%0 Journal Article %J Current Biology %D 2022 %T A neural population selective for song in human auditory cortex %A Sam V. Norman-Haignere %A Jenelle Feather %A Dana Boebinger %A Peter Brunner %A Anthony Ritaccio %A Josh H. McDermott %A Gerwin Schalk %A Nancy Kanwisher %K Auditory Cortex %K component %K ECoG %K Electrocorticography %K fMRI %K music %K natural sounds %K song %K Speech %K voice %X Summary How is music represented in the brain? While neuroimaging has revealed some spatial segregation between responses to music versus other sounds, little is known about the neural code for music itself. To address this question, we developed a method to infer canonical response components of human auditory cortex using intracranial responses to natural sounds, and further used the superior coverage of fMRI to map their spatial distribution. The inferred components replicated many prior findings, including distinct neural selectivity for speech and music, but also revealed a novel component that responded nearly exclusively to music with singing. Song selectivity was not explainable by standard acoustic features, was located near speech- and music-selective responses, and was also evident in individual electrodes. These results suggest that representations of music are fractionated into subpopulations selective for different types of music, one of which is specialized for the analysis of song. %B Current Biology %V 32 %P 1470-1484.e12 %G eng %U https://www.sciencedirect.com/science/article/pii/S0960982222001312 %R https://doi.org/10.1016/j.cub.2022.01.069 %0 Journal Article %J Neuroimage %D 2021 %T Modulation in cortical excitability disrupts information transfer in perceptual-level stimulus processing. %A Moheimanian, Ladan %A Paraskevopoulou, Sivylla E %A Adamek, Markus %A Schalk, Gerwin %A Peter Brunner %K Acoustic Stimulation %K Adult %K Aged %K Alpha Rhythm %K Auditory Cortex %K Brain Mapping %K Cortical Excitability %K Electrocorticography %K Female %K Humans %K Male %K Middle Aged %X

Despite significant interest in the neural underpinnings of behavioral variability, little light has been shed on the cortical mechanism underlying the failure to respond to perceptual-level stimuli. We hypothesized that cortical activity resulting from perceptual-level stimuli is sensitive to the moment-to-moment fluctuations in cortical excitability, and thus may not suffice to produce a behavioral response. We tested this hypothesis using electrocorticographic recordings to follow the propagation of cortical activity in six human subjects that responded to perceptual-level auditory stimuli. Here we show that for presentations that did not result in a behavioral response, the likelihood of cortical activity decreased from auditory cortex to motor cortex, and was related to reduced local cortical excitability. Cortical excitability was quantified using instantaneous voltage during a short window prior to cortical activity onset. Therefore, when humans are presented with an auditory stimulus close to perceptual-level threshold, moment-by-moment fluctuations in cortical excitability determine whether cortical responses to sensory stimulation successfully connect auditory input to a resultant behavioral response.

%B Neuroimage %V 243 %P 118498 %8 11/2021 %G eng %R 10.1016/j.neuroimage.2021.118498 %0 Journal Article %J Neuroimage %D 2021 %T Within-subject reaction time variability: Role of cortical networks and underlying neurophysiological mechanisms. %A Paraskevopoulou, Sivylla E %A Coon, William G %A Peter Brunner %A Miller, Kai J %A Schalk, Gerwin %K Adult %K Algorithms %K Alpha Rhythm %K Cerebral Cortex %K Connectome %K Electrocorticography %K Female %K Gamma Rhythm %K Humans %K Male %K Middle Aged %K Nerve Net %K Psychomotor Performance %K Reaction Time %K Young Adult %X

