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Journal Article•DOI•

Resting-state networks show dynamic functional connectivity in awake humans and anesthetized macaques.

R. Matthew Hutchison, Thilo Womelsdorf, Joseph S. Gati1, Stefan Everling, Ravi S. Menon •
Robarts Research Institute1
01 Sep 2013-Human Brain Mapping (John Wiley & Sons, Ltd)-Vol. 34, Iss: 9, pp 2154-2177
TL;DR: It is found that functional connectivity among nodes comprising the “oculomotor (OCM) network” strongly fluctuated over time during awake as well as anaesthetized states, illustrating that resting‐state functional connectivity is not static and that RSNs can exhibit nonstationary, spontaneous relationships irrespective of conscious, cognitive processing.
Abstract: r r Abstract: Characterization of large-scale brain networks using blood-oxygenation-level-dependent functional magnetic resonance imaging is typically based on the assumption of network stationarity across the duration of scan. Recent studies in humans have questioned this assumption by showing that within-network functional connectivity fluctuates on the order of seconds to minutes. Time-varying profiles of resting-state networks (RSNs) may relate to spontaneously shifting, electrophysiological network states and are thus mechanistically of particular importance. However, because these studies acquired data from awake subjects, the fluctuating connectivity could reflect various forms of conscious brain processing such as passive mind wandering, active monitoring, memory formation, or changes in attention and arousal during image acquisition. Here, we characterize RSN dynamics of anesthetized macaques that control for these accounts, and compare them to awake human subjects. We find that functional connectivity among nodes comprising the ''oculomotor (OCM) network'' strongly fluctuated over time during awake as well as anaesthetized states. For time dependent anal- ysis with short windows (<60 s), periods of positive functional correlations alternated with prominent anticor- relations that were missed when assessed with longer time windows. Similarly, the analysis identified network nodes that transiently link to the OCM network and did not emerge in average RSN analysis. Further- more, time-dependent analysis reliably revealed transient states of large-scale synchronization that spanned all seeds. The results illustrate that resting-state functional connectivity is not static and that RSNs can exhibit non- stationary, spontaneous relationships irrespective of conscious, cognitive processing. The findings imply that mechanistically important network information can be missed when using average functional connectivity as the single network measure.Hum Brain Mapp 00:000-000, 2012. V C 2012 Wiley Periodicals, Inc.

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Citations
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Journal Article•DOI•
Tracking Whole-Brain Connectivity Dynamics in the Resting State

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Elena A. Allen1, Eswar Damaraju1, Sergey M. Plis1, Erik B. Erhardt1, Tom Eichele, Vince D. Calhoun1, Vince D. Calhoun2 •
The Mind Research Network1, University of New Mexico2
01 Mar 2014-Cerebral Cortex
TL;DR: In this article, the authors describe an approach to assess whole-brain functional connectivity dynamics based on spatial independent component analysis, sliding time window correlation, and k-means clustering of windowed correlation matrices.
Abstract: Spontaneous fluctuations are a hallmark of recordings of neural signals, emergent over time scales spanning milliseconds and tens of minutes. However, investigations of intrinsic brain organization based on resting-state functional magnetic resonance imaging have largely not taken into account the presence and potential of temporal variability, as most current approaches to examine functional connectivity (FC) implicitly assume that relationships are constant throughout the length of the recording. In this work, we describe an approach to assess whole-brain FC dynamics based on spatial independent component analysis, sliding time window correlation, and k-means clustering of windowed correlation matrices. The method is applied to resting-state data from a large sample (n = 405) of young adults. Our analysis of FC variability highlights particularly flexible connections between regions in lateral parietal and cingulate cortex, and argues against a labeling scheme where such regions are treated as separate and antagonistic entities. Additionally, clustering analysis reveals unanticipated FC states that in part diverge strongly from stationary connectivity patterns and challenge current descriptions of interactions between large-scale networks. Temporal trends in the occurrence of different FC states motivate theories regarding their functional roles and relationships with vigilance/arousal. Overall, we suggest that the study of time-varying aspects of FC can unveil flexibility in the functional coordination between different neural systems, and that the exploitation of these dynamics in further investigations may improve our understanding of behavioral shifts and adaptive processes.

