Simultaneous decoding of velocity and speed during executed and observed tracking movements: an MEG study

Reinmar Kobler, Masayuki Hirata, Hiroaki Hashimoto, Ryosuke Dowaki, Andreea Ioana Sburlea, Gernot Müller-Putz

Publikation: Beitrag in Buch/Bericht/KonferenzbandBeitrag in einem KonferenzbandForschungBegutachtung

Abstract

Brain signals carry rich information about voluntary upper-limb movements. Accessing this information to control an end-effector (upper-limb, robotic arm, cursor) has been a central topic in brain-computer interface (BCI) research. To date, non-invasive BCIs based on kinematics decoding have focused on extracting partial information (i.e, single or highly correlated kinematic parameters). In this work, we show that low-frequency magnetoencephalographic (MEG) signals simultaneously carry information about multiple kinematic parameters. Using linear models, we decoded cursor velocity and speed during executed and observed tracking movements with moderate (0.2 to 0.4) correlation coefficients (CCs). Comparing the CCs between executed and observed tracking movements, revealed that the MEG signals carried more information (0.1 higher CCs) about velocity and speed during the executed tracking movements. The higher correlations were mainly explained by increased predictive activity in primary sensorimotor areas. We could, therefore, show that non-invasive BCIs have the potential to extract multiple kinematic signals from brain activity in sensorimotor areas.
Originalspracheenglisch
TitelProceedings of the 8th Graz Brain-Computer Interface Conference 2019
UntertitelBridging Science and Application
Redakteure/-innenGernot Müller-Putz, Jonas Ditz, Selina Wriessnegger
ErscheinungsortGraz
Herausgeber (Verlag)Verlag der Technischen Universität Graz
Seiten100-105
Seitenumfang6
ISBN (Print)978-3-85125-682-6
DOIs
PublikationsstatusVeröffentlicht - 18 Sep 2019
Veranstaltung8th Graz Brain-Computer Interface Conference 2019: Bridging Science and Application - Petersgasse 16, Graz, Österreich
Dauer: 16 Sep 201920 Sep 2019
Konferenznummer: 8
https://www.tugraz.at/institutes/ine/graz-bci-conferences/8th-graz-bci-conference-2019/

Konferenz

Konferenz8th Graz Brain-Computer Interface Conference 2019
Kurztitel8th Graz BCI Conference 2017
LandÖsterreich
OrtGraz
Zeitraum16/09/1920/09/19
Internetadresse

Fingerprint

Biomechanical Phenomena
Decoding
Kinematics
Upper Extremity
Brain
Brain-Computer Interfaces
Robotic arms
Brain computer interface
Robotics
End effectors
Linear Models
Research
Sensorimotor Cortex

Schlagwörter

    ASJC Scopus subject areas

    • !!Signal Processing
    • !!Neuroscience (miscellaneous)
    • !!Sensory Systems
    • !!Biomedical Engineering

    Fields of Expertise

    • Human- & Biotechnology

    Treatment code (Nähere Zuordnung)

    • Basic - Fundamental (Grundlagenforschung)

    Dies zitieren

    Kobler, R., Hirata, M., Hashimoto, H., Dowaki, R., Sburlea, A. I., & Müller-Putz, G. (2019). Simultaneous decoding of velocity and speed during executed and observed tracking movements: an MEG study. in G. Müller-Putz, J. Ditz, & S. Wriessnegger (Hrsg.), Proceedings of the 8th Graz Brain-Computer Interface Conference 2019: Bridging Science and Application (S. 100-105). Graz: Verlag der Technischen Universität Graz. https://doi.org/10.3217/978-3-85125-682-6-19

    Simultaneous decoding of velocity and speed during executed and observed tracking movements: an MEG study. / Kobler, Reinmar; Hirata, Masayuki; Hashimoto, Hiroaki; Dowaki, Ryosuke; Sburlea, Andreea Ioana; Müller-Putz, Gernot.

    Proceedings of the 8th Graz Brain-Computer Interface Conference 2019: Bridging Science and Application. Hrsg. / Gernot Müller-Putz; Jonas Ditz; Selina Wriessnegger. Graz : Verlag der Technischen Universität Graz, 2019. S. 100-105.

    Publikation: Beitrag in Buch/Bericht/KonferenzbandBeitrag in einem KonferenzbandForschungBegutachtung

    Kobler, R, Hirata, M, Hashimoto, H, Dowaki, R, Sburlea, AI & Müller-Putz, G 2019, Simultaneous decoding of velocity and speed during executed and observed tracking movements: an MEG study. in G Müller-Putz, J Ditz & S Wriessnegger (Hrsg.), Proceedings of the 8th Graz Brain-Computer Interface Conference 2019: Bridging Science and Application. Verlag der Technischen Universität Graz, Graz, S. 100-105, Graz, Österreich, 16/09/19. https://doi.org/10.3217/978-3-85125-682-6-19
    Kobler R, Hirata M, Hashimoto H, Dowaki R, Sburlea AI, Müller-Putz G. Simultaneous decoding of velocity and speed during executed and observed tracking movements: an MEG study. in Müller-Putz G, Ditz J, Wriessnegger S, Hrsg., Proceedings of the 8th Graz Brain-Computer Interface Conference 2019: Bridging Science and Application. Graz: Verlag der Technischen Universität Graz. 2019. S. 100-105 https://doi.org/10.3217/978-3-85125-682-6-19
    Kobler, Reinmar ; Hirata, Masayuki ; Hashimoto, Hiroaki ; Dowaki, Ryosuke ; Sburlea, Andreea Ioana ; Müller-Putz, Gernot. / Simultaneous decoding of velocity and speed during executed and observed tracking movements: an MEG study. Proceedings of the 8th Graz Brain-Computer Interface Conference 2019: Bridging Science and Application. Hrsg. / Gernot Müller-Putz ; Jonas Ditz ; Selina Wriessnegger. Graz : Verlag der Technischen Universität Graz, 2019. S. 100-105
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    abstract = "Brain signals carry rich information about voluntary upper-limb movements. Accessing this information to control an end-effector (upper-limb, robotic arm, cursor) has been a central topic in brain-computer interface (BCI) research. To date, non-invasive BCIs based on kinematics decoding have focused on extracting partial information (i.e, single or highly correlated kinematic parameters). In this work, we show that low-frequency magnetoencephalographic (MEG) signals simultaneously carry information about multiple kinematic parameters. Using linear models, we decoded cursor velocity and speed during executed and observed tracking movements with moderate (0.2 to 0.4) correlation coefficients (CCs). Comparing the CCs between executed and observed tracking movements, revealed that the MEG signals carried more information (0.1 higher CCs) about velocity and speed during the executed tracking movements. The higher correlations were mainly explained by increased predictive activity in primary sensorimotor areas. We could, therefore, show that non-invasive BCIs have the potential to extract multiple kinematic signals from brain activity in sensorimotor areas.",
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