Resting-state networks show dynamic functional connectivity in awake humans and anesthetized macaques
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‐netwo...
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| Published in | Human brain mapping Vol. 34; no. 9; pp. 2154 - 2177 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
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New York, NY
Blackwell Publishing Ltd
01.09.2013
Wiley-Liss John Wiley & Sons, Inc John Wiley and Sons Inc |
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| Online Access | Get full text |
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| 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 analysis with short windows (<60 s), periods of positive functional correlations alternated with prominent anticorrelations 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. Furthermore, 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 nonstationary, 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 34:2154–2177, 2013. © 2011 Wiley Periodicals, Inc. |
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| AbstractList | 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 analysis with short windows (<60 s), periods of positive functional correlations alternated with prominent anticorrelations 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. Furthermore, 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 nonstationary, 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.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 analysis with short windows (<60 s), periods of positive functional correlations alternated with prominent anticorrelations 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. Furthermore, 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 nonstationary, 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. 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 analysis with short windows (<60 s), periods of positive functional correlations alternated with prominent anticorrelations 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. Furthermore, 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 nonstationary, 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. 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 analysis with short windows (<60 s), periods of positive functional correlations alternated with prominent anticorrelations 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. Furthermore, 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 nonstationary, 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 34:2154-2177, 2013. © 2011 Wiley Periodicals, Inc. [PUBLICATION 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 analysis with short windows (<60 s), periods of positive functional correlations alternated with prominent anticorrelations 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. Furthermore, 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 nonstationary, 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 34:2154–2177, 2013 . © 2011 Wiley Periodicals, Inc. 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 analysis with short windows (<60 s), periods of positive functional correlations alternated with prominent anticorrelations 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. Furthermore, 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 nonstationary, 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 34:2154–2177, 2013. © 2011 Wiley Periodicals, Inc. |
| Author | Menon, Ravi S. Womelsdorf, Thilo Everling, Stefan Hutchison, R. Matthew Gati, Joseph S. |
| AuthorAffiliation | 4 Department of Biology Centre for Vision Research York University Toronto Ontario Canada 2 Department of Physiology and Pharmacology University of Western Ontario London Ontario Canada 1 Graduate Program in Neuroscience University of Western Ontario London Ontario Canada 3 Robarts Research Institute London Ontario Canada |
| AuthorAffiliation_xml | – name: 2 Department of Physiology and Pharmacology University of Western Ontario London Ontario Canada – name: 3 Robarts Research Institute London Ontario Canada – name: 4 Department of Biology Centre for Vision Research York University Toronto Ontario Canada – name: 1 Graduate Program in Neuroscience University of Western Ontario London Ontario Canada |
| Author_xml | – sequence: 1 givenname: R. Matthew surname: Hutchison fullname: Hutchison, R. Matthew organization: Graduate Program in Neuroscience, University of Western Ontario, London, Ontario, Canada – sequence: 2 givenname: Thilo surname: Womelsdorf fullname: Womelsdorf, Thilo organization: Department of Physiology and Pharmacology, University of Western Ontario, London, Ontario, Canada – sequence: 3 givenname: Joseph S. surname: Gati fullname: Gati, Joseph S. organization: Robarts Research Institute, Ontario, London, Canada – sequence: 4 givenname: Stefan surname: Everling fullname: Everling, Stefan organization: Graduate Program in Neuroscience, University of Western Ontario, London, Ontario, Canada – sequence: 5 givenname: Ravi S. surname: Menon fullname: Menon, Ravi S. email: rmenon@imaging.robarts.ca organization: Graduate Program in Neuroscience, University of Western Ontario, London, Ontario, Canada |
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| Keywords | Human macaque Fluctuations Nervous system diseases Radiodiagnosis Monkey functional MRI (fMRI) Nuclear magnetic resonance imaging resting-state Vertebrata dynamics Mammalia functional connectivity Primates nonstationary spontaneous activity fluctuations |
| Language | English |
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| SubjectTerms | Adult Anesthesia, General Animals Biological and medical sciences Brain - physiology Brain Mapping Consciousness - physiology dynamics Electrodiagnosis. Electric activity recording Female fluctuations functional connectivity functional MRI (fMRI) Humans Image Processing, Computer-Assisted Investigative techniques, diagnostic techniques (general aspects) Macaca macaque Magnetic Resonance Imaging Male Medical sciences Nerve Net - physiology Nervous system Neural Pathways - physiology nonstationary Radiodiagnosis. Nmr imagery. Nmr spectrometry Rest - physiology resting-state spontaneous activity |
| Title | Resting-state networks show dynamic functional connectivity in awake humans and anesthetized macaques |
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