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Generative Models of Cortical Oscillations: Neurobiological Implications of the Kuramoto Model

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      Abstract

      Understanding the fundamental mechanisms governing fluctuating oscillations in large-scale cortical circuits is a crucial prelude to a proper knowledge of their role in both adaptive and pathological cortical processes. Neuroscience research in this area has much to gain from understanding the Kuramoto model, a mathematical model that speaks to the very nature of coupled oscillating processes, and which has elucidated the core mechanisms of a range of biological and physical phenomena. In this paper, we provide a brief introduction to the Kuramoto model in its original, rather abstract, form and then focus on modifications that increase its neurobiological plausibility by incorporating topological properties of local cortical connectivity. The extended model elicits elaborate spatial patterns of synchronous oscillations that exhibit persistent dynamical instabilities reminiscent of cortical activity. We review how the Kuramoto model may be recast from an ordinary differential equation to a population level description using the nonlinear Fokker–Planck equation. We argue that such formulations are able to provide a mechanistic and unifying explanation of oscillatory phenomena in the human cortex, such as fluctuating beta oscillations, and their relationship to basic computational processes including multistability, criticality, and information capacity.

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      • Record: found
      • Abstract: found
      • Article: not found

      Functional connectivity in the motor cortex of resting human brain using echo-planar MRI.

      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.
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        • Record: found
        • Abstract: not found
        • Article: not found

        Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging.

        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.
          Bookmark
          • Record: found
          • Abstract: found
          • Article: not found

          The brainweb: phase synchronization and large-scale integration.

          The emergence of a unified cognitive moment relies on the coordination of scattered mosaics of functionally specialized brain regions. Here we review the mechanisms of large-scale integration that counterbalance the distributed anatomical and functional organization of brain activity to enable the emergence of coherent behaviour and cognition. Although the mechanisms involved in large-scale integration are still largely unknown, we argue that the most plausible candidate is the formation of dynamic links mediated by synchrony over multiple frequency bands.
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            Author and article information

            Affiliations
            1simpleSchool of Psychiatry, University of New South Wales Sydney, NSW, Australia
            2simpleThe Black Dog Institute, Prince of Wales Hospital Sydney, NSW, Australia
            3simpleQueensland Institute of Medical Research Brisbane, QLD, Australia
            4simpleRoyal Brisbane and Women's Hospital, Brisbane QLD, Australia
            5simpleResearch Institute MOVE, VU University Amsterdam Amsterdam, Netherlands
            Author notes

            Edited by: Kai J. Miller, University of Washington, USA

            Reviewed by: Carson Chow, University of Pittsburgh, USA; National Institutes of Health, USA; Ole Paulsen, University of Cambridge, UK; University of Oxford, UK

            *Correspondence: Michael Breakspear, 300 Herston Rd, Herston, QLD, 4009, Australia.; e-mail: mbreak@ 123456unsw.edu.au
            Journal
            Front Hum Neurosci
            Front. Hum. Neurosci.
            Frontiers in Human Neuroscience
            Frontiers Research Foundation
            1662-5161
            11 November 2010
            2010
            : 4
            2995481
            21151358
            10.3389/fnhum.2010.00190
            Copyright © 2010 Breakspear, Heitmann and Daffertshofer.

            This is an open-access article subject to an exclusive license agreement between the authors and the Frontiers Research Foundation, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are credited.

            Counts
            Figures: 6, Tables: 0, Equations: 27, References: 86, Pages: 14, Words: 10919
            Categories
            Neuroscience
            Review Article

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