Decoding a Neurofeedback-Modulated Cognitive Arousal State to Investigate Performance Regulation by the Yerkes-Dodson Law

Saman Khazaei, Md Rafiul Amin, Rose T. Faghih

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Enhancing the productivity of humans by regulating arousal during cognitive tasks is a challenging topic in psychology that has a great potential to transform workplaces for increased productivity and educational systems for enhanced performance. In this study, we assess the feasibility of using the Yerkes-Dodson law from psychology to improve performance during a working memory experiment. We employ a Bayesian filtering approach to track cognitive arousal and performance. In particular, by utilizing skin conductance signal recorded during a working memory experiment in the presence of music, we decode a cognitive arousal state. This is done by considering the rate of neural impulse occurrences and their amplitudes as observations for the arousal model. Similarly, we decode a performance state using the number of correct and incorrect responses, and the reaction time as binary and continuous behavioral observations, respectively. We estimate the arousal and performance states within an expectation-maximization framework. Thereafter, we design an arousal-performance model on the basis of the Yerkes-Dodson law and estimate the model parameters via regression analysis. In this experiment musical neurofeedback was used to modulate cognitive arousal. Our investigations indicate that music can be used as a mode of actuation to influence arousal and enhance the cognitive performance during working memory tasks. Our findings can have a significant impact on designing future smart workplaces and online educational systems.

    Original languageEnglish (US)
    Title of host publication43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages6551-6557
    Number of pages7
    ISBN (Electronic)9781728111797
    DOIs
    StatePublished - 2021
    Event43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021 - Virtual, Online, Mexico
    Duration: Nov 1 2021Nov 5 2021

    Publication series

    NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
    ISSN (Print)1557-170X

    Conference

    Conference43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021
    Country/TerritoryMexico
    CityVirtual, Online
    Period11/1/2111/5/21

    ASJC Scopus subject areas

    • Signal Processing
    • Biomedical Engineering
    • Computer Vision and Pattern Recognition
    • Health Informatics

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