Late positive event-related potentials enhancement through independent component analysis clustering
Late positive event-related potentials enhancement through independent component analysis clustering
This paper presents a method to evaluate residual dependencies between sources estimated by ICA to be used in a hierarchical clustering procedure. As a proximity measure a mutual information-based metric is employed. The properties of each group of components are evaluated at each level of the hierarchical tree by two indices that aim at assessing both cluster tightness and physiological reliability through a template matching process. These two indices are used in three different approaches to find the most suitable combination to explore the hierarchical structure of the clustering. This method is aimed at enhancing late positive event-related brain potentials elicited by emotional picture stimuli. Such critical brain events are produced by presenting a subject with emotionally arousing images with respect to neutral ones. Exploiting the modularity of the spatial distribution of late EEG components, ICA can be employed to separate out their contribution, that is then investigated in an automatic ad objective manner by the clustering procedure.
9780863419348
1-4
Milanesi, M.
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James, C.J.
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Martini, N.
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Gemignani, A.
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Ghelarducci, B.
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Menicucci, D.
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Landini, L.
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July 2008
Milanesi, M.
df81551a-ce56-4d94-8850-65416b92bb44
James, C.J.
b3733b1f-a6a1-4c9b-b75c-6191d4142e52
Martini, N.
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Gemignani, A.
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Ghelarducci, B.
36ab1580-0afe-455e-b898-e1d04971168a
Menicucci, D.
1d594e51-0536-457b-a1cd-7a7c1767f1f1
Landini, L.
19d472c7-d12d-4674-87f9-6e57c563b553
Milanesi, M., James, C.J., Martini, N., Gemignani, A., Ghelarducci, B., Menicucci, D. and Landini, L.
(2008)
Late positive event-related potentials enhancement through independent component analysis clustering.
In 4th IET International Conference on Advances in Medical, Signal and Information Processing, 2008 (MEDSIP 2008).
IEEE.
.
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Conference or Workshop Item
(Paper)
Abstract
This paper presents a method to evaluate residual dependencies between sources estimated by ICA to be used in a hierarchical clustering procedure. As a proximity measure a mutual information-based metric is employed. The properties of each group of components are evaluated at each level of the hierarchical tree by two indices that aim at assessing both cluster tightness and physiological reliability through a template matching process. These two indices are used in three different approaches to find the most suitable combination to explore the hierarchical structure of the clustering. This method is aimed at enhancing late positive event-related brain potentials elicited by emotional picture stimuli. Such critical brain events are produced by presenting a subject with emotionally arousing images with respect to neutral ones. Exploiting the modularity of the spatial distribution of late EEG components, ICA can be employed to separate out their contribution, that is then investigated in an automatic ad objective manner by the clustering procedure.
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Published date: July 2008
Venue - Dates:
4th IET International Conference on Advances in Medical Signal and Information Processing, 2008 (MEDSIP 2008), Sta Margherita, Italy, 2008-07-14 - 2008-07-16
Identifiers
Local EPrints ID: 65183
URI: http://eprints.soton.ac.uk/id/eprint/65183
ISBN: 9780863419348
PURE UUID: be2db1fc-198e-40c1-a6ef-364e543a7737
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Date deposited: 17 Feb 2009
Last modified: 05 Mar 2024 17:39
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Contributors
Author:
M. Milanesi
Author:
C.J. James
Author:
N. Martini
Author:
A. Gemignani
Author:
B. Ghelarducci
Author:
D. Menicucci
Author:
L. Landini
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