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      The generation and propagation of the human alpha rhythm

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          Significance

          The alpha rhythm dominates the electroencephalogram during quiet wakefulness, but the brain structures which generate it are not known. Using rare intracranial recordings in epilepsy patients, we find that alpha rhythms propagate toward the back of the brain and that alpha waves in cortex (particularly superficial layers) lead alpha oscillations in the thalamus. These findings shed light on how the human alpha rhythm coordinates activity throughout the brain.

          Abstract

          The alpha rhythm is the longest-studied brain oscillation and has been theorized to play a key role in cognition. Still, its physiology is poorly understood. In this study, we used microelectrodes and macroelectrodes in surgical epilepsy patients to measure the intracortical and thalamic generators of the alpha rhythm during quiet wakefulness. We first found that alpha in both visual and somatosensory cortex propagates from higher-order to lower-order areas. In posterior cortex, alpha propagates from higher-order anterosuperior areas toward the occipital pole, whereas alpha in somatosensory cortex propagates from associative regions toward primary cortex. Several analyses suggest that this cortical alpha leads pulvinar alpha, complicating prevailing theories of a thalamic pacemaker. Finally, alpha is dominated by currents and firing in supragranular cortical layers. Together, these results suggest that the alpha rhythm likely reflects short-range supragranular feedback, which propagates from higher- to lower-order cortex and cortex to thalamus. These physiological insights suggest how alpha could mediate feedback throughout the thalamocortical system.

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          Most cited references60

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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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            Different frequencies for different scales of cortical integration: from local gamma to long range alpha/theta synchronization.

            Cortical activity and perception are not driven by the external stimulus alone; rather sensory information has to be integrated with various other internal constraints such as expectations, recent memories, planned actions, etc. The question is how large scale integration over many remote and size-varying processes might be performed by the brain. We have conducted a series of EEG recordings during processes thought to involve neuronal assemblies of varying complexity. While local synchronization during visual processing evolved in the gamma frequency range, synchronization between neighboring temporal and parietal cortex during multimodal semantic processing evolved in a lower, the beta1 (12-18 Hz) frequency range, and long range fronto-parietal interactions during working memory retention and mental imagery evolved in the theta and alpha (4-8 Hz, 8-12 Hz) frequency range. Thus, a relationship seems to exist between the extent of functional integration and the synchronization-frequency. In particular, long-range interactions in the alpha and theta ranges seem specifically involved in processing of internal mental context, i.e. for top-down processing. We propose that large scale integration is performed by synchronization among neurons and neuronal assemblies evolving in different frequency ranges.
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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

                Journal
                Proc Natl Acad Sci U S A
                Proc. Natl. Acad. Sci. U.S.A
                pnas
                pnas
                PNAS
                Proceedings of the National Academy of Sciences of the United States of America
                National Academy of Sciences
                0027-8424
                1091-6490
                19 November 2019
                4 November 2019
                : 116
                : 47
                : 23772-23782
                Affiliations
                [1] aDepartment of Neurology, Massachusetts General Hospital , Harvard Medical School, Boston, MA 02114;
                [2] bInstitute of Cognitive Neuroscience and Psychology, Research Center for Natural Sciences, Hungarian Academy of Sciences , Budapest 1051, Hungary;
                [3] cFaculty of Information Technology and Bionics, Péter Pázmány Catholic University , Budapest 1088, Hungary;
                [4] dLyon Neuroscience Research Center, Université Claude Bernard , 69100 Villeurbanne, France;
                [5] eUnité d’Hypnologie, Service de Neurologie Fonctionnelle et d’Épileptologie, Hôpital Neurologique, Hospices Civils de Lyon , 69003 Lyon, France;
                [6] fEpilepsy Centrum, National Institute of Clinical Neurosciences , 1145 Budapest, Hungary;
                [7] gDepartment of Functional Neurosurgery, National Institute of Clinical Neurosciences , 1145 Budapest, Hungary;
                [8] hDivision is Institut de Neurosciences des Systèmes, Aix-Marseille Université , 13007 Marseille, France;
                [9] iINSERM, Institut de Neurosciences des Systèmes , 13005 Marseille, France;
                [10] jAssistance Publique–Hôpitaux de Marseille, Timone Hospital , 13005 Marseille, France;
                [11] kComprehensive Epilepsy Center, New York University School of Medicine , New York, NY 10016;
                [12] lDepartment of Psychology, University of California , Berkeley, CA 94720;
                [13] mDepartment of Neurosciences and Radiology, University of California San Diego , La Jolla, CA 93093;
                [14] nDepartment of Neurosurgery, Permanente Medical Group , Redwood City, CA 94063;
                [15] oDepartment of Psychiatry, University of California San Diego , La Jolla, CA 92093
                Author notes
                1To whom correspondence may be addressed. Email: mhalgren@ 123456mit.edu .

                Edited by Gyorgy Buzsáki, New York University Neuroscience Institute, New York, NY, and approved October 11, 2019 (received for review July 30, 2019)

                Author contributions: I.U., E.H., and S.S.C. designed research; I.U., H.B., D.F., L.E., M.R., O.D., W.K.D., R.M.-M., E.H., L.W., P.C., G.H., E.E., and S.S.C. performed research; M.H. and A.M. analyzed data; and M.H. and S.S.C. wrote the paper.

                2Present address: Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139.

                3Present address: Department of Neurological Surgery, Albert Einstein College of Medicine, Bronx, NY 10461.

                Author information
                http://orcid.org/0000-0003-2871-741X
                http://orcid.org/0000-0002-6690-2707
                Article
                PMC6876194 PMC6876194 6876194 201913092
                10.1073/pnas.1913092116
                6876194
                31685634
                7959e4db-9737-450c-bab3-3f83d59a8b5b
                Copyright @ 2019

                Published under the PNAS license.

                History
                Page count
                Pages: 11
                Funding
                Funded by: DOD | United States Navy | Office of Naval Research (ONR) 100000006
                Award ID: N00014-13-1-0672
                Award Recipient : Milan Halgren Award Recipient : Rachel Mak-McCully Award Recipient : Eric Halgren Award Recipient : Gary Heit Award Recipient : Emad Eskandar Award Recipient : Arnold J. Mandell Award Recipient : Sydney Cash
                Funded by: HHS | National Institutes of Health (NIH) 100000002
                Award ID: R01-MH-099645
                Award ID: R01-EB-009282
                Award ID: R01-NS-062092
                Award ID: K24-NS-088568
                Award Recipient : Milan Halgren Award Recipient : Orrin Devinsky Award Recipient : Werner K. Doyle Award Recipient : Rachel Mak-McCully Award Recipient : Eric Halgren Award Recipient : Gary Heit Award Recipient : Emad Eskandar Award Recipient : Arnold J. Mandell Award Recipient : Sydney Cash
                Funded by: Hungarian National Brain Research Program
                Award ID: KTIA_13_NAP-A-IV/1- 4
                Award ID: 6
                Award ID: EU FP7 600925
                Award Recipient : István Ulbert Award Recipient : Daniel Fabo Award Recipient : Lorand Eross Award Recipient : Lucia Wittner
                Funded by: Hungarian Government
                Award ID: KTIA-NAP 13-1- 2013-0001
                Award ID: OTKA PD101754
                Award ID: OTKA K119443
                Award Recipient : István Ulbert Award Recipient : Daniel Fabo Award Recipient : Lorand Eross Award Recipient : Lucia Wittner
                Categories
                Biological Sciences
                Neuroscience

                alpha,laminar,thalamocortical,oscillations,intracranial EEG
                alpha, laminar, thalamocortical, oscillations, intracranial EEG

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