Movieproject2

Overview

This repository contains scripts for converting data to a BIDS-compliant format, preprocessing, analysing, and plotting data from the Naturalistic Neuroimaging Database 3T+ (NNDb-3T+). The accompanying paper, which describes the tasks, MRI protocols, quality control procedures, and more, is available here. The dataset itself is available on the OpenNeuro repository. All scripts used to analyse specific tasks (backtothefuture, somatotopy, retinotopy, tonotopy) are provided in the relevant folders.

Repository Structure

Here is a summary of the main files and folders:

| Script / Folder | Purpose | |-----------------|---------| | conda-py-env.yml | Conda environment specification file. | | 01_convert_to_bids.sh add_intendedfor_field.py cognitron_tobidsfolder.py heuristic_sess01.py heuristic_sess02.py pulselog2sourcedata.py retinotopy_behaviour.py tonotopy_behaviour.py | Convert all raw data into BIDS format. | | 02_run_freesurfer.sh | Run FreeSurfer processing on raw anatomical data. | | 03_run_sswarper.sh | Run SSwarper on raw anatomical data. | | 04_run_suma.sh | Run SUMA to convert FreeSurfer outputs into an AFNI-friendly format. | | 05_plot_fd_alltasks.py | Plot framewise displacement across all tasks (Figure 2 in the paper). | | backtothefuture retinotopy somatotopy tonotopy | Scripts used to analyse each respective task. |

Requirements

To reproduce the outputs or run the scripts, the following dependencies are required:

• Python 3.12.8
• Conda (or another environment manager) to create the conda-py-env.yml environment
• FreeSurfer
• AFNI
• Bash environment for running the .sh scripts
• Standard Python packages (NumPy, SciPy, pandas, matplotlib, etc.) — see conda-py-env.yml for exact versions

Contributing

If you would like to contribute:

• Open an issue for bugs, questions, or feature requests
• Fork the repository and submit a pull request

How to acknowledge

If you use this code or dataset in your work, please cite the associated paper:

[Full citation of NNDb3T+ paper once published]

Additionally, citing the dataset on OpenNeuro is encouraged when reusing the data.

You can also support the project by starring this repository on GitHub ⭐ — it helps others discover the resource and shows appreciation for the work.