02118nas a2200217   4500008004100000245008100041210006900122520141400191653002301605653003501628653001901663653003201682100001701714700001901731700002001750700001501770700001801785700002001803700001901823856005801842       2015                        eng d00aIdentifying the Attended Speaker Using Electrocorticographic (ECoG) Signals.0 aIdentifying the Attended Speaker Using Electrocorticographic ECo3 aPeople affected by severe neuro-degenerative diseases (e.g., late-stage amyotrophic lateral sclerosis (ALS) or locked-in syndrome) eventually lose all muscular control. Thus, they cannot use traditional assistive communication devices that depend on muscle control, or brain-computer interfaces (BCIs) that depend on the ability to control gaze. While auditory and tactile BCIs can provide communication to such individuals, their use typically entails an artificial mapping between the stimulus and the communication intent. This makes these BCIs difficult to learn and use.

In this study, we investigated the use of selective auditory attention to natural speech as an avenue for BCI communication. In this approach, the user communicates by directing his/her attention to one of two simultaneously presented speakers. We used electrocorticographic (ECoG) signals in the gamma band (70–170 Hz) to infer the identity of attended speaker, thereby removing the need to learn such an artificial mapping.

Our results from twelve human subjects show that a single cortical location over superior temporal gyrus or pre-motor cortex is typically sufficient to identify the attended speaker within 10 s and with 77% accuracy (50% accuracy due to chance). These results lay the groundwork for future studies that may determine the real-time performance of BCIs based on selective auditory attention to speech.10aauditory attention10aBrain-computer interface (BCI)10aCocktail Party10aelectrocorticography (ECoG)1 aDijkstra, K.1 aBrunner, Peter1 aGunduz, Aysegul1 aCoon, W.G.1 aRitaccio, A L1 aFarquhar, Jason1 aSchalk, Gerwin  uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4776341/01282nas a2200181   4500008004100000022001400041245005500055210004900110260001200159300001200171520073200183653003500915100002000950700002200970700001900992700001801011856007101029       2015                        eng d  a0018-921900aThe Plurality of Human Brain-Computer Interfacing.0 aPlurality of Human BrainComputer Interfacing  c06/2015  a868-8703 aThe articles in this special issue focus on brain-computer interfacing. The papers are dedicated to this growing and diversifying research enterprise, and features important review articles as well as some important current examples of research in this area. The field of brain-computer interface (BCI) research began to develop about 25 years ago and transformed from initially isolated demonstrations by a few groups into a large scientific enterprise that is currently producing hundreds of peer-reviewed articles and several dedicated conferences and workshops each year. This level of productivity is reflective of the large and continually growing enthusiasm by the scientific community, funding agencies, and the public.10aBrain-computer interface (BCI)1 aMueller-Putz, G1 aMillán, José, R1 aSchalk, Gerwin1 aMueller, K.R.  uhttp://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=711530202800nas a2200349   4500008004100000245012100041210006900162260001200231520168800243653003501931653002501966653003201991653002102023653004902044653002302093653001502116653001302131100002602144700002002170700002102190700001902211700001902230700001702249700002602266700002102292700002002313700001802333700001902351700001702370700001502387856004802402       2014                        eng d00aReal-Time Functional Mapping with Electrocorticography in Pediatric Epilepsy: Comparison with fMRI and ESM Findings.0 aRealTime Functional Mapping with Electrocorticography in Pediatr  c07/20143 aSIGFRIED (SIGnal modeling For Real-time Identification and Event Detection) software provides real-time functional mapping (RTFM) of eloquent cortex for epilepsy patients preparing to undergo resective surgery. This study presents the first application of paradigms used in functional magnetic resonance (fMRI) and electrical cortical stimulation mapping (ESM) studies for shared functional cortical mapping in the context of RTFM. Results from the 3 modalities are compared. A left-handed 13-year-old male with intractable epilepsy participated in functional mapping for localization of eloquent language cortex with fMRI, ESM, and RTFM. For RTFM, data were acquired over the frontal and temporal cortex. Several paradigms were sequentially presented: passive (listening to stories) and active (picture naming and verb generation). For verb generation and story processing, fMRI showed atypical right lateralizing language activation within temporal lobe regions of interest and bilateral frontal activation with slight right lateralization. Left hemisphere ESM demonstrated no eloquent language areas. RTFM procedures using story processing and picture naming elicited activity in the right lateral and basal temporal regions. Verb generation elicited strong right lateral temporal lobe activation, as well as left frontal lobe activation. RTFM results confirmed atypical language lateralization evident from fMRI and ESM. We demonstrated the feasibility and usefulness of a new RTFM stimulation paradigm during presurgical evaluation. Block design paradigms used in fMRI may be optimal for this purpose. Further