Variations in reaction time are a ubiquitous characteristic of human behavior. Extensively documented, they have been successfully modeled using parameters of the subject or the task, but the neural basis of behavioral reaction time that varies within the same subject and the same task has been minimally studied. In this paper, we investigate behavioral reaction time variance using 28 datasets of direct cortical recordings in humans who engaged in four different types of simple sensory-motor reaction time tasks. Using a previously described technique that can identify the onset of population-level cortical activity and a novel functional connectivity algorithm described herein, we show that the cumulative latency difference of population-level neural activity across the task-related cortical network can explain up to 41% of the trial-by-trial variance in reaction time. Furthermore, we show that reaction time variance may primarily be due to the latencies in specific brain regions and demonstrate that behavioral latency variance is accumulated across the whole task-related cortical network. Our results suggest that population-level neural activity monotonically increases prior to movement execution, and that trial-by-trial changes in that increase are, in part, accounted for by inhibitory activity indexed by low-frequency oscillations. This pre-movement neural activity explains 19% of the measured variance in neural latencies in our data. Thus, our study provides a mechanistic explanation for a sizable fraction of behavioral reaction time when the subject's task is the same from trial to trial.

%B Neuroimage %V 237 %P 118127 %8 08/2021 %G eng %R 10.1016/j.neuroimage.2021.118127 %0 Journal Article %J J Neural Eng %D 2019 %T iEEGview: an open-source multifunction GUI-based Matlab toolbox for localization and visualization of human intracranial electrodes. %A Li, Guangye %A Jiang, Shize %A Chen, Chen %A Peter Brunner %A Wu, Zehan %A Schalk, Gerwin %A Chen, Liang %A Zhang, Dingguo %K Brain %K Brain Mapping %K Electrocorticography %K Electrodes, Implanted %K Electroencephalography %K Humans %K Magnetic Resonance Imaging %X

OBJECTIVE: The precise localization of intracranial electrodes is a fundamental step relevant to the analysis of intracranial electroencephalography (iEEG) recordings in various fields. With the increasing development of iEEG studies in human neuroscience, higher requirements have been posed on the localization process, resulting in urgent demand for more integrated, easy-operation and versatile tools for electrode localization and visualization. With the aim of addressing this need, we develop an easy-to-use and multifunction toolbox called iEEGview, which can be used for the localization and visualization of human intracranial electrodes.

APPROACH: iEEGview is written in Matlab scripts and implemented with a GUI. From the GUI, by taking only pre-implant MRI and post-implant CT images as input, users can directly run the full localization pipeline including brain segmentation, image co-registration, electrode reconstruction, anatomical information identification, activation map generation and electrode projection from native brain space into common brain space for group analysis. Additionally, iEEGview implements methods for brain shift correction, visual location inspection on MRI slices and computation of certainty index in anatomical label assignment.

MAIN RESULTS: All the introduced functions of iEEGview work reliably and successfully, and are tested by images from 28 human subjects implanted with depth and/or subdural electrodes.

SIGNIFICANCE: iEEGview is the first public Matlab GUI-based software for intracranial electrode localization and visualization that holds integrated capabilities together within one pipeline. iEEGview promotes convenience and efficiency for the localization process, provides rich localization information for further analysis and offers solutions for addressing raised technical challenges. Therefore, it can serve as a useful tool in facilitating iEEG studies.

