@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.} } @inbook {3548, title = {Near-Instantaneous Classification of Perceptual States from Cortical Surface Recordings}, booktitle = {Brain-Computer Interface Research: A State-of-the-Art Summary}, year = {2015}, pages = {105-114}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {New York City, NY}, abstract = {Human visual processing is of such complexity that, despite decades of focused research, many basic questions remain unanswered. Although we know that the inferotemporal cortex is a key region in object recognition, we don{\textquoteright}t fully understand its physiologic role in brain function, nor do we have the full set of tools to explore this question. Here we show that electrical potentials from the surface of the human brain contain enough information to decode a subject{\textquoteright}s perceptual state accurately, and with fine temporal precision. Electrocorticographic (ECoG) arrays were placed over the inferotemporal cortical areas of seven subjects. Pictures of faces and houses were quickly presented while each subject performed a simple visual task. Results showed that two well-known types of brain signals{\textemdash}event-averaged broadband power and event-averaged raw potential{\textemdash}can independently or together be used to classify the presented image. When applied to continuously recorded brain activity, our decoding technique could accurately predict whether each stimulus was a face, house, or neither, with ~20 ms timing error. These results provide a roadmap for improved brain-computer interfacing tools to help neurosurgeons, research scientists, engineers, and, ultimately, patients.}, keywords = {broadband power, Electrocorticography, event-related potential, fusiform cortex, human vision}, isbn = {978-3-319-25188-2}, issn = {978-3-319-25190-5}, doi = {10.1007/978-3-319-25190-5_10}, url = {http://link.springer.com/chapter/10.1007/978-3-319-25190-5_10}, author = {Miller, Kai J and Gerwin Schalk and Hermes, Dora and Ojemann, Jeffrey G and Rao, Rajesh P N} } @article {3358, title = {Decoding spectrotemporal features of overt and covert speech from the human cortex.}, journal = {Frontiers in Neuroengineering}, volume = {7}, year = {2014}, month = {03/2014}, abstract = {Auditory perception and auditory imagery have been shown to activate overlapping brain regions. We hypothesized that these phenomena also share a common underlying neural representation. To assess this, we used electrocorticography intracranial recordings from epileptic patients performing an out loud or a silent reading task. In these tasks, short stories scrolled across a video screen in two conditions: subjects read the same stories both aloud (overt) and silently (covert). In a control condition the subject remained in a resting state. We first built a high gamma (70{\textendash}150 Hz) neural decoding model to reconstruct spectrotemporal auditory features of self-generated overt speech. We then evaluated whether this same model could reconstruct auditory speech features in the covert speech condition. Two speech models were tested: a spectrogram and a modulation-based feature space. For the overt condition, reconstruction accuracy was evaluated as the correlation between original and predicted speech features, and was significant in each subject (p < 0.00001; paired two-sample t-test). For the covert speech condition, dynamic time warping was first used to realign the covert speech reconstruction with the corresponding original speech from the overt condition. Reconstruction accuracy was then evaluated as the correlation between original and reconstructed speech features. Covert reconstruction accuracy was compared to the accuracy obtained from reconstructions in the baseline control condition. Reconstruction accuracy for the covert condition was significantly better than for the control condition (p < 0.005; paired two-sample t-test). The superior temporal gyrus, pre- and post-central gyrus provided the highest reconstruction information. The relationship between overt and covert speech reconstruction depended on anatomy. These results provide evidence that auditory representations of covert speech can be reconstructed from models that are built from an overt speech data set, supporting a partially shared neural substrate.}, keywords = {covert speech, decoding model, Electrocorticography, pattern recognition, speech production}, doi = {10.3389/fneng.2014.00014}, url = {http://www.ncbi.nlm.nih.gov/pubmed/24904404}, author = {Martin, St{\'e}phanie and Peter Brunner and Holdgraf, Chris and Heinze, Hans-Jochen and Nathan E. Crone and Rieger, Jochem and Gerwin Schalk and Robert T. Knight and Pasley, Brian N.} } @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 {3361, title = {Simultaneous Real-Time Monitoring of Multiple Cortical Systems.