Spaces:
Running
title: CortexLab Dashboard
emoji: 🧠
colorFrom: purple
colorTo: blue
sdk: docker
app_port: 7860
pinned: false
license: cc-by-nc-4.0
short_description: Multimodal fMRI brain encoding · TRIBE-styled live demo
CortexLab Dashboard
Futuristic interactive analysis dashboard for CortexLab - multimodal fMRI brain encoding toolkit built on Meta's TRIBE v2.
Glassmorphism dark theme with 3D brain visualization, real-time inference, and research-grade analysis tools.
Pages
| Page | Description |
|---|---|
| Brain Alignment Benchmark | Score AI models against brain responses with RSA, CKA, Procrustes + permutation tests, bootstrap CIs, FDR correction, noise ceiling, RDM visualization |
| Cognitive Load Scorer | Predict cognitive demand across 4 dimensions with confidence bands, comparison mode, per-ROI breakdown |
| Temporal Dynamics | Raw timecourses, peak latency hierarchy, lag correlation with null bands, cross-ROI lag matrix, sustained/transient decomposition |
| ROI Connectivity | Partial correlation, dendrogram, modularity, degree/betweenness centrality, edge weight distribution, network graph |
| 3D Brain Viewer | Interactive rotatable fsaverage brain with activation overlays, publication-quality 4-panel views, ROI highlighting, sulcal depth blending |
| Live Inference | Real-time brain prediction from webcam, screen capture, or video file with live-updating 3D brain, cognitive load timeline, and metrics |
Quick Start
pip install -r requirements.txt
streamlit run Home.py
Runs on biologically realistic synthetic data by default (HRF convolution, modality-specific ROI activation, spatial smoothing). No GPU or real fMRI data required.
Live Inference (Local Only)
For real-time brain prediction from webcam, screen, or video:
# Install optional capture dependencies
pip install opencv-python mss Pillow
# For real TRIBE v2 inference (needs GPU):
pip install -e ../cortexlab[analysis]
# Start dashboard
streamlit run Home.py
# Navigate to Live Inference page
Without CortexLab installed, live inference runs in simulation mode - predictions are generated from image statistics (brightness, contrast, color) mapped to brain ROIs.
Features
- Futuristic UI: Glassmorphism dark theme, neon accents, gradient headings, glowing metric cards, animated borders
- 3D Brain Hero: Rotatable fsaverage brain mesh on the home page
- Biologically Realistic Data: HRF-convolved synthetic data with modality-specific activation patterns
- Statistical Rigor: Permutation tests, bootstrap CIs, FDR correction, noise ceiling estimation
- Cross-Page State: ROI selections carry between pages, shared session predictions
- File Upload: Upload .npy predictions from real CortexLab runs
- CSV/JSON Export: Download results from every analysis page
- Methodology Docs: Every page has an expandable methodology section with references
Deployment
HuggingFace Spaces
Live at: huggingface.co/spaces/SID2000/cortexlab-dashboard
Docker-based deployment. Live inference page shows simulation mode (no webcam/GPU access in Spaces).
Local
git clone https://github.com/siddhant-rajhans/cortexlab-dashboard.git
cd cortexlab-dashboard
pip install -r requirements.txt
streamlit run Home.py
Links
License
CC BY-NC 4.0