%B J Neural Eng %V 17 %P 016016 %8 12/2019 %G eng %N 1 %R 10.1088/1741-2552/ab51a5 %0 Journal Article %J Journal of Neuroscience Methods %D 2019 %T A quantitative method for evaluating cortical responses to electrical stimulation %A Lawrence J. Crowther %A Peter Brunner %A Christoph Kapeller %A Christoph Guger %A Kyousuke Kamada %A Marjorie E. Bunch %A Bridget K. Frawley %A Timothy M. Lynch %A Anthony L. Ritaccio %A Gerwin Schalk %K Connectivity %K Cortico-cortical evoked potentials %K Electrical stimulation %K Electrocorticography %X Background Electrical stimulation of the cortex using subdurally implanted electrodes can causally reveal structural connectivity by eliciting cortico-cortical evoked potentials (CCEPs). While many studies have demonstrated the potential value of CCEPs, the methods to evaluate them were often relatively subjective, did not consider potential artifacts, and did not lend themselves to systematic scientific investigations. New method We developed an automated and quantitative method called SIGNI (Stimulation-Induced Gamma-based Network Identification) to evaluate cortical population-level responses to electrical stimulation that minimizes the impact of electrical artifacts. We applied SIGNI to electrocorticographic (ECoG) data from eight human subjects who were implanted with a total of 978 subdural electrodes. Across the eight subjects, we delivered 92 trains of approximately 200 discrete electrical stimuli each (amplitude 4–15 mA) to a total of 64 electrode pairs. Results We verified SIGNI's efficacy by demonstrating a relationship between the magnitude of evoked cortical activity and stimulation amplitude, as well as between the latency of evoked cortical activity and the distance from the stimulated locations. Conclusions SIGNI reveals the timing and amplitude of cortical responses to electrical stimulation as well as the structural connectivity supporting these responses. With these properties, it enables exploration of new and important questions about the neurophysiology of cortical communication and may also be useful for pre-surgical planning. %B Journal of Neuroscience Methods %V 311 %P 67 - 75 %G eng %U http://www.sciencedirect.com/science/article/pii/S0165027018302796 %R https://doi.org/10.1016/j.jneumeth.2018.09.034 %0 Journal Article %J Journal of Clinical Neurophysiology %D 2018 %T Electrical Stimulation Mapping of the Brain: Basic Principles and Emerging Alternatives %A Ritaccio, A %A Peter Brunner %A Schalk, G %K Brain Mapping %K Corticocortical-evoked potentials %K electrical stimulation mapping %K Electrocorticography %K Functional localization %K Passive gamma mapping %X The application of electrical stimulation mapping (ESM) of the brain for clinical use is approximating a century. Despite this long-standing history, the value of ESM for guiding surgical resections and sparing eloquent cortex is documented largely by small retrospective studies, and ESM protocols are largely inherited and lack standardization. Although models are imperfect and mechanisms are complex, the probabilistic causality of ESM has guaranteed its perpetuation into the 21st century. At present, electrical stimulation of cortical tissue is being revisited for network connectivity. In addition, noninvasive and passive mapping techniques are rapidly evolving to complement and potentially replace ESM in specific clinical situations. Lesional and epilepsy neurosurgery cases now offer different opportunities for multimodal functional assessments. %B Journal of Clinical Neurophysiology %V 35 %P 86-97 %8 03/2018 %G eng %U https://journals.lww.com/clinicalneurophys/Abstract/2018/03000/Electrical_Stimulation_Mapping_of_the_Brain__.2.aspx %N 2 %R 10.1097/WNP.0000000000000440 %0 Journal Article %J Clinical Neurophysiology %D 2018 %T Passive functional mapping of receptive language areas using electrocorticographic signals %A J.R. Swift %A