BrainGraph: Graph Theory Analysis Tools for Brain MRI Data

BrainGraph is a set of tools for performing graph theory analysis on brain MRI data. It works with outputs from Freesurfer, diffusion tensor tractography, and resting-state fMRI analyses. The package was authored by Christopher G. Watson and includes a graphical user interface for visualization and figure generation.

Use Cases

• Model brain connectivity networks based on diffusion tensor tractography data.
• Analyze cortical morphology using graph metrics derived from Freesurfer outputs like cortical thickness and surface area.
• Investigate functional connectivity patterns using resting-state fMRI data.
• Visualize and explore brain graphs through the included graphical user interface.

Strengths

• Supports analysis of multiple MRI modalities: structural, diffusion, and functional.
• Includes a graphical user interface for visualization and data exploration.
• Provides specific functions for generating publication-ready figures.

Limitations

• Row count and dataset size are unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

Christopher G. Watson

Collection Method

Toolset for analyzing outputs from established neuroimaging pipelines (e.g., Freesurfer, FSL, DPABI).