Maxwell Shinn

TL;DR: A new technique for cortical network mapping based on inter-regional similarity of multiple morphometric parameters measured using multimodal MRI is introduced, finding that the resulting morphometric similarity networks (MSNs) have a complex topological organization comprising modules and high-degree hubs.

TL;DR: It is concluded that human adolescence is associated with biologically plausible changes in structural imaging markers of brain network organization, consistent with the concept of tuning or consolidating anatomical connectivity between frontal cortex and the rest of the connectome.

TL;DR: A generative null model is presented, provided as an open-access software platform, that generates surrogate maps with spatial autocorrelation matched to SA of a target brain map that can simulate surrogate brain maps that preserve the SA of cortical, subcortical, parcellated, and dense brain maps.

TL;DR: A structural covariance network is constructed from MRI measures of cortical thickness on 296 healthy volunteers and a new algorithm is designed for matching sample locations from the Allen Brain Atlas to the nodes of the SCN, exploring the hypothesis that transcriptional networks and structural MRI connectomes are coupled.

TL;DR: This work constructed a structural covariance network (SCN) from MRI measures of cortical thickness on 296 healthy volunteers and designed a new algorithm for matching sample locations from the Allen Brain Atlas to the nodes of the SCN, which defined transcriptomic brain networks (TBN) by estimating gene co-expression between pairs of cortical regions.