This repository contains code associated with the paper "Neural alignment predicts learning outcomes in students taking an introduction to computer science course" by Meir Meshulam, Liat Hasenfratz, Hanna Hillman, Yun-Fei Liu, Mai Nguyen, Kenneth A. Norman and Uri Hasson.
Imaging and behavioral data associated with this project is available on openNeuro.org.
The repository is organized as follows:
root
└── notebooks : jupyter notebooks
└── py : python code
└── masks : anatomical ROI and brain masks
After downloading the data folder from openNeuro, set the variable 'bids_path' in the code to point to the data folder.
Use notebooks for pre-processing of raw data (requires FSL; dependencies in py folder), behavioral analysis and ROI analysis. Analysis notebooks contain the expected outputs. Run times for a single analysis on a single region of interest (ROI) are <1h on a single CPU core.
Use similarity_searchlight.py for whole-brain analysis (requires BrainIAK searchlight).
The code was tested under GNU/Linux (x86_64 architecture) with Jupyter Notebook and BrainIAK (version information below). No special installation is required.
Python v. 3.7.4
Jupyter Notebook v. 6.0.2
BrainIAK v. 0.9.1
FSL v. 6.0.1