02336nas a2200229 4500008004100000022001400041245012600055210006900181260001600250490000700266520152600273653001001799653002501809653002701834653001101861653004101872100001601913700001901929700001901948700001901967856012001986 2024 eng d a2050-084X00aNovel cyclic homogeneous oscillation detection method for high accuracy and specific characterization of neural dynamics.0 aNovel cyclic homogeneous oscillation detection method for high a c2024 Sep 060 v123 a

Determining the presence and frequency of neural oscillations is essential to understanding dynamic brain function. Traditional methods that detect peaks over 1/ noise within the power spectrum fail to distinguish between the fundamental frequency and harmonics of often highly non-sinusoidal neural oscillations. To overcome this limitation, we define fundamental criteria that characterize neural oscillations and introduce the cyclic homogeneous oscillation (CHO) detection method. We implemented these criteria based on an autocorrelation approach to determine an oscillation's fundamental frequency. We evaluated CHO by verifying its performance on simulated non-sinusoidal oscillatory bursts and validated its ability to determine the fundamental frequency of neural oscillations in electrocorticographic (ECoG), electroencephalographic (EEG), and stereoelectroencephalographic (SEEG) signals recorded from 27 human subjects. Our results demonstrate that CHO outperforms conventional techniques in accurately detecting oscillations. In summary, CHO demonstrates high precision and specificity in detecting neural oscillations in time and frequency domains. The method's specificity enables the detailed study of non-sinusoidal characteristics of oscillations, such as the degree of asymmetry and waveform of an oscillation. Furthermore, CHO can be applied to identify how neural oscillations govern interactions throughout the brain and to determine oscillatory biomarkers that index abnormal brain function.

10aBrain10aElectrocorticography10aElectroencephalography10aHumans10aSignal Processing, Computer-Assisted1 aCho, Hohyun1 aAdamek, Markus1 aWillie, Jon, T1 aBrunner, Peter uhttps://neurotechcenter.org/publications/2024/novel-cyclic-homogeneous-oscillation-detection-method-high-accuracy-002549nas a2200325 4500008004100000022001400041245011400055210006900169260001200238300001000250490000800260520151900268653002401787653001001811653001801821653002001839653002501859653001101884653001301895100002401908700002001932700002401952700002301976700002201999700002102021700002502042700001902067700001902086856011802105 2023 eng d a1872-895200aPassive functional mapping of receptive language cortex during general anesthesia using electrocorticography.0 aPassive functional mapping of receptive language cortex during g c03/2023 a31-440 v1473 a

OBJECTIVE: To investigate the feasibility of passive functional mapping in the receptive language cortex during general anesthesia using electrocorticographic (ECoG) signals.

METHODS: We used subdurally placed ECoG grids to record cortical responses to speech stimuli during awake and anesthesia conditions. We identified the cortical areas with significant responses to the stimuli using the spectro-temporal consistency of the brain signal in the broadband gamma (BBG) frequency band (70-170 Hz).

RESULTS: We found that ECoG BBG responses during general anesthesia effectively identify cortical regions associated with receptive language function. Our analyses demonstrated that the ability to identify receptive language cortex varies across different states and depths of anesthesia. We confirmed these results by comparing them to receptive language areas identified during the awake condition. Quantification of these results demonstrated an average sensitivity and specificity of passive language mapping during general anesthesia to be 49±7.7% and 100%, respectively.

CONCLUSION: Our results demonstrate that mapping receptive language cortex in patients during general anesthesia is feasible.

SIGNIFICANCE: Our proposed protocol could greatly expand the population of patients that can benefit from passive language mapping techniques, and could eliminate the risks associated with electrocortical stimulation during an awake craniotomy.