}, journal = {Journal of Neural Engineering}, year = {2014}, month = {10/2014}, abstract = {OBJECTIVE: Real-time monitoring of the brain is potentially valuable for performance monitoring, communication, training or rehabilitation. In natural situations, the brain performs a complex mix of various sensory, motor or cognitive functions. Thus, real-time brain monitoring would be most valuable if (a) it could decode information from multiple brain systems simultaneously, and (b) this decoding of each brain system were robust to variations in the activity of other (unrelated) brain systems. Previous studies showed that it is possible to decode some information from different brain systems in retrospect and/or in isolation. In our study, we set out to determine whether it is possible to simultaneously decode important information about a user from different brain systems in real time, and to evaluate the impact of concurrent activity in different brain systems on decoding performance. APPROACH: We study these questions using electrocorticographic signals recorded in humans. We first document procedures for generating stable decoding models given little training data, and then report their use for offline and for real-time decoding from 12 subjects (six for offline parameter optimization, six for online experimentation). The subjects engage in tasks that involve movement intention, movement execution and auditory functions, separately, and then simultaneously. Main Results: Our real-time results demonstrate that our system can identify intention and movement periods in single trials with an accuracy of 80.4\% and 86.8\%, respectively (where 50\% would be expected by chance). Simultaneously, the decoding of the power envelope of an auditory stimulus resulted in an average correlation coefficient of 0.37 between the actual and decoded power envelopes. These decoders were trained separately and executed simultaneously in real time. SIGNIFICANCE: This study yielded the first demonstration that it is possible to decode simultaneously the functional activity of multiple independent brain systems. Our comparison of univariate and multivariate decoding strategies, and our analysis of the influence of their decoding parameters, provides benchmarks and guidelines for future research on this topic.}, keywords = {auditory processing, Electrocorticography, movement intention, realtime decoding, simultaneous decoding}, doi = {10.1088/1741-2560/11/5/056001}, url = {http://www.ncbi.nlm.nih.gov/pubmed/25080161}, author = {Disha Gupta and Jeremy Jeremy Hill and Peter Brunner and Gunduz, Aysegul and A L Ritaccio and Gerwin Schalk} } @article {3028, title = {Proceedings of the Fourth International Workshop on Advances in Electrocorticography.}, journal = {Epilepsy \& Behavior}, volume = {29}, year = {2013}, month = {11/2013}, pages = {259{\textendash}68}, abstract = {The Fourth International Workshop on Advances in Electrocorticography (ECoG) convened in New Orleans, LA, on October 11{\textendash}12, 2012. The proceedings of the workshop serves as an accurate record of the most contemporary clinical and experimental work on brain surface recording and represents the insights of a unique multidisciplinary ensemble of expert clinicians and scientists. Presentations covered a broad range of topics, including innovations in passive functional mapping, increased understanding of pathologic high-frequency oscillations, evolving sensor technologies, a human trial of ECoG-driven brain{\textendash}machine interface, as well as fresh insights into brain electrical stimulation.}, keywords = {Brain Mapping, Brain{\textendash}computer interface, Electrocorticography, Gamma-frequency electroencephalography, High-frequency oscillations, Neuroprosthetics, Seizure detection, Subdural grid}, doi = {10.1016/j.yebeh.2013.08.012}, url = {http://www.ncbi.nlm.nih.gov/pubmed/24034899}, author = {A L Ritaccio and Peter Brunner and Nathan E. Crone and Gunduz, Aysegul and Hirsch, Lawrence J. and Kanwisher, Nancy and Litt, Brian and Kai J. Miller and Morani, Daniel and Parvizi, Josef and Ramsey, Nick F and Richner, Thomas J. and Tandon, Niton and Williams, Justin and Gerwin Schalk} } @article {2922, title = {Electrocorticographic (ECoG) Correlates of Human Arm Movements.}, journal = {Exp Brain Res}, volume = {223}, year = {2012}, month = {11/2012}, pages = {1-10}, abstract = {Invasive and non-invasive brain-computer interface (BCI) studies have long focused on the motor cortex for kinematic control of artificial devices. Most of these studies have used single-neuron recordings or electroencephalography (EEG). Electrocorticography (ECoG) is a relatively new recording modality in BCI research that has primarily been built on successes in EEG recordings. We built on prior experiments related to single-neuron recording and quantitatively compare the extent to which different brain regions reflect kinematic tuning parameters of hand speed, direction, and velocity in both a reaching and tracing task in humans. Hand and arm movement experiments using ECoG have shown positive results before, but the tasks were not designed to tease out which kinematics are encoded. In non-human primates, the relationships among these kinematics have been more carefully documented, and we sought to begin elucidating that relationship in humans using ECoG. The largest modulation in ECoG activity for direction, speed, and velocity representation was found in the primary motor cortex. We also found consistent cosine tuning across both tasks, to hand direction and velocity in the high gamma band (70-160~Hz). Thus, the results of this study clarify the neural substrates involved in encoding aspects of motor preparation and execution and confirm the important role of the motor cortex in BCI applications.