This repository hosts the code for the statistical analyses of functional magnetic resonance imaging (fMRI) data in the manuscript [PLACEHOLDER].
More information about the scripts can be found in the docstrings.
├── data/
│ └── BIDS : Copy here the BIDS folder from https://osf.io/h95a2/
├── scripts/
│ ├── 1_GLM.m : Perform GLM on preprocessed data.
│ ├── 2_run_mvpa.py : Runs MVPA analysis and show plot.
│ ├── 3_polynomial_regression.py : Runs plynomial regression on MVPA accuracy.
│ ├── 4_perform_PPI.py : Performs PPI analysis.
│ └── 5_inspect_results.R : Inspect results.
To set up the dataset for this repository, follow the instructions below:
-
Clone the repository:
git clone costantinoai/foveal-feedback-2023 cd foveal-feedback-2023
-
Download the dataset from this link.
-
Extract the
BIDS
dataset:-
For Linux and macOS:
- Open a terminal.
- Navigate to the directory where you downloaded the dataset.
- First, combine the parts into a single ZIP file using the
cat
command:cat BIDS.zip.* > BIDS_combined.zip
- Next, extract the combined ZIP file:
unzip BIDS_combined.zip -d ./data
- This will extract the
BIDS
folder into./data
.
-
For Windows:
- Navigate to the folder where you downloaded the dataset using File Explorer.
- Select all the parts of the dataset (
BIDS.zip.001
,BIDS.zip.002
, etc.). - Right-click and choose
Extract All
. - Choose the
.\data
folder within your cloned repository as the destination for extraction.
Ensure that all parts of the dataset are in the same directory before extraction.
-
-
Ensure that the
BIDS
folder is in the./data/
directory.After extraction, check that the
BIDS
folder is located within./data/
in your cloned repository. If it's not, move it there. -
Run the analysis.
You can now run the scripts in
./scripts
in order. The dataset includes the data before and after the GLM, so the GLM estimation can potentially be skipped.