<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Dijkstra, K.</style></author><author><style face="normal" font="default" size="100%">Peter Brunner</style></author><author><style face="normal" font="default" size="100%">Gunduz, Aysegul</style></author><author><style face="normal" font="default" size="100%">Coon, W.G.</style></author><author><style face="normal" font="default" size="100%">A L Ritaccio</style></author><author><style face="normal" font="default" size="100%">Farquhar, Jason</style></author><author><style face="normal" font="default" size="100%">Gerwin Schalk</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Identifying the Attended Speaker Using Electrocorticographic (ECoG) Signals.</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Neural Engineering</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">auditory attention</style></keyword><keyword><style  face="normal" font="default" size="100%">Brain-computer interface (BCI)</style></keyword><keyword><style  face="normal" font="default" size="100%">Cocktail Party</style></keyword><keyword><style  face="normal" font="default" size="100%">electrocorticography (ECoG)</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4776341/</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">People 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.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Korostenskaja, Milena</style></author><author><style face="normal" font="default" size="100%">Adam J Wilson</style></author><author><style face="normal" font="default" size="100%">Rose, Douglas F</style></author><author><style face="normal" font="default" size="100%">Peter Brunner</style></author><author><style face="normal" font="default" size="100%">Gerwin Schalk</style></author><author><style face="normal" font="default" size="100%">Leach, James</style></author><author><style face="normal" font="default" size="100%">Mangano,  Francesco T</style></author><author><style face="normal" font="default" size="100%">Fujiwara, Hisako</style></author><author><style face="normal" font="default" size="100%">Rozhkov, Leonid</style></author><author><style face="normal" font="default" size="100%">Harris, Elana</style></author><author><style face="normal" font="default" size="100%">Chen, Po-Ching</style></author><author><style face="normal" font="default" size="100%">Seo, Joo-Hee</style></author><author><style face="normal" font="default" size="100%">Lee, Ki H</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Real-Time Functional Mapping with Electrocorticography in Pediatric Epilepsy: Comparison with fMRI and ESM Findings.</style></title><secondary-title><style face="normal" font="default" size="100%">Clinical EEG and neuroscience</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Brain-computer interface (BCI)</style></keyword><keyword><style  face="normal" font="default" size="100%">cortical stimulation</style></keyword><keyword><style  face="normal" font="default" size="100%">electrocorticography (ECoG)</style></keyword><keyword><style  face="normal" font="default" size="100%">epilepsy surgery</style></keyword><keyword><style  face="normal" font="default" size="100%">functional magnetic resonance imaging (fMRI)</style></keyword><keyword><style  face="normal" font="default" size="100%">functional mapping</style></keyword><keyword><style  face="normal" font="default" size="100%">pediatrics</style></keyword><keyword><style  face="normal" font="default" size="100%">SIGFRIED</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">07/2014</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/24293161</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">SIGFRIED (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.</style></abstract></record></records></xml>