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Neuron density fundamentally relates to architecture and connectivity of the primate cerebral cortex.

Abstract：

:Studies of structural brain connectivity have revealed many intriguing features of complex cortical networks. To advance integrative theories of cortical organization, an understanding is required of how connectivity interrelates with other aspects of brain structure. Recent studies have suggested that interareal connectivity may be related to a variety of macroscopic as well as microscopic architectonic features of cortical areas. However, it is unclear how these features are inter-dependent and which of them most strongly and fundamentally relate to structural corticocortical connectivity. Here, we systematically investigated the relation of a range of microscopic and macroscopic architectonic features of cortical organization, namely layer III pyramidal cell soma cross section, dendritic synapse count, dendritic synapse density and dendritic tree size as well as area neuron density, to multiple properties of cortical connectivity, using a comprehensive, up-to-date structural connectome of the primate brain. Importantly, relationships were investigated by multi-variate analyses to account for the interrelations of features. Of all considered factors, the classical architectonic parameter of neuron density most strongly and consistently related to essential features of cortical connectivity (existence and laminar patterns of projections, area degree), and in conjoint analyses largely abolished effects of cellular morphological features. These results confirm neuron density as a central architectonic indicator of the primate cerebral cortex that is closely related to essential aspects of brain connectivity and is also highly indicative of further features of the architectonic organization of cortical areas, such as the considered cellular morphological measures. Our findings integrate several aspects of cortical micro- and macroscopic organization, with implications for cortical development and function.

journal_name

Neuroimage

journal_title

NeuroImage

authors

Beul SF,Hilgetag CC

doi

10.1016/j.neuroimage.2019.01.010

subject

Has Abstract

pub_date

2019-04-01 00:00:00

pages

777-792

eissn

1053-8119

issn

1095-9572

pii

S1053-8119(19)30010-2

journal_volume

189

pub_type

杂志文章

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