Data Sheet 1_Gray matter volume alterations in adolescents with ADHD are associated with c

Data Sheet 1 by Meng Chen, uploaded to figshare in May 2026, contains results from a study integrating neuroimaging and transcriptomic data. The 113.2 KB Excel file presents findings from 27 adolescents with ADHD and 34 typically developing controls. It includes results from voxel-based morphometry, gene expression correlations, and machine learning model performance for diagnostic classification.

Use Cases

• Training diagnostic classifiers for ADHD based on gray matter volume patterns.
• Correlating regional brain structural changes with gene expression profiles from the Allen Human Brain Atlas.
• Conducting cell-type enrichment analysis to identify microglial or neuronal signatures associated with brain alterations.
• Replicating partial least squares regression analyses linking neuroimaging and transcriptomic spatial patterns.

Strengths

• Data is derived from a controlled study with 61 participants (27 ADHD, 34 controls).
• Includes performance metrics for three machine learning models, with Random Forest achieving an AUC of 0.871.
• Released under a permissive CC-BY-4.0 license for reuse.

Limitations

• Row count and column-level documentation are unknown, which limits suitability assessment.
• The dataset is small at 113.2 KB, indicating limited scope, likely containing summary results rather than raw data.
• Freshness should be verified as the last update is dated 2026-05-29.

Provenance

Source

Meng Chen via figshare.

Collection Method

Voxel-based morphometry on structural MRI data, correlated with gene expression profiles from the Allen Human Brain Atlas using partial least squares regression.

Freshness

Last updated 2026-05-29 07:02:03.