State transitions through inhibitory interneurons in a cortical network model.

Alexander Bryson,Samuel F Berkovic,Steven Petrou,David B Grayden,Lyle J Graham

doi:10.1371/journal.pcbi.1009521

Abstract

Inhibitory interneurons shape the spiking characteristics and computational properties of cortical networks. Interneuron subtypes can precisely regulate cortical function but the roles of interneuron subtypes for promoting different regimes of cortical activity remains unclear. Therefore, we investigated the impact of fast spiking and non-fast spiking interneuron subtypes on cortical activity using a network model with connectivity and synaptic properties constrained by experimental data. We found that network properties were more sensitive to modulation of the fast spiking population, with reductions of fast spiking excitability generating strong spike correlations and network oscillations. Paradoxically, reduced fast spiking excitability produced a reduction of global excitation-inhibition balance and features of an inhibition stabilised network, in which firing rates were driven by the activity of excitatory neurons within the network. Further analysis revealed that the synaptic interactions and biophysical features associated with fast spiking interneurons, in particular their rapid intrinsic response properties and short synaptic latency, enabled this state transition by enhancing gain within the excitatory population. Therefore, fast spiking interneurons may be uniquely positioned to control the strength of recurrent excitatory connectivity and the transition to an inhibition stabilised regime. Overall, our results suggest that interneuron subtypes can exert selective control over excitatory gain allowing for differential modulation of global network state.

Highlights

Despite comprising only 15 to 20% of cortical neurons, inhibitory interneurons are crucial for the normal operation and computational power of the cortex[1,2,3]
Inhibitory interneurons comprise a significant proportion of all cortical neurons and play a crucial role in sustaining normal neural activity in the brain
We explore the role of interneuron subtypes for modulating neural activity using a network model containing two of the most common interneuron subtypes

Summary

Introduction

Despite comprising only 15 to 20% of cortical neurons, inhibitory interneurons are crucial for the normal operation and computational power of the cortex[1,2,3]. Powerful connectivity between inhibitory and excitatory neurons can stabilise networks possessing strong excitatory-to-excitatory interactions required for tasks such as short-term memory formation[14,15]. Networks possessing these properties are known as inhibition-stabilised networks (ISN) and are associated with unique computational properties such as non-linear receptive field response summation [16,17]. Cortical networks with features consistent with ISNs have been demonstrated in-vivo across multiple cortical regions and during both awake and anaesthetised states [16,18]

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Discussion

Conclusion