Brainloop
 
4. BCI - Brain–computer interfaces 
  4.2. Present-day BCIs
  4.2.3. P300 evoked potentials 

Infrequent or particularly significant auditory, visual, or somatosensory stimuli, when interspersed with frequent or routine stimuli, typically evoke in the EEG over parietal cortex a positive peak at about 300 ms. Donchin and his colleagues have used this ‘P300’ in a BCI.
The user faces a 6 x 6 matrix of letters, numbers, and/or other symbols or commands. Every 125 ms, a single row or column flashes; and, in a complete trial of 12 flashes, each row or column flashes twice. The user makes a selection by counting how many times the row or column containing the desired choice flashes. EEG over parietal cortex is digitized, the average response to each row and column is computed, and P300 amplitude for each possible choice is computed. As the picture shows, P300 is prominent only in the responses elicited by the desired choice, and the BCI uses this effect to determine the user’s intent.
The current P300-based BCI could yield a communication rate of one word (i.e. 5 letters) per minute.

Picture: P300 BCI. A matrix of possible choices is presented on a screen and scalp EEG is recorded over the centroparietal area while these choices flash in succession. Only the choice desired by the user evokes a large P300 potential (i.e. a positive potential about 300 ms after the flash).

In people with visual impairments, auditory or tactile stimuli might be used. Single-trial P300 amplitudes might be used for environmental control in Virtual Realities.
A P300-based BCI has an apparent advantage in that it requires no initial user training.


 
4. BCI - Intro
  4.1. Definition and features of a BCI
  4.1.1. Dependent and independent BCIs
4.1.2. BCI use is a skill
4.1.3. The parts of a BCI
  4.1.3.1. Signal acquisition
4.1.3.2. Signal processing: feature extraction
4.1.3.3. Signal processing: the translation algorithm
4.1.3.4. The output device
4.1.3.5. The operating protocol
4.2. Present-day BCIs
  4.2.1. Visual evoked potentials
4.2.2. Slow cortical potentials
4.2.3. P300 evoked potentials
4.2.4. Mu and beta rhythms
  4.2.4.1. The Wadsworth BCI
4.2.4.2. The Graz BCI
4.2.5. Cortical neuronal action potentials
4.3. The future of BCI-based communication
   

Source: Brain–computer interfaces for communication and control, Clinical Neurophysiology 113 (2002) 767–791, Jonathan R. Wolpaw, Niels Birbaumer, Dennis J. McFarland, Gert Pfurtscheller, Theresa M. Vaughan
 
 
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