4.4 Article

Inhibitory stabilization and visual coding in cortical circuits with multiple interneuron subtypes

Journal

JOURNAL OF NEUROPHYSIOLOGY
Volume 115, Issue 3, Pages 1399-1409

Publisher

AMER PHYSIOLOGICAL SOC
DOI: 10.1152/jn.00732.2015

Keywords

inhibition; V1; modeling

Funding

  1. National Institutes of Health Postdoctoral Fellowship [1F32-DC-014387]
  2. National Science Foundation [DMS-1313225, DMS-1517082, DMS-1517828]
  3. Collaborative Research in Computational Neuroscience (CRCNS) [R01-DC-015139-01ZRG1]
  4. Simons Foundation Collaboration on the Global Brain
  5. Division Of Mathematical Sciences
  6. Direct For Mathematical & Physical Scien [1517828, 1517082] Funding Source: National Science Foundation

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Recent anatomical and functional characterization of cortical inhibitory interneurons has highlighted the diverse computations supported by different subtypes of interneurons. However, most theoretical models of cortex do not feature multiple classes of interneurons and rather assume a single homogeneous population. We study the dynamics of recurrent excitatory-inhibitory model cortical networks with parvalbumin (PV)-, somatostatin (SOM)-, and vasointestinal peptide-expressing (VIP) interneurons, with connectivity properties motivated by experimental recordings from mouse primary visual cortex. Our theory describes conditions under which the activity of such networks is stable and how perturbations of distinct neuronal subtypes recruit changes in activity through recurrent synaptic projections. We apply these conclusions to study the roles of each interneuron subtype in disinhibition, surround suppression, and subtractive or divisive modulation of orientation tuning curves. Our calculations and simulations determine the architectural and stimulus tuning conditions under which cortical activity consistent with experiment is possible. They also lead to novel predictions concerning connectivity and network dynamics that can be tested via optogenetic manipulations. Our work demonstrates that recurrent inhibitory dynamics must be taken into account to fully understand many properties of cortical dynamics observed in experiments.

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