High-amplitude cofluctuations in cortical activity drive functional connectivity
Resting-state functional connectivity is used throughout neuroscience to study brain organization and to generate biomarkers of development, disease, and cognition. The processes that give rise to correlated activity are, however, poorly understood. Here we decompose resting-state functional connect...
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| Published in | Proceedings of the National Academy of Sciences - PNAS Vol. 117; no. 45; pp. 28393 - 28401 |
|---|---|
| Main Authors | , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
National Academy of Sciences
10.11.2020
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| Subjects | |
| Online Access | Get full text |
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| Abstract | Resting-state functional connectivity is used throughout neuroscience to study brain organization and to generate biomarkers of development, disease, and cognition. The processes that give rise to correlated activity are, however, poorly understood. Here we decompose resting-state functional connectivity using a temporal unwrapping procedure to assess the contributions of moment-to-moment activity cofluctuations to the overall connectivity pattern. This approach temporally resolves functional connectivity at a timescale of single frames, which enables us to make direct comparisons of cofluctuations of network organization with fluctuations in the blood oxygen level-dependent (BOLD) time series. We show that surprisingly, only a small fraction of frames exhibiting the strongest cofluctuation amplitude are required to explain a significant fraction of variance in the overall pattern of connection weights as well as the network’s modular structure. These frames coincide with frames of high BOLD activity amplitude, corresponding to activity patterns that are remarkably consistent across individuals and identify fluctuations in default mode and control network activity as the primary driver of resting-state functional connectivity. Finally, we demonstrate that cofluctuation amplitude synchronizes across subjects during movie watching and that high-amplitude frames carry detailed information about individual subjects (whereas low-amplitude frames carry little). Our approach reveals fine-scale temporal structure of resting-state functional connectivity and discloses that frame-wise contributions vary across time. These observations illuminate the relation of brain activity to functional connectivity and open a number of directions for future research. |
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| AbstractList | Resting-state functional connectivity is used throughout neuroscience to study brain organization and to generate biomarkers of development, disease, and cognition. The processes that give rise to correlated activity are, however, poorly understood. Here we decompose resting-state functional connectivity using a temporal unwrapping procedure to assess the contributions of moment-to-moment activity cofluctuations to the overall connectivity pattern. This approach temporally resolves functional connectivity at a timescale of single frames, which enables us to make direct comparisons of cofluctuations of network organization with fluctuations in the blood oxygen level-dependent (BOLD) time series. We show that surprisingly, only a small fraction of frames exhibiting the strongest cofluctuation amplitude are required to explain a significant fraction of variance in the overall pattern of connection weights as well as the network's modular structure. These frames coincide with frames of high BOLD activity amplitude, corresponding to activity patterns that are remarkably consistent across individuals and identify fluctuations in default mode and control network activity as the primary driver of resting-state functional connectivity. Finally, we demonstrate that cofluctuation amplitude synchronizes across subjects during movie watching and that high-amplitude frames carry detailed information about individual subjects (whereas low-amplitude frames carry little). Our approach reveals fine-scale temporal structure of resting-state functional connectivity and discloses that frame-wise contributions vary across time. These observations illuminate the relation of brain activity to functional connectivity and open a number of directions for future research. Resting-state functional connectivity is used throughout neuroscience to study brain organization and to generate biomarkers of development, disease, and cognition. The processes that give rise to correlated activity are, however, poorly understood. Here we decompose resting-state functional connectivity using a temporal unwrapping procedure to assess the contributions of moment-to-moment activity cofluctuations to the overall connectivity pattern. This approach temporally resolves functional connectivity at a timescale of single frames, which enables us to make direct comparisons of cofluctuations of network organization with fluctuations in the blood oxygen level-dependent (BOLD) time series. We show that surprisingly, only a small fraction of frames exhibiting the strongest cofluctuation amplitude are required to explain a significant fraction of variance in the overall pattern of connection weights as well as the network's modular structure. These frames coincide with frames of high BOLD activity amplitude, corresponding to activity patterns that are remarkably consistent across individuals and identify fluctuations in default mode and control network activity as the primary driver of resting-state functional connectivity. Finally, we demonstrate that cofluctuation amplitude synchronizes across subjects during movie watching and that high-amplitude frames carry detailed information about individual subjects (whereas low-amplitude frames carry little). Our approach reveals fine-scale temporal structure of resting-state functional connectivity and discloses that frame-wise contributions vary across time. These observations illuminate the relation of brain activity to functional connectivity and open a number of directions for future research.Resting-state functional connectivity is used throughout neuroscience to study brain organization and to generate biomarkers of development, disease, and cognition. The processes that give rise to correlated activity are, however, poorly understood. Here we decompose resting-state functional connectivity using a temporal unwrapping