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/