@article {3419, title = {Brain-to-text: Decoding spoken sentences from phone representations in the brain.}, journal = {Journal of Neural Engineering}, year = {2015}, month = {06/2015}, abstract = {It has long been speculated whether communication between humans and machines based on natural speech related cortical activity is possible. Over the past decade, studies have suggested that it is feasible to recognize isolated aspects of speech from neural signals, such as auditory features, phones or one of a few isolated words. However, until now it remained an unsolved challenge to decode continuously spoken speech from the neural substrate associated with speech and language processing. Here, we show for the first time that continuously spoken speech can be decoded into the expressed words from intracranial electrocorticographic (ECoG) recordings.Specifically, we implemented a system, which we call Brain-To-Text that models single phones, employs techniques from automatic speech recognition (ASR), and thereby transforms brain activity while speaking into the corresponding textual representation. Our results demonstrate that our system can achieve word error rates as low as 25\% and phone error rates below 50\%. Additionally, our approach contributes to the current understanding of the neural basis of continuous speech production by identifying those cortical regions that hold substantial information about individual phones. In conclusion, the Brain-To- Text system described in this paper represents an important step toward human-machine communication based on imagined speech.}, keywords = {automatic speech recognition, brain-computer interface, broadband gamma, ECoG, Electrocorticography, pattern recognition, speech decoding, speech production}, doi = {10.3389/fnins.2015.00217}, url = {http://journal.frontiersin.org/article/10.3389/fnins.2015.00217/abstract}, author = {Herff, C. and Heger, D. and Pesters, Adriana de and Telaar, D. and Peter Brunner and Gerwin Schalk and Schultz, T.} } @article {3416, title = {Proceedings of the Fifth International Workshop on Advances in Electrocorticography.}, journal = {Epilepsy Behav}, volume = {41}, year = {2014}, month = {12/2014}, pages = {183-92}, abstract = {

The Fifth International Workshop on Advances in Electrocorticography convened in San Diego, CA, on November 7-8, 2013. Advancements in methodology, implementation, and commercialization across both research and in the interval year since the last workshop were the focus of the gathering. Electrocorticography (ECoG) is now firmly established as a preferred signal source for advanced research in functional, cognitive, and neuroprosthetic domains. Published output in ECoG fields has increased tenfold in the past decade. These proceedings attempt to summarize the state of the art.

}, keywords = {Brain Mapping, brain-computer interface, electrical stimulation mapping, Electrocorticography, functional mapping, Gamma-frequency electroencephalography, High-frequency oscillations, Neuroprosthetics, Seizure detection, Subdural grid}, issn = {1525-5069}, doi = {10.1016/j.yebeh.2014.09.015}, url = {http://www.ncbi.nlm.nih.gov/pubmed/25461213}, author = {A L Ritaccio and Peter Brunner and Gunduz, Aysegul and Hermes, Dora and Hirsch, Lawrence J and Jacobs, Joshua and Kamada, Kyousuke and Kastner, Sabine and Robert T. Knight and Lesser, Ronald P and Miller, Kai and Sejnowski, Terrence and Worrell, Gregory and Gerwin Schalk} } @article {2924, title = {Proceedings of the Third International Workshop on Advances in Electrocorticography.}, journal = {Epilepsy Behav}, volume = {25}, year = {2012}, month = {12/2012}, pages = {605-13}, abstract = {The Third International Workshop on Advances in Electrocorticography (ECoG) was convened in Washington, DC, on November 10-11, 2011. As in prior meetings, a true multidisciplinary fusion of clinicians, scientists, and engineers from many disciplines gathered to summarize contemporary experiences in brain surface recordings. The proceedings of this meeting serve as evidence of a very robust and transformative field but will yet again require revision to incorporate the advances that the following year will surely bring.}, keywords = {Brain Mapping, brain-computer interface, Electrocorticography, Gamma-frequency electroencephalography, high-frequency oscillation, Neuroprosthetics, Seizure detection, Subdural grid}, issn = {1525-5069}, doi = {10.1016/j.yebeh.2012.09.016}, url = {http://www.ncbi.nlm.nih.gov/pubmed/23160096}, author = {A L Ritaccio and Beauchamp, Michael and Bosman, Conrado and Peter Brunner and Chang, Edward and Nathan E. Crone and Gunduz, Aysegul and Disha Gupta and Robert T. Knight and Leuthardt, Eric and Litt, Brian and Moran, Daniel and Ojemann, Jeffrey and Parvizi, Josef and Ramsey, Nick and Rieger, Jochem and Viventi, Jonathan and Voytek, Bradley and Williams, Justin and Gerwin Schalk} } @article {2202, title = {Rapid Communication with a "P300" Matrix Speller Using Electrocorticographic Signals (ECoG).}, journal = {Front Neurosci}, volume = {5}, year = {2011}, month = {02/2011}, pages = {5}, abstract = {

A\ brain-computer interface\ (BCI) can provide a non-muscular communication channel to severely disabled people. One particular realization of a\ BCI\ is the P300 matrix speller that was originally described by Farwell and Donchin (1988). This speller uses event-related potentials (ERPs) that include the P300 ERP. All previous online studies of the P300 matrix speller used scalp-recorded electroencephalography (EEG) and were limited in their communication performance to only a few characters per minute. In our study, we investigated the feasibility of using electrocorticographic (ECoG) signals for online operation of the matrix speller, and determined associated spelling rates. We used the matrix speller that is implemented in the BCI2000 system. This speller used ECoG signals that were recorded from frontal, parietal, and occipital areas in one subject. This subject spelled a total of 444 characters in online experiments. The results showed that the subject sustained a rate of 17\ characters/min (i.e., 69\ bits/min), and achieved a peak rate of 22\ characters/min (i.e., 113\ bits/min). Detailed analysis of the results suggests that ERPs over visual areas (i.e., visual evoked potentials) contribute significantly to the performance of the matrix speller\ BCI\ system. Our results also point to potential reasons for the apparent advantages in spelling performance of ECoG compared to EEG. Thus, with additional verification in more subjects, these results may further extend the communication options for people with serious neuromuscular disabilities.

