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Inferring Neuronal Network Mechanisms Underlying Anesthesia-Induced Oscillations Using Mathematical Models

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Dynamic Neuroscience

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Abstract

Modern anesthetics have been in use since the mid-nineteenth century, yet their mechanism of action on the level of neuronal systems is largely unknown. Anesthetics induce widespread and stereotypic changes in oscillatory patterns in EEG suggesting they operate on the scale of neuronal circuits to produce the anesthetic state. Details of anesthetic-induced alterations to neuronal circuits have only begun to be investigated and one of the main tools used to elucidate these changes is mathematical models. Here we show how biophysically constrained mathematical models help us infer the cellular and network mechanisms underlying the generation of large scale oscillatory behavior. The physiology of both cortical and subcortical regions and the specific targets of various anesthetics inform the network topology that is capable of generating rhythmic activity in anesthetized states. Models not only predict the networks underlying anesthesia-induced oscillations but also guide experiments to further understand the role of these oscillations in the behavioral states that accompany anesthesia.

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Authors and Affiliations

  1. School of Neuroscience, Virginia Tech, Blacksburg, VA, USA

    Sujith Vijayan

  2. Boston University, Boston, MA, USA

    Michelle McCarthy

Authors
  1. Sujith Vijayan
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  2. Michelle McCarthy
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Correspondence to Sujith Vijayan .

Editor information

Editors and Affiliations

  1. School of Medicine, New York University, New York, NY, USA

    Zhe Chen

  2. Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, USA

    Sridevi V. Sarma

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Vijayan, S., McCarthy, M. (2018). Inferring Neuronal Network Mechanisms Underlying Anesthesia-Induced Oscillations Using Mathematical Models. In: Chen, Z., Sarma, S.V. (eds) Dynamic Neuroscience. Springer, Cham. https://doi.org/10.1007/978-3-319-71976-4_12

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  • DOI: https://doi.org/10.1007/978-3-319-71976-4_12

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-71975-7

  • Online ISBN: 978-3-319-71976-4

  • eBook Packages: EngineeringEngineering (R0)

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