10aAnesthesia, General10aBrain10aBrain Mapping10aCerebral Cortex10aElectrocorticography10aHumans10aLanguage1 aNourmohammadi, Amin1 aSwift, James, R1 ade Pesters, Adriana1 aGuay, Christian, S1 aAdamo, Matthew, A1 aDalfino, John, C1 aRitaccio, Anthony, L1 aSchalk, Gerwin1 aBrunner, Peter uhttps://neurotechcenter.org/publications/2023/passive-functional-mapping-receptive-language-cortex-during-general01952nas a2200337 4500008004100000022001400041245006800055210006600123300001800189490000700207520101700214653002001231653001401251653000901265653002501274653000901299653001001308653001901318653000901337653001101346653001001357100002901367700002101396700002001417700001901437700002201456700002401478700001901502700002101521856007201542 2022 eng d a0960-982200aA neural population selective for song in human auditory cortex0 aneural population selective for song in human auditory cortex a1470-1484.e120 v323 aSummary 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.10aAuditory Cortex10acomponent10aECoG10aElectrocorticography10afMRI10amusic10anatural sounds10asong10aSpeech10avoice1 aNorman-Haignere, Sam, V.1 aFeather, Jenelle1 aBoebinger, Dana1 aBrunner, Peter1 aRitaccio, Anthony1 aMcDermott, Josh, H.1 aSchalk, Gerwin1 aKanwisher, Nancy uhttps://www.sciencedirect.com/science/article/pii/S096098222200131202268nas a2200337 4500008004100000022001400041245011100055210006900166260001200235300001100247490000800258520124200266653002501508653001001533653000901543653001701552653002001569653001801589653002601607653002501633653001101658653001101669653000901680653001601689100002301705700003201728700001901760700001901779700001901798856011301817 2021 eng d a1095-957200aModulation in cortical excitability disrupts information transfer in perceptual-level stimulus processing.0 aModulation in cortical excitability disrupts information transfe c11/2021 a1184980 v2433 a

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.

10aAcoustic Stimulation10aAdult10aAged10aAlpha Rhythm10aAuditory Cortex10aBrain Mapping10aCortical Excitability10aElectrocorticography10aFemale10aHumans10aMale10aMiddle Aged1 aMoheimanian, Ladan1 aParaskevopoulou, Sivylla, E1 aAdamek, Markus1 aSchalk, Gerwin1 aBrunner, Peter uhttps://neurotechcenter.org/publications/2021/modulation-cortical-excitability-disrupts-information-transfer02749nas a2200373 4500008004100000022001400041245011800055210006900173260001200242300001100254490000800265520163200273653001001905653001501915653001701930653002001947653001501967653002501982653001102007653001702018653001102035653000902046653001602055653001402071653002802085653001802113653001602131100003202147700002102179700001902200700001902219700001902238856011802257 2021 eng d a1095-957200aWithin-subject reaction time variability: Role of cortical networks and underlying neurophysiological mechanisms.0 aWithinsubject reaction time variability Role of cortical network c08/2021 a1181270 v2373 a

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.

10aAdult10aAlgorithms10aAlpha Rhythm10aCerebral Cortex10aConnectome10aElectrocorticography10aFemale10aGamma Rhythm10aHumans10aMale10aMiddle Aged10aNerve Net10aPsychomotor Performance10aReaction Time10aYoung Adult1 aParaskevopoulou, Sivylla, E1 aCoon, William, G1 aBrunner, Peter1 aMiller, Kai, J1 aSchalk, Gerwin uhttps://neurotechcenter.org/publications/2021/within-subject-reaction-time-variability-role-cortical-networks-and02978nas a2200313 4500008004100000022001400041245013700055210006900192260001200261300001100273490000700284520198000291653001002271653001802281653002502299653002602324653002702350653001102377653003102388100001602419700001702435700001502452700001902467700001402486700001902500700001602519700001902535856011002554 2019 eng d a1741-255200aiEEGview: an open-source multifunction GUI-based Matlab toolbox for localization and visualization of human intracranial electrodes.0 aiEEGview an opensource multifunction GUIbased Matlab toolbox for c12/2019 a0160160 v173 a

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.

