Investigations into resting-state connectivity using independent component analysis.

Journal article

Inferring resting-state connectivity patterns from functional magnetic resonance imaging (fMRI) data is a challenging task for any analytical technique. In this paper, we review a probabilistic independent component analysis (PICA) approach, optimized for the analysis of fMRI data, and discuss the role which this exploratory technique can take in scientific investigations into the structure of these effects. We apply PICA to fMRI data acquired at rest, in order to characterize the spatio-temp...

Expand abstract

Authors: Beckmann, C; DeLuca, M; Devlin, J; Smith, S

• Publication status: Published
• Journal: Philosophical transactions of the Royal Society of London. Series B, Biological sciences
• Volume: 360
• Issue: 1457
• Pages: 1001-1013
• Publication date: 2005-05-01
• DOI: 10.1098/rstb.2005.1634
• EISSN: 1471-2970
• ISSN: 0962-8436
• Language: English
• Keywords: Data Interpretation, Statistical; Brain Mapping; Models, Statistical; Brain; Humans; Magnetic Resonance Imaging; Models, Neurological