These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Search MEDLINE/PubMed

  • Title: Motor imagery and action observation: modulation of sensorimotor brain rhythms during mental control of a brain-computer interface.
    Author: Neuper C, Scherer R, Wriessnegger S, Pfurtscheller G.
    Journal: Clin Neurophysiol; 2009 Feb; 120(2):239-47. PubMed ID: 19121977.
    Abstract:
    OBJECTIVE: This study investigates the impact of a continuously presented visual feedback in the form of a grasping hand on the modulation of sensorimotor EEG rhythms during online control of a brain-computer interface (BCI). METHODS: Two groups of participants were trained to use left or right hand motor imagery to control a specific output signal on a computer monitor: the experimental group controlled a moving hand performing an object-related grasp ('realistic feedback'), whereas the control group controlled a moving bar ('abstract feedback'). Continuous feedback was realized by using the outcome of a real-time classifier which was based on EEG signals recorded from left and right central sites. RESULTS: The classification results show no difference between the two feedback groups. For both groups, ERD/ERS analysis revealed a significant larger ERD during feedback presentation compared to an initial motor imagery screening session without feedback. Increased ERD during online BCI control was particularly found for the lower alpha (8-10 Hz) and for the beta bands (16-20, 20-24 Hz). CONCLUSIONS: The present study demonstrates that visual BCI feedback clearly modulates sensorimotor EEG rhythms. When the feedback provides equivalent information on both the continuous and final outcomes of mental actions, the presentation form (abstract versus realistic) does not influence the performance in a BCI, at least in initial training sessions. SIGNIFICANCE: The present results are of practical interest for classifier development and BCI use in the field of motor restoration.
    [Abstract] [Full Text] [Related] [New Search]