We are analyzing https://link.springer.com/article/10.1007/s10548-014-0401-7.

Title:
Modulation of Posterior Alpha Activity by Spatial Attention Allows for Controlling A Continuous Brain–Computer Interface | Brain Topography
Description:
Here we report that the modulation of alpha activity by covert attention can be used as a control signal in an online brain–computer interface, that it is reliable, and that it is robust. Subjects were instructed to orient covert visual attention to the left or right hemifield. We decoded the direction of attention from the magnetoencephalogram by a template matching classifier and provided the classification outcome to the subject in real-time using a novel graphical user interface. Training data for the templates were obtained from a Posner-cueing task conducted just before the BCI task. Eleven subjects participated in four sessions each. Eight of the subjects achieved classification rates significantly above chance level. Subjects were able to significantly increase their performance from the first to the second session. Individual patterns of posterior alpha power remained stable throughout the four sessions and did not change with increased performance. We conclude that posterior alpha power can successfully be used as a control signal in brain–computer interfaces. We also discuss several ideas for further improving the setup and propose future research based on solid hypotheses about behavioral consequences of modulating neuronal oscillations by brain computer interfacing.
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Keywords {🔍}

article, pubmed, google, scholar, attention, alpha, braincomputer, brain, cas, jensen, interface, activity, neurosci, bci, doi, research, covert, access, eeg, central, eng, data, spatial, oostenveld, oscillations, neural, information, posterior, horschig, subjects, classification, privacy, cookies, content, control, visual, task, performance, cognitive, open, bias, bahramisharif, van, psychol, visuospatial, ieee, trans, rehabil, author, analysis,

Topics {✒️}

robert oostenveld & ole jensen double-blind placebo-controlled study eeg-based brain-computer interfaces continuous brain–computer interface aberrant alpha lateralization month download article/chapter brain-state dependent stimulation brain computer interfacing brain-computer interfacing classes brain-computer interface graz brain-computer interface online brain–computer interface independent brain-computer communication alpha-band brain oscillations event-related band power event-related desynchronization research subject-specific spatial patterns posner-cueing task conducted alpha-band eeg synchronization van dongen-boomsma attention-deficit/hyperactivity disorder author information authors brain-computer interface randomized placebo-controlled trial high-density eeg study alpha-band electroencephalographic activity high-density ssvep data tangential derivative mapping brain–computer interfaces brain-computer interfaces brain-computer communication open source software covert visuospatial attention author correspondence posterior alpha power full article pdf posterior alpha activity real-time eeg analysis controlled access bias correction term anticipatory alpha oscillations alpha activity induced visual spatial attention graphical user interface hum brain mapp healthy brain” funded privacy choices/manage cookies alpha oscillations correlate oscillatory alpha activity van schouwenburg mr

Questions {❓}

Vollebregt MA, van Dongen-Boomsma M, Buitelaar JK, Slaats-Willemse D (2013) Does EEG-neurofeedback improve neurocognitive functioning in children with attention-deficit/hyperactivity disorder?

Schema {🗺️}

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         description:Here we report that the modulation of alpha activity by covert attention can be used as a control signal in an online brain–computer interface, that it is reliable, and that it is robust. Subjects were instructed to orient covert visual attention to the left or right hemifield. We decoded the direction of attention from the magnetoencephalogram by a template matching classifier and provided the classification outcome to the subject in real-time using a novel graphical user interface. Training data for the templates were obtained from a Posner-cueing task conducted just before the BCI task. Eleven subjects participated in four sessions each. Eight of the subjects achieved classification rates significantly above chance level. Subjects were able to significantly increase their performance from the first to the second session. Individual patterns of posterior alpha power remained stable throughout the four sessions and did not change with increased performance. We conclude that posterior alpha power can successfully be used as a control signal in brain–computer interfaces. We also discuss several ideas for further improving the setup and propose future research based on solid hypotheses about behavioral consequences of modulating neuronal oscillations by brain computer interfacing.
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