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Open AccessJournal ArticleDOI

Methods to detect, characterize, and remove motion artifact in resting state fMRI

TLDR
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.
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This article is published in NeuroImage.The article was published on 2014-01-01 and is currently open access. It has received 2713 citations till now. The article focuses on the topics: Resting state fMRI.

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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.
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Intrinsic and Task-Evoked Network Architectures of the Human Brain

TL;DR: The results indicate the brain's functional network architecture during task performance is shaped primarily by an intrinsic network architecture that is also present during rest, and secondarily by evoked task-general and task-specific network changes.
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ICA-AROMA: A robust ICA-based strategy for removing motion artifacts from fMRI data

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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Generation and Evaluation of a Cortical Area Parcellation from Resting-State Correlations

TL;DR: The boundary map- derived parcellation contained parcels that overlapped with architectonic mapping of areas 17, 2, 3, and 4, and their connectivity patterns were reliable across individual subjects, suggesting that RSFC-boundary map-derived parcels provide information about the location and extent of human cortical areas.
References
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Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion

TL;DR: The results suggest the need for greater care in dealing with subject motion, and the need to critically revisit previous rs-fcMRI work that may not have adequately controlled for effects of transient subject movements.
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The organization of the human cerebral cortex estimated by intrinsic functional connectivity

TL;DR: In this paper, the organization of networks in the human cerebrum was explored using resting-state functional connectivity MRI data from 1,000 subjects and a clustering approach was employed to identify and replicate networks of functionally coupled regions across the cerebral cortex.
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Least - squares frequency analysis of unequally spaced data

TL;DR: In this article, the statistical properties of least-squares frequency analysis of unequally spaced data are examined and it is shown that the reduction in the sum of squares at a particular frequency is a X22 variable.
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Functional network organization of the human brain

TL;DR: In this article, the authors studied functional brain organization in healthy adults using resting state functional connectivity MRI and proposed two novel brain wide graphs, one of 264 putative functional areas, the other a modification of voxelwise networks that eliminates potentially artificial short-distance relationships.
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