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Objective selection of EEG late potentials through residual dependence estimation of independent components

Objective selection of EEG late potentials through residual dependence estimation of independent components
Objective selection of EEG late potentials through residual dependence estimation of independent components
This paper presents a novel method to objectively select electroencephalographic (EEG) cortical sources estimated by independent component analysis (ICA) in event-related potential (ERP) studies.
A proximity measure based on mutual information is employed to estimate residual dependences of the components that are then hierarchically clustered based on these residual dependences.
Next, the properties of each group of components are evaluated at each level of the hierarchical tree by two indices that aim to assess both cluster tightness and physiological reliability through a template matching process.
These two indices are combined in three different approaches to bringto light the hierarchical structure of the cluster organizations.
Our method is tested on a set of experiments with the purpose of enhancing late positive ERPs elicited by emotional picture stimuli.
Results suggest that the best way to look for physiologically plausible late positive potential (LPP) sources is to explore in depth the tightness of those clusters that, taken together, best resemble the template.
According to our results, after brain sources clustering, LPPs are always identified more accurately than from ensemble-averaged raw data.
Since the late components of an ERP involve the same associative areas, regardless of the modality of stimulation or specific tasks administered, the proposed method can be simply adapted to other ERP studies, and extended from psychophysiological
independent component analysis, clustering, EEG event-related potentials
0967-3334
779-794
Milanesi, M.
df81551a-ce56-4d94-8850-65416b92bb44
James, C. J.
79a03a14-ca4c-4247-8792-7cd771554797
Martini, N.
dfe71306-8742-4229-8d34-bcfeb1c0e650
Menicucci, D.
1d594e51-0536-457b-a1cd-7a7c1767f1f1
Gemignani, A.
bc8879d9-2063-4b78-a629-80f1a2ea9cb4
Ghelarducci, B.
36ab1580-0afe-455e-b898-e1d04971168a
Landini, L.
19d472c7-d12d-4674-87f9-6e57c563b553
Milanesi, M.
df81551a-ce56-4d94-8850-65416b92bb44
James, C. J.
79a03a14-ca4c-4247-8792-7cd771554797
Martini, N.
dfe71306-8742-4229-8d34-bcfeb1c0e650
Menicucci, D.
1d594e51-0536-457b-a1cd-7a7c1767f1f1
Gemignani, A.
bc8879d9-2063-4b78-a629-80f1a2ea9cb4
Ghelarducci, B.
36ab1580-0afe-455e-b898-e1d04971168a
Landini, L.
19d472c7-d12d-4674-87f9-6e57c563b553

Milanesi, M., James, C. J., Martini, N., Menicucci, D., Gemignani, A., Ghelarducci, B. and Landini, L. (2009) Objective selection of EEG late potentials through residual dependence estimation of independent components. Physiological Measurement, 30 (8), 779-794. (doi:10.1088/0967-3334/30/8/004).

Record type: Article

Abstract

This paper presents a novel method to objectively select electroencephalographic (EEG) cortical sources estimated by independent component analysis (ICA) in event-related potential (ERP) studies.
A proximity measure based on mutual information is employed to estimate residual dependences of the components that are then hierarchically clustered based on these residual dependences.
Next, the properties of each group of components are evaluated at each level of the hierarchical tree by two indices that aim to assess both cluster tightness and physiological reliability through a template matching process.
These two indices are combined in three different approaches to bringto light the hierarchical structure of the cluster organizations.
Our method is tested on a set of experiments with the purpose of enhancing late positive ERPs elicited by emotional picture stimuli.
Results suggest that the best way to look for physiologically plausible late positive potential (LPP) sources is to explore in depth the tightness of those clusters that, taken together, best resemble the template.
According to our results, after brain sources clustering, LPPs are always identified more accurately than from ensemble-averaged raw data.
Since the late components of an ERP involve the same associative areas, regardless of the modality of stimulation or specific tasks administered, the proposed method can be simply adapted to other ERP studies, and extended from psychophysiological

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More information

Published date: August 2009
Keywords: independent component analysis, clustering, EEG event-related potentials

Identifiers

Local EPrints ID: 79181
URI: http://eprints.soton.ac.uk/id/eprint/79181
ISSN: 0967-3334
PURE UUID: 4f4709b1-4705-448f-8757-0bfe8f35ab3c

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Date deposited: 15 Mar 2010
Last modified: 14 Mar 2024 00:28

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Contributors

Author: M. Milanesi
Author: C. J. James
Author: N. Martini
Author: D. Menicucci
Author: A. Gemignani
Author: B. Ghelarducci
Author: L. Landini

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