Decoded Neurofeedback Research Articles

A decoded neurofeedback method for MEG/SSVEF

Event Abstract Back to Event A decoded neurofeedback method for MEG/SSVEF Hiroki Ora1, 2 and Kenji Kansaku1, 2* 1 Research Institute of National Rehabilitation Center for Persons with Disabilities, Department of Rehabilitation for Brain Function, Japan 2 The University of Electro-Communications, Brain Science Inspired Life Support Research Center, Japan Decoded neurofeedback method was recently proposed to lead brain activity to a target state (Shibata, et al., 2011). While researchers utilized functional magnetic resonance imaging in the former studies, little is focused on magnetoencephalography (MEG). Real-time magnetoencephalography (rtMEG) is an emerging neurofeedback technology that could potentially benefit multiple areas of basic and clinical neuroscience, and in this study, we used an rtMEG system to perform decoded neurofeedback training for MEG/steady-state visual evoked field (SSVEF). Five able-bodied participants (age 33.2 years old, 5 females) participated in this study. The visual stimuli were displayed on a screen in front of the participant, and consisted of a circular checkerboard patch on the left and a circular checkerboard patch on the right. The checkerboard patches flickered at 5 (left) or 6 (right) Hz. They were asked to attend to the left, right, or middle of the screen in a SSVEF task. The used MEG scanner was a 306-channel Elekta Neuromag system (Elekta Oy, Helsinki, Finland). We constructed a sparse multinomial logistic regression (SMLR) decoder from MEG signals during the SSVEF task in each participant. We then conducted 3-day MEG neurofeedback training. In a trial, a white fixation cross was turned green for 5 second, then a green solid circle, whose radius indicated a score of the SMLR decoder, was presented. Participants were asked to “somehow regulate your brain activity to make the green solid circle bigger while the fixation cross is green.” During the trainings, no flickering visual stimuli were presented. After the trainings, the SSVEF task was used again to evaluate the training effects. Furthermore, we analyzed weights of the SMLR decoders to determine a subset of MEG sensors that contributed to decode the attended orientation. The SMLR decoder was able to classify the MEG signals into 3 attentional directions (left, right or middle) (88.2 %). The participants were able to increase decoder scores through the trainings (p<0.05). In the post-training SSVEF tasks, accuracy for the target orientation was higher than that for the non-target orientation (p<0.05). Analysis of weights of the decoders demonstrated that sensors on the occipital region contributed to decode the attended orientation (p<0.05, Bonferroni corrected). The results suggest that the decoded neurofeedback training was effective for MEG/SSVEF, and the method may enhance robustness of steady-state visual evoked potential (SSVEP)-based Brain-Computer Interface (BCI). Keywords: Magnetic Resonance Imaging, decoded neurofeedback, Magnetoencephalography (MEG), Real-time magnetoencephalography, Steady-state visual evoked field Conference: 2015 International Workshop on Clinical Brain-Machine Interfaces (CBMI2015), Tokyo, Japan, 13 Mar - 15 Mar, 2015. Presentation Type: Poster 1-6 Topic: Clinical Brain-Machine Interfaces Citation: Ora H and Kansaku K (2015). A decoded neurofeedback method for MEG/SSVEF. Conference Abstract: 2015 International Workshop on Clinical Brain-Machine Interfaces (CBMI2015). doi: 10.3389/conf.fnhum.2015.218.00007 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 23 Apr 2015; Published Online: 29 Apr 2015. * Correspondence: Dr. Kenji Kansaku, Research Institute of National Rehabilitation Center for Persons with Disabilities, Department of Rehabilitation for Brain Function, Tokorozawa, Saitama, Japan, kansakuk@dokkyomed.ac.jp Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. 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