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      Concealed Around-the-Ear EEG Captures Cognitive Processing in a Visual Simon Task


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          In theory, miniaturized systems such as the around-the-ear electrode arrays (cEEGrids) enable mobile monitoring of the electroencephalogram (EEG) in a variety of real life situations without interfering with the natural setting. However, the research benefit of such cEEGrid recordings critically depends on their validity. To investigate whether visual and motor processing are reflected in the cEEGrid-EEG, a direct comparison of EEG that was concurrently recorded with the cEEGrids and with a high-density cap setup was conducted. Thirteen participants performed a classic Simon task in which letters were presented laterally and a lateralized choice response was executed. N1, P1 and P300 event-related potential (ERP) waveforms were extracted from cEEGrid-EEG: they were found to be strongly correlated with corresponding waveforms extracted from cap-EEG but with lower signal strength and lower signal-to-noise-ratio (SNR). Event-related lateralizations (ERLs) recorded at posterior scalp sites were well reflected in middle cEEGrid pairs. Moreover, the effect size of the Simon correspondence effect on the extracted ERLs was similar between the two systems. However, lateralizations at central cap sites were less well reflected in the cEEGrid-EEG indicating a difficulty in capturing motor response preparation and execution. These results show that well-described visual and cognitive ERPs and ERLs can be measured using the cEEGrids, while motor-related cortical potentials are not well captured. This study further demonstrates the potential and possible limitations of unobtrusive cEEGrid-EEG recordings.

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          ADJUST: An automatic EEG artifact detector based on the joint use of spatial and temporal features.

          Abstract A successful method for removing artifacts from electroencephalogram (EEG) recordings is Independent Component Analysis (ICA), but its implementation remains largely user-dependent. Here, we propose a completely automatic algorithm (ADJUST) that identifies artifacted independent components by combining stereotyped artifact-specific spatial and temporal features. Features were optimized to capture blinks, eye movements, and generic discontinuities on a feature selection dataset. Validation on a totally different EEG dataset shows that (1) ADJUST's classification of independent components largely matches a manual one by experts (agreement on 95.2% of the data variance), and (2) Removal of the artifacted components detected by ADJUST leads to neat reconstruction of visual and auditory event-related potentials from heavily artifacted data. These results demonstrate that ADJUST provides a fast, efficient, and automatic way to use ICA for artifact removal.
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            How about taking a low-cost, small, and wireless EEG for a walk?

            To build a low-cost, small, and wireless electroencephalogram (EEG) system suitable for field recordings, we merged consumer EEG hardware with an EEG electrode cap. Auditory oddball data were obtained while participants walked outdoors on university campus. Single-trial P300 classification with linear discriminant analysis revealed high classification accuracies for both indoor (77%) and outdoor (69%) recording conditions. We conclude that good quality, single-trial EEG data suitable for mobile brain-computer interfaces can be obtained with affordable hardware. Copyright © 2012 Society for Psychophysiological Research.
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              Guidelines for the recording and quantitative analysis of electroencephalographic activity in research contexts.

              Developments in technologic and analytical procedures applied to the study of brain electrical activity have intensified interest in this modality as a means of examining brain function. The impact of these new developments on traditional methods of acquiring and analyzing electroencephalographic activity requires evaluation. Ultimately, the integration of the old with the new must result in an accepted standardized methodology to be used in these investigations. In this paper, basic procedures and recent developments involved in the recording and analysis of brain electrical activity are discussed and recommendations are made, with emphasis on psychophysiological applications of these procedures.

                Author and article information

                Front Hum Neurosci
                Front Hum Neurosci
                Front. Hum. Neurosci.
                Frontiers in Human Neuroscience
                Frontiers Media S.A.
                08 June 2017
                : 11
                : 290
                [1] 1Leibniz Research Centre for Working Environment and Human Factors, TU Dortmund University Dortmund, Germany
                [2] 2Neuropsychology Lab, Department of Psychology, European Medical School, University of Oldenburg Oldenburg, Germany
                [3] 3Cluster of Excellence Hearing4All, University of Oldenburg Oldenburg, Germany
                Author notes

                Edited by: Klaus Gramann, Technische Universität Berlin, Germany

                Reviewed by: Magdalena Ietswaart, University of Stirling, United Kingdom; Yuan-Pin Lin, National Sun Yat-sen University, Taiwan; Yijun Wang, University of California, San Diego, United States

                *Correspondence: Marlene Pacharra pacharra@ 123456ifado.de
                Copyright © 2017 Pacharra, Debener and Wascher.

                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) or licensor 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.

                : 15 February 2017
                : 17 May 2017
                Page count
                Figures: 6, Tables: 0, Equations: 16, References: 33, Pages: 11, Words: 7058
                Funded by: Deutsche Forschungsgemeinschaft 10.13039/501100001659
                Funded by: Leibniz-Gemeinschaft 10.13039/501100001664
                Original Research

                around-the-ear eeg,ceegrid,mobile eeg,simon effect,stimulus-response correspondence
                around-the-ear eeg, ceegrid, mobile eeg, simon effect, stimulus-response correspondence


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