02265nas a2200241   4500008004100000022001400041245007900055210006900134260001200203300001400215490000700229520157600236653001601812653000801828653001201836653001401848653002401862100002601886700001801912700002401930700002101954856004801975       2000                        eng d  a0896-026700aMu and beta rhythm topographies during motor imagery and actual movements.0 aMu and beta rhythm topographies during motor imagery and actual   c03/2000  a177–1860 v123 aPeople can learn to control the 8-12 Hz mu rhythm and/or the 18-25 Hz beta rhythm in the EEG recorded over sensorimotor cortex and use it to control a cursor on a video screen. Subjects often report using motor imagery to control cursor movement, particularly early in training. We compared in untrained subjects the EEG topographies associated with actual hand movement to those associated with imagined hand movement. Sixty-four EEG channels were recorded while each of 33 adults moved left- or right-hand or imagined doing so. Frequency-specific differences between movement or imagery and rest, and between right- and left-hand movement or imagery, were evaluated by scalp topographies of voltage and r spectra, and principal component analysis. Both movement and imagery were associated with mu and beta rhythm desynchronization. The mu topographies showed bilateral foci of desynchronization over sensorimotor cortices, while the beta topographies showed peak desynchronization over the vertex. Both mu and beta rhythm left/right differences showed bilateral central foci that were stronger on the right side. The independence of mu and beta rhythms was demonstrated by differences for movement and imagery for the subjects as a group and by principal components analysis. The results indicated that the effects of imagery were not simply an attenuated version of the effects of movement. They supply evidence that motor imagery could play an important role in EEG-based communication, and suggest that mu and beta rhythms might provide independent control signals.10abeta rhythm10aEEG10aimagery10amu rhythm10asensorimotor cortex1 aMcFarland, Dennis, J.1 aMiner, L., A.1 aVaughan, Theresa, M1 aWolpaw, Jonathan  uhttp://www.ncbi.nlm.nih.gov/pubmed/1079168102346nas a2200181   4500008004100000022001400041245008500055210006900140260001200209300001600221490000700237520178000244653002802024100001802052700002602070700002102096856004702117       1998                        eng d  a0003-999300aAnswering questions with an electroencephalogram-based brain-computer interface.0 aAnswering questions with an electroencephalogrambased braincompu  c09/1998  a1029–10330 v793 aOBJECTIVE:
To demonstrate that humans can learn to control selected electroencephalographic components and use that control to answer simple questions.
METHODS:
Four adults (one with amyotrophic lateral sclerosis) learned to use electroencephalogram (EEG) mu rhythm (8 to 12Hz) or beta rhythm (18 to 25Hz) activity over sensorimotor cortex to control vertical cursor movement to targets at the top or bottom edge of a video screen. In subsequent sessions, the targets were replaced with the words YES and NO, and individuals used the cursor to answer spoken YES/NO questions from single- or multiple-topic question sets. They confirmed their answers through the response verification (RV) procedure, in which the word positions were switched and the question was answered again.
RESULTS:
For 5 consecutive sessions after initial question training, individuals were asked an average of 4.0 to 4.6 questions per minute; 64% to 87% of their answers were confirmed by the RV procedure and 93% to 99% of these answers were correct. Performances for single- and multiple-topic question sets did not differ significantly.
CONCLUSIONS:
The results indicate that (1) EEG-based cursor control can be used to answer simple questions with a high degree of accuracy, (2) attention to auditory queries and formulation of answers does not interfere with EEG-based cursor control, (3) question complexity (at least as represented by single versus multiple-topic question sets) does not noticeably affect performance, and (4) the RV procedure improves accuracy as expected. Several options for increasing the speed of communication appear promising. An EEG-based brain-computer interface could provide a new communication and control modality for people with severe motor disabilities.10aUser-Computer Interface1 aMiner, L., A.1 aMcFarland, Dennis, J.1 aWolpaw, Jonathan  uhttp://www.ncbi.nlm.nih.gov/pubmed/974967802088nas a2200265   4500008004100000022001400041245006600055210006300121260001200184300001400196490000800210520131500218653003101533653001701564653002701581653002101608653001401629653001901643653002401662100002401686700001801710700002601728700002101754856004701775       1998                        eng d  a0013-469400aEEG-based communication: analysis of concurrent EMG activity.0 aEEGbased communication analysis of concurrent EMG activity  c12/1998  a428–4330 v1073 aOBJECTIVE:
Recent studies indicate that people can learn to control the amplitude of mu or beta rhythms in the EEG recorded from the scalp over sensorimotor cortex and can use that control to move a cursor to targets on the computer screen. While subjects do not move during performance, it is possible that inapparent or unconscious muscle contractions contribute to the changes in the mu and beta rhythm activity responsible for cursor movement. We evaluated this possibility.
METHODS:
EMG was recorded from 10 distal limb muscle groups while five trained subjects used mu or beta rhythms to move a cursor to targets at the bottom or top edge of a computer screen.
RESULTS:
EMG activity was very low during performance, averaging 4.0+/-4.4% (SD) of maximum voluntary contraction. Most important, the correlation, measured as r2, between target position and EMG activity averaged only 0.01+/-0.02, much lower than the correlation between target position and the EEG activity that controlled cursor movement, which averaged 0.39+/-0.18.
CONCLUSIONS:
These results strongly support the conclusion that EEG-based cursor control does no depend on concurrent muscle activity. EEG-based communication and control might provide a new augmentative communication option for those with severe motor disabilities.10aaugmentative communication10aconditioning10aElectroencephalography10aElectromyography10amu rhythm10aRehabilitation10asensorimotor cortex1 aVaughan, Theresa, M1 aMiner, L., A.1 aMcFarland, Dennis, J.1 aWolpaw, Jonathan  uhttp://www.ncbi.nlm.nih.gov/pubmed/9922089