Brainloop
 
4. BCI - Brain–computer interfaces
  4.1. Definition and features of a BCI
  4.1.2. BCI use is a skill

A BCI changes electrophysiological signals from mere reflections of central nervous system activity into the intended products of that activity: messages and commands that act on the world. It changes a signal such as an EEG rhythm or a neuronal firing rate from a reflection of brain function into the end product of that function: an output that accomplishes the person's intent.

A BCI replaces nerves and muscles and the movements they produce with electrophysiological signals and the hardware and software that translate those signals into actions. The brain's normal neuromuscular output channels depend for their successful operation on feedback.

As a replacement for the brain's normal neuromuscular output channels, a BCI also depends on feedback and on adaptation of brain activity based on that feedback. Thus, a BCI system must provide feedback and must interact in a productive fashion with the adaptations the brain makes in response to that feedback. This means that BCI operation depends on the interaction of two adaptive controllers: the user's brain and the BCI itself.

Successful BCI operation requires that the user develop and maintain a new skill, a skill that consists not of proper muscle control but rather of proper control of specific electrophysiological signals; and it also requires that the BCI translate that control into output that accomplishes the user's intent. In the independent BCI the P300 generated in response to the desired letter occurs without training. Nevertheless, once this P300 is engaged as a communication channel, it is likely to undergo adaptive modification, and the recognition and productive engagement of this adaptation will be important for continued successful BCI operation.

 
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