W.G. Coon %A C. Guger %A Peter Brunner %A M. Bunch %A T. Lynch %A B. Frawley %A A.L. Ritaccio %A G. Schalk %K ECoG %K Electrocorticography %K functional mapping %K Intracranial %K Receptive language %B Clinical Neurophysiology %V 129 %P 2517 - 2524 %G eng %U http://www.sciencedirect.com/science/article/pii/S1388245718312288 %R https://doi.org/10.1016/j.clinph.2018.09.007 %0 Journal Article %J Brain-Computer Interfaces %D 2016 %T Differential roles of high gamma and local motor potentials for movement preparation and execution %A Gunduz, Aysegul %A Peter Brunner %A Sharma, Mohit %A Leuthardt, Eric C. %A Ritaccio, Anthony L. %A Pesaran, Bijan %A Schalk, Gerwin %K BCI %K brain-computer interfaces %K ECoG %K Electrocorticography %K sensorimotor systems %X Determining a person’s intent, such as the planned direction of their movement, directly from their cortical activity could support important applications such as brain-computer interfaces (BCIs). Continuing development of improved BCI systems requires a better understanding of how the brain prepares for and executes movements. To contribute to this understanding, we recorded surface cortical potentials (electrocorticographic signals; ECoG) in 11 human subjects performing a delayed center-out task to establish the differential role of high gamma activity (HGA) and the local motor potential (LMP) as a function of time and anatomical area during movement preparation and execution. High gamma modulations mostly confirm previous findings of sensorimotor cortex involvement, whereas modulations in LMPs are observed in prefrontal cortices. These modulations include directional information during movement planning as well as execution. Our results suggest that sampling signals from these widely distributed cortical areas improves decoding accuracy. %B Brain-Computer Interfaces %V 3 %P 88-102 %8 May %G eng %N 2 %R https://doi.org/10.1080/2326263X.2016.1179087 %0 Journal Article %J Journal of Neural Engineering %D 2015 %T Brain-to-text: Decoding spoken sentences from phone representations in the brain. %A Herff, C. %A Heger, D. %A Pesters, Adriana de %A Telaar, D. %A Peter Brunner %A Gerwin Schalk %A Schultz, T. %K automatic speech recognition %K brain-computer interface %K broadband gamma %K ECoG %K Electrocorticography %K pattern recognition %K speech decoding %K speech production %X 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. %B Journal of Neural Engineering %8 06/2015 %G eng %U http://journal.frontiersin.org/article/10.3389/fnins.2015.00217/abstract %R 10.3389/fnins.2015.00217 %0 Journal Article %J Frontiers in Neuroengineering %D 2014 %T Decoding spectrotemporal features of overt and covert speech from the human cortex. %A Martin, Stéphanie %A Peter Brunner %A Holdgraf, Chris %A Heinze, Hans-Jochen %A Nathan E. Crone %A Rieger, Jochem %A Gerwin Schalk %A Robert T. Knight %A Pasley, Brian N. %K covert speech %K decoding model %K Electrocorticography %K pattern recognition %K speech production %X 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 (70–150 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. %B Frontiers in Neuroengineering %V 7 %8 03/2014 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/24904404 %N 14 %R 10.3389/fneng.2014.00014 %0 Journal Article %J Epilepsy Behav %D 2014 %T Proceedings of the Fifth International Workshop on Advances in Electrocorticography. %A A L Ritaccio %A Peter Brunner %A Gunduz, Aysegul %A Hermes, Dora %A Hirsch, Lawrence J %A Jacobs, Joshua %A Kamada, Kyousuke %A Kastner, Sabine %A Robert T. Knight %A Lesser, Ronald P %A Miller, Kai %A Sejnowski, Terrence %A Worrell, Gregory %A Gerwin Schalk %K Brain Mapping %K brain-computer interface %K electrical stimulation mapping %K Electrocorticography %K functional mapping %K Gamma-frequency electroencephalography %K High-frequency oscillations %K Neuroprosthetics %K Seizure detection %K Subdural grid %X

