02134nas 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_1007936nas a2200361 4500008004100000022001400041245009600055210006900151260001200220300001100232490000800243520694900251653001507200653001007215653002807225653002007253653001007273653002507283653002407308653001107332653001107343653000907354653001607363653001907379653001607398100001607414700001907430700002207449700001707471700001707488700002107505856004807526 2010 eng d a1091-649000aCortical activity during motor execution, motor imagery, and imagery-based online feedback.0 aCortical activity during motor execution motor imagery and image c03/2010 a4430-50 v1073 a

Imagery of motor movement plays an important role in learning of complex motor skills, from learning to serve in tennis to perfecting a pirouette in ballet. What and where are the neural substrates that underlie motor imagery-based learning? We measured electrocorticographic cortical surface potentials in eight human subjects during overt action and kinesthetic imagery of the same movement, focusing on power in "high frequency" (76-100 Hz) and "low frequency" (8-32 Hz) ranges. We quantitatively establish that the spatial distribution of local neuronal population activity during motor imagery mimics the spatial distribution of activity during actual motor movement. By comparing responses to electrocortical stimulation with imagery-induced cortical surface activity, we demonstrate the role of primary motor areas in movement imagery. The magnitude of imagery-induced cortical activity change was approximately 25% of that associated with actual movement. However, when subjects learned to use this imagery to control a computer cursor in a simple feedback task, the imagery-induced activity change was significantly augmented, even exceeding that of overt movement.

10aAdolescent10aAdult10aBiofeedback, Psychology10aCerebral Cortex10aChild10aElectric Stimulation10aElectrocardiography10aFemale10aHumans10aMale10aMiddle Aged10aMotor Activity10aYoung Adult1 aMiller, K J1 aSchalk, Gerwin1 aFetz, Eberhard, E1 aNijs, Marcel1 aOjemann, J G1 aRao, Rajesh, P N uhttp://www.ncbi.nlm.nih.gov/pubmed/2016008401979nas a2200373 4500008004100000022001400041245011800055210006900173260000900242300001100251490000900262520077500271653001501046653002401061653003001085653001101115653000901126653003501135653003201170653002301202653003101225653003201256653002801288653001801316100002001334700001701354700001901371700002001390700002401410700001701434700001701451700002101468856011601489 2009 eng d a1557-170X00aDetection of spontaneous class-specific visual stimuli with high temporal accuracy in human electrocorticography.0 aDetection of spontaneous classspecific visual stimuli with high  c2009 a6465-80 v20093 aMost brain-computer interface classification experiments from electrical potential recordings have been focused on the identification of classes of stimuli or behavior where the timing of experimental parameters is known or pre-designated. Real world experience, however, is spontaneous, and to this end we describe an experiment predicting the occurrence, timing, and types of visual stimuli perceived by a human subject from electrocorticographic recordings. All 300 of 300 presented stimuli were correctly detected, with a temporal precision of order 20 ms. The type of stimulus (face/house) was correctly identified in 95% of these cases. There were approximately 20 false alarm events, corresponding to a late 2nd neuronal response to a previously identified event.10aAlgorithms10aElectrocardiography10aEvoked Potentials, Visual10aHumans10aMale10aPattern Recognition, Automated10aPattern Recognition, Visual10aPhotic Stimulation10aReproducibility of Results10aSensitivity and Specificity10aUser-Computer Interface10aVisual Cortex1 aMiller, John, W1 aHermes, Dora1 aSchalk, Gerwin1 aRamsey, Nick, F1 aJagadeesh, Bharathi1 aNijs, Marcel1 aOjemann, J G1 aRao, Rajesh, P N uhttps://neurotechcenter.org/publications/2009/detection-spontaneous-class-specific-visual-stimuli-high-temporal02173nas a2200361 4500008004100000022001400041245007200055210006900127260000900196300001200205520109300217653001501310653001001325653001501335653002401350653002901374653001101403653001101414653000901425653001601434653001701450653003501467653002401502653003401526653002801560100002001588700002101608700001901629700001701648700002101665700001701686856010801703 2008 eng d a1557-170X00aThree cases of feature correlation in an electrocorticographic BCI.0 aThree cases of feature correlation in an electrocorticographic B c2008 a5318-213 aThree human subjects participated in a closed-loop brain computer interface cursor control experiment mediated by implanted subdural electrocorticographic arrays. The paradigm consisted of several stages: baseline recording, hand and tongue motor tasks as the basis for feature selection, two closed-loop one-dimensional feedback experiments with each of these features, and a two-dimensional feedback experiment using both of the features simultaneously. The two selected features were simple channel and frequency band combinations associated with change during hand and tongue movement. Inter-feature correlation and cross-correlation between features during different epochs of each task were quantified for each stage of the experiment. Our anecdotal, three subject, result suggests that while high correlation between horizontal and vertical control signal can initially preclude successful two-dimensional cursor control, a feedback-based learning strategy can be successfully employed by the subject to overcome this limitation and progressively decorrelate these control signals.10aAdolescent10aAdult10aAlgorithms10aElectrocardiography10aEvoked Potentials, Motor10aFemale10aHumans10aMale10aMiddle Aged10aMotor Cortex10aPattern Recognition, Automated10aStatistics as Topic10aTask Performance and Analysis10aUser-Computer Interface1 aMiller, John, W1 aBlakely, Timothy1 aSchalk, Gerwin1 aNijs, Marcel1 aRao, Rajesh, P N1 aOjemann, J G uhttps://neurotechcenter.org/publications/2008/three-cases-feature-correlation-electrocorticographic-bci02238nas a2200325 4500008004100000022001400041245007500055210006900130260001200199300001200211490000700223520137400230653001001604653001801614653001101632653001101643653000901654653001601663653001701679653001301696100002001709700001901729700001901748700002101767700002601788700001301814700002001827700001701847856004801864 2007 eng d a1529-240100aSpectral Changes in Cortical Surface Potentials During Motor Movement.0 aSpectral Changes in Cortical Surface Potentials During Motor Mov c02/2007 a2424-320 v273 a

