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

Yifan Gu,Yang Qi,Pulin Gong

doi:10.1371/journal.pcbi.1006902

Abstract

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.

Highlights

An essential step toward understanding cortical circuits is to interrelate their connectivity and their spatiotemporal dynamics that underlie brain functions [1, 2]
To integrate essential anatomical and physiological properties of local cortical circuits and to elucidate mechanistic links between them, we develop a novel circuit model capturing key synaptic connectivity features
We show that the model explains the emergence of a range of connectivity patterns such as rich-club connectivity, and gives rise to a rich repertoire of cortical states

Summary

Introduction

An essential step toward understanding cortical circuits is to interrelate their connectivity and their spatiotemporal dynamics that underlie brain functions [1, 2]. Local cortical circuits with these connectivity properties possess significant heterogeneity in synaptic efficacy [5, 6], as well as in the number of connections each neuron sends (out-degree) and receives (in-degree), as strongly suggested by both transfer entropybased effective connectivity measures [7, 8] and anatomically constrained modeling studies [9, 10]. Recent recordings in the cortex of awake mice and monkeys have revealed that cortical neurons differ in their coupling to the overall firing of the population, ranging from strongly correlated “choristers” to weakly correlated “soloists” [12] Despite these variable and diverse neural response properties, it has been found that at the level of neural circuits, there exist structured spatiotemporal patterns, such as propagating waves [13,14,15] and precisely timed spiking triplets [14]. It remains unclear whether and how these seemingly distinct neural dynamics at different neural levels can be reconciled, and how these neural dynamics relate to the underlying network structure

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Discussion

Conclusion