03989nas a2200193   4500008004100000245005800041210005600099260001200155490000800167520340900175653000803584653000803592653002903600653003003629100001703659700002703676700001703703856007503720       2020                        eng d00aBrain-computer interfaces: Definitions and principles0 aBraincomputer interfaces Definitions and principles  c03/20200 v1683 aThroughout life, the central nervous system (CNS) interacts with the world and with the body by activating muscles and excreting hormones. In contrast, brain-computer interfaces (BCIs) quantify CNS activity and translate it into new artificial outputs that replace, restore, enhance, supplement, or improve the natural CNS outputs. BCIs thereby modify the interactions between the CNS and the environment. Unlike the natural CNS outputs that come from spinal and brainstem motoneurons, BCI outputs come from brain signals that represent activity in other CNS areas, such as the sensorimotor cortex. If BCIs are to be useful for important communication and control tasks in real life, the CNS must control these brain signals nearly as reliably and accurately as it controls spinal motoneurons. To do this, they might, for example, need to incorporate software that mimics the function of the subcortical and spinal mechanisms that participate in normal movement control. The realization of high reliability and accuracy is perhaps the most difficult and critical challenge now facing BCI research and development.

The ongoing adaptive modifications that maintain effective natural CNS outputs take place primarily in the CNS. The adaptive modifications that maintain effective BCI outputs can also take place in the BCI. This means that the BCI operation depends on the effective collaboration of two adaptive controllers, the CNS and the BCI. Realization of this second adaptive controller, the BCI, and management of its interactions with concurrent adaptations in the CNS comprise another complex and critical challenge for BCI development.

BCIs can use different kinds of brain signals recorded in different ways from different brain areas. Decisions about which signals recorded in which ways from which brain areas should be selected for which applications are empirical questions that can only be properly answered by experiments.

BCIs, like other communication and control technologies, often face artifacts that contaminate or imitate their chosen signals. Noninvasive BCIs (e.g., EEG- or fNIRS-based) need to take special care to avoid interpreting nonbrain signals (e.g., cranial EMG) as brain signals. This typically requires comprehensive topographical and spectral evaluations.

In theory, the outputs of BCIs can select a goal or control a process. In the future, the most effective BCIs will probably be those that combine goal selection and process control so as to distribute control between the BCI and the application in a fashion suited to the current action. Through such distribution, BCIs may most effectively imitate natural CNS operation.

The primary measure of BCI development is the extent to which BCI systems benefit people with neuromuscular disorders. Thus, BCI clinical evaluation, validation, and dissemination is a key step. It is at the same time a complex and difficult process that depends on multidisciplinary collaboration and management of the demanding requirements of clinical studies.

Twenty-five years ago, BCI research was an esoteric endeavor pursued in only a few isolated laboratories. It is now a steadily growing field that engages many hundreds of scientists, engineers, and clinicians throughout the world in an increasingly interconnected community that is addressing the key issues and pursuing the high potential of BCI technology.10aBCI10aBMI10abrain-computer interface10abrain–machine interface1 aWolpaw, J.R.1 aMillán, José, del R.1 aRamsey, N.F.  uhttps://www.sciencedirect.com/science/article/pii/B978044463934900002001471nas a2200325   4500008004100000022001400041245006200055210005900117260001200176300001400188490000600202520059000208653000800798653002800806653000800834653000800842653002600850653002900876653002800905653000800933653000800941653002300949653002800972653001001000653001101010100002501021700003001046700002101076856004801097       2007                        eng d  a1743-444000aBrain-computer interface systems: progress and prospects.0 aBraincomputer interface systems progress and prospects  c07/2007  a463–4740 v43 aBrain-computer interface (BCI) systems support communication through direct measures of neural activity without muscle activity. BCIs may provide the best and sometimes the only communication option for users disabled by the most severe neuromuscular disorders and may eventually become useful to less severely disabled and/or healthy individuals across a wide range of applications. This review discusses the structure and functions of BCI systems, clarifies terminology and addresses practical applications. Progress and opportunities in the field are also identified and explicated.10aALS10aassistive communication10aBCI10aBMI10abrain-acuated control10abrain-computer interface10abrain-machine interface10aEEG10aERP10alocked-in syndrome10aslow cortical potential10aSSVEP10aStroke1 aAllison, Brendan, Z.1 aWolpaw, Elizabeth, Winter1 aWolpaw, Jonathan  uhttp://www.ncbi.nlm.nih.gov/pubmed/17605682