2,455 citations

Journal Article•DOI•
Dynamic functional connectivity: Promise, issues, and interpretations

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R. Matthew Hutchison1, Thilo Womelsdorf2, Elena A. Allen3, Elena A. Allen4, Peter A. Bandettini5, Vince D. Calhoun4, Vince D. Calhoun6, Maurizio Corbetta7, Maurizio Corbetta8, Stefania Della Penna8, Jeff H. Duyn5, Gary H. Glover9, Javier Gonzalez-Castillo5, Daniel A. Handwerker5, Shella D. Keilholz10, Vesa Kiviniemi11, David A. Leopold5, Francesco de Pasquale8, Olaf Sporns12, Martin Walter13, Martin Walter14, Catie Chang5 •
University of Western Ontario1, York University2, University of Bergen3, The Mind Research Network4, National Institutes of Health5, University of New Mexico6, Washington University in St. Louis7, University of Chieti-Pescara8, Stanford University9, Georgia Institute of Technology10, Oulu University Hospital11, Indiana University12, Otto-von-Guericke University Magdeburg13, Leibniz Institute for Neurobiology14
15 Oct 2013-NeuroImage
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.

2,332 citations

Additional excerpts

  • ...Hutchison et al. / NeuroImage 80 (2013) 360–378...

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Journal Article•DOI•
The Chronnectome: Time-Varying Connectivity Networks as the Next Frontier in fMRI Data Discovery

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Vince D. Calhoun1, Vince D. Calhoun2, Robyn L. Miller1, Godfrey D. Pearlson, Tulay Adali3 •
The Mind Research Network1, University of New Mexico2, University of Maryland, Baltimore County3
22 Oct 2014-Neuron
TL;DR: This Perspective uses the term "chronnectome" to describe metrics that allow a dynamic view of coupling and focuses on multivariate approaches developed in the group and review a number of approaches with an emphasis on matrix decompositions such as principle component analysis and independent component analysis.

1,148 citations

Cites background from "Resting-state networks show dynamic..."

  • ...Based on the rapid increase in journal papers focused on dynamic connectivity (Allen et al., 2014; Calhoun et al., 2013b; Chang and Glover 2010; Hutchison et al., 2013a; Hutchison et al., 2013b; Keilholz 2014; Keilholz et al., 2013; Leonardi et al., 2013; Sako glu et al., 2010), including recent…...

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  • ...Since then, multiple chronnectomic studies have appeared (for a recent review, see Hutchison et al., 2013a)....

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  • ...…in journal papers focused on dynamic connectivity (Allen et al., 2014; Calhoun et al., 2013b; Chang and Glover 2010; Hutchison et al., 2013a; Hutchison et al., 2013b; Keilholz 2014; Keilholz et al., 2013; Leonardi et al., 2013; Sako glu et al., 2010), including recent work showing that…...

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Journal Article•DOI•
The dynamic functional connectome: State-of-the-art and perspectives

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Maria Giulia Preti1, Thomas A. W. Bolton1, Dimitri Van De Ville1•
École Polytechnique Fédérale de Lausanne1
15 Oct 2017-NeuroImage
TL;DR: This review aims to provide a comprehensive description of the dFC approaches proposed so far, and point at the directions that the authors see as most promising for the future developments of the field.

1,032 citations

Journal Article•DOI•
Dynamic functional connectivity analysis reveals transient states of dysconnectivity in schizophrenia

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Eswar Damaraju1, Elena A. Allen2, Elena A. Allen1, Aysenil Belger3, Judith M. Ford4, Judith M. Ford5, Sarah McEwen6, Daniel H. Mathalon5, Daniel H. Mathalon4, Bryon A. Mueller7, Godfrey D. Pearlson8, Steven G. Potkin9, Adrian Preda9, Jessica A. Turner10, Jatin G. Vaidya11, T.G.M. van Erp9, Vince D. Calhoun12, Vince D. Calhoun1 •
The Mind Research Network1, University of Bergen2, University of North Carolina at Chapel Hill3, University of California, San Francisco4, Veterans Health Administration5, University of California, Los Angeles6, University of Minnesota7, Yale University8, University of California, Irvine9, Georgia State University10, University of Iowa11, University of New Mexico12
01 Jan 2014-NeuroImage: Clinical
TL;DR: The results support and expand current knowledge regarding dysconnectivity in schizophrenia, and strongly advocate the use of dynamic analyses to better account for and understand functional connectivity differences.

