Multimodal MRI and DTI Networks in Obsessive-Compulsive Disorder

Encompassing multimodal structural neuroimaging data from 30 unmedicated patients with obsessive-compulsive disorder (OCD) and 34 healthy controls. It was created by Seung-Goo Kim and published in 2020, applying the mCCA+jICA fusion method to T1-weighted MRI and diffusion tensor imaging (DTI) data. The analysis identified six highly correlated multimodal networks with significant alterations in gray and white matter.

Use Cases

• Apply the mCCA+jICA method to T1-weighted MRI and DTI data to identify correlated multimodal networks.
• Analyze alterations in interrelated gray and white matter networks over occipital and parietal cortices in OCD patients.
• Investigate the correlation between white matter networks around the basal ganglia and the 'harm/checking' subdimension of OC symptoms.
• Compare the covariance structure of anatomical alterations in 30 unmedicated OCD patients versus 34 healthy controls.

Strengths

• Includes data from 64 total subjects (30 patients, 34 controls).
• Applies a multivariate fusion method (mCCA+jICA) to multimodal structural data.
• Identifies six highly correlated multimodal networks with statistical significance (p < 0.0001).
• Findings are validated against a False Discovery Rate threshold (q ≤ 0.05).

Limitations

• Sample size is relatively small (64 total subjects), limiting statistical power for subgroup analyses.
• Data is cross-sectional, providing no longitudinal information on disease progression or treatment effects.
• Specifics on raw data dimensions, file formats, and preprocessing steps are not provided in the description.

Provenance

Source

Dryad digital repository.

Collection Method

Multimodal fusion analysis (mCCA+jICA) applied to T1-weighted MRI and DTI scans.

Freshness

Data was last updated in June 2020.