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      High and low gamma EEG oscillations in central sensorimotor areas are conversely modulated during the human gait cycle.

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          Abstract

          Investigating human brain function is essential to develop models of cortical involvement during walking. Such models could advance the analysis of motor impairments following brain injuries (e.g., stroke) and may lead to novel rehabilitation approaches. In this work, we applied high-density EEG source imaging based on individual anatomy to enable neuroimaging during walking. To minimize the impact of muscular influence on EEG recordings we introduce a novel artifact correction method based on spectral decomposition. High γ oscillations (>60Hz) were previously reported to play an important role in motor control. Here, we investigate high γ amplitudes while focusing on two different aspects of a walking experiment, namely the fact that a person walks and the rhythmicity of walking. We found that high γ amplitudes (60-80Hz), located focally in central sensorimotor areas, were significantly increased during walking compared to standing. Moreover, high γ (70-90Hz) amplitudes in the same areas are modulated in relation to the gait cycle. Since the spectral peaks of high γ amplitude increase and modulation do not match, it is plausible that these two high γ elements represent different frequency-specific network interactions. Interestingly, we found high γ (70-90Hz) amplitudes to be coupled to low γ (24-40Hz) amplitudes, which both are modulated in relation to the gait cycle but conversely to each other. In summary, our work is a further step towards modeling cortical involvement during human upright walking.

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          Author and article information

          Journal
          Neuroimage
          NeuroImage
          1095-9572
          1053-8119
          May 15 2015
          : 112
          Affiliations
          [1 ] Graz University of Technology, Institute for Knowledge Discovery, Laboratory of Brain-Computer Interfaces, Graz, Austria; BioTechMed-Graz, Graz, Austria.
          [2 ] Graz University of Technology, Institute for Knowledge Discovery, Laboratory of Brain-Computer Interfaces, Graz, Austria; BioTechMed-Graz, Graz, Austria; Rehabilitation Clinic Judendorf-Strassengel, Judendorf-Strassengel, Austria.
          [3 ] Graz University of Technology, Institute for Knowledge Discovery, Laboratory of Brain-Computer Interfaces, Graz, Austria; BioTechMed-Graz, Graz, Austria; Department of Biomechanical Engineering, Delft University of Technology, Delft, The Netherlands.
          [4 ] Graz University of Technology, Institute for Knowledge Discovery, Laboratory of Brain-Computer Interfaces, Graz, Austria; BioTechMed-Graz, Graz, Austria. Electronic address: gernot.mueller@tugraz.at.
          Article
          S1053-8119(15)00227-X
          10.1016/j.neuroimage.2015.03.045
          25818687
          264319ac-5162-4593-a0dd-757e6e75dd03
          Copyright © 2015 Elsevier Inc. All rights reserved.
          History

          Electroencephalography (EEG) source imaging,High gamma oscillations,Human gait,Robotic gait training,Sensorimotor system

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