{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T20:37:35Z","timestamp":1762375055511},"reference-count":26,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2006,5,4]],"date-time":"2006-05-04T00:00:00Z","timestamp":1146700800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Magnetic Resonance in Med"],"published-print":{"date-parts":[[2006,6]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Task\u2010related head movement during acquisition of fMRI data represents a serious confound for both motion correction and estimates of task\u2010related activation. Cost functions implemented in most conventional motion\u2010correction algorithms compare two volumes for similarity but fail to account for signal variability that is <jats:italic>not<\/jats:italic> due to motion (e.g., brain activation). We therefore recently proposed the theoretical basis for a novel method for fMRI motion correction, termed motion\u2010corrected independent component analysis (MCICA), that allows for brain activation present in an fMRI time\u2010series to be implicitly modeled and mitigates motion\u2010induced signal changes without having to directly estimate the motion parameters (Liao et al., IEEE Transactions on Medical Imaging 2005;25:29\u201344). To explore the effects of non\u2010movement\u2010related signal changes on registration error, we performed several previously proposed test simulations (Freire et al., IEEE Transactions on Medical Imaging 2002;21:470\u2013484) to evaluate the performance of MCICA and compare it with the conventional square\u2010of\u2010difference\u2010based measures such as LS\u2010SPM and LS\u2010AIR. We demonstrate that for both simulated data and real fMRI images, the proposed MCICA method performs favorably. Specifically, in simulations MCICA was more robust to the addition of simulated activation, and did not lead to the detection of false activations after correction for simulated task\u2010correlated motion. With actual data from a motor fMRI experiment, the time course of the derived continually task\u2010related ICA component became more correlated with the underlying behavioral task after preprocessing with MCICA compared to other methods, and the associated activation map was more clustered in the primary motor and supplementary motor cortices without spurious activation at the brain edge. We conclude that assessing the statistical properties of a motion\u2010corrupted volume in relation to other volumes in the series, as is done with MCICA, is an accurate means of differentiating between motion\u2010induced signal changes and other sources of variability in fMRI data. Magn Reson Med, 2006. \u00a9 2006 Wiley\u2010Liss, Inc.<\/jats:p>","DOI":"10.1002\/mrm.20893","type":"journal-article","created":{"date-parts":[[2006,5,4]],"date-time":"2006-05-04T21:22:54Z","timestamp":1146777774000},"page":"1396-1413","update-policy":"http:\/\/dx.doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Isolation and minimization of head motion\u2010induced signal variations in fMRI data using independent component analysis"],"prefix":"10.1002","volume":"55","author":[{"given":"Rui","family":"Liao","sequence":"first","affiliation":[]},{"given":"Martin J.","family":"McKeown","sequence":"additional","affiliation":[]},{"given":"Jeffrey L.","family":"Krolik","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2006,5,4]]},"reference":[{"key":"e_1_2_10_2_2","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.1910310307"},{"key":"e_1_2_10_3_2","first-page":"69","article-title":"Analysis of functional MRI time\u2010series","volume":"2","author":"Friston KJ","year":"1994","journal-title":"Hum Brain Mapp"},{"key":"e_1_2_10_4_2","doi-asserted-by":"publisher","DOI":"10.1097\/00004728-199801000-00027"},{"key":"e_1_2_10_5_2","first-page":"139","article-title":"Automatic 3D segmentation of neuro\u2010anatomical structures from MRI","author":"Collins DL","year":"1995","journal-title":"Inform Process Med Imaging"},{"key":"e_1_2_10_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/S1361-8415(99)80030-9"},{"key":"e_1_2_10_7_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2002.1009383"},{"key":"e_1_2_10_8_2","doi-asserted-by":"publisher","DOI":"10.1006\/nimg.1999.0515"},{"key":"e_1_2_10_9_2","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.1880070219"},{"key":"e_1_2_10_10_2","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1522-2594(199905)41:5<964::AID-MRM16>3.0.CO;2-D"},{"key":"e_1_2_10_11_2","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1097-0193(1998)6:3<160::AID-HBM5>3.0.CO;2-1"},{"key":"e_1_2_10_12_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2004.837791"},{"key":"e_1_2_10_13_2","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1995.7.6.1129"},{"key":"e_1_2_10_14_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-49197-2_22"},{"key":"e_1_2_10_15_2","unstructured":"StudholmeC HillDLG HawkesDJ.Multiresolution voxel similarity measures for MR\u2010PET registration. In: Proceedings of the 14th International Conference IMPI '95. Information Processing Medical Imaging 1995;287\u2013298."},{"key":"e_1_2_10_16_2","doi-asserted-by":"publisher","DOI":"10.1007\/10704282_65"},{"key":"e_1_2_10_17_2","unstructured":"ViolaPA.Alignment by maximization of mutual information. Ph.D. dissertation Massachusetts Institute of Technology Cambridge MA USA 1994."},{"key":"e_1_2_10_18_2","first-page":"1717","article-title":"The principal axes transformation\u2014a method for image registration","volume":"31","author":"Alpert NM","year":"1990","journal-title":"J Nucl Med"},{"key":"e_1_2_10_19_2","doi-asserted-by":"publisher","DOI":"10.1109\/42.836369"},{"key":"e_1_2_10_20_2","doi-asserted-by":"publisher","DOI":"10.1097\/00004728-199707000-00007"},{"key":"e_1_2_10_21_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0730-725X(99)00059-4"},{"key":"e_1_2_10_22_2","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.1910350312"},{"key":"e_1_2_10_23_2","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1097-0193(1998)6:5\/6<368::AID-HBM7>3.0.CO;2-E"},{"key":"e_1_2_10_24_2","unstructured":"2002 MIT Press Cambridge MA MJ McKeown FT Sommer A Wichert Deterministic and stochastic features of fMRI data: implications for data averaging advances in exploratory analysis and data modeling in functional neuroimaging"},{"key":"e_1_2_10_25_2","volume-title":"Introduction to optimization theory","author":"Gottfried BS","year":"1973"},{"key":"e_1_2_10_26_2","volume-title":"Studies in linear and nonlinear programming","author":"Arrow KJ","year":"1958"},{"key":"e_1_2_10_27_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2003.819294"}],"container-title":["Magnetic Resonance in Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.wiley.com\/onlinelibrary\/tdm\/v1\/articles\/10.1002%2Fmrm.20893","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/mrm.20893","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,12]],"date-time":"2023-10-12T18:54:57Z","timestamp":1697136897000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/mrm.20893"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2006,5,4]]},"references-count":26,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2006,6]]}},"alternative-id":["10.1002\/mrm.20893"],"URL":"https:\/\/doi.org\/10.1002\/mrm.20893","archive":["Portico"],"relation":{},"ISSN":["0740-3194","1522-2594"],"issn-type":[{"value":"0740-3194","type":"print"},{"value":"1522-2594","type":"electronic"}],"subject":[],"published":{"date-parts":[[2006,5,4]]},"assertion":[{"value":"2005-07-09","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2006-02-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2006-05-04","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}