

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