CineBrain: A Large-Scale Multi-Modal Brain Dataset for Naturalistic Audiovisual Narrative Processing
Jianxiong Gao, Yichang Liu, Baofeng Yang, Jianfeng Feng, Yanwei Fuβ
π Overview
CineBrain is a large-scale multimodal brain dataset containing fMRI, EEG, and ECG recordings collected while participants watched episodes of The Big Bang Theory.
It supports research on:
- Video decoding from multimodal neural signals
- Auditory decoding from naturalistic narrative listening
- Cross-modal EEG-to-fMRI translation
- Stimulus-to-brain modeling under real-world audiovisual viewing
π§© Codebase
This codebase is built upon CogVideo (v1.0, not CogVideo 1.5):
π https://github.com/zai-org/CogVideo/releases/tag/v1.0
π Quick Start
1οΈβ£ Install CogVideo Environment
Follow the official CogVideo v1.0 setup guide.
2οΈβ£ Install Additional Dependencies
pip install -r requirements.txt
3οΈβ£ Prepare Models
- Download the CogVideo-5B base model
- Download CineBrain-related weights from HuggingFace
π¦ Dataset
Full dataset, documentation, and metadata are available on HuggingFace:
π CineBrain Dataset
Includes:
- fMRI recordings
- EEG & ECG signals
- Synchronized video, audio, and subtitles
- Time-aligned captions & event annotations
π Citation
If you find this work useful, please cite:
@article{gao2025cinebrain,
title={CineBrain: A Large-Scale Multi-Modal Brain Dataset During Naturalistic Audiovisual Narrative Processing},
author={Gao, Jianxiong and Liu, Yichang and Yang, Baofeng and Feng, Jianfeng and Fu, Yanwei},
journal={arXiv preprint arXiv:2503.06940},
year={2025}
}
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Base model
zai-org/CogVideoX-5b