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  • Authors: Leon A. Lieblang;
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  • image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Authors: Ina Pichlmayr; Peter Lehmkuhl;
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao https://doi.org/10.1...arrow_drop_down
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    https://doi.org/10.1007/978-3-...
    Book . 1988 . Peer-reviewed
    License: Springer TDM
    Data sources: Crossref
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao https://doi.org/10.1...arrow_drop_down
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      https://doi.org/10.1007/978-3-...
      Book . 1988 . Peer-reviewed
      License: Springer TDM
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  • image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Authors: Preuss, Robert;

    A number of stochastic models and statistical tests are synthesised to develop a general framework for signal analysis and classification. The particular application which provides a focus for this work is the automatic real-time analysis and classification of human electroencephalograms as a clinical aid to diagnosis, treatment and long term monitoring of epileptic patients. Stochastic modelling and estimation procedures are described; these procedures can be employed together with previously recorded data to determine signal classes which are differentiated on the basis of their first and second order moments. Since nearly all analyses of the electroencephalogram study only these moments, and because these moments have been demonstrated to be reliable indicators of the physiological condition, it is expected that the resulting signal classes will be clinically meaningful. It is shown that standard methods of statical hypothesis testing can be used to classify segments of the electroencephalographic record, various approximations are introduced, including a hierarchical test procedure, to develop suboptimal but computationally efficient classification procedures. The use of expert judgement to relate these stochastically differentiated signal classes to the answers to clinically meaningful questions is also discussed; this relationship then permits the system to provide its classification results in a clinically meaningful form.

    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao VTT Research Informa...arrow_drop_down
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
  • Authors: Girijesh Prasad;

    A brain–machine interface (BMI) is a biohybrid system intended as an alternative communication channel for people suffering from severe motor impairments. A BMI can involve either invasively implanted electrodes or non-invasive imaging systems. The focus in this chapter is on non-invasive approaches; EEG-based BMI is the most widely investigated. Event-related de-synchronization/ synchronization (ERD/ERS) of sensorimotor rhythms (SMRs), P300, and steady-state visual evoked potential (SSVEP) are the three main cortical activation patterns used for designing an EEG-based BMI. A BMI involves multiple stages: brain data acquisition, pre-processing, feature extraction, and feature classification, along with a device to communicate or control with or without neurofeedback. Despite extensive research worldwide, there are still several challenges to be overcome in making BMI practical for daily use. One such is to account for non-stationary brainwaves dynamics. Also, some people may initially find it difficult to establish a reliable BMI with sufficient accuracy. BMI research, however, is progressing in two broad areas: replacing neuromuscular pathways and neurorehabilitation.

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    Authors: Mühl, C.; Heylen, Dirk; Nijholt, Anton;

    The brain is involved in the registration, evaluation, and representation of emotional events, and in the subsequent planning and execution of adequate actions. Novel interface technologies – so-called affective brain-computer interfaces (aBCI) - can use this rich neural information, occurring in response to affective stimulation, for the detection of the affective state of the user. This chapter gives an overview of the promises and challenges that arise from the possibility of neurophysiology-based affect detection, with a special focus on electrophysiological signals. After outlining the potential of aBCI relative to other sensing modalities, the reader is introduced to the neurophysiological and neurotechnological background of this interface technology. Potential application scenarios are situated in a general framework of brain-computer interfaces. Finally, the main scientific and technological challenges that have to be solved on the way toward reliable affective brain-computer interfaces are discussed.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ DLR publication serv...arrow_drop_down
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  • Authors: Riitta Hari;

    This chapter introduces magnetoencephalography (MEG), a tool to study brain dynamics in basic and clinical neuroscience. MEG picks up brain signals with millisecond resolution, as does electroencephalography, but without distortion by skull and scalp. The chapter describes current instrumentation based on superconducting quantum interference devices (SQUIDs). It delineates basic characteristics of measured signals: (1) brain rhythms and their reactivity during sensory processing and various tasks and (2) evoked responses elicited by sensory stimuli, and the dependence of these responses on various stimulus characteristics. Signals are described from healthy and diseased brains. The chapter presents studies of the brain basis of cognition and social interaction studied in dual-MEG setups and describes how MEG applications can be broadened by innovative setups, including frequency tagging. Progress in the field is predicted regarding sensor technology, data analysis, and multimodal brain imaging, all of which could strengthen MEG’s role in the study of brain dynamics.

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  • image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Authors: Ina Pichlmayr;
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao https://doi.org/10.1...arrow_drop_down
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    https://doi.org/10.1007/978-3-...
    Book . 1985 . Peer-reviewed
    License: Springer TDM
    Data sources: Crossref
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao https://doi.org/10.1...arrow_drop_down
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      https://doi.org/10.1007/978-3-...
      Book . 1985 . Peer-reviewed
      License: Springer TDM
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  • Authors: George Dassios; Athanassios S. Fokas;
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    Authors: Maria De los Angeles Robinson Agramonte; Carlos Alberto Gonçalves; Dario Siniscalco;
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ https://openresearch...arrow_drop_down
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    https://openresearchlibrary.or...
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    https://doi.org/10.3390/books9...
    Book . 2019 . Peer-reviewed
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  • Authors: Hideki Nakano;
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The following results are related to Neuroinformatics. Are you interested to view more results? Visit OpenAIRE - Explore.
  • Authors: Leon A. Lieblang;
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  • image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Authors: Ina Pichlmayr; Peter Lehmkuhl;
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao https://doi.org/10.1...arrow_drop_down
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    https://doi.org/10.1007/978-3-...
    Book . 1988 . Peer-reviewed
    License: Springer TDM
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao https://doi.org/10.1...arrow_drop_down
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      https://doi.org/10.1007/978-3-...
      Book . 1988 . Peer-reviewed
      License: Springer TDM
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  • image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Authors: Preuss, Robert;