906 citations

Cites background from "Resting-state networks show dynamic..."

  • ...…variability (Fox andRaichle, 2007), reports have alsohighlighted the pitfall of over-interpreting fluctuations in FC as having a neural origin, when in fact these fluctuations can arise from basic BOLD signal properties (Handwerker et al., 2012; Hutchison et al., 2013; Keilholz et al., 2013)....

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  • ...…in both animals and humans demonstrated that the spontaneous blood oxygen level dependent (BOLD) signals measured during rest exhibit intrinsic spatiotemporal dynamic organization (Chang and Glover, 2010; Hutchison et al., 2013b; Keilholz et al., 2013; Liu and Duyn, 2013; Sakoğlu et al., 2010)....

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  • ...…studies both in animals and humans have highlighted the nonstationary nature of functional connectivity in BOLD fMRI data (Chang and Glover, 2010; Hutchison et al., 2013), we sought to determine whether the observed sFNC differences were primarily driven by certain connectivity configurations…...

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  • ...…and humans have highlighted the nonstationary nature of functional connectivity in BOLD fMRI data (Chang and Glover, 2010; Hutchison et al., 2013), we sought to determine whether the observed sFNC differences were primarily driven by certain connectivity configurations (Hutchison et al., 2013a)....

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  • ...This measure of average connectivity, although useful, might not be enough to fully characterize the dynamically changing association between networks which is thought to be critical to process, coordinate, integrate and respond to internal and external stimuli (Hutchison et al., 2013)....

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References
More filters
Journal Article•DOI•
Functional connectivity in the motor cortex of resting human brain using echo-planar MRI.

[...]

Bharat B. Biswal1, F Z Yetkin1, Victor M. Haughton1, James S. Hyde1•
Medical College of Wisconsin1
01 Oct 1995-Magnetic Resonance in Medicine
TL;DR: It is concluded that correlation of low frequency fluctuations, which may arise from fluctuations in blood oxygenation or flow, is a manifestation of functional connectivity of the brain.
Abstract: An MRI time course of 512 echo-planar images (EPI) in resting human brain obtained every 250 ms reveals fluctuations in signal intensity in each pixel that have a physiologic origin. Regions of the sensorimotor cortex that were activated secondary to hand movement were identified using functional MRI methodology (FMRI). Time courses of low frequency (< 0.1 Hz) fluctuations in resting brain were observed to have a high degree of temporal correlation (P < 10(-3)) within these regions and also with time courses in several other regions that can be associated with motor function. It is concluded that correlation of low frequency fluctuations, which may arise from fluctuations in blood oxygenation or flow, is a manifestation of functional connectivity of the brain.

8,766 citations

"Resting-state networks show dynamic..." refers background in this paper

  • ...Mice, rats, monkeys, and humans [Biswal et al., 1995; Jonckers et al., 2011; Lu et al., 2007; Vincent et al., 2007], all show robust and reproducible RSNs....

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  • ...Second, the present work offers preliminary evidence that much like RSN organization [Biswal et al., 1995; Beckmann et al., 2005; Hutchison et al., 2010, 2011; Jonckers et al., 2011; Vincent et al., 2007], dynamic relationships within the networks are also a conserved brain property across mammals....

    [...]

  • ..., 2007], closely resemble task-based activation networks [Biswal et al., 1995; Fox et al., 2006a; Smith et al., 2009; Vincent et al., 2007], and are believed to be of neuronal origin [Britz et al....

    [...]

  • ...…al., 2009; Honey et al., 2009; Kelly et al., 2010; Margulies et al., 2009; Vincent et al., 2007], closely resemble task-based activation networks [Biswal et al., 1995; Fox et al., 2006a; Smith et al., 2009; Vincent et al., 2007], and are believed to be of neuronal origin [Britz et al., 2010;…...

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  • ..., 1993] and the demonstration of the first maps based on these spatiotemporal coherences [Biswal et al., 1995], resting-state functional magnetic resonance imaging (RSfMRI) has become an important tool for characterizing functional brain networks....

    [...]