}, keywords = {arm tuning, brain-computer interfaces, cosine tuning, Electrocorticography, Motor Cortex, subdural electroencephalography}, issn = {1432-1106}, doi = {10.1007/s00221-012-3226-1}, url = {http://www.ncbi.nlm.nih.gov/pubmed/23001369}, author = {Nicholas R Anderson and Blakely, Timothy and Gerwin Schalk and Leuthardt, E C and Moran, Daniel W} } @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 {2097, title = {Recording Human Electrocorticographic (ECoG) Signals for Neuroscientific Research and Real-time Functional Cortical Mapping.}, journal = {J Vis Exp}, year = {2012}, month = {05/2012}, abstract = {

Neuroimaging studies of human cognitive, sensory, and motor processes are usually based on noninvasive techniques such as electroencephalography (EEG), magnetoencephalography or functional magnetic-resonance imaging. These techniques have either inherently low temporal or low spatial resolution, and suffer from low signal-to-noise ratio and/or poor high-frequency sensitivity. Thus, they are suboptimal for exploring the short-lived spatio-temporal dynamics of many of the underlying brain processes. In contrast, the invasive technique of electrocorticography (ECoG) provides brain signals that have an exceptionally high signal-to-noise ratio, less susceptibility to artifacts than EEG, and a high spatial and temporal resolution (i.e., \<1 cm/\<1 millisecond, respectively). ECoG involves measurement of electrical brain signals using electrodes that are implanted subdurally on the surface of the brain. Recent studies have shown that ECoG amplitudes in certain frequency bands carry substantial information about task-related activity, such as motor execution and planning,\ auditory\ processing and visual-spatial attention. Most of this information is captured in the high gamma range (around 70-110 Hz). Thus, gamma activity has been proposed as a robust and general indicator of local cortical function. ECoG can also reveal functional connectivity and resolve finer task-related spatial-temporal dynamics, thereby advancing our understanding of large-scale cortical processes. It has especially proven useful for advancing brain-computer interfacing (BCI) technology for decoding a user{\textquoteright}s intentions to enhance or improve communication and control. Nevertheless, human ECoG data are often hard to obtain because of the risks and limitations of the invasive procedures involved, and the need to record within the constraints of clinical settings. Still, clinical monitoring to localize epileptic foci offers a unique and valuable opportunity to collect human ECoG data. We describe our methods for collecting recording ECoG, and demonstrate how to use these signals for important real-time applications such as clinical mapping and brain-computer interfacing. Our example uses the BCI2000 software platform and the SIGFRIED method, an application for real-time mapping of brain functions. This procedure yields information that clinicians can subsequently use to guide the complex and laborious process of functional mapping by electrical stimulation. PREREQUISITES AND PLANNING: Patients with drug-resistant partial epilepsy may be candidates for resective surgery of an epileptic focus to minimize the frequency of seizures. Prior to resection, the patients undergo monitoring using subdural electrodes for two purposes: first, to localize the epileptic focus, and second, to identify nearby critical brain areas (i.e., eloquent cortex) where resection could result in long-term functional deficits. To implant electrodes, a craniotomy is performed to open the skull. Then, electrode grids and/or strips are placed on the cortex, usually beneath the dura. A typical grid has a set of 8 x 8 platinum-iridium electrodes of 4 mm diameter (2.3 mm exposed surface) embedded in silicon with an inter-electrode distance of 1cm. A strip typically contains 4 or 6 such electrodes in a single line. The locations for these grids/strips are planned by a team of neurologists and neurosurgeons, and are based on previous EEG monitoring, on a structural MRI of the patient{\textquoteright}s brain, and on relevant factors of the patient{\textquoteright}s history. Continuous recording over a period of 5-12 days serves to localize epileptic foci, and electrical stimulation via the implanted electrodes allows clinicians to map eloquent cortex. At the end of the monitoring period, explantation of the electrodes and therapeutic resection are performed together in one procedure. In addition to its primary clinical purpose, invasive monitoring also provides a unique opportunity to acquire human ECoG data for neuroscientific research. The decision to include a prospective patient in the research is based on the planned location of their electrodes, on the patient{\textquoteright}s performance scores on neuropsychological