procedure to assess the contributions of moment-to-moment activity cofluctuations to the overall connectivity pattern. This approach temporally resolves functional connectivity at a timescale of single frames, which enables us to make direct comparisons of cofluctuations of network organization with fluctuations in the blood oxygen level-dependent (BOLD) time series. We show that surprisingly, only a small fraction of frames exhibiting the strongest cofluctuation amplitude are required to explain a significant fraction of variance in the overall pattern of connection weights as well as the network's modular structure. These frames coincide with frames of high BOLD activity amplitude, corresponding to activity patterns that are remarkably consistent across individuals and identify fluctuations in default mode and control network activity as the primary driver of resting-state functional connectivity. Finally, we demonstrate that cofluctuation amplitude synchronizes across subjects during movie watching and that high-amplitude frames carry detailed information about individual subjects (whereas low-amplitude frames carry little). Our approach reveals fine-scale temporal structure of resting-state functional connectivity and discloses that frame-wise contributions vary across time. These observations illuminate the relation of brain activity to functional connectivity and open a number of directions for future research. Despite widespread applications, the origins of functional connectivity remain elusive. Here we analyze human functional neuroimaging data. We decompose resting-state functional connectivity across time to assess the contributions of moment-to-moment activity cofluctuations to the overall connectivity pattern. We show that functional connectivity is driven by a small number of high-amplitude frames. We show that these frames are underpinned by a specific mode of brain activity; that the topography of this mode gets modulated during in-scanner tasks; and that high-amplitude frames encode personalized, subject-specific information. In summary, our parameter-free method provides an exact mathematical link between functional connectivity and frame-wise cofluctuations, creating opportunities for studying both static and time-varying functional brain networks. Resting-state functional connectivity is used throughout neuroscience to study brain organization and to generate biomarkers of development, disease, and cognition. The processes that give rise to correlated activity are, however, poorly understood. Here we decompose resting-state functional connectivity using a temporal unwrapping procedure to assess the contributions of moment-to-moment activity cofluctuations to the overall connectivity pattern. This approach temporally resolves functional connectivity at a timescale of single frames, which enables us to make direct comparisons of cofluctuations of network organization with fluctuations in the blood oxygen level-dependent (BOLD) time series. We show that surprisingly, only a small fraction of frames exhibiting the strongest cofluctuation amplitude are required to explain a significant fraction of variance in the overall pattern of connection weights as well as the network’s modular structure. These frames coincide with frames of high BOLD activity amplitude, corresponding to activity patterns that are remarkably consistent across individuals and identify fluctuations in default mode and control network activity as the primary driver of resting-state functional connectivity. Finally, we demonstrate that cofluctuation amplitude synchronizes across subjects during movie watching and that high-amplitude frames carry detailed information about individual subjects (whereas low-amplitude frames carry little). Our approach reveals fine-scale temporal structure of resting-state functional connectivity and discloses that frame-wise contributions vary across time. These observations illuminate the relation of brain activity to functional connectivity and open a number of directions for future research. |
| Author | Esfahlani, Farnaz Zamani Byrge, Lisa Sporns, Olaf Faskowitz, Joshua Betzel, Richard F. Jo, Youngheun Kennedy, Daniel P. |
| Author_xml | – sequence: 1 givenname: Farnaz Zamani surname: Esfahlani fullname: Esfahlani, Farnaz Zamani – sequence: 2 givenname: Youngheun surname: Jo fullname: Jo, Youngheun – sequence: 3 givenname: Joshua surname: Faskowitz fullname: Faskowitz, Joshua – sequence: 4 givenname: Lisa surname: Byrge fullname: Byrge, Lisa – sequence: 5 givenname: Daniel P. surname: Kennedy fullname: Kennedy, Daniel P. – sequence: 6 givenname: Olaf surname: Sporns fullname: Sporns, Olaf – sequence: 7 givenname: Richard F. surname: Betzel fullname: Betzel, Richard F. |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/33093200$$D View this record in MEDLINE/PubMed |
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| Keywords | naturalistic stimuli time-varying connectivity dynamics functional connectivity |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Author contributions: F.Z.E., Y.J., and R.F.B. designed research; F.Z.E., Y.J., and R.F.B. performed research; F.Z.E., Y.J., J.F., L.B., D.P.K., and O.S. contributed new reagents/analytic tools; F.Z.E., Y.J., and R.F.B. analyzed data; and F.Z.E., Y.J., J.F., L.B., D.P.K., O.S., and R.F.B. wrote the paper. Edited by Marcus E. Raichle, Washington University in St. Louis, St. Louis, MO, and approved September 11, 2020 (received for review March 24, 2020) 1F.Z.E. and Y.J. contributed equally to this work. |
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| Snippet | Resting-state functional connectivity is used throughout neuroscience to study brain organization and to generate biomarkers of development, disease, and... Despite widespread applications, the origins of functional connectivity remain elusive. Here we analyze human functional neuroimaging data. We decompose... |
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| SubjectTerms | Activity patterns Amplitudes Biological Sciences Biomarkers Brain Brain - diagnostic imaging Brain - physiology Brain architecture Brain Mapping - methods Cognition Fluctuations Frames Humans Magnetic Resonance Imaging - methods Modular structures Nerve Net - physiology Nervous system Neural networks Neural Pathways Oxygen - blood Physical Sciences Rest - physiology Time dependence |
| Title | High-amplitude cofluctuations in cortical activity drive functional connectivity |
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