Journal Article•DOI•
Distributed Hierarchical Processing in the Primate Cerebral Cortex

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Daniel J. Felleman1, David C. Van Essen2•
University of Texas at Austin1, California Institute of Technology2
01 Jan 1991-Cerebral Cortex
TL;DR: A summary of the layout of cortical areas associated with vision and with other modalities, a computerized database for storing and representing large amounts of information on connectivity patterns, and the application of these data to the analysis of hierarchical organization of the cerebral cortex are reported on.
Abstract: In recent years, many new cortical areas have been identified in the macaque monkey. The number of identified connections between areas has increased even more dramatically. We report here on (1) a summary of the layout of cortical areas associated with vision and with other modalities, (2) a computerized database for storing and representing large amounts of information on connectivity patterns, and (3) the application of these data to the analysis of hierarchical organization of the cerebral cortex. Our analysis concentrates on the visual system, which includes 25 neocortical areas that are predominantly or exclusively visual in function, plus an additional 7 areas that we regard as visual-association areas on the basis of their extensive visual inputs. A total of 305 connections among these 32 visual and visual-association areas have been reported. This represents 31% of the possible number of pathways if each area were connected with all others. The actual degree of connectivity is likely to be closer to 40%. The great majority of pathways involve reciprocal connections between areas. There are also extensive connections with cortical areas outside the visual system proper, including the somatosensory cortex, as well as neocortical, transitional, and archicortical regions in the temporal and frontal lobes. In the somatosensory/motor system, there are 62 identified pathways linking 13 cortical areas, suggesting an overall connectivity of about 40%. Based on the laminar patterns of connections between areas, we propose a hierarchy of visual areas and of somatosensory/motor areas that is more comprehensive than those suggested in other recent studies. The current version of the visual hierarchy includes 10 levels of cortical processing. Altogether, it contains 14 levels if one includes the retina and lateral geniculate nucleus at the bottom as well as the entorhinal cortex and hippocampus at the top. Within this hierarchy, there are multiple, intertwined processing streams, which, at a low level, are related to the compartmental organization of areas V1 and V2 and, at a high level, are related to the distinction between processing centers in the temporal and parietal lobes. However, there are some pathways and relationships (about 10% of the total) whose descriptions do not fit cleanly into this hierarchical scheme for one reason or another. In most instances, though, it is unclear whether these represent genuine exceptions to a strict hierarchy rather than inaccuracies or uncertainities in the reported assignment.

7,796 citations

Journal Article•DOI•
The human brain is intrinsically organized into dynamic, anticorrelated functional networks

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Michael D. Fox1, Abraham Z. Snyder1, Justin L. Vincent1, Maurizio Corbetta1, David C. Van Essen1, Marcus E. Raichle1 •
Washington University in St. Louis1
05 Jul 2005-Proceedings of the National Academy of Sciences of the United States of America
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.
Abstract: During performance of attention-demanding cognitive tasks, certain regions of the brain routinely increase activity, whereas others routinely decrease activity. In this study, we investigate the extent to which this task-related dichotomy is represented intrinsically in the resting human brain through examination of spontaneous fluctuations in the functional MRI blood oxygen level-dependent signal. We identify two diametrically opposed, widely distributed brain networks on the basis of both spontaneous correlations within each network and anticorrelations between networks. One network consists of regions routinely exhibiting task-related activations and the other of regions routinely exhibiting task-related deactivations. This intrinsic organization, featuring the presence of anticorrelated networks in the absence of overt task performance, provides a critical context in which to understand brain function. We suggest that both task-driven neuronal responses and behavior are reflections of this dynamic, ongoing, functional organization of the brain.

7,741 citations

"Resting-state networks show dynamic..." refers background in this paper

  • ...The role of anticorrelations within RSNs remains unclear and controversial [Cole et al., 2010; Fox et al., 2005; Murphy et al., 2009], though it has been suggested that they subserve a ‘‘differentiating role,’’ segregating neuronal processes that have competing representations [Fox et al....

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  • ...The role of anticorrelations within RSNs remains unclear and controversial [Cole et al., 2010; Fox et al., 2005; Murphy et al., 2009], though it has been suggested that they subserve a ‘‘differentiating role,’’ segregating neuronal processes that have competing representations [Fox et al., 2005]....

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  • ..., 2009], though it has been suggested that they subserve a ‘‘differentiating role,’’ segregating neuronal processes that have competing representations [Fox et al., 2005]....

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Journal Article•DOI•
Neurophysiological investigation of the basis of the fMRI signal

[...]

