Please use this identifier to cite or link to this item:
Title: State transitions through inhibitory interneurons in a cortical network model.
Austin Authors: Bryson, Alexander ;Berkovic, Samuel F ;Petrou, Steven;Grayden, David B
Affiliation: The Florey Institute of Neuroscience and Mental Health
Epilepsy Research Centre
Department of Biomedical Engineering, University of Melbourne, Melbourne, Australia
Issue Date: 15-Oct-2021
Date: 2021-10
Publication information: PLoS Computational Biology 2021; 17(10): e1009521
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.
DOI: 10.1371/journal.pcbi.1009521
ORCID: 0000-0002-0033-8197
Journal: PLoS Computational Biology
PubMed URL: 34653178
PubMed URL:
Type: Journal Article
Appears in Collections:Journal articles

Show full item record

Page view(s)

checked on Sep 28, 2023

Google ScholarTM


Items in AHRO are protected by copyright, with all rights reserved, unless otherwise indicated.