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      Movement-Modulation of Local Power and Phase Amplitude Coupling in Bilateral Globus Pallidus Interna in Parkinson Disease

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          Abstract

          There is converging evidence that bilateral basal ganglia motor networks jointly support normal movement behaviors including unilateral movements. The extent and manner in which these networks interact during lateralized movement remains unclear. In this study, simultaneously recorded bilateral Globus Pallidus interna (GPi) local field potentials (LFP) were examined from 19 subjects with idiopathic Parkinson disease (PD), while undergoing awake deep brain stimulation (DBS) implantation. Recordings were carried out during two behavioral states; rest and cued left hand movement (finger tapping). The state-dependent effects on α- β oscillatory power and β phase-encoded phase amplitude coupling (PAC), including symmetrical and assymetrical changes between hemispheres, were identified. Unilateral hand movement resulted in symmetrical oscillatory power suppression within bilateral GPi at α (8–12 Hz) and high β (21–35 Hz) and increase in power of high frequency oscillations (HFO, 200–300 Hz) frequency bands. Asymmetrical attenuation was also observed at both low β (13–20 Hz) and low γ (40–80 Hz) bands within the contralateral GPi ( P = 0.009). In addition, unilateral movement effects on PAC were confined to the contralateral GPi with attenuation of both low β-low γ and β-HFO PAC ( P < 0.05). Further analysis showed that the lateralized attenuation of low β and low γ power did not correlate with low β-low γ PAC changes. The overall coherence between bilateral GPi was not significantly altered with unilateral movement, however the preferred phase difference in the high β range increased from 0.23 (±1.31) radians during rest to 1.99 (±0.78) radians during movement execution. Together, the present results suggest that unilateral motor control involves bilateral basal ganglia networks with movement features differentially encoded by distinct frequency bands. The lateralization of low β and low γ attenuation with movement suggests that these frequency bands are specific to the motor act whereas symmetrical expression of α, high β, and HFO oscillations best correspond to motor state. The restriction of movement-related PAC modulation to the contralateral GPi indicates that cross-frequency interactions appear to be associated with lateralized movements. Despite no significant movement-related changes in the interhemispheric coherence, the increase in phase difference suggests that the communication between bilateral GPi is altered with unilateral movement.

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          Identifying true brain interaction from EEG data using the imaginary part of coherency.

          The main obstacle in interpreting EEG/MEG data in terms of brain connectivity is the fact that because of volume conduction, the activity of a single brain source can be observed in many channels. Here, we present an approach which is insensitive to false connectivity arising from volume conduction. We show that the (complex) coherency of non-interacting sources is necessarily real and, hence, the imaginary part of coherency provides an excellent candidate to study brain interactions. Although the usual magnitude and phase of coherency contain the same information as the real and imaginary parts, we argue that the Cartesian representation is far superior for studying brain interactions. The method is demonstrated for EEG measurements of voluntary finger movement. We found: (a) from 5 s before to movement onset a relatively weak interaction around 20 Hz between left and right motor areas where the contralateral side leads the ipsilateral side; and (b) approximately 2-4 s after movement, a stronger interaction also at 20 Hz in the opposite direction. It is possible to reliably detect brain interaction during movement from EEG data. The method allows unambiguous detection of brain interaction from rhythmic EEG/MEG data.
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            Large-scale recording of neuronal ensembles.

            How does the brain orchestrate perceptions, thoughts and actions from the spiking activity of its neurons? Early single-neuron recording research treated spike pattern variability as noise that needed to be averaged out to reveal the brain's representation of invariant input. Another view is that variability of spikes is centrally coordinated and that this brain-generated ensemble pattern in cortical structures is itself a potential source of cognition. Large-scale recordings from neuronal ensembles now offer the opportunity to test these competing theoretical frameworks. Currently, wire and micro-machined silicon electrode arrays can record from large numbers of neurons and monitor local neural circuits at work. Achieving the full potential of massively parallel neuronal recordings, however, will require further development of the neuron-electrode interface, automated and efficient spike-sorting algorithms for effective isolation and identification of single neurons, and new mathematical insights for the analysis of network properties.
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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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                Author and article information

                Contributors
                Journal
                Front Hum Neurosci
                Front Hum Neurosci
                Front. Hum. Neurosci.
                Frontiers in Human Neuroscience
                Frontiers Media S.A.
                1662-5161
                09 July 2018
                2018
                : 12
                : 270
                Affiliations
                [1] 1Department of Neurosurgery, University of California , Los Angeles, Los Angeles, CA, United States
                [2] 2Institute for Digital Research and Education, University of California , Los Angeles, Los Angeles, CA, United States
                [3] 3Neuroscience Interdepartmental Program, University of California , Los Angeles, Los Angeles, CA, United States
                [4] 4Brain Research Institute, University of California , Los Angeles, Los Angeles, CA, United States
                Author notes

                Edited by: Peter Sörös, University of Oldenburg, Germany

                Reviewed by: Wolf-Julian Neumann, Charité Universitätsmedizin Berlin, Germany; Bettina Pollok, Heinrich Heine Universität Düsseldorf, Germany

                *Correspondence: Mahsa Malekmohammadi mmalekmohammadi@ 123456mednet.ucla.edu
                Article
                10.3389/fnhum.2018.00270
                6046436
                30038563
                7fb822d1-0abb-49eb-beea-43fde3e16ab0
                Copyright © 2018 AuYong, Malekmohammadi, Ricks-Oddie and Pouratian.

                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) and the copyright owner(s) 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
                : 20 February 2018
                : 11 June 2018
                Page count
                Figures: 3, Tables: 1, Equations: 0, References: 96, Pages: 13, Words: 9426
                Funding
                Funded by: National Institutes of Health 10.13039/100000002
                Award ID: K23 EB014326, R01 NS097782, R25 NS079198
                Funded by: American Parkinson Disease Association 10.13039/100006309
                Categories
                Neuroscience
                Original Research

                Neurosciences
                parkinson disease,β oscillations,phase amplitude coupling,interhemispheric coordination,globus pallidus interna

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