Cytoarchitectonic similarity is a wiring principle of the human connectome

Abstract

Understanding the wiring diagram of the human cerebral cortex is a fundamental challenge in neuroscience. Elemental aspects of its organization remain elusive. Here we examine which structural traits of cortical regions, particularly their cytoarchitecture and thickness, relate to the existence and strength of inter-regional connections. We use the architecture data from the classic work of von Economo and Koskinas and state-of-the-art diffusion-based connectivity data from the Human Connectome Project. Our results reveal a prominent role of the cytoarchitectonic similarity of supragranular layers for predicting the existence and strength of connections. In contrast, cortical thickness similarity was not related to the existence or strength of connections. These results are in line with findings for non-human mammalian cerebral cortices, suggesting overarching wiring principles of the mammalian cerebral cortex. The results invite hypotheses about evolutionary conserved neurobiological mechanisms that give rise to the relation of cytoarchitecture and connectivity in the human cerebral cortex.

Structural covariance networks are coupled to expression of genes enriched in supragranular layers of the human cortex

“…Here we have compared the organization of a structural covariance network, derived from cortical thickness measurements in 152 left-hemisphere regions in 296 healthy young participants, to the organization of a transcriptional network, derived from gene expression measurements in the same 152 regions in 6 adult post mortem brains. Since transcriptionally and histologically similar brain regions are more likely to be anatomically connected (Goulas et al 2016), and since structural covariance is a putative marker of anatomical connectivity, we made two, related hypothetical predictions: i) that co-expression of genes should be correlated with the strength of structural covariance between regions; and ii) that the topology of the structural covariance network should be coupled to the topology of the transcriptional brain network. Considering co-expression of the nearly complete genome, we found no more than modest support for these predictions: the two networks had qualitatively similar topology, their edge weights were significantly correlated and there was evidence for greater whole genome co-expression between brain regions that were assigned to the same topological module of the SCN's community structure.…”

Development of Microstructural and Morphological Cortical Profiles in the Neonatal Brain

“…Although alterations in perinatal neurodevelopmental processes have been associated with later cognitive and behavioural difficulties, quantifying myelo-or cytoarchitecture anatomical circuit development in the living human neonate is challenging. A relatively simple hypothesis of cortical connectivity is "similar prefers similar" (Goulas et al, 2016), that is areas with similar cytoarchitecture preferentially connect. In this context, Magnetic Resonance Imaging (MRI)-based methods such as regional structural covariance (Evans, 2013) offer a proxy measure of brain connectivity, with structural similarity of spatially distinct regions of cortex reflecting coordinated maturation .…”

Morphometric Similarity Networks Detect Microscale Cortical Organisation And Predict Inter-Individual Cognitive Variation

“…There is also growing evidence that cytoarchitectonic similarity predicts axonal connectivity between cortical areas, with greater probability of axonal connectivity between histologically similar areas (Goulas et al, 2017;Goulas et al, 2016…”

“…First, there is histological evidence from non-human primates that axo-synaptic connectivity is stronger between micro-structurally similar cortical regions than between cytoarchitectonically distinct areas (Barbas, 2015;Goulas et al, 2017;Goulas et al, 2016). Second, there is encouraging evidence that conventional MRI sequences can serve as proxy markers of cortical microstructure.…”

“…To this point, we have highlighted results that show morphometric similarity is strongly associated with cytoarchitectonic and genomic measures of histological similarity between cortical areas. To the extent that histological (cytoarchitectonic or 26 transcriptional) similarity is coupled to axonal connectivity between cortical areas (Fulcher and Fornito, 2016;Goulas et al, 2017;Goulas et al, 2016), we can therefore expect morphometric similarity measured by MRI to be at least an approximate marker of axonal connectivity. However, to verify this important interpretation more directly, we generalised the MSN approach to analysis of whole brain connectomes in the macaque monkey.…”