assessments, and on their informed consent, which is predicated on their understanding that participation in research is optional and is not related to their treatment. As with all research involving human subjects, the research protocol must be approved by the hospital{\textquoteright}s institutional review board. The decision to perform individual experimental tasks is made day-by-day, and is contingent on the patient{\textquoteright}s endurance and willingness to participate. Some or all of the experiments may be prevented by problems with the clinical state of the patient, such as post-operative facial swelling, temporary aphasia, frequent seizures, post-ictal fatigue and confusion, and more general pain or discomfort. At the Epilepsy Monitoring Unit at Albany Medical Center in Albany, New York, clinical monitoring is implemented around the clock using a 192-channel Nihon-Kohden Neurofax monitoring system. Research recordings are made in collaboration with the Wadsworth Center of the New York State Department of Health in Albany. Signals from the ECoG electrodes are fed simultaneously to the research and the clinical systems via splitter connectors. To ensure that the clinical and research systems do not interfere with each other, the two systems typically use separate grounds. In fact, an epidural strip of electrodes is sometimes implanted to provide a ground for the clinical system. Whether research or clinical recording system, the grounding electrode is chosen to be distant from the predicted epileptic focus and from cortical areas of interest for the research. Our research system consists of eight synchronized 16-channel g.USBamp amplifier/digitizer units (g.tec, Graz, Austria). These were chosen because they are safety-rated and FDA-approved for invasive recordings, they have a very low noise-floor in the high-frequency range in which the signals of interest are found, and they come with an SDK that allows them to be integrated with custom-written research software. In order to capture the high-gamma signal accurately, we acquire signals at 1200Hz sampling rate-considerably higher than that of the typical EEG experiment or that of many clinical monitoring systems. A built-in low-pass filter automatically prevents aliasing of signals higher than the digitizer can capture. The patient{\textquoteright}s eye gaze is tracked using a monitor with a built-in Tobii T-60 eye-tracking system (Tobii Tech., Stockholm, Sweden). Additional accessories such as joystick, bluetooth Wiimote (Nintendo Co.), data-glove (5(th) Dimension Technologies), keyboard, microphone, headphones, or video camera are connected depending on the requirements of the particular experiment. Data collection, stimulus presentation, synchronization with the different input/output accessories, and real-time analysis and visualization are accomplished using our BCI2000 software. BCI2000 is a freely available general-purpose software system for real-time biosignal data acquisition, processing and feedback. It includes an array of pre-built modules that can be flexibly configured for many different purposes, and that can be extended by researchers{\textquoteright} own code in C++, MATLAB or Python. BCI2000 consists of four modules that communicate with each other via a network-capable protocol: a Source module that handles the acquisition of brain signals from one of 19 different hardware systems from different manufacturers; a Signal Processing module that extracts relevant ECoG features and translates them into output signals; an Application module that delivers stimuli and feedback to the subject; and the Operator module that provides a graphical interface to the investigator. A number of different experiments may be conducted with any given patient. The priority of experiments will be determined by the location of the particular patient{\textquoteright}s electrodes. However, we usually begin our experimentation using the SIGFRIED (SIGnal modeling For Realtime Identification and Event Detection) mapping method, which detects and displays significant task-related activity in real time. The resulting functional map allows us to further tailor subsequent experimental protocols and may also prove as a useful starting point for traditional mapping by electrocortical stimulation (ECS). Although ECS mapping remains the gold standard for predicting the clinical outcome of resection, the process of ECS mapping is time consuming and also has other problems, such as after-discharges or seizures. Thus, a passive functional mapping technique may prove valuable in providing an initial estimate of the locus of eloquent cortex, which may then be confirmed and refined by ECS. The results from our passive SIGFRIED mapping technique have been shown to exhibit substantial concurrence with the results derived using ECS mapping. The protocol described in this paper establishes a general methodology for gathering human ECoG data, before proceeding to illustrate how experiments can be initiated using the BCI2000 software platform. Finally, as a specific example, we describe how to perform passive functional mapping using the BCI2000-based SIGFRIED system.

