Determination of neural state classification metrics from the power spectrum of human ECoG

Matthew Kelsey; David Politte; Ryan Verner; John M. Zempel; Tracy Nolan; Abbas Babajani-Feremi; Fred Prior; Linda J. Larson-Prior

doi:10.1109/EMBC.2012.6346926

Determination of neural state classification metrics from the power spectrum of human ECoG

Matthew Kelsey, David Politte, Ryan Verner, John M. Zempel, Tracy Nolan, Abbas Babajani-Feremi, Fred Prior, Linda J. Larson-Prior

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

Brain electrical activity exhibits scale-free dynamics that follow power law scaling. Previous works have shown that broadband spectral power exhibits state-dependent scaling with a log frequency exponent that systematically varies with neural state. However, the frequency ranges which best characterize biological state are not consistent across brain location or subject. An adaptive piecewise linear fitting solution was developed to extract features for classification of brain state. Performance was evaluated by comparison to an a posteriori based feature search method. This analysis, using the 1/ characteristics of the human ECoG signal, demonstrates utility in advancing the ability to perform automated brain state discrimination.

Original language	English
Title of host publication	2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012
Pages	4336-4340
Number of pages	5
DOIs	https://doi.org/10.1109/EMBC.2012.6346926
State	Published - 2012
Event	34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012 - San Diego, CA, United States Duration: Aug 28 2012 → Sep 1 2012

Publication series

Name	Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)	1557-170X

Conference

Conference	34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012
Country/Territory	United States
City	San Diego, CA
Period	08/28/12 → 09/1/12

Access to Document

10.1109/EMBC.2012.6346926

Cite this

Kelsey, M., Politte, D., Verner, R., Zempel, J. M., Nolan, T., Babajani-Feremi, A., Prior, F., & Larson-Prior, L. J. (2012). Determination of neural state classification metrics from the power spectrum of human ECoG. In 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012 (pp. 4336-4340). Article 6346926 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). https://doi.org/10.1109/EMBC.2012.6346926

Kelsey, Matthew ; Politte, David ; Verner, Ryan et al. / Determination of neural state classification metrics from the power spectrum of human ECoG. 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012. 2012. pp. 4336-4340 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

@inproceedings{0727371fb71a4266a79c1b135ca06adc,

title = "Determination of neural state classification metrics from the power spectrum of human ECoG",

abstract = "Brain electrical activity exhibits scale-free dynamics that follow power law scaling. Previous works have shown that broadband spectral power exhibits state-dependent scaling with a log frequency exponent that systematically varies with neural state. However, the frequency ranges which best characterize biological state are not consistent across brain location or subject. An adaptive piecewise linear fitting solution was developed to extract features for classification of brain state. Performance was evaluated by comparison to an a posteriori based feature search method. This analysis, using the 1/ characteristics of the human ECoG signal, demonstrates utility in advancing the ability to perform automated brain state discrimination.",

author = "Matthew Kelsey and David Politte and Ryan Verner and Zempel, {John M.} and Tracy Nolan and Abbas Babajani-Feremi and Fred Prior and Larson-Prior, {Linda J.}",

year = "2012",

doi = "10.1109/EMBC.2012.6346926",

language = "English",

isbn = "9781424441198",

series = "Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS",

pages = "4336--4340",

booktitle = "2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012",

note = "34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012 ; Conference date: 28-08-2012 Through 01-09-2012",

}

Kelsey, M, Politte, D, Verner, R, Zempel, JM, Nolan, T, Babajani-Feremi, A, Prior, F & Larson-Prior, LJ 2012, Determination of neural state classification metrics from the power spectrum of human ECoG. in 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012., 6346926, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, pp. 4336-4340, 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012, San Diego, CA, United States, 08/28/12. https://doi.org/10.1109/EMBC.2012.6346926

Determination of neural state classification metrics from the power spectrum of human ECoG. / Kelsey, Matthew; Politte, David; Verner, Ryan et al.
2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012. 2012. p. 4336-4340 6346926 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Kelsey M, Politte D, Verner R, Zempel JM, Nolan T, Babajani-Feremi A et al. Determination of neural state classification metrics from the power spectrum of human ECoG. In 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012. 2012. p. 4336-4340. 6346926. (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). doi: 10.1109/EMBC.2012.6346926

Determination of neural state classification metrics from the power spectrum of human ECoG

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