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Updated: May 31, 2026

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
Published on: November 1, 2019
STATISTICAL ANALYSIS OF CORTICAL MORPHOMETRICS USING POOLED DISTANCES BASED ON LABELED CORTICAL DISTANCE MAPS
E Ceyhan1, M Hosakere, T Nishino
1Dept. of Mathematics, Koç University, 34450, Sariyer, Istanbul, Turkey.
Labeled Cortical Distance Mapping (LCDM) analysis reveals significant shape differences in the ventral medial prefrontal cortex (VMPFC) in individuals with major depressive disorder (MDD) or at high risk for MDD. These findings suggest potential cortical thinning associated with MDD.
Area of Science:
- Neuroimaging
- Computational Anatomy
- Psychiatry
Background:
- Neuropsychiatric disorders are associated with structural brain changes, particularly in cortical morphology.
- Labeled Cortical Distance Mapping (LCDM) quantifies these shape differences using distances from gray matter voxels to the cortical surface.
- Existing methods using LCDM summary statistics may not capture all available morphometric information.
Purpose of the Study:
- To investigate the robustness of pooled LCDM distance analysis to assumption violations.
- To explore the utility of pooled LCDM distances for detecting group differences in cortical morphometry.
- To identify specific morphometric alterations in the ventral medial prefrontal cortex (VMPFC) in major depressive disorder (MDD) and high-risk (HR) individuals.
Main Methods:
- Pooled LCDM distances from subjects within diagnostic groups (MDD, HR, healthy controls).
- Assessed the robustness of parametric and nonparametric statistical tests to non-normality and within-sample dependence of LCDM data.
- Applied the methodology to analyze gray matter morphometry in the VMPFC of MDD, HR, and healthy subjects.
Main Results:
- Classical parametric tests demonstrated robustness to non-normality and within-sample dependence in pooled LCDM data.
- Nonparametric tests were robust to within-sample dependence.
- Pooled LCDM distance analysis revealed significant morphometric differences in the VMPFC between groups.
- Specifically, decreased distances were observed in the VMPFC for individuals with MDD or at HR, suggesting cortical thinning.
Conclusions:
- Pooled LCDM distance analysis is a powerful and robust method for detecting group differences in cortical morphometry, even with assumption violations.
- The findings indicate significant alterations in VMPFC structure associated with MDD and high risk for the disorder.
- This methodology holds promise for application to other cortical structures and neuropsychiatric conditions.
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