README.md

---
license: apache-2.0
language:
- en
tags:
- fMRI
- EEG
- neuroscience
- brain-imaging
- science
- huggingscience
size_categories:
- 100K<n<1M
task_categories:
- text-to-video
- image-to-video
pretty_name: CineBrain
---

# CineBrain: A Large-Scale Multi-Modal Brain Dataset During Naturalistic Audiovisual Narrative Processing
[![ArXiv](https://img.shields.io/badge/ArXiv-2503.06940-b31b1b.svg?logo=arXiv)](https://arxiv.org/abs/2503.06940)

CineBrain is a large-scale multimodal brain dataset comprising fMRI, EEG, and ECG recordings collected while participants watched episodes of *The Big Bang Theory*.  
It supports research on **neural decoding**, **multimodal learning**, and **modality transfer** in naturalistic narrative processing.

---

## 🧠 Dataset Description

### Summary
- **Participants**: 6 subjects  
- **Stimuli**: 30 episodes of *The Big Bang Theory* (first 18 minutes per episode)  
- **Recording time**: 6 hours per subject (36 hours total)  
- **Modalities**:  
  - fMRI: TR = 0.8s  
  - EEG: 64 channels, 1000 Hz  
  - ECG: synchronous recording  

### Supported Tasks
- **Multimodal Brain Analysis** – Linking audiovisual stimuli and neural responses  
- **Neural Decoding** – Inferring cognitive states from fMRI/EEG  
- **Cross-Modal Learning** – Shared representations across fMRI, EEG, ECG  
- **Modality Transfer** – Predicting **fMRI from EEG** and **EEG from fMRI**

---

## 📂 Dataset Structure

**Repository Contents**
- `videos.tar` – Video stimuli (8100 clips from 30 episodes)  
- `sub-00xx/` – Participant folders with raw + preprocessed fMRI/EEG  
- `captions-qwen-2.5-vl-7b.json` – Auto-generated video captions  

**Inside Each Participant Folder**
- `fMRI_raw_data.tar` – raw fMRI  
- `fMRI_preprocessed_data.tar` – preprocessed fMRI  
- `EEG_preprocessed_data.tar` – preprocessed EEG  

**Data Statistics**
| Modality | Sampling | Duration | Size (approx.) |
|----------|----------|----------|----------------|
| fMRI     | TR=0.8s  | 6h/subject | ~12 GB total |
| EEG      | 1000 Hz, 64 ch | 6h/subject | ~72 GB total |
| Video    | 30 eps × 18 min | 8100 clips | ~2.6 GB |

**Data Splits**
- **Subjects 1, 2, 6** → Episodes 1–20 (5400 clips)  
- **Subjects 3, 4, 5** → Episodes 1–10 and 21–30 (5400 clips)  

Total: **36 hours** of brain recordings across all subjects.

## Raw Data Links
Raw EEG data (.mff format)
🔗 https://www.modelscope.cn/datasets/Jianxionggao/CineBrain_EEG_Raw

Raw fMRI data (BIDS format)
🔗 https://www.modelscope.cn/datasets/Jianxionggao/CineBrain_fMRI_Raw

Preprocessed fMRI data (CIFTI format)
🔗 https://www.modelscope.cn/datasets/Jianxionggao/CineBrain_fMRI_CIFTI


---

## 📌 Important Notes
- **Data Release**: Fully open and downloadable  
- **Cross-Dataset Correspondence**: Subjects **1, 2, 3, 4** in CineBrain map to Subjects **6, 8, 1, 4** in [fMRI-Shape](https://huggingface.co/datasets/Fudan-fMRI/fMRI-Shape) and [fMRI-Objaverse](https://huggingface.co/datasets/Fudan-fMRI/fMRI-Objaverse)  

---

## 🏗 Dataset Creation

### Motivation
CineBrain is designed to support **naturalistic neuroscience research**, with focuses on:  
- Narrative comprehension  
- Multisensory integration  
- Individual variability in brain responses  
- Temporal dynamics of engagement  

### Source Data & Preprocessing
- **fMRI**: High temporal resolution (TR=0.8s)  
- **EEG**: High sampling rate (1000 Hz)  
- **Preprocessing**: Standard pipelines, artifact removal, QC  

⚠️ **Ethics**: All data anonymized. Please follow ethical guidelines when using human neuroimaging data.  

---

## ⚖️ Considerations for Use

### Social Impact
- Advance understanding of **narrative processing**  
- Support **brain–computer interface** research  
- Enable **clinical applications** for attention/comprehension disorders  

### Potential Biases
- **Demographic bias**: Limited participant diversity  
- **Cultural bias**: English-language sitcom  
- **Selection bias**: Likely university volunteers  

---

## 📎 Additional Information
- **License**: [Apache-2.0](https://www.apache.org/licenses/LICENSE-2.0)  
- **Languages**: English audiovisual content  

### Citation
If you find our paper useful for your research and applications, please cite using this BibTeX:

```bibtex
@misc{gao2025cinebrain,
  title={CineBrain: A Large-Scale Multi-Modal Brain Dataset During Naturalistic Audiovisual Narrative Processing}, 
  author={Jianxiong Gao and Yichang Liu and Baofeng Yang and Jianfeng Feng and Yanwei Fu},
  year={2025},
  eprint={2503.06940},
  archivePrefix={arXiv},
  primaryClass={cs.CV},
  url={https://arxiv.org/abs/2503.06940}, 
}