Structure-phenotype associations for Julich-Brain Cytoarchitectonic Atlas regions

Our aim in this project was to characterize the behavioral profile of brain regions defined in the Julich-Brain Cytoarchitectonic Atlas by mapping interindividual variability in local structure as measured with grey matter volume (GMV) to interindividual variability in psychometric data. From a large cohort of healthy individuals [Nooner et al. 2012](https://doi.org/10.3389/fnins.2012.00152), we selected a subgroup of 466 participants with good quality preprocessed T1-weighted MR-scans, using CAT12 toolbox [http://www.neuro.uni-jena.de/cat/](http://www.neuro.uni-jena.de/cat/), and available scores in a broad range of psychometric measures covering multiple cognitive domains (such as attention, episodic memory), personality and emotion scores. The preprocessed individual GMV maps, their corresponding psychometric scores and the regions of the Julich-Brain Cytoarchitectonic Atlas are then entered into the pyJUSBB tool [https://github.com/shahrzadkh/pyJUSBB/](https://github.com/shahrzadkh/pyJUSBB/), where non-parametric partial correlations between variability in average GMV in each of the brain regions and each of the 48 behavioral scores are assessed and ranked to create the behavioral profile of each region. The stability of each association is demonstrated as 95% Bootstrap confidence interval (10000 times).