Published April 30, 2025 | Version v1
Journal article Open

Untangling stability and gain modulation in cortical circuits with multiple interneuron classes

  • 1. University of Pittsburgh
  • 2. University of Chicago

Description

Synaptic inhibition is the mechanistic backbone of a suite of cortical functions, not the least of which are maintaining network stability and modulating neuronal gain. In cortical models with a single inhibitory neuron class, network stabilization and gain control work in opposition to one another – meaning high gain coincides with low stability and vice versa. It is now clear that cortical inhibition is diverse, with molecularly distinguished cell classes having distinct positions within the cortical circuit. We analyze circuit models with pyramidal neurons (E) as well as parvalbumin (PV) and somatostatin (SOM) expressing interneurons. We show how, in E – PV – SOM recurrently connected networks, SOM-mediated modulation can lead to simultaneous increases in neuronal gain and network stability. Our work exposes how the impact of a modulation mediated by SOM neurons depends critically on circuit connectivity and the network state.

Data availability

All code can be found on GitHub in the repository at https://github.com/brain-math/stability-gain-with-multiple-INs (copy archived at Doiron lab, 2025).

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Additional details

Identifiers

DOI
10.7554/eLife.99808
Other
oai:uchicago.tind.io:15044

Funding

Human Frontier Science Program
LT0005/2024-L
National Institutes of Health
1U19NS107613
National Institutes of Health
R01DC015139
Office of Naval Research
N00014-18-1-2002
Simons Foundation
542967
National Institutes of Health
R01NS133598

UChicago Information

Division(s)
Biological Sciences Division, Physical Sciences Division
Department(s)
Neurobiology, Statistics
Center(s) or Institute(s)
Grossman Center for Quantitative Biology and Human Behavior