}, keywords = {brain-computer interface, Electrocorticography, event-related potential, P300, speller}, issn = {1662-453X}, doi = {10.3389/fnins.2011.00005}, url = {http://www.ncbi.nlm.nih.gov/pubmed/21369351}, author = {Peter Brunner and A L Ritaccio and Emrich, Joseph F and H Bischof and Gerwin Schalk} } @conference {2261, title = {Brain-Computer Interaction.}, booktitle = {5th Intl. Conference on Augmented Cognition}, year = {2009}, month = {2009}, publisher = {Springer}, organization = {Springer}, abstract = {

Detection and automated interpretation of attention-related or intention-related brain activity carries significant promise for many military and civilian applications. This interpretation of brain activity could provide information about a person{\textquoteright}s intended movements, imagined movements, or attentional focus, and thus could be valuable for optimizing or replacing traditional motor-based communication between a person and a computer or other output devices. We describe here the objective and preliminary results of our studies in this area.

}, keywords = {BCI, brain-computer interface, neural engineering, neural prosthesis}, isbn = {978-3-642-02811-3}, doi = {10.1007/978-3-642-02812-0_81}, url = {http://link.springer.com/chapter/10.1007\%2F978-3-642-02812-0_81}, author = {Peter Brunner and Gerwin Schalk} } @article {3113, title = {A scanning protocol for a sensorimotor rhythm-based brain-computer interface.}, journal = {Biological psychology}, volume = {80}, year = {2009}, month = {02/2009}, pages = {169{\textendash}175}, abstract = {The scanning protocol is a novel brain-computer interface (BCI) implementation that can be controlled with sensorimotor rhythms (SMRs) of the electroencephalogram (EEG). The user views a screen that shows four choices in a linear array with one marked as target. The four choices are successively highlighted for 2.5s each. When a target is highlighted, the user can select it by modulating the SMR. An advantage of this method is the capacity to choose among multiple choices with just one learned SMR modulation. Each of 10 naive users trained for ten 30 min sessions over 5 weeks. User performance improved significantly (p<0.001) over the sessions and ranged from 30 to 80\% mean accuracy of the last three sessions (chance accuracy=25\%). The incidence of correct selections depended on the target position. These results suggest that, with further improvements, a scanning protocol can be effective. The ultimate goal is to expand it to a large matrix of selections.}, keywords = {BCI, brain-computer interface, scanning protocol, sensorimotor rhythm}, issn = {1873-6246}, doi = {10.1016/j.biopsycho.2008.08.004}, url = {http://www.ncbi.nlm.nih.gov/pubmed/18786603}, author = {Friedrich, Elisabeth V. C. and Dennis J. McFarland and Neuper, Christa and Theresa M Vaughan and Peter Brunner and Jonathan Wolpaw} } @article {3108, title = {Toward a high-throughput auditory P300-based brain-computer interface.}, journal = {Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology}, volume = {120}, year = {2009}, month = {07/2009}, pages = {1252{\textendash}1261}, abstract = {OBJECTIVE: Brain-computer interface (BCI) technology can provide severely disabled people with non-muscular communication. For those most severely disabled, limitations in eye mobility or visual acuity may necessitate auditory BCI systems. The present study investigates the efficacy of the use of six environmental sounds to operate a 6x6 P300 Speller. METHODS: A two-group design was used to ascertain whether participants benefited from visual cues early in training. Group A (N=5) received only auditory stimuli during all 11 sessions, whereas Group AV (N=5) received simultaneous auditory and visual stimuli in initial sessions after which the visual stimuli were systematically removed. Stepwise linear discriminant analysis determined the matrix item that elicited the largest P300 response and thereby identified the desired choice. RESULTS: Online results and offline analyses showed that the two groups achieved equivalent accuracy. In the last session, eight of 10 participants achieved 50\% or more, and four of these achieved 75\% or more, online accuracy (2.8\% accuracy expected by chance). Mean bit rates averaged about 2 bits/min, and maximum bit rates reached 5.6 bits/min. CONCLUSIONS: This study indicates that an auditory P300 BCI is feasible, that reasonable classification accuracy and rate of communication are achievable, and that the paradigm should be further evaluated with a group of severely disabled participants who have limited visual mobility. SIGNIFICANCE: With further development, this auditory P300 BCI could be of substantial value to severely disabled people who cannot use a visual BCI.}, keywords = {brain-computer interface, brain-machine interface, EEG, event-related potential, P300, Rehabilitation}, issn = {1872-8952}, doi = {10.1016/j.clinph.2009.04.019}, url = {http://www.ncbi.nlm.nih.gov/pubmed/19574091}, author = {Klobassa, D. S. and Theresa M Vaughan and Peter Brunner and Schwartz, N. E. and Jonathan Wolpaw and Neuper, C. and Sellers, E. W.} }