Dynamic control of modeled tonic-clonic seizure states with closed-loop stimulation

Seizure control using deep brain stimulation (DBS) provides an alternative therapy to patients with intractable and drug resistant epilepsy. This paper presents novel DBS stimulus protocols to disrupt seizures. Two protocols are presented: open-loop stimulation and a closed-loop feedback system util...

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Main Authors: Bryce eBeverlin II, Theoden I Netoff
Format: Article
Language:English
Published: Frontiers Media S.A. 2013-02-01
Series:Frontiers in Neural Circuits
Subjects:
Online Access:http://journal.frontiersin.org/Journal/10.3389/fncir.2012.00126/full
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spelling doaj-245eb0b8a8954792b25c3280ebb1dee42020-11-24T23:37:55ZengFrontiers Media S.A.Frontiers in Neural Circuits1662-51102013-02-01610.3389/fncir.2012.0012639012Dynamic control of modeled tonic-clonic seizure states with closed-loop stimulationBryce eBeverlin II0Theoden I Netoff1University of MinnesotaUniversity of MinnesotaSeizure control using deep brain stimulation (DBS) provides an alternative therapy to patients with intractable and drug resistant epilepsy. This paper presents novel DBS stimulus protocols to disrupt seizures. Two protocols are presented: open-loop stimulation and a closed-loop feedback system utilizing measured firing rates to adjust stimulus frequency. Stimulation suppression is demonstrated in a computational model using 3000 excitatory Morris-Lecar model neurons connected with depressing synapses. Cells are connected using second order network topology to simulate network topologies measured in cortical networks. The network spontaneously switches from tonic to clonic as synaptic strengths and tonic input to the neurons decreases. To this model we add periodic stimulation pulses to simulate DBS. Periodic forcing can synchronize or desynchronize an oscillating population of neurons, depending on the stimulus frequency and amplitude. Therefore, it is possible to either extend or truncate the tonic or clonic phases of the seizure. Stimuli applied at the firing rate of the neuron generally synchronize the population while stimuli slightly slower than the firing rate prevent synchronization. We present an adaptive stimulation algorithm that measures the firing rate of a neuron and adjusts the stimulus to maintain a relative stimulus frequency to firing frequency and demonstrate it in a computational model of a tonic-clonic seizure. This adaptive algorithm can affect the duration of the tonic phase using much smaller stimulus amplitudes than the open-loop control.http://journal.frontiersin.org/Journal/10.3389/fncir.2012.00126/fullDeep Brain StimulationsynchronySeizure modeltonic clonicperiodic stimulation
collection DOAJ
language English
format Article
sources DOAJ
author Bryce eBeverlin II
Theoden I Netoff
spellingShingle Bryce eBeverlin II
Theoden I Netoff
Dynamic control of modeled tonic-clonic seizure states with closed-loop stimulation
Frontiers in Neural Circuits
Deep Brain Stimulation
synchrony
Seizure model
tonic clonic
periodic stimulation
author_facet Bryce eBeverlin II
Theoden I Netoff
author_sort Bryce eBeverlin II
title Dynamic control of modeled tonic-clonic seizure states with closed-loop stimulation
title_short Dynamic control of modeled tonic-clonic seizure states with closed-loop stimulation
title_full Dynamic control of modeled tonic-clonic seizure states with closed-loop stimulation
title_fullStr Dynamic control of modeled tonic-clonic seizure states with closed-loop stimulation
title_full_unstemmed Dynamic control of modeled tonic-clonic seizure states with closed-loop stimulation
title_sort dynamic control of modeled tonic-clonic seizure states with closed-loop stimulation
publisher Frontiers Media S.A.
series Frontiers in Neural Circuits
issn 1662-5110
publishDate 2013-02-01
description Seizure control using deep brain stimulation (DBS) provides an alternative therapy to patients with intractable and drug resistant epilepsy. This paper presents novel DBS stimulus protocols to disrupt seizures. Two protocols are presented: open-loop stimulation and a closed-loop feedback system utilizing measured firing rates to adjust stimulus frequency. Stimulation suppression is demonstrated in a computational model using 3000 excitatory Morris-Lecar model neurons connected with depressing synapses. Cells are connected using second order network topology to simulate network topologies measured in cortical networks. The network spontaneously switches from tonic to clonic as synaptic strengths and tonic input to the neurons decreases. To this model we add periodic stimulation pulses to simulate DBS. Periodic forcing can synchronize or desynchronize an oscillating population of neurons, depending on the stimulus frequency and amplitude. Therefore, it is possible to either extend or truncate the tonic or clonic phases of the seizure. Stimuli applied at the firing rate of the neuron generally synchronize the population while stimuli slightly slower than the firing rate prevent synchronization. We present an adaptive stimulation algorithm that measures the firing rate of a neuron and adjusts the stimulus to maintain a relative stimulus frequency to firing frequency and demonstrate it in a computational model of a tonic-clonic seizure. This adaptive algorithm can affect the duration of the tonic phase using much smaller stimulus amplitudes than the open-loop control.
topic Deep Brain Stimulation
synchrony
Seizure model
tonic clonic
periodic stimulation
url http://journal.frontiersin.org/Journal/10.3389/fncir.2012.00126/full
work_keys_str_mv AT bryceebeverlinii dynamiccontrolofmodeledtonicclonicseizurestateswithclosedloopstimulation
AT theodeninetoff dynamiccontrolofmodeledtonicclonicseizurestateswithclosedloopstimulation
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