http://www.nitrc.org/forum/forum.php?forum_id=8518 <table border="0" width="100%"><tr><td align="left"/><td align="right"><a href="https://www.ncbi.nlm.nih.gov/sites/entrez?db=pubmed&amp;cmd=Link&amp;LinkName=pubmed_pubmed&amp;from_uid=29673968">Related Articles</a></td></tr></table> <p><b>Model Order Effects on ICA of Resting-State Complex-Valued fMRI Data: Application to Schizophrenia.</b></p> <p>J Neurosci Methods. 2018 Apr 16;:</p> <p>Authors: Kuang LD, Lin QH, Gong XF, Cong F, Sui J, Calhoun VD</p> <p>Abstract<br/> BACKGROUND: Component splitting at higher model orders is a widely accepted finding for independent component analysis (ICA) of functional magnetic resonance imaging (fMRI) data. However, our recent study found that intact components occurred with subcomponents at higher model orders.<br/> NEW METHOD: This study investigated model order effects on ICA of resting-state complex-valued fMRI data from 82 subjects, which included 40 healthy controls (HCs) and 42 schizophrenia patients. In addition, we explored underlying causes for distinct component splitting between complex-valued data and magnitude-only data by examining model order effects on ICA of phase fMRI data. A best run selection method was proposed to combine subject averaging and a one-sample t-test. We selected the default mode network (DMN)-, visual-, and sensorimotor-related components from the best run of ICA at varying model orders from 10 to 140.<br/> RESULTS: Results show that component integration occurred in complex-valued and phase analyses, whereas component splitting emerged in magnitude-only analysis with increasing model order. Incorporation of phase data appears to play a complementary role in preserving integrity of brain networks.<br/> COMPARISON WITH EXISTING METHOD(S): When compared with magnitude-only analysis, the intact DMN component obtained in complex-valued analysis at higher model orders exhibited highly significant subject-level differences between HCs and patients with schizophrenia. We detected significantly higher activity and variation in anterior areas for HCs and in posterior areas for patients with schizophrenia.<br/> CONCLUSIONS: These results demonstrate the potential of complex-valued fMRI data to contribute generally and specifically to brain network analysis in identification of schizophrenia-related changes.<br/> </p><p>PMID: 29673968 [PubMed - as supplied by publisher]</p> en-us Copyright 2000-2026 NITRC OSI Mon, 27 Apr 2026 19:20:25 GMT http://blogs.law.harvard.edu/tech/rss NITRC RSS generator