A brain-machine interface for control of medically-induced coma.

Medically-induced coma is a drug-induced state of profound brain inactivation and unconsciousness used to treat refractory intracranial hypertension and to manage treatment-resistant epilepsy. The state of coma is achieved by continually monitoring the patient's brain activity with an electroen...

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Autores principales:	Maryam M Shanechi, Jessica J Chemali, Max Liberman, Ken Solt, Emery N Brown
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/c87d2825bff44a7e8c5cee37c4eb3026
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spelling	oai:doaj.org-article:c87d2825bff44a7e8c5cee37c4eb30262021-11-18T05:53:27ZA brain-machine interface for control of medically-induced coma.1553-734X1553-735810.1371/journal.pcbi.1003284https://doaj.org/article/c87d2825bff44a7e8c5cee37c4eb30262013-10-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24204231/pdf/?tool=EBIhttps://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Medically-induced coma is a drug-induced state of profound brain inactivation and unconsciousness used to treat refractory intracranial hypertension and to manage treatment-resistant epilepsy. The state of coma is achieved by continually monitoring the patient's brain activity with an electroencephalogram (EEG) and manually titrating the anesthetic infusion rate to maintain a specified level of burst suppression, an EEG marker of profound brain inactivation in which bursts of electrical activity alternate with periods of quiescence or suppression. The medical coma is often required for several days. A more rational approach would be to implement a brain-machine interface (BMI) that monitors the EEG and adjusts the anesthetic infusion rate in real time to maintain the specified target level of burst suppression. We used a stochastic control framework to develop a BMI to control medically-induced coma in a rodent model. The BMI controlled an EEG-guided closed-loop infusion of the anesthetic propofol to maintain precisely specified dynamic target levels of burst suppression. We used as the control signal the burst suppression probability (BSP), the brain's instantaneous probability of being in the suppressed state. We characterized the EEG response to propofol using a two-dimensional linear compartment model and estimated the model parameters specific to each animal prior to initiating control. We derived a recursive Bayesian binary filter algorithm to compute the BSP from the EEG and controllers using a linear-quadratic-regulator and a model-predictive control strategy. Both controllers used the estimated BSP as feedback. The BMI accurately controlled burst suppression in individual rodents across dynamic target trajectories, and enabled prompt transitions between target levels while avoiding both undershoot and overshoot. The median performance error for the BMI was 3.6%, the median bias was -1.4% and the overall posterior probability of reliable control was 1 (95% Bayesian credibility interval of [0.87, 1.0]). A BMI can maintain reliable and accurate real-time control of medically-induced coma in a rodent model suggesting this strategy could be applied in patient care.Maryam M ShanechiJessica J ChemaliMax LibermanKen SoltEmery N BrownPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 9, Iss 10, p e1003284 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Maryam M Shanechi Jessica J Chemali Max Liberman Ken Solt Emery N Brown A brain-machine interface for control of medically-induced coma.
description	Medically-induced coma is a drug-induced state of profound brain inactivation and unconsciousness used to treat refractory intracranial hypertension and to manage treatment-resistant epilepsy. The state of coma is achieved by continually monitoring the patient's brain activity with an electroencephalogram (EEG) and manually titrating the anesthetic infusion rate to maintain a specified level of burst suppression, an EEG marker of profound brain inactivation in which bursts of electrical activity alternate with periods of quiescence or suppression. The medical coma is often required for several days. A more rational approach would be to implement a brain-machine interface (BMI) that monitors the EEG and adjusts the anesthetic infusion rate in real time to maintain the specified target level of burst suppression. We used a stochastic control framework to develop a BMI to control medically-induced coma in a rodent model. The BMI controlled an EEG-guided closed-loop infusion of the anesthetic propofol to maintain precisely specified dynamic target levels of burst suppression. We used as the control signal the burst suppression probability (BSP), the brain's instantaneous probability of being in the suppressed state. We characterized the EEG response to propofol using a two-dimensional linear compartment model and estimated the model parameters specific to each animal prior to initiating control. We derived a recursive Bayesian binary filter algorithm to compute the BSP from the EEG and controllers using a linear-quadratic-regulator and a model-predictive control strategy. Both controllers used the estimated BSP as feedback. The BMI accurately controlled burst suppression in individual rodents across dynamic target trajectories, and enabled prompt transitions between target levels while avoiding both undershoot and overshoot. The median performance error for the BMI was 3.6%, the median bias was -1.4% and the overall posterior probability of reliable control was 1 (95% Bayesian credibility interval of [0.87, 1.0]). A BMI can maintain reliable and accurate real-time control of medically-induced coma in a rodent model suggesting this strategy could be applied in patient care.
format	article
author	Maryam M Shanechi Jessica J Chemali Max Liberman Ken Solt Emery N Brown
author_facet	Maryam M Shanechi Jessica J Chemali Max Liberman Ken Solt Emery N Brown
author_sort	Maryam M Shanechi
title	A brain-machine interface for control of medically-induced coma.
title_short	A brain-machine interface for control of medically-induced coma.
title_full	A brain-machine interface for control of medically-induced coma.
title_fullStr	A brain-machine interface for control of medically-induced coma.
title_full_unstemmed	A brain-machine interface for control of medically-induced coma.
title_sort	brain-machine interface for control of medically-induced coma.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/c87d2825bff44a7e8c5cee37c4eb3026
work_keys_str_mv	AT maryammshanechi abrainmachineinterfaceforcontrolofmedicallyinducedcoma AT jessicajchemali abrainmachineinterfaceforcontrolofmedicallyinducedcoma AT maxliberman abrainmachineinterfaceforcontrolofmedicallyinducedcoma AT kensolt abrainmachineinterfaceforcontrolofmedicallyinducedcoma AT emerynbrown abrainmachineinterfaceforcontrolofmedicallyinducedcoma AT maryammshanechi brainmachineinterfaceforcontrolofmedicallyinducedcoma AT jessicajchemali brainmachineinterfaceforcontrolofmedicallyinducedcoma AT maxliberman brainmachineinterfaceforcontrolofmedicallyinducedcoma AT kensolt brainmachineinterfaceforcontrolofmedicallyinducedcoma AT emerynbrown brainmachineinterfaceforcontrolofmedicallyinducedcoma
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A brain-machine interface for control of medically-induced coma.

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