| Autor: |
Daeglau M; Neurocognition and Functional Neurorehabilitation Group, Neuropsychology Lab, Department of Psychology, School of Medicine and Health Sciences, Carl von Ossietzky University Oldenburg, 26111 Oldenburg, Germany., Wallhoff F; Institute for Assistive Technologies, Jade University of Applied Science, 26389 Oldenburg, Germany., Debener S; Neuropsychology Lab, Department of Psychology, School of Medicine and Health Sciences, Carl von Ossietzky University Oldenburg, 26111 Oldenburg, Germany.; Cluster of Excellence Hearing4All, Carl von Ossietzky University Oldenburg, 26111 Oldenburg, Germany.; Research Center Neurosensory Science, Carl von Ossietzky University Oldenburg, 26111 Oldenburg, Germany., Condro IS; Institute for Assistive Technologies, Jade University of Applied Science, 26389 Oldenburg, Germany., Kranczioch C; Neurocognition and Functional Neurorehabilitation Group, Neuropsychology Lab, Department of Psychology, School of Medicine and Health Sciences, Carl von Ossietzky University Oldenburg, 26111 Oldenburg, Germany.; Research Center Neurosensory Science, Carl von Ossietzky University Oldenburg, 26111 Oldenburg, Germany., Zich C; Neurocognition and Functional Neurorehabilitation Group, Neuropsychology Lab, Department of Psychology, School of Medicine and Health Sciences, Carl von Ossietzky University Oldenburg, 26111 Oldenburg, Germany.; Department of Clinical and Movement Neuroscience, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK. |
| Abstrakt: |
Optimizing neurofeedback (NF) and brain-computer interface (BCI) implementations constitutes a challenge across many fields and has so far been addressed by, among others, advancing signal processing methods or predicting the user's control ability from neurophysiological or psychological measures. In comparison, how context factors influence NF/BCI performance is largely unexplored. We here investigate whether a competitive multi-user condition leads to better NF/BCI performance than a single-user condition. We implemented a foot motor imagery (MI) NF with mobile electroencephalography (EEG). Twenty-five healthy, young participants steered a humanoid robot in a single-user condition and in a competitive multi-user race condition using a second humanoid robot and a pseudo competitor. NF was based on 8-30 Hz relative event-related desynchronization (ERD) over sensorimotor areas. There was no significant difference between the ERD during the competitive multi-user condition and the single-user condition but considerable inter-individual differences regarding which condition yielded a stronger ERD. Notably, the stronger condition could be predicted from the participants' MI-induced ERD obtained before the NF blocks. Our findings may contribute to enhance the performance of NF/BCI implementations and highlight the necessity of individualizing context factors. |
