A Comprehensive Assessment of Regional Variation in the Impact of Head Micromovements on Functional Connectomics
Chao-Gan Yan,Brian Cheung,Clare Kelly,Stanley J. Colcombe,R. Cameron Craddock,R. Cameron Craddock,Adriana Di Martino,Qingyang Li,Xi-Nian Zuo,F. Xavier Castellanos,F. Xavier Castellanos,Michael P. Milham,Michael P. Milham +12 more
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TLDR
A comprehensive voxel-based examination of the impact of motion on the BOLD signal suggests that positive relationships may reflect neural origins of motion while negative relationships are likely to originate from motion artifact.About:
This article is published in NeuroImage.The article was published on 2013-08-01 and is currently open access. It has received 1300 citations till now. The article focuses on the topics: Connectomics.read more
Citations
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Methods to detect, characterize, and remove motion artifact in resting state fMRI
Jonathan D. Power,Anish Mitra,Timothy O. Laumann,Abraham Z. Snyder,Bradley L. Schlaggar,Steven E. Petersen +5 more
TL;DR: It is found that motion-induced signal changes are often complex and variable waveforms, often shared across nearly all brain voxels, and often persist more than 10s after motion ceases, which increase observed RSFC correlations in a distance-dependent manner.
Journal ArticleDOI
Dynamic functional connectivity: Promise, issues, and interpretations
R. Matthew Hutchison,Thilo Womelsdorf,Elena A. Allen,Elena A. Allen,Peter A. Bandettini,Vince D. Calhoun,Vince D. Calhoun,Maurizio Corbetta,Maurizio Corbetta,Stefania Della Penna,Jeff H. Duyn,Gary H. Glover,Javier Gonzalez-Castillo,Daniel A. Handwerker,Shella D. Keilholz,Vesa Kiviniemi,David A. Leopold,Francesco de Pasquale,Olaf Sporns,Martin Walter,Martin Walter,Catie Chang +21 more
TL;DR: Emerging evidence suggests that dynamic FC metrics may index changes in macroscopic neural activity patterns underlying critical aspects of cognition and behavior, though limitations with regard to analysis and interpretation remain.
Journal ArticleDOI
DPABI: Data Processing & Analysis for (Resting-State) Brain Imaging.
TL;DR: The newly developed toolbox, DPABI, which was evolved from REST and DPARSF is introduced, designed to make data analysis require fewer manual operations, be less time-consuming, have a lower skill requirement, a smaller risk of inadvertent mistakes, and be more comparable across studies.
Journal ArticleDOI
The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism
A Di Martino,C-G Yan,Qingyang Li,E Denio,Francisco X. Castellanos,Francisco X. Castellanos,Kaat Alaerts,Kaat Alaerts,Jeffrey S. Anderson,Michal Assaf,Susan Y. Bookheimer,Mirella Dapretto,Ben Deen,Ben Deen,Sonja Delmonte,Ilan Dinstein,Ilan Dinstein,Birgit Ertl-Wagner,Damien A. Fair,Louise Gallagher,Daniel P. Kennedy,Daniel P. Kennedy,Christopher L. Keown,Christian Keysers,Christian Keysers,Janet E. Lainhart,Catherine Lord,Beatriz Luna,Vinod Menon,Nancy J. Minshew,Christopher S. Monk,Sophia Mueller,R-A Müller,Mary Beth Nebel,Joel T. Nigg,Kirsten O'Hearn,Kevin A. Pelphrey,Scott Peltier,Jeffrey D. Rudie,Stefan Sunaert,Mark Thioux,Mark Thioux,J M Tyszka,Lucina Q. Uddin,Judith Verhoeven,Nicole Wenderoth,Jillian Lee Wiggins,Stewart H. Mostofsky,Stewart H. Mostofsky,Michael P. Milham,Michael P. Milham +50 more
TL;DR: W Whole-brain analyses reconciled seemingly disparate themes of both hypo- and hyperconnectivity in the ASD literature; both were detected, although hypoconnectivity dominated, particularly for corticocortical and interhemispheric functional connectivity.
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ICA-AROMA: A robust ICA-based strategy for removing motion artifacts from fMRI data
Raimon H. R. Pruim,Maarten Mennes,Daan van Rooij,Alberto Llera,Jan K. Buitelaar,Christian F. Beckmann +5 more
TL;DR: The results show that ICA-AROMA effectively reduces motion-induced signal variations in fMRI data, is applicable across datasets without requiring classifier re-training, and preserves the temporal characteristics of the f MRI data.
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