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A State-space Model of the Burst Suppression Ratio

Overview
Journal Annu Int Conf IEEE Eng Med Biol Soc
Specialty Biomedical Engineering
Date 2012 Jan 19
PMID 22254587
Citations 15
Authors
Jessica J Chemali
K F Kevin Wong
Ken Solt
Emery N Brown
Affiliations
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Abstract

Burst suppression is an electroencephalogram pattern observed in states of severely reduced brain activity, such as general anesthesia, hypothermia and anoxic brain injuries. The burst suppression ratio (BSR), defined as the fraction of EEG spent in suppression per epoch, is the standard quantitative measure used to characterize burst suppression. We present a state space model to compute a dynamic estimate of the BSR as the instantaneous probability of suppression. We estimate the model using an approximate EM algorithm and illustrate its application in the analysis of rodent burst suppression recordings under general anesthesia. Our approach removes the need to artificially average the ratio over long epochs and allows us to make formal statistical comparisons of burst activity at different time points. Our state-space model suggests a more principled way to analyze this key EEG feature that may offer more informative assessments of its associated brain state.

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References
1.
Smith A, Frank L, Wirth S, Yanike M, Hu D, Kubota Y . Dynamic analysis of learning in behavioral experiments. J Neurosci. 2004; 24(2):447-61. PMC: 6729979. DOI: 10.1523/JNEUROSCI.2908-03.2004. View
2.
Brown E, Lydic R, Schiff N . General anesthesia, sleep, and coma. N Engl J Med. 2010; 363(27):2638-50. PMC: 3162622. DOI: 10.1056/NEJMra0808281. View
3.
Smith A, Brown E . Estimating a state-space model from point process observations. Neural Comput. 2003; 15(5):965-91. DOI: 10.1162/089976603765202622. View
4.
Rampil I . A primer for EEG signal processing in anesthesia. Anesthesiology. 1998; 89(4):980-1002. DOI: 10.1097/00000542-199810000-00023. View
5.
Vijn P, Sneyd J . I.v. anaesthesia and EEG burst suppression in rats: bolus injections and closed-loop infusions. Br J Anaesth. 1998; 81(3):415-21. DOI: 10.1093/bja/81.3.415. View