Code in this folder copied from https://github.com/HuthLab/deep-fMRI-dataset. See that wonderful repo for up-to-date code!
deep-fMRI-dataset
Code accompanying data release of natural language listening data from 5 fMRI sessions for each of 8 subjects (LeBel et al.) that can be found at openneuro.
- need to grab
em_data
directory from there - need to download data following the below instructions below
- need to set appropriate paths in encoding/feature_space.py
- download data with
python 00_load_dataset.py
- This function will create a
data
dir if it does not exist and will use datalad to download the preprocessed data as well as feature spaces needed for fitting semantic encoding models. It will download ~20gb of data.
- This function will create a
- for fitting glove need to download glove embeddings with
00_glove_prepare.py
model fitting
python 01_fit_encoding.py --subject UTS03 --feature eng1000
- The other optional parameters that encoding.py takes such as sessions, ndelays, single_alpha allow the user to change the amount of data and regularization aspects of the linear regression used.
- This function will then save model performance metrics and model weights as numpy arrays.