Structural Brain Networks in Trigeminal Neuralgia Patients and Controls

A graph dataset of whole-brain structural networks reconstructed from diffusion tensor imaging (DTI) tractography data for 30 trigeminal neuralgia patients and 20 matched controls. The data includes 90x90 connectivity matrices analyzed with Network-Based Statistics and graph theoretical methods to profile global and nodal properties. The dataset was authored by Xiao-Yi Guo and last updated on 2026-05-29.

Use Cases

• Identify pain-side-specific subnetworks based on connectivity matrices.
• Analyze global and nodal graph properties to understand network stability in trigeminal neuralgia.
• Investigate structural connectivity between salience and somatosensory processing regions like the anterior cingulate gyrus and postcentral gyrus.
• Compare alterations in visual and attention-related regions on the non-pain side.

Strengths

• Includes data from 30 patients and 20 matched controls, providing a basis for comparison.
• Networks are derived from DTI tractography, a standard method for studying white matter structure.
• Analysis includes both Network-Based Statistics and graph theoretical methods for a multi-faceted view.

Limitations

• Dataset is very small at 32.5 KB, indicating limited raw data or a summary document.
• Row count and column-level documentation are unknown, requiring manual inspection after download.
• The primary file format is DOCX, which may not be a standard format for graph data interchange.

Provenance

Source

figshare, authored by Xiao-Yi Guo.

Collection Method

Whole-brain structural networks reconstructed from DTI tractography data.

Freshness

Last updated 2026-05-29 06:15:01; freshness should be verified.