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      A mechanism for inter-areal coherence through communication based on connectivity and oscillatory power

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          Summary

          Inter-areal coherence between field potentials is a widespread phenomenon in cortex. Coherence has been hypothesized to reflect phase-synchronization between oscillators and flexibly gate communication according to behavioral and cognitive demands. We reveal an alternative mechanism where coherence is not the cause but the consequence of communication and naturally emerges because spiking activity in a sending area causes post-synaptic potentials both in the same and in other areas. Consequently, coherence depends in a lawful manner on power and phase-locking in the sender and connectivity. Changes in oscillatory power explained prominent changes in fronto-parietal and LGN-V1 coherence across behavioral conditions. Optogenetic experiments and excitatory-inhibitory network simulations identified afferent synaptic inputs rather than spiking entrainment as the principal determinant of coherence. These findings suggest that unique spectral profiles of different brain areas automatically give rise to large-scale coherence patterns that follow anatomical connectivity and continuously reconfigure as a function of behavior and cognition.

          Highlights

          • Synaptic projections from a sending to a receiving area explain long-range coherence

          • Inter-areal coherence can be predicted by power and connectivity

          • Power explains major changes in long-range coherence across behavioral states

          • Coherence emerges without spiking entrainment due to afferent synaptic inputs

          Abstract

          Schneider et al. establish a mechanism for inter-areal coherence between field potentials, where it is the result and not the cause of communication. Consequently, coherence depends in a lawful manner on connectivity and power and does not require spiking entrainment. This mechanism explains behavior-related changes in fronto-parietal and LGN-V1 coherence.

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          Most cited references108

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          FieldTrip: Open Source Software for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data

          This paper describes FieldTrip, an open source software package that we developed for the analysis of MEG, EEG, and other electrophysiological data. The software is implemented as a MATLAB toolbox and includes a complete set of consistent and user-friendly high-level functions that allow experimental neuroscientists to analyze experimental data. It includes algorithms for simple and advanced analysis, such as time-frequency analysis using multitapers, source reconstruction using dipoles, distributed sources and beamformers, connectivity analysis, and nonparametric statistical permutation tests at the channel and source level. The implementation as toolbox allows the user to perform elaborate and structured analyses of large data sets using the MATLAB command line and batch scripting. Furthermore, users and developers can easily extend the functionality and implement new algorithms. The modular design facilitates the reuse in other software packages.
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            Dynamic predictions: oscillations and synchrony in top-down processing.

            Classical theories of sensory processing view the brain as a passive, stimulus-driven device. By contrast, more recent approaches emphasize the constructive nature of perception, viewing it as an active and highly selective process. Indeed, there is ample evidence that the processing of stimuli is controlled by top-down influences that strongly shape the intrinsic dynamics of thalamocortical networks and constantly create predictions about forthcoming sensory events. We discuss recent experiments indicating that such predictions might be embodied in the temporal structure of both stimulus-evoked and ongoing activity, and that synchronous oscillations are particularly important in this process. Coherence among subthreshold membrane potential fluctuations could be exploited to express selective functional relationships during states of expectancy or attention, and these dynamic patterns could allow the grouping and selection of distributed neuronal responses for further processing.
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              The origin of extracellular fields and currents--EEG, ECoG, LFP and spikes.

              Neuronal activity in the brain gives rise to transmembrane currents that can be measured in the extracellular medium. Although the major contributor of the extracellular signal is the synaptic transmembrane current, other sources--including Na(+) and Ca(2+) spikes, ionic fluxes through voltage- and ligand-gated channels, and intrinsic membrane oscillations--can substantially shape the extracellular field. High-density recordings of field activity in animals and subdural grid recordings in humans, combined with recently developed data processing tools and computational modelling, can provide insight into the cooperative behaviour of neurons, their average synaptic input and their spiking output, and can increase our understanding of how these processes contribute to the extracellular signal.
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                Author and article information

                Contributors
                Journal
                Neuron
                Neuron
                Neuron
                Cell Press
                0896-6273
                1097-4199
                15 December 2021
                15 December 2021
                : 109
                : 24
                : 4050-4067.e12
                Affiliations
                [1 ]Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt am Main, Germany
                [2 ]German Primate Center, 37077 Göttingen, Germany
                [3 ]Faculty of Biology and Psychology, University of Goettingen, 37073 Goettingen, Germany
                [4 ]Donders Centre for Neuroscience, Department of Neuroinformatics, Radboud University Nijmegen, 6525 Nijmegen, the Netherlands
                Author notes
                []Corresponding author marius.schneider@ 123456esi-frankfurt.de
                [∗∗ ]Corresponding author martin.vinck@ 123456esi-frankfurt.de
                [5]

                Lead contact

                Article
                S0896-6273(21)00710-8
                10.1016/j.neuron.2021.09.037
                8691951
                34637706
                ad92a0d1-d0c2-47c5-978a-67326c2d738b
                © 2021 The Author(s)

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 9 September 2020
                : 14 July 2021
                : 17 September 2021
                Categories
                Article

                Neurosciences
                coherence,phase locking,gamma,beta,v1,lgn,7b,f5,mouse,macaque
                Neurosciences
                coherence, phase locking, gamma, beta, v1, lgn, 7b, f5, mouse, macaque

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