Temporal-specific complexity of spiking patterns in spontaneous activity induced by a dual complex network structure

Sou Nobukawa,Haruhiko Nishimura,Teruya Yamanishi

doi:10.1038/s41598-019-49286-8

Sou Nobukawa, Haruhiko Nishimura + Show 1 more

Open Access

https://doi.org/10.1038/s41598-019-49286-8

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Abstract

Temporal fluctuation of neural activity in the brain has an important function in optimal information processing. Spontaneous activity is a source of such fluctuation. The distribution of excitatory postsynaptic potentials (EPSPs) between cortical pyramidal neurons can follow a log-normal distribution. Recent studies have shown that networks connected by weak synapses exhibit characteristics of a random network, whereas networks connected by strong synapses have small-world characteristics of small path lengths and large cluster coefficients. To investigate the relationship between temporal complexity spontaneous activity and structural network duality in synaptic connections, we executed a simulation study using the leaky integrate-and-fire spiking neural network with log-normal synaptic weight distribution for the EPSPs and duality of synaptic connectivity, depending on synaptic weight. We conducted multiscale entropy analysis of the temporal spiking activity. Our simulation demonstrated that, when strong synaptic connections approach a small-world network, specific spiking patterns arise during irregular spatio-temporal spiking activity, and the complexity at the large temporal scale (i.e., slow frequency) is enhanced. Moreover, we confirmed through a surrogate data analysis that slow temporal dynamics reflect a deterministic process in the spiking neural networks. This modelling approach may improve the understanding of the spatio-temporal complex neural activity in the brain.

Highlights

Recent progress in studies using neuroimaging modalities has elucidated the structure of the whole network of the brain, which is composed of individual regions and connections, called a connectome[1,2]
We executed a simulation study using the leaky integrate-and-fire spiking neural network with log-normal synaptic weight distribution in excitatory post-synaptic potentials (EPSPs) and with the duality of complex network consisting of a weak synaptic random network and a strong synaptic small-world network
We found that in cases in which the small-worldness of strong synaptic connections was enhanced, specific spiking patterns arose during temporal irregular spiking activity

Summary

Introduction

Recent progress in studies using neuroimaging modalities has elucidated the structure of the whole network of the brain, which is composed of individual regions and connections, called a connectome[1,2]. Despite the intra-regional cortical networks level without these hierarchical topological structures, the neural network exhibits various types of complex spatio-temporal behaviours[7,8,9,10,11,12,13,14,15] To describe these behaviours, randomly connected network models, which are approximations for complex cortical networks, were initially proposed, and produced highly irregular behaviours through mutual interactions[7,8,9,10]. It can induce burst spiking, which has a vital function during hippocampal memory consolidation[28]

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