http://www.nitrc.org/forum/forum.php?forum_id=6830 <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=27859975">Related Articles</a></td></tr></table> <p><b>Population-Level Correction of Systematic Motion Artifacts in fMRI in Patients with Ischemic Stroke.</b></p> <p>J Neuroimaging. 2016 Nov 17;:</p> <p>Authors: Aranyi C, Opposits G, Nagy M, Berényi E, Vér C, Csiba L, Katona P, Spisák T, Emri M</p> <p>Abstract<br/> BACKGROUND: The aim of this study was to reveal potential sources of systematic motion artifacts in stroke functional magnetic resonance imaging (fMRI) focusing on those causing stimulus-correlated motion on the individual-level and separate the motion effect on the fMRI signal changing from the activation-induced alteration at population level.<br/> METHODS: Eleven ischemic stroke patients were examined by fMRI. The fMRI paradigm was based on passive ankle movement on both the healthy and the paretic leg's side. Three individual-level motion correction strategies were compared and we introduced five measures to characterize each subjects' in-scanner relative head movement. After analyzing the correlation of motion parameters and the subjects' physiological scale scores, we selected a parameter to model the motion-related artifacts in the second-level analysis.<br/> RESULTS: At first (individual) level analysis, the noise-component correction-based CompCor method provided the highest -log10(p) value of cluster-level occurrence probability at 12.4/13.6 for healthy and paretic side stimulus, respectively, with a maximal z-value of 15/16.3. Including the motion parameter at second (group) level resulted in lower cluster occurrence values at 10.9/5.55 while retaining the maximal z-value.<br/> CONCLUSIONS: We proposed a postprocessing pipeline for ischemic stroke fMRI data that combine the CompCor correction at first level with the modeling of motion effect at second-level analysis by a parameter obtained from fMRI data. Our solution is applicable for any fMRI-based stroke rehabilitation study since it does not require any MRI-compatible motion capture system and is based on commonly used methods.<br/> </p><p>PMID: 27859975 [PubMed - as supplied by publisher]</p> en-us Copyright 2000-2026 NITRC OSI Wed, 06 May 2026 5:22:55 GMT http://blogs.law.harvard.edu/tech/rss NITRC RSS generator