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      Laminar Distribution of Phase-Amplitude Coupling of Spontaneous Current Sources and Sinks

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          Abstract

          Although resting-state functional connectivity is a commonly used neuroimaging paradigm, the underlying mechanisms remain unknown. Thalamo-cortical and cortico-cortical circuits generate oscillations at different frequencies during spontaneous activity. However, it remains unclear how the various rhythms interact and whether their interactions are lamina-specific. Here we investigated intra- and inter-laminar spontaneous phase-amplitude coupling (PAC). We recorded local-field potentials using laminar probes inserted in the forelimb representation of rat area S1. We then computed time-series of frequency-band- and lamina-specific current source density (CSD), and PACs of CSD for all possible pairs of the classical frequency bands in the range of 1–150 Hz. We observed both intra- and inter-laminar spontaneous PAC. Of 18 possible combinations, 12 showed PAC, with the highest measures of interaction obtained for the pairs of the theta/gamma and delta/gamma bands. Intra- and inter-laminar PACs involving layers 2/3–5a were higher than those involving layer 6. Current sinks (sources) in the delta band were associated with increased (decreased) amplitudes of high-frequency signals in the beta to fast gamma bands throughout layers 2/3–6. Spontaneous sinks (sources) of the theta and alpha bands in layers 2/3–4 were on average linked to dipoles completed by sources (sinks) in layer 6, associated with high (low) amplitudes of the beta to fast-gamma bands in the entire cortical column. Our findings show that during spontaneous activity, delta, theta, and alpha oscillations are associated with periodic excitability, which for the theta and alpha bands is lamina-dependent. They further emphasize the differences between the function of layer 6 and that of the superficial layers, and the role of layer 6 in controlling activity in those layers. Our study links theories on the involvement of PAC in resting-state functional connectivity with previous work that revealed lamina-specific anatomical thalamo-cortico-cortical connections.

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          Most cited references35

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          Neuronal circuits of the neocortex.

          We explore the extent to which neocortical circuits generalize, i.e., to what extent can neocortical neurons and the circuits they form be considered as canonical? We find that, as has long been suspected by cortical neuroanatomists, the same basic laminar and tangential organization of the excitatory neurons of the neocortex is evident wherever it has been sought. Similarly, the inhibitory neurons show characteristic morphology and patterns of connections throughout the neocortex. We offer a simple model of cortical processing that is consistent with the major features of cortical circuits: The superficial layer neurons within local patches of cortex, and within areas, cooperate to explore all possible interpretations of different cortical input and cooperatively select an interpretation consistent with their various cortical and subcortical inputs.
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            Measuring phase-amplitude coupling between neuronal oscillations of different frequencies.

            Neuronal oscillations of different frequencies can interact in several ways. There has been particular interest in the modulation of the amplitude of high-frequency oscillations by the phase of low-frequency oscillations, since recent evidence suggests a functional role for this type of cross-frequency coupling (CFC). Phase-amplitude coupling has been reported in continuous electrophysiological signals obtained from the brain at both local and macroscopic levels. In the present work, we present a new measure for assessing phase-amplitude CFC. This measure is defined as an adaptation of the Kullback-Leibler distance-a function that is used to infer the distance between two distributions-and calculates how much an empirical amplitude distribution-like function over phase bins deviates from the uniform distribution. We show that a CFC measure defined this way is well suited for assessing the intensity of phase-amplitude coupling. We also review seven other CFC measures; we show that, by some performance benchmarks, our measure is especially attractive for this task. We also discuss some technical aspects related to the measure, such as the length of the epochs used for these analyses and the utility of surrogate control analyses. Finally, we apply the measure and a related CFC tool to actual hippocampal recordings obtained from freely moving rats and show, for the first time, that the CA3 and CA1 regions present different CFC characteristics.
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              The phase of ongoing EEG oscillations predicts visual perception.

              Oscillations are ubiquitous in electrical recordings of brain activity. While the amplitude of ongoing oscillatory activity is known to correlate with various aspects of perception, the influence of oscillatory phase on perception remains unknown. In particular, since phase varies on a much faster timescale than the more sluggish amplitude fluctuations, phase effects could reveal the fine-grained neural mechanisms underlying perception. We presented brief flashes of light at the individual luminance threshold while EEG was recorded. Although the stimulus on each trial was identical, subjects detected approximately half of the flashes (hits) and entirely missed the other half (misses). Phase distributions across trials were compared between hits and misses. We found that shortly before stimulus onset, each of the two distributions exhibited significant phase concentration, but at different phase angles. This effect was strongest in the theta and alpha frequency bands. In this time-frequency range, oscillatory phase accounted for at least 16% of variability in detection performance and allowed the prediction of performance on the single-trial level. This finding indicates that the visual detection threshold fluctuates over time along with the phase of ongoing EEG activity. The results support the notion that ongoing oscillations shape our perception, possibly by providing a temporal reference frame for neural codes that rely on precise spike timing.
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                Author and article information

                Contributors
                Journal
                Front Neurosci
                Front Neurosci
                Front. Neurosci.
                Frontiers in Neuroscience
                Frontiers Media S.A.
                1662-4548
                1662-453X
                22 December 2015
                2015
                : 9
                : 454
                Affiliations
                McConnell Brain Imaging Centre, Montreal Neurological Institute and Departments of Neurology, Neurosurgery, Physiology and Biomedical Engineering, McGill University Montreal, QC, Canada
                Author notes

                Edited by: Pedro Antonio Valdes-Sosa, Centro de Neurociencias de Cuba, Cuba

                Reviewed by: Guido Nolte, Fraunhofer FIRST, Germany; Stefan Haufe, Columbia University in the City of New York, USA

                *Correspondence: Amir Shmuel amir.shmuel@ 123456mcgill.ca

                This article was submitted to Brain Imaging Methods, a section of the journal Frontiers in Neuroscience

                †Present Address: Roberto C. Sotero, Department of Radiology and Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada

                ‡These authors have contributed equally to this work.

                Article
                10.3389/fnins.2015.00454
                4686797
                26733778
                edab5f56-26cc-4b69-945d-28a6bfdcec09
                Copyright © 2015 Sotero, Bortel, Naaman, Mocanu, Kropf, Villeneuve and Shmuel.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 28 May 2015
                : 16 November 2015
                Page count
                Figures: 10, Tables: 1, Equations: 12, References: 57, Pages: 19, Words: 12535
                Funding
                Funded by: Human Frontier Science Program 10.13039/501100000854
                Award ID: RGY0080/2008
                Funded by: Canadian Institutes of Health Research 10.13039/501100000024
                Award ID: MOP-102599
                Funded by: Natural Sciences and Engineering Research Council of Canada 10.13039/501100000038
                Award ID: RGPIN 375457-2009
                Funded by: Industry Canada 10.13039/501100003102
                Funded by: Faculty of Medicine, McGill University 10.13039/100008644
                Categories
                Neuroscience
                Original Research

                Neurosciences
                spontaneous activity,resting state functional connectivity,local-field potentials (lfp),current-source density (csd),cross-frequency coupling,phase-amplitude coupling,primary somatosensory cortex,cortical layers

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