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Tree-dependent and topographic independent component analysis for fMRI analysis

Meyer-Bläse, Anke and Theis, Fabian J. and Lange, Oliver and Puntonet, Carlos G. (2004) Tree-dependent and topographic independent component analysis for fMRI analysis. In: Puntonet, Carlos G., (ed.) Independent component analysis and blind signal separation: fifth international conference, ICA 2004, Granada, Spain, September 22 - 24, 2004; proceedings. Lecture Notes in Computer Science, 3195. Springer, Berlin, pp. 782-789. ISBN 3-540-23056-4, 978-3-540-23056-4.

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Abstract

Recently, a new paradigm in ICA emerged, that of finding ldquoclustersrdquo of dependent components. This striking philosophy found its implementation in two new ICA algorithms: tree–dependent and topographic ICA. Applied to fMRI, this leads to the unifying paradigm of combining two powerful exploratory data analysis methods, ICA and unsupervised clustering techniques. For the fMRI data, a ...

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Item Type:Book Section
Date:2004
Institutions:Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang
Identification Number:
ValueType
10.1007/978-3-540-30110-3_99DOI
Related URLs:
URLURL Type
http://www.springerlink.com/content/mmagn4fpmtmb6ukm/Publisher
Subjects:500 Science > 570 Life sciences
Status:Published
Refereed:Unknown
Created at the University of Regensburg:Unknown
Owner: Gertraud Kellers
Deposited On:01 Oct 2010 07:52
Last Modified:01 Oct 2010 07:52
Item ID:16880
Owner Only: item control page
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