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.

%B Epilepsy Behav %V 41 %P 183-92 %8 12/2014 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/25461213 %R 10.1016/j.yebeh.2014.09.015 %0 Journal Article %J Journal of Neural Engineering %D 2014 %T Simultaneous Real-Time Monitoring of Multiple Cortical Systems. %A Disha Gupta %A Jeremy Jeremy Hill %A Peter Brunner %A Gunduz, Aysegul %A A L Ritaccio %A Gerwin Schalk %K auditory processing %K Electrocorticography %K movement intention %K realtime decoding %K simultaneous decoding %X 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. %B Journal of Neural Engineering %8 10/2014 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/25080161 %R 10.1088/1741-2560/11/5/056001 %0 Journal Article %J Epilepsy & Behavior %D 2013 %T Proceedings of the Fourth International Workshop on Advances in Electrocorticography. %A A L Ritaccio %A Peter Brunner %A Nathan E. Crone %A Gunduz, Aysegul %A Hirsch, Lawrence J. %A Kanwisher, Nancy %A Litt, Brian %A Kai J. Miller %A Morani, Daniel %A Parvizi, Josef %A Ramsey, Nick F %A Richner, Thomas J. %A Tandon, Niton %A Williams, Justin %A Gerwin Schalk %K Brain Mapping %K Brain–computer interface %K Electrocorticography %K Gamma-frequency electroencephalography %K High-frequency oscillations %K Neuroprosthetics %K Seizure detection %K Subdural grid %X The Fourth International Workshop on Advances in Electrocorticography (ECoG) convened in New Orleans, LA, on October 11–12, 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–machine interface, as well as fresh insights into brain electrical stimulation. %B Epilepsy & Behavior %V 29 %P 259–68 %8 11/2013 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/24034899 %N 2 %R 10.1016/j.yebeh.2013.08.012 %0 Journal Article %J Epilepsy Behav %D 2012 %T Proceedings of the Third International Workshop on Advances in Electrocorticography. %A A L Ritaccio %A Beauchamp, Michael %A Bosman, Conrado %A Peter Brunner %A Chang, Edward %A Nathan E. Crone %A Gunduz, Aysegul %A Disha Gupta %A Robert T. Knight %A Leuthardt, Eric %A Litt, Brian %A Moran, Daniel %A Ojemann, Jeffrey %A Parvizi, Josef %A Ramsey, Nick %A Rieger, Jochem %A Viventi, Jonathan %A Voytek, Bradley %A Williams, Justin %A Gerwin Schalk %K Brain Mapping %K brain-computer interface %K Electrocorticography %K Gamma-frequency electroencephalography %K high-frequency oscillation %K Neuroprosthetics %K Seizure detection %K Subdural grid %X 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. %B Epilepsy Behav %V 25 %P 605-13 %8 12/2012 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/23160096 %N 4 %R 10.1016/j.yebeh.2012.09.016 %0 Journal Article %J J Vis Exp %D 2012 %T Recording Human Electrocorticographic (ECoG) Signals for Neuroscientific Research and Real-time Functional Cortical Mapping. %A Jeremy Jeremy Hill %A Disha Gupta %A Peter Brunner %A Gunduz, Aysegul %A Adamo, Matthew A %A A L Ritaccio %A Gerwin Schalk %K BCI2000 %K brain-computer interfacing %K Electrocorticography %K epilepsy monitoring %K functional brain mapping %K issue 64 %K Magnetic Resonance Imaging %K MRI %K neuroscience %K SIGFRIED %X

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'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's brain, and on relevant factors of the patient'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'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's institutional review board. The decision to perform individual experimental tasks is made day-by-day, and is contingent on the patient'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'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' 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'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.

%B J Vis Exp %8 05/2012 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/22782131 %N 64 %R 10.3791/3993 %0 Journal Article %J Front Hum Neurosci %D 2011 %T Neural Correlates of Covert Attention in Electrocorticographic (ECoG) Signals in Humans. %A Gunduz, Aysegul %A Peter Brunner %A Amy Daitch %A Leuthardt, E C %A A L Ritaccio %A Pesaran, Bijan %A Gerwin Schalk %K covert attention %K Electrocorticography %K intention %K motor response %K visual-spatial attention %X

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.

%B Front Hum Neurosci %V 5 %P 89 %8 09/2011 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/22046153 %R 10.3389/fnhum.2011.00089 %0 Journal Article %J Front Neurosci %D 2011 %T Rapid Communication with a "P300" Matrix Speller Using Electrocorticographic Signals (ECoG). %A Peter Brunner %A A L Ritaccio %A Emrich, Joseph F %A H Bischof %A Gerwin Schalk %K brain-computer interface %K Electrocorticography %K event-related potential %K P300 %K speller %X

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.

%B Front Neurosci %V 5 %P 5 %8 02/2011 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/21369351 %R 10.3389/fnins.2011.00005