Nikos K. Logothetis1, J Pauls1, Mark Augath1, T Trinath1, Axel Oeltermann1 •
Max Planck Society1
12 Jul 2001-Nature
TL;DR: These findings suggest that the BOLD contrast mechanism reflects the input and intracortical processing of a given area rather than its spiking output, and that LFPs yield a better estimate of BOLD responses than the multi-unit responses.
Abstract: Functional magnetic resonance imaging (fMRI) is widely used to study the operational organization of the human brain, but the exact relationship between the measured fMRI signal and the underlying neural activity is unclear. Here we present simultaneous intracortical recordings of neural signals and fMRI responses. We compared local field potentials (LFPs), single- and multi-unit spiking activity with highly spatio-temporally resolved blood-oxygen-level-dependent (BOLD) fMRI responses from the visual cortex of monkeys. The largest magnitude changes were observed in LFPs, which at recording sites characterized by transient responses were the only signal that significantly correlated with the haemodynamic response. Linear systems analysis on a trialby-trial basis showed that the impulse response of the neurovascular system is both animal- and site-specific, and that LFPs yield a better estimate of BOLD responses than the multi-unit responses. These findings suggest that the BOLD contrast mechanism reflects the input and intracortical processing of a given area rather than its spiking output.

6,140 citations

Additional excerpts

  • ...Beyond establishing a link between neural activity and the hemodynamic BOLD activity [Logothetis et al., 2001], previous work using EEG-fMRI has attempted to directly derive the electrophysiological correlate of RSfMRI fluctuations [Britz et al., 2010; He et al., 2008; Laufs, 2008, 2010; Liu et…...

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Journal Article•DOI•
Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging.

[...]

Michael D. Fox1, Marcus E. Raichle1•
Washington University in St. Louis1
01 Sep 2007-Nature Reviews Neuroscience
TL;DR: Recent studies examining spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal of functional magnetic resonance imaging as a potentially important and revealing manifestation of spontaneous neuronal activity are reviewed.
Abstract: The majority of functional neuroscience studies have focused on the brain's response to a task or stimulus. However, the brain is very active even in the absence of explicit input or output. In this Article we review recent studies examining spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal of functional magnetic resonance imaging as a potentially important and revealing manifestation of spontaneous neuronal activity. Although several challenges remain, these studies have provided insight into the intrinsic functional architecture of the brain, variability in behaviour and potential physiological correlates of neurological and psychiatric disease.

6,135 citations

"Resting-state networks show dynamic..." refers background in this paper

  • ...…2009; Vincent et al., 2007], and are believed to be of neuronal origin [Britz et al., 2010; Laufs, 2008; Mantini et al., 2007; Musso et al., 2010; Nir et al., 2008; Shmuel and Leopold, 2008], though their physiological origin remains uncertain [Buckner and Vincent, 2007; Fox and Raichle, 2007]....

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  • ..., 2008; Shmuel and Leopold, 2008], though their physiological origin remains uncertain [Buckner and Vincent, 2007; Fox and Raichle, 2007]....

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Related Papers (5)
Tracking Whole-Brain Connectivity Dynamics in the Resting State

[...]

01 Mar 2014-Cerebral Cortex
Elena A. Allen, Eswar Damaraju, Sergey M. Plis, Erik B. Erhardt, Tom Eichele, Vince D. Calhoun, Vince D. Calhoun 
Functional connectivity in the motor cortex of resting human brain using echo-planar MRI.

[...]

01 Oct 1995-Magnetic Resonance in Medicine
Bharat B. Biswal, F Z Yetkin, Victor M. Haughton, James S. Hyde 
The human brain is intrinsically organized into dynamic, anticorrelated functional networks

[...]

05 Jul 2005-Proceedings of the National Academy of Sciences of the United States of America
Michael D. Fox, Abraham Z. Snyder, Justin L. Vincent, Maurizio Corbetta, David C. Van Essen, Marcus E. Raichle 
Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion

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01 Feb 2012-NeuroImage
Jonathan D. Power, Kelly Anne Barnes, Abraham Z. Snyder, Bradley L. Schlaggar, Steven E. Petersen 
Consistent resting-state networks across healthy subjects

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12 Sep 2006-Proceedings of the National Academy of Sciences of the United States of America
Jessica S. Damoiseaux, Serge A.R.B. Rombouts, Frederik Barkhof, Philip Scheltens, Cornelis J. Stam, Stephen M. Smith, Christian F. Beckmann