Region-wise Connectivity-based Psychometric Prediction using the Julich-Brain Cytoarchitectonic Atlas (v1.0)

Many studies have been investigating the relationships between interindividual variability in brain regions’ connectivity and behavioral phenotypes, by utilizing connectivity-based prediction models. Recently, we demonstrated that a combination of whole-brain and region-wise connectivity-based psychometric prediction (CBPP) approach can provide important insight in the predictive model, and hence in brain-behavior relationships, by offering interpretable patterns. Here, we applied this approach using the Julich-Brain Cytoarchitectonic Atlas with the resting-state functional connectivity and psychometric variables from the Human Connectome Project dataset, illustrating each brain region’s predictive power for a range of psychometric variables. As a result, a psychometric prediction profile was established for each brain region, which can be validated against brain mapping literature.