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Open AccessJournal ArticleDOI

Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion

TLDR
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.
About
This article is published in NeuroImage.The article was published on 2012-02-01 and is currently open access. It has received 6411 citations till now. The article focuses on the topics: Dynamic functional connectivity & Resting state fMRI.

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Citations
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Journal ArticleDOI

The minimal preprocessing pipelines for the Human Connectome Project.

TL;DR: The minimal preprocessing pipelines for structural, functional, and diffusion MRI that were developed by the HCP to accomplish many low level tasks, including spatial artifact/distortion removal, surface generation, cross-modal registration, and alignment to standard space are described.
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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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Conn: A Functional Connectivity Toolbox for Correlated and Anticorrelated Brain Networks

TL;DR: The results indicate that the CompCor method increases the sensitivity and selectivity of fcMRI analysis, and show a high degree of interscan reliability for many fc MRI measures.
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Methods to detect, characterize, and remove motion artifact in resting state fMRI

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

The economy of brain network organization

TL;DR: It is proposed that brain organization is shaped by an economic trade-off between minimizing costs and allowing the emergence of adaptively valuable topological patterns of anatomical or functional connectivity between multiple neuronal populations.
References
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Book

Networks: An Introduction

Mark Newman
TL;DR: This book brings together for the first time the most important breakthroughs in each of these fields and presents them in a coherent fashion, highlighting the strong interconnections between work in different areas.
Journal ArticleDOI

Community detection in graphs

TL;DR: A thorough exposition of community structure, or clustering, is attempted, from the definition of the main elements of the problem, to the presentation of most methods developed, with a special focus on techniques designed by statistical physicists.
Journal ArticleDOI

Community detection in graphs

TL;DR: A thorough exposition of the main elements of the clustering problem can be found in this paper, with a special focus on techniques designed by statistical physicists, from the discussion of crucial issues like the significance of clustering and how methods should be tested and compared against each other, to the description of applications to real networks.
Journal ArticleDOI

The human brain is intrinsically organized into dynamic, anticorrelated functional networks

TL;DR: It is suggested that both task-driven neuronal responses and behavior are reflections of this dynamic, ongoing, functional organization of the brain, featuring the presence of anticorrelated networks in the absence of overt task performance.
Journal ArticleDOI

Maps of random walks on complex networks reveal community structure

TL;DR: An information theoretic approach is introduced that reveals community structure in weighted and directed networks of large-scale biological and social systems and reveals a directional pattern of citation from the applied fields to the basic sciences.
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