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Independent Component Analysis of Functional Magnetic Resonance Imaging Data Using Wavelet Dictionaries.

Abstract:

Functional Magnetic Resonance Imaging (FMRI) allows indirect observation of brain activity through changes in blood oxygenation, which are driven by neural activity. ICA has become a popular exploratory analysis approach due its advantages over regression methods in accounting for structured noise as well as signals of interest. However, standard ICA in FMRI ignores some of the spatial and temporal structure contained in such data. Using prior knowledge that the Blood Oxygenation Level Depend...

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Publication status:
Published

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Institution:
University of Oxford
Department:
Oxford, MPLS, Statistics, Clinical Medicine
Role:
Author
More by this author
Institution:
University of Oxford
Department:
Oxford, MSD, Clinical Neuroscience
Role:
Author

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Role:
Editor
Role:
Editor
Role:
Editor
Role:
Editor
Publisher:
Springer Publisher's website
Volume:
4666
Pages:
625-632
Publication date:
2007-01-01
DOI:
EISSN:
1611-3349
ISSN:
0302-9743
URN:
uuid:1846440a-7c74-46c1-89cf-eae7512683b3
Source identifiers:
97532
Local pid:
pubs:97532
ISBN:
978-3-540-74493-1

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