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      On the Stability of BOLD fMRI Correlations

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          Abstract

          Measurement of correlations between brain regions (functional connectivity) using blood oxygen level dependent (BOLD) fMRI has proven to be a powerful tool for studying the functional organization of the brain. Recently, dynamic functional connectivity has emerged as a major topic in the resting-state BOLD fMRI literature. Here, using simulations and multiple sets of empirical observations, we confirm that imposed task states can alter the correlation structure of BOLD activity. However, we find that observations of “dynamic” BOLD correlations during the resting state are largely explained by sampling variability. Beyond sampling variability, the largest part of observed “dynamics” during rest is attributable to head motion. An additional component of dynamic variability during rest is attributable to fluctuating sleep state. Thus, aside from the preceding explanatory factors, a single correlation structure—as opposed to a sequence of distinct correlation structures—may adequately describe the resting state as measured by BOLD fMRI. These results suggest that resting-state BOLD correlations do not primarily reflect moment-to-moment changes in cognitive content. Rather, resting-state BOLD correlations may predominantly reflect processes concerned with the maintenance of the long-term stability of the brain's functional organization.

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          Variability, compensation and homeostasis in neuron and network function.

          Neurons in most animals live a very long time relative to the half-lives of all of the proteins that govern excitability and synaptic transmission. Consequently, homeostatic mechanisms are necessary to ensure stable neuronal and network function over an animal's lifetime. To understand how these homeostatic mechanisms might function, it is crucial to understand how tightly regulated synaptic and intrinsic properties must be for adequate network performance, and the extent to which compensatory mechanisms allow for multiple solutions to the production of similar behaviour. Here, we use examples from theoretical and experimental studies of invertebrates and vertebrates to explore several issues relevant to understanding the precision of tuning of synaptic and intrinsic currents for the operation of functional neuronal circuits.
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            The temporal structures and functional significance of scale-free brain activity.

            Scale-free dynamics, with a power spectrum following P proportional to f(-beta), are an intrinsic feature of many complex processes in nature. In neural systems, scale-free activity is often neglected in electrophysiological research. Here, we investigate scale-free dynamics in human brain and show that it contains extensive nested frequencies, with the phase of lower frequencies modulating the amplitude of higher frequencies in an upward progression across the frequency spectrum. The functional significance of scale-free brain activity is indicated by task performance modulation and regional variation, with beta being larger in default network and visual cortex and smaller in hippocampus and cerebellum. The precise patterns of nested frequencies in the brain differ from other scale-free dynamics in nature, such as earth seismic waves and stock market fluctuations, suggesting system-specific generative mechanisms. Our findings reveal robust temporal structures and behavioral significance of scale-free brain activity and should motivate future study on its physiological mechanisms and cognitive implications. Copyright 2010 Elsevier Inc. All rights reserved.
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              The resting brain: unconstrained yet reliable.

              Recent years have witnessed an upsurge in the usage of resting-state functional magnetic resonance imaging (fMRI) to examine functional connectivity (fcMRI), both in normal and pathological populations. Despite this increasing popularity, concerns about the psychologically unconstrained nature of the "resting-state" remain. Across studies, the patterns of functional connectivity detected are remarkably consistent. However, the test-retest reliability for measures of resting state fcMRI measures has not been determined. Here, we quantify the test-retest reliability, using resting scans from 26 participants at 3 different time points. Specifically, we assessed intersession (>5 months apart), intrasession ( nonsignificant), 2) correlation valence (positive > negative), and 3) network membership (default mode > task positive network). Short- and long-term measures of the consistency of global connectivity patterns were highly robust. Finally, hierarchical clustering solutions were highly reproducible, both across participants and sessions. Our findings provide a solid foundation for continued examination of resting state fcMRI in typical and atypical populations.
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                Author and article information

                Journal
                Cereb Cortex
                Cereb. Cortex
                cercor
                Cerebral Cortex (New York, NY)
                Oxford University Press
                1047-3211
                1460-2199
                October 2017
                02 September 2016
                01 October 2018
                : 27
                : 10
                : 4719-4732
                Affiliations
                [1 ] Department of Neurology, Washington University School of Medicine , St. Louis, MO 63110, USA
                [2 ] Department of Radiology, Washington University School of Medicine , St. Louis, MO 63110, USA
                [3 ] VISN 17 Center of Excellence for Research on Returning War Veterans, Waco, TX 76711, USA
                [4 ] Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX 75235, USA
                [5 ] Department of Psychological and Brain Sciences, Washington University in St. Louis , St. Louis, MO 63110, USA
                [6 ] Department of Psychiatry, Washington University School of Medicine , St. Louis, MO 63110, USA
                [7 ] Department of Mathematics, Washington University in St. Louis, St. Louis, MO 63130, USA
                [8 ] Institute for Medical Psychology, Christian-Albrechts-Universitat zu Kiel , Kiel, Germany
                [9 ] Department of Neurology, Brain Imaging Center, Goethe-Universitat Frankfurt am Main , Frankfurt, Germany
                [10 ] Department of Neurology, Christian-Albrechts-Universitat zu Kiel , Kiel, Germany
                [11 ] Departmen of Pediatrics, Washington University School of Medicine , St. Louis, MO 63110, USA
                [12 ] Department of Anatomy and Neurobiology, Washington University School of Medicine, St. Louis, MO 63110, USA
                Author notes
                [* ]Address correspondence to T. O. Laumann, Department of Neurology, Washington University School of Medicine, 660 S Euclid Ave, Box 8111, St. Louis, MO 63110, USA. Email: laumannt@ 123456wusm.wustl.edu
                Article
                PMC6248456 PMC6248456 6248456 bhw265
                10.1093/cercor/bhw265
                6248456
                27591147
                fb2c3ff9-6613-4a8d-aa98-1a890ddfe796
                © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com
                History
                : 03 August 2016
                : 01 August 2016
                : 02 August 2016
                Page count
                Pages: 14
                Funding
                Funded by: Intellectual and Developmental Disabilities Research Center 10.13039/100007857
                Award ID: P30 HD062171
                Award ID: U54 HD087011
                Funded by: Mallinckrodt Institute of Radiology Pilot Grant (NUFD)
                Funded by: Child Neurology Foundation Scientific Research Award (NUFD) 10.13039/100006457
                Award ID: NS088590
                Award ID: NSF GRFP DGE1143954
                Award ID: NSF-DMS1300280
                Funded by: Bundesministerium für Bildung und Forschung 10.13039/501100002347
                Award ID: 01EV0703
                Categories
                Original Articles

                resting state,dynamics,BOLD fMRI,functional connectivity,nonstationarity

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