Emergence of spatially heterogeneous burst suppression in a neural field model of electrocortical activity

Frontiers in Systems Neuroscience
Ingo BojakDavid T J Liley

Abstract

Burst suppression in the electroencephalogram (EEG) is a well-described phenomenon that occurs during deep anesthesia, as well as in a variety of congenital and acquired brain insults. Classically it is thought of as spatially synchronous, quasi-periodic bursts of high amplitude EEG separated by low amplitude activity. However, its characterization as a "global brain state" has been challenged by recent results obtained with intracranial electrocortigraphy. Not only does it appear that burst suppression activity is highly asynchronous across cortex, but also that it may occur in isolated regions of circumscribed spatial extent. Here we outline a realistic neural field model for burst suppression by adding a slow process of synaptic resource depletion and recovery, which is able to reproduce qualitatively the empirically observed features during general anesthesia at the whole cortex level. Simulations reveal heterogeneous bursting over the model cortex and complex spatiotemporal dynamics during simulated anesthetic action, and provide forward predictions of neuroimaging signals for subsequent empirical comparisons and more detailed characterization. Because burst suppression corresponds to a dynamical end-point of brain activit...Continue Reading

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Citations

Mar 29, 2016·NeuroImage·Levin KuhlmannDavid T J Liley
May 6, 2016·Frontiers in Cellular Neuroscience·Thomas LissekMazahir T Hasan
Aug 11, 2015·Frontiers in Systems Neuroscience·Axel Hutt, Anthony G Hudetz
Feb 24, 2017·Nature Neuroscience·Michael Breakspear
Dec 23, 2015·Journal of Clinical Neurophysiology : Official Publication of the American Electroencephalographic Society·Mihai MoldovanMirela V Simon
Sep 12, 2019·Journal of Computational Neuroscience·Jiang-Ling SongM Brandon Westover
Jan 29, 2020·Journal of Computational Neuroscience·Farshad Shirani
Aug 24, 2016·Journal of Mathematical Biology·Sensen Liu, ShiNung Ching

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