http://www.nitrc.org/forum/forum.php?forum_id=2509 <table border="0" width="100%"><tr><td align="left"/></tr></table> <p><b>Semi-Blind Independent Component Analysis of fMRI Based on Real-Time fMRI System.</b></p> <p>IEEE Trans Neural Syst Rehabil Eng. 2012 Jan 23;</p> <p>Authors: Ma X, Zhang H, Zhao X, Yao L, Long Z</p> <p>Abstract<br/> Real-time functional magnetic resonance imaging (fMRI) is a type of neurofeedback tool that enables researchers to train individuals to actively gain control over their brain activation. Independent component analysis (ICA) based on data-driven model is seldom used in real-time fMRI studies due to large time cost, though it has been very popular to offline analysis of fMRI data. The feasibility of performing real-time ICA (rtICA) processing has been demonstrated by previous study. However, rtICA was only applied to analyze single-slice data rather than full-brain data. In order to improve the performance of rtICA, we proposed semi-blind real-time ICA (sb-rtICA) for our real-time fMRI system by adding regularization of certain estimated time courses using the experiment paradigm information to rtICA. Both simulated and real-time fMRI experiment were conducted to compare the two approaches. Results from simulated and real full-brain fMRI data demonstrate that sb-rtICA outperforms rtICA in robustness, computational time and spatial detection power. Moreover, in contrast to rtICA, the first component estimated by sb-rtICA tends to be the target component in more sliding windows.<br/> </p><p>PMID: 22275721 [PubMed - as supplied by publisher]</p> en-us Copyright 2000-2026 NITRC OSI Sun, 26 Apr 2026 0:19:24 GMT http://blogs.law.harvard.edu/tech/rss NITRC RSS generator