}, keywords = {BCI2000, brain-computer interfacing, Electrocorticography, epilepsy monitoring, functional brain mapping, issue 64, Magnetic Resonance Imaging, MRI, neuroscience, SIGFRIED}, issn = {1940-087X}, doi = {10.3791/3993}, url = {http://www.ncbi.nlm.nih.gov/pubmed/22782131}, author = {Jeremy Jeremy Hill and Disha Gupta and Peter Brunner and Gunduz, Aysegul and Adamo, Matthew A and A L Ritaccio and Gerwin Schalk} } @article {2210, title = {Temporal evolution of gamma activity in human cortex during an overt and covert word repetition task.}, journal = {Front Hum Neurosci}, volume = {6}, year = {2012}, month = {05/2012}, pages = {99}, abstract = {

Several scientists have proposed different models for cortical processing of speech. Classically, the regions participating in language were thought to be modular with a linear sequence of activations. More recently, modern theoretical models have posited a more hierarchical and distributed interaction of anatomic areas for the various stages of speech processing. Traditional imaging techniques can only define the location or time of cortical activation, which impedes the further evaluation and refinement of these models. In this study, we take advantage of recordings from the surface of the brain [electrocorticography (ECoG)], which can accurately detect the location and timing of cortical activations, to study the time course of ECoG high gamma (HG) modulations during an overt and covert word repetition task for different cortical areas. For overt word production, our results show substantial perisylvian cortical activations early in the perceptual phase of the task that were maintained through word articulation. However, this broad activation is attenuated during the expressive phase of covert word repetition. Across the different repetition tasks, the utilization of the different cortical sites within the perisylvian region varied in the degree of activation dependent on which stimulus was provided (auditoryor visual cue) and whether the word was to be spoken or imagined. Taken together, the data support current models of speech that have been previously described with functional imaging. Moreover, this study demonstrates that the broad perisylvian speech network activates early and maintains suprathreshold activation throughout the word repetition task that appears to be modulated by the demands of different conditions.

}, keywords = {cortex, Electrocorticography, gamma rhythms, human, Speech}, issn = {1662-5161}, doi = {10.3389/fnhum.2012.00099}, url = {http://www.ncbi.nlm.nih.gov/pubmed/22563311}, author = {Leuthardt, E C and Pei, Xiao-Mei and Breshears, Jonathan and Charles M Gaona and Sharma, Mohit and Zachary V. Freudenberg and Barbour, Dennis L and Gerwin Schalk} } @article {2101, title = {Neural Correlates of Covert Attention in Electrocorticographic (ECoG) Signals in Humans.}, journal = {Front Hum Neurosci}, volume = {5}, year = {2011}, month = {09/2011}, pages = {89}, abstract = {

Attention is a cognitive selection mechanism that allocates the limited processing resources of the brain to the sensory streams most relevant to our immediate goals, thereby enhancing responsiveness and behavioral performance. The underlying neural mechanisms of orienting attention are distributed across a widespread cortical network. While aspects of this network have been extensively studied, details about the electrophysiological dynamics of this network are scarce. In this study, we investigated attentional networks using electrocorticographic (ECoG) recordings from the surface of the brain, which combine broad spatial coverage with high temporal resolution, in five human subjects. ECoG was recorded when subjects covertly attended to a spatial location and responded to contrast changes in the presence of distractors in a modified Posner cueing task. ECoG amplitudes in the alpha, beta, and gamma bands identified neural changes associated with covert attention and motor preparation/execution in the different stages of the task. The results show that attentional engagement was primarily associated with ECoG activity in the visual, prefrontal, premotor, and parietal cortices. Motor preparation/execution was associated with ECoG activity in premotor/sensorimotor cortices. In summary, our results illustrate rich and distributed cortical dynamics that are associated with orienting attention and the subsequent motor preparation and execution. These findings are largely consistent with and expand on primate studies using intracortical recordings and human functional neuroimaging studies.

}, keywords = {covert attention, Electrocorticography, intention, motor response, visual-spatial attention}, issn = {1662-5161}, doi = {10.3389/fnhum.2011.00089}, url = {http://www.ncbi.nlm.nih.gov/pubmed/22046153}, author = {Gunduz, Aysegul and Peter Brunner and Amy Daitch and Leuthardt, E C and A L Ritaccio and Pesaran, Bijan 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} }