10aBrain10aBrain Mapping10aElectrocorticography10aElectrodes, Implanted10aElectroencephalography10aHumans10aMagnetic Resonance Imaging1 aLi, Guangye1 aJiang, Shize1 aChen, Chen1 aBrunner, Peter1 aWu, Zehan1 aSchalk, Gerwin1 aChen, Liang1 aZhang, Dingguo uhttps://neurotechcenter.org/publications/2019/ieegview-open-source-multifunction-gui-based-matlab-toolbox02512nas a2200289 4500008004100000022001400041245008600055210006900141300001200210490000800222520158400230653001701814653003901831653002701870653002501897100002701922700001901949700002401968700002101992700002102013700002402034700002502058700002302083700002602106700001902132856007102151 2019 eng d a0165-027000aA quantitative method for evaluating cortical responses to electrical stimulation0 aquantitative method for evaluating cortical responses to electri a67 - 750 v3113 aBackground 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.10aConnectivity10aCortico-cortical evoked potentials10aElectrical stimulation10aElectrocorticography1 aCrowther, Lawrence, J.1 aBrunner, Peter1 aKapeller, Christoph1 aGuger, Christoph1 aKamada, Kyousuke1 aBunch, Marjorie, E.1 aFrawley, Bridget, K.1 aLynch, Timothy, M.1 aRitaccio, Anthony, L.1 aSchalk, Gerwin uhttp://www.sciencedirect.com/science/article/pii/S016502701830279601703nas a2200241 4500008004100000022002700041245009200068210006900160260001200229300001000241490000700251520086400258653001801122653003801140653003501178653002501213653002801238653002601266100001601292700001901308700001401327856012001341 2018 eng d a0736-0258/18/3502-008600aElectrical Stimulation Mapping of the Brain: Basic Principles and Emerging Alternatives0 aElectrical Stimulation Mapping of the Brain Basic Principles and c03/2018 a86-970 v353 aThe 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.10aBrain Mapping10aCorticocortical-evoked potentials10aelectrical stimulation mapping10aElectrocorticography10aFunctional localization10aPassive gamma mapping1 aRitaccio, A1 aBrunner, Peter1 aSchalk, G uhttps://journals.lww.com/clinicalneurophys/Abstract/2018/03000/Electrical_Stimulation_Mapping_of_the_Brain__.2.aspx02860nas a2200361 4500008004100000022001400041245011700055210006900172300001900241490000700260520181600267653000902083653002502092653000802117653002802125653002002153653000702173653000802180653002802188653000802216653002502224653002802249653000802277100001802285700001402303700001702317700001802334700001902352700001902371700002302390700001402413856007102427 2018 eng d a0960-982200aEncoding of Multiple Reward-Related Computations in Transient and Sustained High-Frequency Activity in Human OFC0 aEncoding of Multiple RewardRelated Computations in Transient and a2889 - 2899.e30 v283 aSummary Human orbitofrontal cortex (OFC) has long been implicated in value-based decision making. In recent years, convergent evidence from human and model organisms has further elucidated its role in representing reward-related computations underlying decision making. However, a detailed description of these processes remains elusive due in part to (1) limitations in our ability to observe human OFC neural dynamics at the timescale of decision processes and (2) methodological and interspecies differences that make it challenging to connect human and animal findings or to resolve discrepancies when they arise. Here, we sought to address these challenges by conducting multi-electrode electrocorticography (ECoG) recordings in neurosurgical patients during economic decision making to elucidate the electrophysiological signature, sub-second temporal profile, and anatomical distribution of reward-related computations within human OFC. We found that high-frequency activity (HFA) (70–200 Hz) reflected multiple valuation components grouped in two classes of valuation signals that were dissociable in temporal profile and information content: (1) fast, transient responses reflecting signals associated with choice and outcome processing, including anticipated risk and outcome regret, and (2) sustained responses explicitly encoding what happened in the immediately preceding trial. Anatomically, these responses were widely distributed in partially overlapping networks, including regions in the central OFC (Brodmann areas 11 and 13), which have been consistently implicated in reward processing in animal single-unit studies. Together, these results integrate insights drawn from human and animal studies and provide evidence for a role of human OFC in representing multiple reward computations.10aECoC10aElectrocorticography10aERP10aevent-related potential10afield potential10aFP10aHFA10ahigh-frequency activity10aOFC10aorbitofrontal cortex10areward-prediction error10aRPE1 aSaez, Ignacio1 aLin, Jack1 aStolk, Arjen1 aChang, Edward1 aParvizi, Josef1 aSchalk, Gerwin1 aKnight, Robert, T.1 aHsu, Ming uhttp://www.sciencedirect.com/science/article/pii/S096098221830975800831nas a2200277 