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      Mechanisms for Phase Shifting in Cortical Networks and their Role in Communication through Coherence

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          Abstract

          In the primate visual cortex, the phase of spikes relative to oscillations in the local field potential (LFP) in the gamma frequency range (30–80 Hz) can be shifted by stimulus features such as orientation and thus the phase may carry information about stimulus identity. According to the principle of communication through coherence (CTC), the relative LFP phase between the LFPs in the sending and receiving circuits affects the effectiveness of the transmission. CTC predicts that phase shifting can be used for stimulus selection. We review and investigate phase shifting in models of periodically driven single neurons and compare it with phase shifting in models of cortical networks. In a single neuron, as the driving current is increased, the spike phase varies systematically while the firing rate remains constant. In a network model of reciprocally connected excitatory (E) and inhibitory (I) cells phase shifting occurs in response to both injection of constant depolarizing currents and to brief pulses to I cells. These simple models provide an account for phase-shifting observed experimentally and suggest a mechanism for implementing CTC. We discuss how this hypothesis can be tested experimentally using optogenetic techniques.

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          Most cited references59

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          Interneurons of the neocortical inhibitory system.

          Mammals adapt to a rapidly changing world because of the sophisticated cognitive functions that are supported by the neocortex. The neocortex, which forms almost 80% of the human brain, seems to have arisen from repeated duplication of a stereotypical microcircuit template with subtle specializations for different brain regions and species. The quest to unravel the blueprint of this template started more than a century ago and has revealed an immensely intricate design. The largest obstacle is the daunting variety of inhibitory interneurons that are found in the circuit. This review focuses on the organizing principles that govern the diversity of inhibitory interneurons and their circuits.
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            Dynamics of sparsely connected networks of excitatory and inhibitory spiking neurons.

            N Brunel (2000)
            The dynamics of networks of sparsely connected excitatory and inhibitory integrate-and-fire neurons are studied analytically. The analysis reveals a rich repertoire of states, including synchronous states in which neurons fire regularly; asynchronous states with stationary global activity and very irregular individual cell activity; and states in which the global activity oscillates but individual cells fire irregularly, typically at rates lower than the global oscillation frequency. The network can switch between these states, provided the external frequency, or the balance between excitation and inhibition, is varied. Two types of network oscillations are observed. In the fast oscillatory state, the network frequency is almost fully controlled by the synaptic time scale. In the slow oscillatory state, the network frequency depends mostly on the membrane time constant. Finite size effects in the asynchronous state are also discussed.
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              Modulation of Oscillatory Neuronal Synchronization by Selective Visual Attention

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                Author and article information

                Journal
                Front Hum Neurosci
                Front. Hum. Neurosci.
                Frontiers in Human Neuroscience
                Frontiers Research Foundation
                1662-5161
                02 November 2010
                2010
                : 4
                Affiliations
                [1] 1simpleDonders Institute for Brain, Cognition and Behavior, Radboud University Nijmegen Nijmegen, Netherlands
                [2] 2simplePhysics and Astronomy Department, University of North Carolina Chapel Hill, NC, USA
                [3] 3simpleHoward Hughes Medical Institute, Salk Institute for Biological Studies La Jolla, CA, USA
                [4] 4simpleDivision of Biological Studies, University of California at San Diego La Jolla, CA, USA
                Author notes

                Edited by: Thilo Womelsdorf, Robarts Research Institute London, Canada

                Reviewed by: Markus Siegel, Massachusetts Institute of Technology, USA; Stephanie R. Jones, Harvard Medical School, USA; Ole Paulsen, University of Cambridge, UK

                *Correspondence: Paul H.Tiesinga, Donders Centre for Neuroscience/FNWI, Radboud University Nijmegen, P.O. Box 9010, 6500 GL Nijmegen, Netherlands. e-mail: p.tiesinga@ 123456science.ru.nl
                Article
                10.3389/fnhum.2010.00196
                2987601
                21103013
                f2ce5c5e-4760-4e22-b118-a6a55bbb9104
                Copyright © 2010 Tiesinga and Sejnowski.

                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.

                Page count
                Figures: 6, Tables: 0, Equations: 1, References: 74, Pages: 14, Words: 12647
                Categories
                Neuroscience
                Perspective Article

                Neurosciences
                phase shifting,phase locking,attention,synchrony,gamma oscillations
                Neurosciences
                phase shifting, phase locking, attention, synchrony, gamma oscillations

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