Details

Autor(en) / Beteiligte

• Gu, Yifan
• Qi, Yang
• Gong, Pulin
• Beck, Jeff

Titel

Rich-club connectivity, diverse population coupling, and dynamical activity patterns emerging from local cortical circuits

Ist Teil von

• PLoS computational biology, 2019-04, Vol.15 (4), p.e1006902-e1006902

Ort / Verlag

United States: Public Library of Science

Erscheinungsjahr

2019

Link zum Volltext

Quelle

EZB Free E-Journals

Beschreibungen/Notizen

• Experimental studies have begun revealing essential properties of the structural connectivity and the spatiotemporal activity dynamics of cortical circuits. To integrate these properties from anatomy and physiology, and to elucidate the links between them, we develop a novel cortical circuit model that captures a range of realistic features of synaptic connectivity. We show that the model accounts for the emergence of higher-order connectivity structures, including highly connected hub neurons that form an interconnected rich-club. The circuit model exhibits a rich repertoire of dynamical activity states, ranging from asynchronous to localized and global propagating wave states. We find that around the transition between asynchronous and localized propagating wave states, our model quantitatively reproduces a variety of major empirical findings regarding neural spatiotemporal dynamics, which otherwise remain disjointed in existing studies. These dynamics include diverse coupling (correlation) between spiking activity of individual neurons and the population, dynamical wave patterns with variable speeds and precise temporal structures of neural spikes. We further illustrate how these neural dynamics are related to the connectivity properties by analysing structural contributions to variable spiking dynamics and by showing that the rich-club structure is related to the diverse population coupling. These findings establish an integrated account of structural connectivity and activity dynamics of local cortical circuits, and provide new insights into understanding their working mechanisms.