Resting-state EEG correlates of motor learning performance in a force-field adaptation task

Özdenizci, Ozan and Yalçın, Mustafa and Erdoğan, Ahmetcan and Patoğlu, Volkan and Grosse-Wentrup, Moritz and Çetin, Müjdat (2016) Resting-state EEG correlates of motor learning performance in a force-field adaptation task. In: 24th Signal Processing and Communication Application Conference (SIU 2016), Zonguldak, Turkey

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Recent BCI-based stroke rehabilitation studies focus on exploiting information obtained from sensorimotor EEG activity. In the present study, to extend this focus beyond sensorimotor rhythms, we investigate associative brain areas that are also related with motor learning skills. Based on experimental data from twenty-one healthy subjects, resting-state EEG recorded prior to the experiment was used to predict motor learning performance during a force-field adaptation task in which subjects performed center-out reaching movements disturbed by an external force-field. A broad resting-state beta-power configuration was found to be predictive of motor adaptation rate. Our findings suggest that resting EEG beta-power is an indicator of subjects' ability to learn new motor skills and adapt to different sensorimotor states. This information can be further exploited in a novel BCI-based stroke rehabilitation approach we propose.
Item Type: Papers in Conference Proceedings
Uncontrolled Keywords: force-field adaptation, brain-computer interfaces, EEG, resting-state, motor learning
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Q Science > QP Physiology
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Electronics
Faculty of Engineering and Natural Sciences
Depositing User: Müjdat Çetin
Date Deposited: 13 Nov 2016 15:41
Last Modified: 26 Apr 2022 09:24

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