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      High-frequency brain activity and muscle artifacts in MEG/EEG: a review and recommendations

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          Abstract

          In recent years high-frequency brain activity in the gamma-frequency band (30–80 Hz) and above has become the focus of a growing body of work in MEG/EEG research. Unfortunately, high-frequency neural activity overlaps entirely with the spectral bandwidth of muscle activity (~20–300 Hz). It is becoming appreciated that artifacts of muscle activity may contaminate a number of non-invasive reports of high-frequency activity. In this review, the spectral, spatial, and temporal characteristics of muscle artifacts are compared with those described (so far) for high-frequency neural activity. In addition, several of the techniques that are being developed to help suppress muscle artifacts in MEG/EEG are reviewed. Suggestions are made for the collection, analysis, and presentation of experimental data with the aim of reducing the number of publications in the future that may contain muscle artifacts.

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          Synaptic mechanisms of synchronized gamma oscillations in inhibitory interneuron networks.

          Gamma frequency oscillations are thought to provide a temporal structure for information processing in the brain. They contribute to cognitive functions, such as memory formation and sensory processing, and are disturbed in some psychiatric disorders. Fast-spiking, parvalbumin-expressing, soma-inhibiting interneurons have a key role in the generation of these oscillations. Experimental analysis in the hippocampus and the neocortex reveals that synapses among these interneurons are highly specialized. Computational analysis further suggests that synaptic specialization turns interneuron networks into robust gamma frequency oscillators.
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            Human EEG responses to 1-100 Hz flicker: resonance phenomena in visual cortex and their potential correlation to cognitive phenomena.

            The individual properties of visual objects, like form or color, are represented in different areas in our visual cortex. In order to perceive one coherent object, its features have to be bound together. This was found to be achieved in cat and monkey brains by temporal correlation of the firing rates of neurons which code the same object. This firing rate is predominantly observed in the gamma frequency range (approx. 30-80 Hz, mainly around 40 Hz). In addition, it has been shown in humans that stimuli which flicker at gamma frequencies are processed faster by our brains than when they flicker at different frequencies. These effects could be due to neural oscillators, which preferably oscillate at certain frequencies, so-called resonance frequencies. It is also known that neurons in visual cortex respond to flickering stimuli at the frequency of the flickering light. If neural oscillators exist with resonance frequencies, they should respond more strongly to stimulation with their resonance frequency. We performed an experiment, where ten human subjects were presented flickering light at frequencies from 1 to 100 Hz in 1-Hz steps. The event-related potentials exhibited steady-state oscillations at all frequencies up to at least 90 Hz. Interestingly, the steady-state potentials exhibited clear resonance phenomena around 10, 20, 40 and 80 Hz. This could be a potential neural basis for gamma oscillations in binding experiments. The pattern of results resembles that of multiunit activity and local field potentials in cat visual cortex.
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              Coupling between neuronal firing, field potentials, and FMRI in human auditory cortex.

              Functional magnetic resonance imaging (fMRI) is an important tool for investigating human brain function, but the relationship between the hemodynamically based fMRI signals in the human brain and the underlying neuronal activity is unclear. We recorded single unit activity and local field potentials in auditory cortex of two neurosurgical patients and compared them with the fMRI signals of 11 healthy subjects during presentation of an identical movie segment. The predicted fMRI signals derived from single units and the measured fMRI signals from auditory cortex showed a highly significant correlation (r = 0.75, P < 10(-47)). Thus, fMRI signals can provide a reliable measure of the firing rate of human cortical neurons.
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                Author and article information

                Journal
                Front Hum Neurosci
                Front Hum Neurosci
                Front. Hum. Neurosci.
                Frontiers in Human Neuroscience
                Frontiers Media S.A.
                1662-5161
                15 April 2013
                2013
                : 7
                : 138
                Affiliations
                CUBRIC, School of Psychology, Cardiff University Cardiff, UK
                Author notes

                Edited by: Markus Butz, University College London, UK

                Reviewed by: Sylvain Baillet, McGill University, Canada; Joerg F. Hipp, University of Tübingen, Germany

                *Correspondence: Suresh D. Muthukumaraswamy, CUBRIC, School of Psychology, Cardiff University, Park Place, Cardiff CF10 3AT, UK. e-mail: sdmuthu@ 123456cardiff.ac.uk
                Article
                10.3389/fnhum.2013.00138
                3625857
                23596409
                e58fac85-e464-4094-b920-2f6a87f7d109
                Copyright © 2013 Muthukumaraswamy.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.

                History
                : 14 February 2013
                : 28 March 2013
                Page count
                Figures: 2, Tables: 0, Equations: 0, References: 132, Pages: 11, Words: 10840
                Categories
                Neuroscience
                Review Article

                Neurosciences
                high-frequency activity,muscle artifacts,gamma-band activity,magnetoencephalography,electroencephalography

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