4500008004100000022001400041245009500055210006900150300001600219490000800235653000900243653002500252653002300277653001700300653002300317100001600340700001500356700001400371700001900385700001400404700001400418700001600432700001900448700001500467856007100482 2018 eng d a1388-245700aPassive functional mapping of receptive language areas using electrocorticographic signals0 aPassive functional mapping of receptive language areas using ele a2517 - 25240 v12910aECoG10aElectrocorticography10afunctional mapping10aIntracranial10aReceptive language1 aSwift, J.R.1 aCoon, W.G.1 aGuger, C.1 aBrunner, Peter1 aBunch, M.1 aLynch, T.1 aFrawley, B.1 aRitaccio, A.L.1 aSchalk, G. uhttp://www.sciencedirect.com/science/article/pii/S138824571831228801925nas a2200265 4500008004100000245010300041210006900144260000800213300001100221490000600232520106300238653000801301653003001309653000901339653002501348653002501373100002001398700001901418700001801437700002401455700002601479700001901505700001901524856011601543 2016 eng d00aDifferential roles of high gamma and local motor potentials for movement preparation and execution0 aDifferential roles of high gamma and local motor potentials for  cMay a88-1020 v33 aDetermining 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.10aBCI10abrain-computer interfaces10aECoG10aElectrocorticography10asensorimotor systems1 aGunduz, Aysegul1 aBrunner, Peter1 aSharma, Mohit1 aLeuthardt, Eric, C.1 aRitaccio, Anthony, L.1 aPesaran, Bijan1 aSchalk, Gerwin uhttps://neurotechcenter.org/publications/2016/differential-roles-high-gamma-and-local-motor-potentials-movement02272nas a2200277 4500008004100000245008600041210006900127260001200196520140600208653003301614653002901647653002001676653000901696653002501705653002401730653002001754653002201774100001401796700001401810700002401824700001501848700001901863700001901882700001601901856007701917 2015 eng d00aBrain-to-text: Decoding spoken sentences from phone representations in the brain.0 aBraintotext Decoding spoken sentences from phone representations c06/20153 aIt 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.10aautomatic speech recognition10abrain-computer interface10abroadband gamma10aECoG10aElectrocorticography10apattern recognition10aspeech decoding10aspeech production1 aHerff, C.1 aHeger, D.1 ade Pesters, Adriana1 aTelaar, D.1 aBrunner, Peter1 aSchalk, Gerwin1 aSchultz, T. uhttp://journal.frontiersin.org/article/10.3389/fnins.2015.00217/abstract02134nas a2200253 4500008004100000020002200041022002200063245009200085210006900177260005700246300001200303520128900315653002001604653002501624653002801649653002001677653001701697100001901714700001901733700001701752700002401769700002101793856006601814 2015 eng d a978-3-319-25188-2 a978-3-319-25190-500aNear-Instantaneous Classification of Perceptual States from Cortical Surface Recordings0 aNearInstantaneous Classification of Perceptual States from Corti aNew York City, NYbSpringer International Publishing a105-1143 aHuman 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’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’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—event-averaged broadband power and event-averaged raw potential—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.10abroadband power10aElectrocorticography10aevent-related potential10afusiform cortex10ahuman vision1 aMiller, Kai, J1 aSchalk, Gerwin1 aHermes, Dora1 aOjemann, Jeffrey, G1 aRao, Rajesh, P N uhttp://link.springer.com/chapter/10.1007/978-3-319-25190-5_1002900nas a2200277 4500008004100000245008800041210006900129260001200198490000600210520205900216653001802275653001902293653002502312653002402337653002202361100002302383700001902406700002002425700002402445700002202469700001902491700001902510700002302529700002202552856004802574 2014 eng d00aDecoding spectrotemporal features of overt and covert speech from the human cortex.0 aDecoding spectrotemporal features of overt and covert speech fro c03/20140 v73 aAuditory 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.10acovert speech10adecoding model10aElectrocorticography10apattern recognition10aspeech production1 aMartin, Stéphanie1 aBrunner, Peter1 aHoldgraf, Chris1 aHeinze, Hans-Jochen1 aCrone, Nathan, E.1 aRieger, Jochem1 aSchalk, Gerwin1 aKnight, Robert, T.1 aPasley, Brian, N. uhttp://www.ncbi.nlm.nih.gov/pubmed/2490440401857nas a2200421 4500008004100000022001400041245008900055210006900144260001200213300001100225490000700236520059500243653001800838653002900856653003500885653002500920653002300945653004300968653003201011653002101043653002201064653001801086100001801104700001901122700002001141700001701161700002401178700001901202700002101221700002001242700002301262700002201285700001601307700002401323700002101347700001901368856004801387 2014 eng d a1525-506900aProceedings of the Fifth International Workshop on Advances in Electrocorticography.0 aProceedings of the Fifth International Workshop on Advances in E c12/2014 a183-920 v413 a

