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ICASSP
2010
IEEE

Independent subspace analysis with prior information for fMRI data

10 years 8 months ago
Independent subspace analysis with prior information for fMRI data
Independent component analysis (ICA) has been successfully applied for the analysis of functional magnetic resonance imaging (fMRI) data. However, independence might be too strong a constraint for certain sources. In this paper, we present an independent subspace analysis (ISA) framework that forms independent subspaces among the estimated sources having dependencies by a hierarchial clustering approach and subsequently separates the dependent sources in the task-related subspace using prior information. We study the incorporation of two types of prior information to transform the sources within the task-related subspace: sparsity and task-related time courses. We demonstrate the effectiveness of our proposed method for source separation of multi-subject fMRI data from a visuomotor task. Our results show that physiologically meaningful dependencies among sources can be identified using our subspace approach and the dependent estimated components can be further separated effectively...
Sai Ma, Xi-Lin Li, Nicolle M. Correa, Tülay A
Added 26 Jan 2011
Updated 26 Jan 2011
Type Journal
Year 2010
Where ICASSP
Authors Sai Ma, Xi-Lin Li, Nicolle M. Correa, Tülay Adali, Vince D. Calhoun
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