# Diversity of meso-scale architecture in human and non-human connectomes

## TL;DR

This study reveals that brain connectomes contain diverse meso-scale community structures, including assortative, core-periphery, and disassortative types, which are linked to functional connectivity, gene expression, and cognitive performance.

## Contribution

It uncovers the presence of multiple community types in connectomes across species using stochastic blockmodels, expanding beyond the traditional assortative view.

## Key findings

- Many communities are assortative, others form core-periphery and disassortative structures.
- Community diversity peaks in control and subcortical systems in humans.
- Individual differences in community diversity predict cognitive task performance.

## Abstract

The brain's functional diversity is reflected in the meso-scale architecture of its connectome, i.e. its division into clusters and communities of topologically-related brain regions. The dominant view, and one that is reinforced by current analysis techniques, is that communities are strictly assortative and segregated from one another, purportedly for the purpose of carrying out specialized information processing. Such a view, however, precludes the possibility of non-assortative communities that could engender a richer functional repertoire by allowing for a more complex set of inter-community interactions. Here, we use weighted stochastic blockmodels to uncover the meso-scale architecture of \emph{Drosophila}, mouse, rat, macaque, and human connectomes. We confirm that while many communities are assortative, others form core-periphery and disassortative structures, which in the human better recapitulate observed patterns of functional connectivity and in the mouse better recapitulate observed patterns of gene co-expression than other community detection techniques. We define a set of network measures for quantifying the diversity of community types in which brain regions participate. Finally, we show that diversity is peaked in control and subcortical systems in humans, and that individual differences in diversity within those systems predicts cognitive performance on Stroop and Navon tasks. In summary, our report paints a more diverse portrait of connectome meso-scale structure and demonstrates its relevance for cognitive performance.