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Brain Responses to Errors During 3D Motion in a Hapto-Visual VR

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Haptics: Perception, Devices, Control, and Applications (EuroHaptics 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9775))

Abstract

We investigated brain potentials recorded by electroencephalography (EEG) signals in response to unpredictable haptic/kinesthetic disturbances to a continuously moving object in a hapto-visual 3D virtual world that highly resembles reality. Participants moved a virtual object from an initial position to a target position in the virtual environment. A large cylinder obscured part of the motion between the origin and the target. The position of the emerging object under the cylinder is disturbed, and hence unexpected, for part of the scenarios. This disturbance is perceived as an error. We examined the EEG signals locked to the error. Our results show a consistent disturbance-locked potential with an early negative peak followed by a positive peak. Peak-to-peak amplitude increased with the disturbance magnitude. Source estimation at the time of the negative and positive peaks revealed a strong activity in the vicinity of Brodmann area (BA) 7, known to be involved in hapto-visual integration and in the neural computation of dynamic motor errors. These results demonstrate the presence of haptic-disturbance-related brain activity under conditions of continuous motion. Results further suggest a feedback signal for error detection and correction in EEG-based Brain-Computer Interfaces (BCI) in applications such as telesurgery, manipulation of remote objects and rehabilitation.

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Acknowledgments

We would like to thank the laboratory engineer Tami Gelfeld for helping in the design and implementation of the experimental set-up.

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Correspondence to Boris Yazmir .

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Yazmir, B., Reiner, M., Pratt, H., Zacksenhouse, M. (2016). Brain Responses to Errors During 3D Motion in a Hapto-Visual VR. In: Bello, F., Kajimoto, H., Visell, Y. (eds) Haptics: Perception, Devices, Control, and Applications. EuroHaptics 2016. Lecture Notes in Computer Science(), vol 9775. Springer, Cham. https://doi.org/10.1007/978-3-319-42324-1_12

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  • DOI: https://doi.org/10.1007/978-3-319-42324-1_12

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