    A number of stochastic models and statistical tests are synthesised to develop a general framework for signal analysis and classification. The particular application which provides a focus for this work is the automatic real-time analysis and classification of human electroencephalograms as a clinical aid to diagnosis, treatment and long term monitoring of epileptic patients. Stochastic modelling and estimation procedures are described; these procedures can be employed together with previously recorded data to determine signal classes which are differentiated on the basis of their first and second order moments. Since nearly all analyses of the electroencephalogram study only these moments, and because these moments have been demonstrated to be reliable indicators of the physiological condition, it is expected that the resulting signal classes will be clinically meaningful. It is shown that standard methods of statical hypothesis testing can be used to classify segments of the electroencephalographic record, various approximations are introduced, including a hierarchical test procedure, to develop suboptimal but computationally efficient classification procedures. The use of expert judgement to relate these stochastically differentiated signal classes to the answers to clinically meaningful questions is also discussed; this relationship then permits the system to provide its classification results in a clinically meaningful form.

    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao VTT Research Informa...arrow_drop_down
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
  • Authors: Girijesh Prasad;

    A brain–machine interface (BMI) is a biohybrid system intended as an alternative communication channel for people suffering from severe motor impairments. A BMI can involve either invasively implanted electrodes or non-invasive imaging systems. The focus in this chapter is on non-invasive approaches; EEG-based BMI is the most widely investigated. Event-related de-synchronization/ synchronization (ERD/ERS) of sensorimotor rhythms (SMRs), P300, and steady-state visual evoked potential (SSVEP) are the three main cortical activation patterns used for designing an EEG-based BMI. A BMI involves multiple stages: brain data acquisition, pre-processing, feature extraction, and feature classification, along with a device to communicate or control with or without neurofeedback. Despite extensive research worldwide, there are still several challenges to be overcome in making BMI practical for daily use. One such is to account for non-stationary brainwaves dynamics. Also, some people may initially find it difficult to establish a reliable BMI with sufficient accuracy. BMI research, however, is progressing in two broad areas: replacing neuromuscular pathways and neurorehabilitation.

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Mühl, C.; Heylen, Dirk; Nijholt, Anton;

    The brain is involved in the registration, evaluation, and representation of emotional events, and in the subsequent planning and execution of adequate actions. Novel interface technologies – so-called affective brain-computer interfaces (aBCI) - can use this rich neural information, occurring in response to affective stimulation, for the detection of the affective state of the user. This chapter gives an overview of the promises and challenges that arise from the possibility of neurophysiology-based affect detection, with a special focus on electrophysiological signals. After outlining the potential of aBCI relative to other sensing modalities, the reader is introduced to the neurophysiological and neurotechnological background of this interface technology. Potential application scenarios are situated in a general framework of brain-computer interfaces. Finally, the main scientific and technological challenges that have to be solved on the way toward reliable affective brain-computer interfaces are discussed.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ DLR publication serv...arrow_drop_down
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  • Authors: Riitta Hari;

    This chapter introduces magnetoencephalography (MEG), a tool to study brain dynamics in basic and clinical neuroscience. MEG picks up brain signals with millisecond resolution, as does electroencephalography, but without distortion by skull and scalp. The chapter describes current instrumentation based on superconducting quantum interference devices (SQUIDs). It delineates basic characteristics of measured signals: (1) brain rhythms and their reactivity during sensory processing and various tasks and (2) evoked responses elicited by sensory stimuli, and the dependence of these responses on various stimulus characteristics. Signals are described from healthy and diseased brains. The chapter presents studies of the brain basis of cognition and social interaction studied in dual-MEG setups and describes how MEG applications can be broadened by innovative setups, including frequency tagging. Progress in the field is predicted regarding sensor technology, data analysis, and multimodal brain imaging, all of which could strengthen MEG’s role in the study of brain dynamics.

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    Authors: Ina Pichlmayr;
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao https://doi.org/10.1...arrow_drop_down
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    https://doi.org/10.1007/978-3-...
    Book . 1985 . Peer-reviewed
    License: Springer TDM
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao https://doi.org/10.1...arrow_drop_down
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      https://doi.org/10.1007/978-3-...
      Book . 1985 . Peer-reviewed
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  • Authors: George Dassios; Athanassios S. Fokas;
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    Authors: Maria De los Angeles Robinson Agramonte; Carlos Alberto Gonçalves; Dario Siniscalco;
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ https://openresearch...arrow_drop_down
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  • Authors: Hideki Nakano;
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