NDLI: Semiblind Spatial ICA of fMRI Using Spatial Constraints

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Semiblind Spatial ICA of fMRI Using Spatial Constraints

Content Provider	PubMed Central
Author	Lin, Qiu-hua Liu, Jingyu Zheng, Yong-rui Liang, Hualou Calhoun, Vince D.
Copyright Year	2009
Abstract	Independent component analysis (ICA) utilizing prior information, also called semiblind ICA, has demonstrated considerable promise in the analysis of functional magnetic resonance imaging (fMRI). So far, temporal information about fMRI has been used in temporal ICA or spatial ICA as additional constraints to improve estimation of task-related components. Considering that prior information about spatial patterns is also available, a semiblind spatial ICA algorithm utilizing the spatial information was proposed within the framework of constrained ICA with fixed-point learning. The proposed approach was first tested with synthetic fMRI-like data, and then was applied to real fMRI data from 11 subjects performing a visuomotor task. Three components of interest including two task-related components and the “default mode” component were automatically extracted, and atlas-defined masks were used as the spatial constraints. The default mode network, a set of regions that appear correlated in particular in the absence of tasks or external stimuli and is of increasing interest in fMRI studies, was found to be greatly improved when incorporating spatial prior information. Results from simulation and real fMRI data demonstrate that the proposed algorithm can improve ICA performance compared to a different semiblind ICA algorithm and a standard blind ICA algorithm.
Related Links	http://dx.doi.org/10.1002/hbm.20919
Ending Page	1088
Page Count	13
Starting Page	1076
File Format	PDF
ISSN	10659471
e-ISSN	10970193
Journal	Human brain mapping
Issue Number	7
Volume Number	31
Language	English
Publisher Date	2009-12-01
Access Restriction	Open
Subject Keyword	Anatomy Radiological and Ultrasound Technology Radiology Nuclear Medicine and imaging Neurology Clinical Neurology Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Anatomy Neurology Radiology, Nuclear Medicine and Imaging Neurology (clinical) Radiological and Ultrasound Technology

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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