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Towards a consensus regarding global signal regression for resting state functional connectivity MRI

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TLDR
It is highlighted that there is not a single “right” way to process resting state data that reveals the “true” nature of the brain, and different processing approaches likely reveal complementary insights about the brain's functional organisation.
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This article is published in NeuroImage.The article was published on 2017-07-01 and is currently open access. It has received 793 citations till now. The article focuses on the topics: Resting state fMRI.

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Benchmarking of participant-level confound regression strategies for the control of motion artifact in studies of functional connectivity.

TL;DR: A systematic evaluation of 14 participant‐level confound regression methods for functional connectivity highlights the heterogeneous efficacy of existing methods, and suggests that different confounding regression strategies may be appropriate in the context of specific scientific goals.
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The brain’s default network: updated anatomy, physiology and evolving insights

TL;DR: Progress in understanding the organization and function of networks embedded within association regions is described, with findings from humans, monkeys and rodents indicating that multiple subnetworks make up the default network.
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Methods for cleaning the BOLD fMRI signal

TL;DR: The importance of signal denoising as an essential step in the analysis pipeline of task‐based and resting state fMRI studies is summarized and practical recommendations regarding the optimization of the preprocessing pipeline are indicated.
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Reduced default mode network functional connectivity in patients with recurrent major depressive disorder.

TL;DR: It is found that default mode network functional connectivity remains a prime target for understanding the pathophysiology of depression, with particular relevance to revealing mechanisms of effective treatments, and reduced rather than increased FC within the DMN is found.
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Task-induced brain state manipulation improves prediction of individual traits.

TL;DR: It is shown that task-based functional connectivity better predicts intelligence-related measures than rest-based connectivity, suggesting that cognitive tasks amplify individual differences in trait-relevant circuitry.
References
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Journal ArticleDOI

A default mode of brain function.

TL;DR: A baseline state of the normal adult human brain in terms of the brain oxygen extraction fraction or OEF is identified, suggesting the existence of an organized, baseline default mode of brain function that is suspended during specific goal-directed behaviors.
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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.
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Functional connectivity in the resting brain: A network analysis of the default mode hypothesis

TL;DR: This study constitutes, to the knowledge, the first resting-state connectivity analysis of the default mode and provides the most compelling evidence to date for the existence of a cohesive default mode network.
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A component based noise correction method (CompCor) for BOLD and perfusion based fMRI

TL;DR: A component based method for the reduction of noise in both blood oxygenation level-dependent (BOLD) and perfusion-based functional magnetic resonance imaging (fMRI) data is presented and the temporal standard deviation of resting-state perfusion and BOLD data in gray matter regions was significantly reduced.
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Movement-related effects in fMRI time-series

TL;DR: The empirical analyses suggest that (in extreme situations) over 90% of fMRI signal can be attributed to movement, and that this artifactual component can be successfully removed.
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