Closed-loop control of a fragile network: application to seizure-like dynamics of an epilepsy model

Frontiers in Neuroscience
Daniel EhrensSridevi V Sarma

Abstract

It has recently been proposed that the epileptic cortex is fragile in the sense that seizures manifest through small perturbations in the synaptic connections that render the entire cortical network unstable. Closed-loop therapy could therefore entail detecting when the network goes unstable, and then stimulating with an exogenous current to stabilize the network. In this study, a non-linear stochastic model of a neuronal network was used to simulate both seizure and non-seizure activity. In particular, synaptic weights between neurons were chosen such that the network's fixed point is stable during non-seizure periods, and a subset of these connections (the most fragile) were perturbed to make the same fixed point unstable to model seizure events; and, the model randomly transitions between these two modes. The goal of this study was to measure spike train observations from this epileptic network and then apply a feedback controller that (i) detects when the network goes unstable, and then (ii) applies a state-feedback gain control input to the network to stabilize it. The stability detector is based on a 2-state (stable, unstable) hidden Markov model (HMM) of the network, and detects the transition from the stable mode to the...Continue Reading

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Citations

Jul 6, 2016·Frontiers in Neuroscience·Adeline ZbrzeskiSylvie Renaud
Jul 28, 2016·Frontiers in Neuroscience·James WrightJonathan C Tapson
Oct 22, 2016·Frontiers in Neuroinformatics·Angel LareoFrancisco de Borja Rodriguez
Mar 23, 2018·Neural Computation·Roman A SandlerVasilis Z Marmarelis
Jan 5, 2018·Journal of Neural Engineering·M F BolusG B Stanley
Nov 17, 2020·Network Neuroscience·Pragya SrivastavaDanielle S Bassett
Jan 16, 2019·Physics of Life Reviews·Fabrizio De Vico Fallani, Danielle S Bassett
Sep 16, 2020·Journal of Neural Engineering·M F BolusG B Stanley
Sep 7, 2021·Biomedical Physics & Engineering Express·Hossein Sohanian Haghighi, Amir H D Markazi

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