Academic Journal
A Comparative Study on the Detection of Covert Attention in Event-Related EEG and MEG Signals to Control a BCI
| العنوان: | A Comparative Study on the Detection of Covert Attention in Event-Related EEG and MEG Signals to Control a BCI |
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| المؤلفون: | Christoph Reichert, Stefan Dürschmid, Hans-Jochen Heinze, Hermann Hinrichs |
| المصدر: | Frontiers in Neuroscience, Vol 11 (2017) |
| بيانات النشر: | Frontiers Media S.A. |
| سنة النشر: | 2017 |
| المجموعة: | Directory of Open Access Journals: DOAJ Articles |
| مصطلحات موضوعية: | multi-modal control, brain-computer interface, spatial filter, CCA, ERP, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571 |
| الوصف: | In brain-computer interface (BCI) applications the detection of neural processing as revealed by event-related potentials (ERPs) is a frequently used approach to regain communication for people unable to interact through any peripheral muscle control. However, the commonly used electroencephalography (EEG) provides signals of low signal-to-noise ratio, making the systems slow and inaccurate. As an alternative noninvasive recording technique, the magnetoencephalography (MEG) could provide more advantageous electrophysiological signals due to a higher number of sensors and the magnetic fields not being influenced by volume conduction. We investigated whether MEG provides higher accuracy in detecting event-related fields (ERFs) compared to detecting ERPs in simultaneously recorded EEG, both evoked by a covert attention task, and whether a combination of the modalities is advantageous. In our approach, a detection algorithm based on spatial filtering is used to identify ERP/ERF components in a data-driven manner. We found that MEG achieves higher decoding accuracy (DA) compared to EEG and that the combination of both further improves the performance significantly. However, MEG data showed poor performance in cross-subject classification, indicating that the algorithm's ability for transfer learning across subjects is better in EEG. Here we show that BCI control by covert attention is feasible with EEG and MEG using a data-driven spatial filter approach with a clear advantage of the MEG regarding DA but with a better transfer learning in EEG. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| تدمد: | 1662-453X |
| Relation: | http://journal.frontiersin.org/article/10.3389/fnins.2017.00575/full; https://doaj.org/toc/1662-453X; https://doaj.org/article/e854f67c4a8a43e293001534b77693f4 |
| DOI: | 10.3389/fnins.2017.00575 |
| الاتاحة: | https://doi.org/10.3389/fnins.2017.00575 https://doaj.org/article/e854f67c4a8a43e293001534b77693f4 |
| رقم الانضمام: | edsbas.80308855 |
| قاعدة البيانات: | BASE |
Full Text Finder | تدمد: | 1662453X |
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| DOI: | 10.3389/fnins.2017.00575 |