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Brain connectivity analysis from EEG signals using stable phase-synchronized states during face perception tasks

Brain connectivity analysis from EEG signals using stable phase-synchronized states during face perception tasks
Brain connectivity analysis from EEG signals using stable phase-synchronized states during face perception tasks
Degree of phase synchronization between different Electroencephalogram (EEG) channels is known to be the manifestation of the underlying mechanism of information coupling between different brain regions. In this paper, we apply a continuous wavelet transform (CWT) based analysis technique on EEG data, captured during face perception tasks, to explore the temporal evolution of phase synchronization, from the onset of a stimulus. Our explorations show that there exists a small set (typically 3 – 5) of unique synchronized patterns or synchrostates, each of which are stable of the order of milliseconds. Particularly, in the beta (?) band, which has been reported to be associated with visual processing task, the number of such stable states has been found to be three consistently. During processing of the stimulus, the switching between these states occurs abruptly but the switching characteristic follows a well-behaved and repeatable sequence. This is observed in a single subject analysis as well as a multiple-subject group-analysis in adults during face perception. We also show that although these patterns remain topographically similar for the general category of face perception task, the sequence of their occurrence and their temporal stability varies markedly between different face perception scenarios (stimuli) indicating towards different dynamical characteristics for information processing, which is stimulus-specific in nature. Subsequently, we translated these stable states into brain complex networks and derived some informative network measures for characterizing the degree of segregated processing and information integration in those synchrostates, leading to a new methodology for characterizing information processing in human brain. The proposed methodology of modelling the functional brain connectivity through these synchrostates may be viewed as a new way of quantitative characterization of the cognitive ability of the subject, stimuli and information integration/segregation capability
0378-4371
273-295
Jamal, Wasifa
3f70176e-843e-46b7-8447-4eefaef104f1
Das, Saptarshi
e06f2eb0-1e3e-453c-ba78-82eed18ceac9
Maharatna, Koushik
93bef0a2-e011-4622-8c56-5447da4cd5dd
Pan, Indranil
350268de-fe15-47c8-97b2-68a9ff240b47
Kuyucu, Doga
7798a520-38f0-43ab-8854-a8643bd5558c
Jamal, Wasifa
3f70176e-843e-46b7-8447-4eefaef104f1
Das, Saptarshi
e06f2eb0-1e3e-453c-ba78-82eed18ceac9
Maharatna, Koushik
93bef0a2-e011-4622-8c56-5447da4cd5dd
Pan, Indranil
350268de-fe15-47c8-97b2-68a9ff240b47
Kuyucu, Doga
7798a520-38f0-43ab-8854-a8643bd5558c

Jamal, Wasifa, Das, Saptarshi, Maharatna, Koushik, Pan, Indranil and Kuyucu, Doga (2015) Brain connectivity analysis from EEG signals using stable phase-synchronized states during face perception tasks. Physica A: Statistical Mechanics and its Applications, 434, 273-295. (doi:10.1016/j.physa.2015.03.087).

Record type: Article

Abstract

Degree of phase synchronization between different Electroencephalogram (EEG) channels is known to be the manifestation of the underlying mechanism of information coupling between different brain regions. In this paper, we apply a continuous wavelet transform (CWT) based analysis technique on EEG data, captured during face perception tasks, to explore the temporal evolution of phase synchronization, from the onset of a stimulus. Our explorations show that there exists a small set (typically 3 – 5) of unique synchronized patterns or synchrostates, each of which are stable of the order of milliseconds. Particularly, in the beta (?) band, which has been reported to be associated with visual processing task, the number of such stable states has been found to be three consistently. During processing of the stimulus, the switching between these states occurs abruptly but the switching characteristic follows a well-behaved and repeatable sequence. This is observed in a single subject analysis as well as a multiple-subject group-analysis in adults during face perception. We also show that although these patterns remain topographically similar for the general category of face perception task, the sequence of their occurrence and their temporal stability varies markedly between different face perception scenarios (stimuli) indicating towards different dynamical characteristics for information processing, which is stimulus-specific in nature. Subsequently, we translated these stable states into brain complex networks and derived some informative network measures for characterizing the degree of segregated processing and information integration in those synchrostates, leading to a new methodology for characterizing information processing in human brain. The proposed methodology of modelling the functional brain connectivity through these synchrostates may be viewed as a new way of quantitative characterization of the cognitive ability of the subject, stimuli and information integration/segregation capability

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Accepted/In Press date: 26 February 2015
Published date: 15 September 2015
Organisations: Electronic & Software Systems

Identifiers

Local EPrints ID: 376719
URI: https://eprints.soton.ac.uk/id/eprint/376719
ISSN: 0378-4371
PURE UUID: 86407340-0260-4c4d-a740-e474d0f1fe06

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Date deposited: 07 May 2015 08:37
Last modified: 09 Sep 2019 18:39

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Contributors

Author: Wasifa Jamal
Author: Saptarshi Das
Author: Indranil Pan
Author: Doga Kuyucu

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