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.

10aBrain Mapping10abrain-computer interface10aelectrical stimulation mapping10aElectrocorticography10afunctional mapping10aGamma-frequency electroencephalography10aHigh-frequency oscillations10aNeuroprosthetics10aSeizure detection10aSubdural grid1 aRitaccio, A L1 aBrunner, Peter1 aGunduz, Aysegul1 aHermes, Dora1 aHirsch, Lawrence, J1 aJacobs, Joshua1 aKamada, Kyousuke1 aKastner, Sabine1 aKnight, Robert, T.1 aLesser, Ronald, P1 aMiller, Kai1 aSejnowski, Terrence1 aWorrell, Gregory1 aSchalk, Gerwin uhttp://www.ncbi.nlm.nih.gov/pubmed/2546121302940nas a2200229 4500008004100000245006800041210006600109260001200175520223700187653002402424653002502448653002302473653002202496653002602518100001702544700002502561700001902586700002002605700001802625700001902643856004802662 2014 eng d00aSimultaneous Real-Time Monitoring of Multiple Cortical Systems.0 aSimultaneous RealTime Monitoring of Multiple Cortical Systems c10/20143 aOBJECTIVE: 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.10aauditory processing10aElectrocorticography10amovement intention10arealtime decoding10asimultaneous decoding1 aGupta, Disha1 aHill, Jeremy, Jeremy1 aBrunner, Peter1 aGunduz, Aysegul1 aRitaccio, A L1 aSchalk, Gerwin uhttp://www.ncbi.nlm.nih.gov/pubmed/2508016101886nas a2200397 4500008004100000245009000041210006900131260001200200300001300212490000700225520069800232653001800930653003100948653002500979653004301004653003201047653002101079653002201100653001801122100001801140700001901158700002201177700002001199700002501219700002101244700001601265700001901281700001901300700001901319700002001338700002401358700001801382700002101400700001901421856004801440 2013 eng d00aProceedings of the Fourth International Workshop on Advances in Electrocorticography.0 aProceedings of the Fourth International Workshop on Advances in  c11/2013 a259–680 v293 aThe 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.10aBrain Mapping10aBrain–computer interface10aElectrocorticography10aGamma-frequency electroencephalography10aHigh-frequency oscillations10aNeuroprosthetics10aSeizure detection10aSubdural grid1 aRitaccio, A L1 aBrunner, Peter1 aCrone, Nathan, E.1 aGunduz, Aysegul1 aHirsch, Lawrence, J.1 aKanwisher, Nancy1 aLitt, Brian1 aMiller, Kai, J1 aMorani, Daniel1 aParvizi, Josef1 aRamsey, Nick, F1 aRichner, Thomas, J.1 aTandon, Niton1 aWilliams, Justin1 aSchalk, Gerwin uhttp://www.ncbi.nlm.nih.gov/pubmed/2403489902208nas a2200265 