Functional Connectivity Analyzer

A comprehensive Python-based tool for analyzing functional connectivity in the brain using fMRI time-series data. This project enables spectral analysis, ROI extraction, and connectivity matrix generation to assess how brain areas communicate during rest or task-based activity.

Features

• ROI Signal Extraction: Extract time-series signals from different brain regions
• Spectral Analysis: Compute frequency-domain synchronization metrics
• Connectivity Metrics:
  • Coherence analysis
  • Phase-locking value (PLV)
  • Cross-correlation
  • Mutual information
• Visualization: Interactive connectivity matrices and network graphs
• Statistical Analysis: Significance testing and thresholding
• Data Export: Save results in various formats (CSV, JSON, PNG)

Installation

1. Clone the repository:

git clone <repository-url>
cd functional-connectivity-analyzer

2. Install dependencies:

pip install -r requirements.txt

Quick Start

Run the demo with synthetic data to see the tool in action:

python demo.py

This will:

• Generate synthetic fMRI data
• Compute multiple connectivity metrics
• Create visualizations
• Save results to demo_results/ directory

Running Your Own Analysis

For detailed instructions on how to use the tool with your own fMRI data, please refer to the comprehensive USAGE_GUIDE.txt file.

Examples

# Basic usage example
python examples/basic_usage.py

# Advanced analysis example  
python examples/advanced_analysis.py

Dependencies

nilearn, nibabel, scipy, numpy, matplotlib, plotly, networkx, scikit-learn, pandas, mne

License

MIT License