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      Impaired evoked and resting-state brain oscillations in patients with liver cirrhosis as revealed by magnetoencephalography ☆☆

      research-article
      a , b , * , a , d , b , f , c , b , c , b , d , e
      NeuroImage : Clinical
      Elsevier
      CFF, critical flicker frequency, CON, control, CSI, component similarity index, EEG, electroencephalography, EMG, electromyogram, ERA, event related averages, FUF, fusion frequency, GSI, general similarity index, GW, Gabor wavelet, HE, hepatic encephalopathy, HESA, hepatic encephalopathy scoring algorithm, ICA, independent component analysis, MEG, magnetoencephalography, MELD score, model of end-stage liver disease-score, MSC, magnitude squared coherence, PCA, principal component analysis, SSVEF/SSVEP/SSVER, steady state visual evoked field/potential/response, SW, sine wave, Visual steady state evoked fields, Liver cirrhosis, Impaired neuronal oscillations, Critical flicker and fusion frequency, Resting frequency

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          Abstract

          A number of studies suggest that the clinical manifestation of neurological deficits in hepatic encephalopathy results from pathologically synchronized neuronal oscillations and altered oscillatory coupling. In the present study spontaneous and evoked oscillatory brain activities were analyzed jointly with established behavioral measures of altered visual oscillatory processing. Critical flicker and fusion frequencies (CFF, FUF) were measured in 25 patients diagnosed with liver cirrhosis and 30 healthy controls. Magnetoencephalography (MEG) data were collected at rest and during a visual task employing repetitive stimulation. Resting MEG and evoked fields were analyzed. CFF and FUF were found to be reduced in patients, providing behavioral evidence for deficits in visual oscillatory processing. These alterations were found to be related to resting brain activity in patients, namely that the lower the dominant MEG frequency at rest, the lower the CFF and FUF. An analysis of evoked fields at sensor level indicated that in comparison to normal controls, patients were not able to dynamically adapt to flickering visual stimulation. Evoked activity was also analyzed based on independent components (ICs) derived by independent component analysis. The similarity between the shape of each IC and an artificial sine function representing the stimulation frequency was tested via magnitude squared coherence. In controls, we observed a small number of components that correlated strongly with the sine function and a high number of ICs that did not correlate with the sine function. Interestingly, patient data were characterized by a high number of moderately correlating components. Taken together, these results indicate a fundamental divergence of the cerebral resonance activity in cirrhotic patients.

          Highlights

          • Cirrhotic patients show a fundamental divergence of cerebral resonance activity.

          • Patients show an impaired dynamical adaptation to visual flickering stimulation.

          • The MEG findings were significantly related to neuropsychological testing.

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          Most cited references48

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          Spatiotemporal signal space separation method for rejecting nearby interference in MEG measurements.

          Limitations of traditional magnetoencephalography (MEG) exclude some important patient groups from MEG examinations, such as epilepsy patients with a vagus nerve stimulator, patients with magnetic particles on the head or having magnetic dental materials that cause severe movement-related artefact signals. Conventional interference rejection methods are not able to remove the artefacts originating this close to the MEG sensor array. For example, the reference array method is unable to suppress interference generated by sources closer to the sensors than the reference array, about 20-40 cm. The spatiotemporal signal space separation method proposed in this paper recognizes and removes both external interference and the artefacts produced by these nearby sources, even on the scalp. First, the basic separation into brain-related and external interference signals is accomplished with signal space separation based on sensor geometry and Maxwell's equations only. After this, the artefacts from nearby sources are extracted by a simple statistical analysis in the time domain, and projected out. Practical examples with artificial current dipoles and interference sources as well as data from real patients demonstrate that the method removes the artefacts without altering the field patterns of the brain signals.
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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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              Steady-state visually evoked potentials: focus on essential paradigms and future perspectives.

              After 40 years of investigation, steady-state visually evoked potentials (SSVEPs) have been shown to be useful for many paradigms in cognitive (visual attention, binocular rivalry, working memory, and brain rhythms) and clinical neuroscience (aging, neurodegenerative disorders, schizophrenia, ophthalmic pathologies, migraine, autism, depression, anxiety, stress, and epilepsy). Recently, in engineering, SSVEPs found a novel application for SSVEP-driven brain-computer interface (BCI) systems. Although some SSVEP properties are well documented, many questions are still hotly debated. We provide an overview of recent SSVEP studies in neuroscience (using implanted and scalp EEG, fMRI, or PET), with the perspective of modern theories about the visual pathway. We investigate the steady-state evoked activity, its properties, and the mechanisms behind SSVEP generation. Next, we describe the SSVEP-BCI paradigm and review recently developed SSVEP-based BCI systems. Lastly, we outline future research directions related to basic and applied aspects of SSVEPs. Copyright 2009 Elsevier Ltd. All rights reserved.
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                Author and article information

                Contributors
                Journal
                Neuroimage (Amst)
                Neuroimage (Amst)
                NeuroImage : Clinical
                Elsevier
                2213-1582
                13 June 2013
                13 June 2013
                2013
                : 2
                : 873-882
                Affiliations
                [a ]Biomagnetic Center, Department of Neurology, University Hospital Jena, Erlanger Allee 101, 07747 Jena, Germany
                [b ]CSCC, Center for Sepsis Control and Care, Erlanger 101, 07747 Jena, Germany
                [c ]Department of Neurology, University Hospital Jena, Erlanger Allee 101, 07747 Jena, Germany
                [d ]Faculty VI, Department of Psychology, Neuropsychology Lab, University of Oldenburg, 26111 Oldenburg, Germany
                [e ]Center for Neurosensory Science and Systems, University of Oldenburg, 26111 Oldenburg, Germany
                [f ]Division of Gastroenterology, Hepatology and Infectious Diseases, Department of Internal Medicine II, Erlanger Allee 101, 07747 Jena, Germany
                Author notes
                [* ]Corresponding author at: Biomagnetic Center, Department of Neurology, University Hospital Jena, Erlanger Allee 101, 07747 Jena, Germany. Tel.: + 49 3641 9 325 780; fax: + 49 3641 9 325 772. theresa@ 123456biomag.uni.jena.de
                Article
                S2213-1582(13)00071-5
                10.1016/j.nicl.2013.06.003
                3777687
                24179838
                a8265853-8119-4a12-984e-fde50e451c32
                © 2013 The Authors

                This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-No Derivative Works License, which permits non-commercial use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 29 January 2013
                : 21 May 2013
                : 5 June 2013
                Categories
                Article

                cff, critical flicker frequency,con, control,csi, component similarity index,eeg, electroencephalography,emg, electromyogram,era, event related averages,fuf, fusion frequency,gsi, general similarity index,gw, gabor wavelet,he, hepatic encephalopathy,hesa, hepatic encephalopathy scoring algorithm,ica, independent component analysis,meg, magnetoencephalography,meld score, model of end-stage liver disease-score,msc, magnitude squared coherence,pca, principal component analysis,ssvef/ssvep/ssver, steady state visual evoked field/potential/response,sw, sine wave,visual steady state evoked fields,liver cirrhosis,impaired neuronal oscillations,critical flicker and fusion frequency,resting frequency

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