4500008004100000022001400041245006800055210006500123260001200188300000900200490000800209520143000217653001501647653003001662653001801692653002501710653001701735653003601752100002601788700002101814700001901835700001901854700002101873856004801894 2012 eng d a1432-110600aElectrocorticographic (ECoG) Correlates of Human Arm Movements.0 aElectrocorticographic ECoG Correlates of Human Arm Movements c11/2012 a1-100 v2233 aInvasive 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.10aarm tuning10abrain-computer interfaces10acosine tuning10aElectrocorticography10aMotor Cortex10asubdural electroencephalography1 aAnderson, Nicholas, R1 aBlakely, Timothy1 aSchalk, Gerwin1 aLeuthardt, E C1 aMoran, Daniel, W uhttp://www.ncbi.nlm.nih.gov/pubmed/2300136901889nas a2200469 4500008004100000022001400041245008900055210006900144260001200213300001100225490000700236520052900243653001800772653002900790653002500819653004300844653003100887653002100918653002200939653001800961100001800979700002300997700002001020700001901040700001801059700002201077700002001099700001701119700002301136700002001159700001601179700001801195700002101213700001901234700001701253700001901270700002201289700002001311700002101331700001901352856004801371 2012 eng d a1525-506900aProceedings of the Third International Workshop on Advances in Electrocorticography.0 aProceedings of the Third International Workshop on Advances in E c12/2012 a605-130 v253 aThe 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.10aBrain Mapping10abrain-computer interface10aElectrocorticography10aGamma-frequency electroencephalography10ahigh-frequency oscillation10aNeuroprosthetics10aSeizure detection10aSubdural grid1 aRitaccio, A L1 aBeauchamp, Michael1 aBosman, Conrado1 aBrunner, Peter1 aChang, Edward1 aCrone, Nathan, E.1 aGunduz, Aysegul1 aGupta, Disha1 aKnight, Robert, T.1 aLeuthardt, Eric1 aLitt, Brian1 aMoran, Daniel1 aOjemann, Jeffrey1 aParvizi, Josef1 aRamsey, Nick1 aRieger, Jochem1 aViventi, Jonathan1 aVoytek, Bradley1 aWilliams, Justin1 aSchalk, Gerwin uhttp://www.ncbi.nlm.nih.gov/pubmed/2316009610628nas a2200313 4500008004100000022001400041245012900055210006900184260001200253520965800265653001209923653003109935653002509966653002409991653002910015653001310044653003110057653000810088653001710096653001310113100002510126700001710151700001910168700002010187700002210207700001810229700001910247856004810266 2012 eng d a1940-087X00aRecording Human Electrocorticographic (ECoG) Signals for Neuroscientific Research and Real-time Functional Cortical Mapping.0 aRecording Human Electrocorticographic ECoG Signals for Neuroscie c05/20123 a

