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Linking dynamics of the inhibitory network to the input structure

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Abstract

Networks of inhibitory interneurons are found in many distinct classes of biological systems. Inhibitory interneurons govern the dynamics of principal cells and are likely to be critically involved in the coding of information. In this theoretical study, we describe the dynamics of a generic inhibitory network in terms of low-dimensional, simplified rate models. We study the relationship between the structure of external input applied to the network and the patterns of activity arising in response to that stimulation. We found that even a minimal inhibitory network can generate a great diversity of spatio-temporal patterning including complex bursting regimes with non-trivial ratios of burst firing. Despite the complexity of these dynamics, the network’s response patterns can be predicted from the rankings of the magnitudes of external inputs to the inhibitory neurons. This type of invariant dynamics is robust to noise and stable in densely connected networks with strong inhibitory coupling. Our study predicts that the response dynamics generated by an inhibitory network may provide critical insights about the temporal structure of the sensory input it receives.

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Acknowledgments

This study was supported by grants from NIDCD (R01 DC012943) and ONR (MURI: N000141310672). We thank Andrey Shilnikov and Mark Stopfer for fruitful discussions.

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Authors and Affiliations

  1. Department of Medicine, University of California San Diego, La Jolla, CA, 92093, USA

    Maxim Komarov & Maxim Bazhenov

  2. Department of Physics and Astronomy, University of Potsdam, Karl-Liebnecht-Str 24, 14476, Potsdam, Germany

    Maxim Komarov

  3. Department of Control Theory, Nizhny Novgorod State University, Gagarin av. 23, 606950, Nizhny Novgorod, Russia

    Maxim Komarov

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  1. Maxim Komarov
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Correspondence to Maxim Bazhenov.

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Action Editor: A. Compte

The work is supported by NIH (R01 DC012943) and ONR (N000141310672) to MB. MK acknowledges Alexander von Humboldt-Foundation, Russian Science foundation (project 14-12-00811) and ONR N00014-16-1-2252 for support.

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Komarov, M., Bazhenov, M. Linking dynamics of the inhibitory network to the input structure. J Comput Neurosci 41, 367–391 (2016). https://doi.org/10.1007/s10827-016-0622-8

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