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

doi:10.3217/978-3-85125-682-6-19

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

Institute of Neural Engineering (7090)

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

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.

Original language	English
Title of host publication	Proceedings of the 8th Graz Brain-Computer Interface Conference 2019
Subtitle of host publication	Bridging Science and Application
Editors	Gernot Müller-Putz, Jonas Ditz, Selina Wriessnegger
Place of Publication	Graz
Publisher	Verlag der Technischen Universität Graz
Pages	100-105
Number of pages	6
ISBN (Print)	978-3-85125-682-6
DOIs	https://doi.org/10.3217/978-3-85125-682-6-19
Publication status	Published - 18 Sept 2019
Event	8th Graz Brain-Computer Interface Conference 2019: Bridging Science and Application - Petersgasse 16, Graz, Austria Duration: 16 Sept 2019 → 20 Sept 2019 Conference number: 8 https://www.tugraz.at/institutes/ine/graz-bci-conferences/8th-graz-bci-conference-2019/

Conference

Conference	8th Graz Brain-Computer Interface Conference 2019
Abbreviated title	GBCIC 2019
Country/Territory	Austria
City	Graz
Period	16/09/19 → 20/09/19
Internet address	https://www.tugraz.at/institutes/ine/graz-bci-conferences/8th-graz-bci-conference-2019/

Keywords

magnetoencephalography
kinematics
velocity
speed
brain-computer interface
motor cortex
continuous movement
parietal cortex

ASJC Scopus subject areas

Signal Processing
Neuroscience (miscellaneous)
Sensory Systems
Biomedical Engineering

Fields of Expertise

Human- & Biotechnology

Treatment code (Nähere Zuordnung)

Basic - Fundamental (Grundlagenforschung)

Access to Document

10.3217/978-3-85125-682-6-19Licence: CC BY-ND 4.0

EU - Feel Your Reach - Non-invasive decoding of cortical patterns induced by goal directed movement intentions and artificial sensory feedback in humans
Müller-Putz, G.
1/05/16 → 31/07/21
Project: Research project

Simultaneous decoding of velocity and speed during executed and observed tracking movements: an MEG study
Reinmar Kobler (Speaker)
19 Sept 2019
Activity: Talk or presentation › Talk at conference or symposium › Science to science

Cite this

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 (Eds.), Proceedings of the 8th Graz Brain-Computer Interface Conference 2019: Bridging Science and Application (pp. 100-105). 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 et al.
Proceedings of the 8th Graz Brain-Computer Interface Conference 2019: Bridging Science and Application. ed. / Gernot Müller-Putz; Jonas Ditz; Selina Wriessnegger. Graz: Verlag der Technischen Universität Graz, 2019. p. 100-105.

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

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 (eds), Proceedings of the 8th Graz Brain-Computer Interface Conference 2019: Bridging Science and Application. Verlag der Technischen Universität Graz, Graz, pp. 100-105, 8th Graz Brain-Computer Interface Conference 2019, Graz, Austria, 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, editors, Proceedings of the 8th Graz Brain-Computer Interface Conference 2019: Bridging Science and Application. Graz: Verlag der Technischen Universität Graz. 2019. p. 100-105 doi: 10.3217/978-3-85125-682-6-19

Kobler, Reinmar ; Hirata, Masayuki ; Hashimoto, Hiroaki et al. / 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. editor / Gernot Müller-Putz ; Jonas Ditz ; Selina Wriessnegger. Graz : Verlag der Technischen Universität Graz, 2019. pp. 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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AB - 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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ER -

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

Abstract

Conference

Keywords

ASJC Scopus subject areas

Fields of Expertise

Treatment code (Nähere Zuordnung)

Access to Document

Fingerprint

Projects

EU - Feel Your Reach - Non-invasive decoding of cortical patterns induced by goal directed movement intentions and artificial sensory feedback in humans

Activities

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

Cite this