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Affective Aspects of Perceived Loss of Control and Potential Implications for Brain-Computer Interfaces

Frontiers in human neuroscience, 2017-07, Vol.11, p.370-370 [Peer Reviewed Journal]

COPYRIGHT 2017 Frontiers Research Foundation ;2017. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;Copyright © 2017 Grissmann, Zander, Faller, Brönstrup, Kelava, Gramann and Gerjets. 2017 Grissmann, Zander, Faller, Brönstrup, Kelava, Gramann and Gerjets ;ISSN: 1662-5161 ;EISSN: 1662-5161 ;DOI: 10.3389/fnhum.2017.00370 ;PMID: 28769776

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  • Title:
    Affective Aspects of Perceived Loss of Control and Potential Implications for Brain-Computer Interfaces
  • Author: Grissmann, Sebastian ; Zander, Thorsten O ; Faller, Josef ; Brönstrup, Jonas ; Kelava, Augustin ; Gramann, Klaus ; Gerjets, Peter
  • Subjects: Algorithms ; Brain research ; brain-computer interface (BCI) ; Classification ; EEG ; Electroencephalography ; electroencephalography (EEG) ; Emotional behavior ; Fourier transforms ; frontal alpha asymmetry (FAA) ; independent component analysis (ICA) ; Interfaces ; International conferences ; Localization ; loss of control (LOC) ; Mental task performance ; Neuroscience
  • Is Part Of: Frontiers in human neuroscience, 2017-07, Vol.11, p.370-370
  • Description: Most brain-computer interfaces (BCIs) focus on detecting single aspects of user states (e.g., motor imagery) in the electroencephalogram (EEG) in order to use these aspects as control input for external systems. This communication can be effective, but unaccounted mental processes can interfere with signals used for classification and thereby introduce changes in the signal properties which could potentially impede BCI classification performance. To improve BCI performance, we propose deploying an approach that potentially allows to describe different mental states that could influence BCI performance. To test this approach, we analyzed neural signatures of potential affective states in data collected in a paradigm where the complex user state of perceived loss of control (LOC) was induced. In this article, source localization methods were used to identify brain dynamics with source located outside but affecting the signal of interest originating from the primary motor areas, pointing to interfering processes in the brain during natural human-machine interaction. In particular, we found affective correlates which were related to perceived LOC. We conclude that additional context information about the ongoing user state might help to improve the applicability of BCIs to real-world scenarios.
  • Publisher: Switzerland: Frontiers Research Foundation
  • Language: English
  • Identifier: ISSN: 1662-5161
    EISSN: 1662-5161
    DOI: 10.3389/fnhum.2017.00370
    PMID: 28769776
  • Source: Open Access: PubMed Central
    Geneva Foundation Free Medical Journals at publisher websites
    AUTh Library subscriptions: ProQuest Central
    Directory of Open Access Journals
    ROAD: Directory of Open Access Scholarly Resources
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