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  Partial amplitude synchronization detection in brain signals using Bayesian Gaussian mixture models

Rio, M., Hutt, A., Munk, M., & Girau, B. (2011). Partial amplitude synchronization detection in brain signals using Bayesian Gaussian mixture models. Journal of Physiology, 105(1-3), 98-105. doi:10.1016/j.jphysparis.2011.07.018.

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Rio, M, Author
Hutt, A, Author
Munk, M1, 2, Author              
Girau, B, Author
Affiliations:
1Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497798              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: The present work investigates instantaneous synchronization in multivariate signals. It introduces a new method to detect subsets of synchronized time series that do not consider any baseline information. The method is based on a Bayesian Gaussian mixture model applied at each location of a time–frequency map. The work assesses the relevance of detected subsets by a stability measure. The application to Local Field Potentials measured during a visuo-motor experiment in monkeys reveals a subset of synchronized time series measured in the visual cortex.

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 Dates: 2011-06
 Publication Status: Published in print
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 Rev. Type: -
 Identifiers: DOI: 10.1016/j.jphysparis.2011.07.018
BibTex Citekey: RioHMG2011
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Title: Journal of Physiology
Source Genre: Journal
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Pages: - Volume / Issue: 105 (1-3) Sequence Number: - Start / End Page: 98 - 105 Identifier: -