Abstract
Metrics of brain morphology are increasingly being used to examine inter-individual differences, making it important to evaluate the reliability of these structural measures. Here we used two open-access datasets to assess the intersession reliability of three cortical measures (thickness, gyrification, and fractal dimensionality) and two subcortical measures (volume and fractal dimensionality). Reliability was generally good, particularly with the gyrification and fractal dimensionality measures. One dataset used a sequence previously optimized for brain morphology analyses and had particularly high reliability. Examining the reliability of morphological measures is critical before the measures can be validly used to investigate inter-individual differences.
Highlights
A growing number of studies have investigated relationships between brain morphology and inter-individual differences
While volumetric measures—cortical thickness and subcortical volume—have been evaluated previously, we evaluated the reliability of shape-related measures, gyrification and fractal dimensionality
Estimates clustered closely for all scans from the same individual. This qualitative finding was corroborated by high intraclass correlation coefficient (ICC) values, .816 and .945 for thickness and gyrification, respectively
Summary
A growing number of studies have investigated relationships between brain morphology and inter-individual differences. An important assumption that underlies these studies is that estimates of brain morphology are reliable. While numerous studies have investigated the test–retest reliability for estimates of cortical thickness (e.g., [1,2,3,4,5,6,7]) and subcortical volume (e.g., [7,8,9,10,11,12]), the reliability of other measures of brain morphology has been less. Gyrification has been associated with a myriad of other inter-individual measures, as reviewed by Mietchen and Gaser [14]
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