In the first large study of its kind, we quantified changes in electrocorticographic signals associated with motor movement across 22 subjects with subdural electrode arrays placed for identification of seizure foci. Patients underwent a 5-7 d monitoring period with array placement, before seizure focus resection, and during this time they participated in the study. An interval-based motor-repetition task produced consistent and quantifiable spectral shifts that were mapped on a Talairach-standardized template cortex. Maps were created independently for a high-frequency band (HFB) (76-100 Hz) and a low-frequency band (LFB) (8-32 Hz) for several different movement modalities in each subject. The power in relevant electrodes consistently decreased in the LFB with movement, whereas the power in the HFB consistently increased. In addition, the HFB changes were more focal than the LFB changes. Sites of power changes corresponded to stereotactic locations in sensorimotor cortex and to the results of individual clinical electrical cortical mapping. Sensorimotor representation was found to be somatotopic, localized in stereotactic space to rolandic cortex, and typically followed the classic homunculus with limited extrarolandic representation.

10aAdult10aBrain Mapping10aFemale10aHumans10aMale10aMiddle Aged10aMotor Cortex10aMovement1 aMiller, John, W1 aLeuthardt, E C1 aSchalk, Gerwin1 aRao, Rajesh, P N1 aAnderson, Nicholas, R1 aMoran, D1 aMiller, John, W1 aOjemann, J G uhttp://www.ncbi.nlm.nih.gov/pubmed/1732944101844nas a2200289 4500008004100000022001400041245008100055210006900136260001200205300001000217490000700227520100900234653002001243653002701263653001301290653002201303653001101325653003101336653002801367653001501395100001901410700002001429700001901449700002101468700001701489856004801506 2006 eng d a1534-432000aElectrocorticography-based brain computer interface--the Seattle experience.0 aElectrocorticographybased brain computer interfacethe Seattle ex c06/2006 a194-80 v143 a

Electrocorticography (ECoG) has been demonstrated to be an effective modality as a platform for brain-computer interfaces (BCIs). Through our experience with ten subjects, we further demonstrate evidence to support the power and flexibility of this signal for BCI usage. In a subset of four patients, closed-loop BCI experiments were attempted with the patient receiving online feedback that consisted of one-dimensional cursor movement controlled by ECoG features that had shown correlation with various real and imagined motor and speech tasks. All four achieved control, with final target accuracies between 73%-100%. We assess the methods for achieving control and the manner in which enhancing online control can be accomplished by rescreening during online tasks. Additionally, we assess the relevant issues of the current experimental paradigm in light of their clinical constraints.

10aCerebral Cortex10aElectroencephalography10aEpilepsy10aEvoked Potentials10aHumans10aTherapy, Computer-Assisted10aUser-Computer Interface10aWashington1 aLeuthardt, E C1 aMiller, John, W1 aSchalk, Gerwin1 aRao, Rajesh, P N1 aOjemann, J G uhttp://www.ncbi.nlm.nih.gov/pubmed/16792292