ArticlePLoS computational biology2013
A brain-machine interface for control of medically-induced coma.
Article in PLoS computational biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 49 citations in OpenAlex.
- Variability in pharmacologically-induced coma for treatment of refractory status epilepticus.PloS one · 2018Trial
- Ambient Music Decreases EEG Burst-Suppression Ratio During General Anesthesia in Rats.Sensors (Basel, Switzerland) · 2026Article
- Augmented State-Space Modeling and Control of Latent Arousal States Under Inhibitory and Excitatory Conditions.IEEE open journal of engineering in medicine and biology · 2026Article
- Brain-computer interfaces for neuropsychiatric disorders.Nature reviews bioengineering · 2024Article
- Closed-loop control of anesthetic state in nonhuman primates.PNAS nexus · 2023Article
- Profile of Emery N. Brown.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Etiology of Burst Suppression EEG Patterns.Frontiers in psychology · 2021Article
- Constructing a control-ready model of EEG signal during general anesthesia in humans.IFAC-PapersOnLine · 2020Article
- A simulation-based comparative analysis of PID and LQG control for closed-loop anesthesia delivery.IFAC-PapersOnLine · 2020Article
- Optimizing the learning rate for adaptive estimation of neural encoding models.PLoS computational biology · 2018Article
- Closed-Loop Intravenous Drug Administration Using Photoplethysmography.IEEE journal of translational engineering in health and medicine · 2018Article
- Design, implementation, and evaluation of a physiological closed-loop control device for medically-induced coma.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2017Article
- Nitrous oxide-induced slow and delta oscillations.Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2016Observational
- A Review of Control Strategies in Closed-Loop Neuroprosthetic Systems.Frontiers in neuroscience · 2016Review
- A PK-PD model of ketamine-induced high-frequency oscillations.Journal of neural engineering · 2015Article
- Robust control of burst suppression for medical coma.Journal of neural engineering · 2015Article
- Spatial variation in automated burst suppression detection in pharmacologically induced coma.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2015Article
- Propofol and sevoflurane induce distinct burst suppression patterns in rats.Frontiers in systems neuroscience · 2014Article
- Burst suppression probability algorithms: state-space methods for tracking EEG burst suppression.Journal of neural engineering · 2013Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.