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.

10aBCI200010abrain-computer interfacing10aElectrocorticography10aepilepsy monitoring10afunctional brain mapping10aissue 6410aMagnetic Resonance Imaging10aMRI10aneuroscience10aSIGFRIED1 aHill, Jeremy, Jeremy1 aGupta, Disha1 aBrunner, Peter1 aGunduz, Aysegul1 aAdamo, Matthew, A1 aRitaccio, A L1 aSchalk, Gerwin uhttp://www.ncbi.nlm.nih.gov/pubmed/2278213102945nas a2200289 4500008004100000022001400041245010600055210006900161260001200230300000700242490000600249520210500255653001102360653002502371653001802396653001002414653001102424100001902435700001802454700002402472700002202496700001802518700002902536700002302565700001902588856004802607 2012 eng d a1662-516100aTemporal evolution of gamma activity in human cortex during an overt and covert word repetition task.0 aTemporal evolution of gamma activity in human cortex during an o c05/2012 a990 v63 a

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.

10acortex10aElectrocorticography10agamma rhythms10ahuman10aSpeech1 aLeuthardt, E C1 aPei, Xiao-Mei1 aBreshears, Jonathan1 aGaona, Charles, M1 aSharma, Mohit1 aFreudenberg, Zachary, V.1 aBarbour, Dennis, L1 aSchalk, Gerwin uhttp://www.ncbi.nlm.nih.gov/pubmed/2256331102535nas a2200277 4500008004100000022001400041245009300055210006900148260001200217300000700229490000600236520172900242653002101971653002501992653001402017653001902031653002902050100002002079700001902099700001602118700001902134700001802153700001902171700001902190856004802209 2011 eng d a1662-516100aNeural Correlates of Covert Attention in Electrocorticographic (ECoG) Signals in Humans.0 aNeural Correlates of Covert Attention in Electrocorticographic E c09/2011 a890 v53 a

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.

10acovert attention10aElectrocorticography10aintention10amotor response10avisual-spatial attention1 aGunduz, Aysegul1 aBrunner, Peter1 aDaitch, Amy1 aLeuthardt, E C1 aRitaccio, A L1 aPesaran, Bijan1 aSchalk, Gerwin uhttp://www.ncbi.nlm.nih.gov/pubmed/2204615303409nas a2200253 4500008004100000022001400041245009700055210006900152260001200221300000600233490000600239520266600245653002902911653002502940653002802965653000902993653001203002100001903014700001803033700002203051700001503073700001903088856004803107 2011 eng d a1662-453X00aRapid Communication with a "P300" Matrix Speller Using Electrocorticographic Signals (ECoG).0 aRapid Communication with a P300 Matrix Speller Using Electrocort c02/2011 a50 v53 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.

10abrain-computer interface10aElectrocorticography10aevent-related potential10aP30010aspeller1 aBrunner, Peter1 aRitaccio, A L1 aEmrich, Joseph, F1 aBischof, H1 aSchalk, Gerwin uhttp://www.ncbi.nlm.nih.gov/pubmed/2136935103691nas a2200193 4500008004100000245013500041210006900176260001200245490000700257520302900264653002903293653002503322653001703347100001903364700002903383700002003412700001803432856004703450 2009 eng d00aMicroscale recording from human motor cortex: implications for minimally invasive electrocorticographic brain-computer interfaces.0 aMicroscale recording from human motor cortex implications for mi c07/20090 v273 a

OBJECT: 

There is a growing interest in the use of recording from the surface of the brain, known as electrocorticography (ECoG), as a practical signal platform for brain-computer interface application. The signal has a combination of high signal quality and long-term stability that may be the ideal intermediate modality for future application. The research paradigm for studying ECoG signals uses patients requiring invasive monitoring for seizure localization. The implanted arrays span cortex areas on the order of centimeters. Currently, it is unknown what level of motor information can be discerned from small regions of human cortex with microscale ECoG recording.

METHODS: 

In this study, a patient requiring invasive monitoring for seizure localization underwent concurrent implantation with a 16-microwire array (1-mm electrode spacing) placed over primary motor cortex. Microscale activity was recorded while the patient performed simple contra- and ipsilateral wrist movements that were monitored in parallel with electromyography. Using various statistical methods, linear and nonlinear relationships between these microcortical changes and recorded electromyography activity were defined.

RESULTS: 

Small regions of primary motor cortex (< 5 mm) carry sufficient information to separate multiple aspects of motor movements (that is, wrist flexion/extension and ipsilateral/contralateral movements).

CONCLUSIONS: 

These findings support the conclusion that small regions of cortex investigated by ECoG recording may provide sufficient information about motor intentions to support brain-computer interface operations in the future. Given the small scale of the cortical region required, the requisite implanted array would be minimally invasive in terms of surgical placement of the electrode array.

10abrain-computer interface10aElectrocorticography10aMotor Cortex1 aLeuthardt, E C1 aFreudenberg, Zachary, V.1 aBundy, David, T1 aRoland, Jarod uhttp://dx.doi.org/10.3171/2009.4.FOCUS0980