development is needed to create age-appropriate RTFM test batteries.10aBrain-computer interface (BCI)10acortical stimulation10aelectrocorticography (ECoG)10aepilepsy surgery10afunctional magnetic resonance imaging (fMRI)10afunctional mapping10apediatrics10aSIGFRIED1 aKorostenskaja, Milena1 aWilson, Adam, J1 aRose, Douglas, F1 aBrunner, Peter1 aSchalk, Gerwin1 aLeach, James1 aMangano, Francesco, T1 aFujiwara, Hisako1 aRozhkov, Leonid1 aHarris, Elana1 aChen, Po-Ching1 aSeo, Joo-Hee1 aLee, Ki, H  uhttp://www.ncbi.nlm.nih.gov/pubmed/2429316102258nas a2200193   4500008004100000022001400041245006700055210006500122260001200187300001100199490000600210520166100216653003501877653003401912653003201946100001901978700001901997856004802016       2011                        eng d  a1941-118900aBrain-computer interfaces using electrocorticographic signals.0 aBraincomputer interfaces using electrocorticographic signals  c10/2011  a140-540 v43 a<p><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">Many studies over the past two decades have shown that people and animals can use brain signals to convey their intent to a computer using brain-computer interfaces (BCIs). BCI systems measure specific features of brain activity and translate them into control signals that drive an output. The sensor modalities that have most commonly been used in BCI studies have been electroencephalographic (EEG) recordings from the scalp and single-neuron recordings from within the cortex. Over the past decade, an increasing number of studies has explored the use of electrocorticographic (ECoG) activity recorded directly from the surface of the brain. ECoG has attracted substantial and increasing interest, because it has been shown to reflect specific details of actual and imagined actions, and because its technical characteristics should readily support robust and chronic implementations of BCI systems in humans. This review provides general perspectives on the ECoG platform; describes the different electrophysiological features that can be detected in ECoG; elaborates on the signal acquisition issues, protocols, and online performance of ECoG-based BCI studies to date; presents important limitations of current ECoG studies; discusses opportunities for further research; and finally presents a vision for eventual clinical implementation. In summary, the studies presented to date strongly encourage further research using the ECoG platform for basic neuroscientific research, as well as for translational neuroprosthetic applications.</span></p>10aBrain-computer interface (BCI)10abrain-machine interface (BMI)10aelectrocorticography (ECoG)1 aSchalk, Gerwin1 aLeuthardt, E C  uhttp://www.ncbi.nlm.nih.gov/pubmed/2227379602866nas a2200289   4500008004100000022001400041245008600055210006900141260001200210300001400222490000600236520197100242653003102213653003502244653003302279100002102312700002102333700002202354700002602376700002002402700001902422700002102441700002102462700002102483700002402504856004802528       2000                        eng d  a1063-652800aBrain-computer interface technology: a review of the first international meeting.0 aBraincomputer interface technology a review of the first interna  c06/2000  a164–1730 v83 aOver the past decade, many laboratories have begun to explore brain-computer interface (BCI) technology as a radically new communication option for those with neuromuscular impairments that prevent them from using conventional augmentative communication methods. BCI's provide these users with communication channels that do not depend on peripheral nerves and muscles. This article summarizes the first international meeting devoted to BCI research and development. Current BCI's use electroencephalographic (EEG) activity recorded at the scalp or single-unit activity recorded from within cortex to control cursor movement, select letters or icons, or operate a neuroprosthesis. The central element in each BCI is a translation algorithm that converts electrophysiological input from the user into output that controls external devices. BCI operation depends on effective interaction between two adaptive controllers, the user who encodes his or her commands in the electrophysiological input provided to the BCI, and the BCI which recognizes the commands contained in the input and expresses them in device control. Current BCI's have maximum information transfer rates of 5-25 b/min. Achievement of greater speed and accuracy depends on improvements in signal processing, translation algorithms, and user training. These improvements depend on increased interdisciplinary cooperation between neuroscientists, engineers, computer programmers, psychologists, and rehabilitation specialists, and on adoption and widespread application of objective methods for evaluating alternative methods. The practical use of BCI technology depends on the development of appropriate applications, identification of appropriate user groups, and careful attention to the needs and desires of individual users. BCI research and development will also benefit from greater emphasis on peer-reviewed publications, and from adoption of standard venues for presentations and discussion.10aaugmentative communication10aBrain-computer interface (BCI)10aelectroencephalography (EEG)1 aWolpaw, Jonathan1 aBirbaumer, Niels1 aHeetderks, W., J.1 aMcFarland, Dennis, J.1 aPeckham, P., H.1 aSchalk, Gerwin1 aDonchin, Emanuel1 aQuatrano, L., A.1 aRobinson, C., J.1 aVaughan, Theresa, M  uhttp://www.ncbi.nlm.nih.gov/pubmed/10896178