%0 Book Section %B Brain-Computer Interface Research: A State-of-the-Art Summary %D 2015 %T Near-Instantaneous Classification of Perceptual States from Cortical Surface Recordings %A Miller, Kai J %A Gerwin Schalk %A Hermes, Dora %A Ojemann, Jeffrey G %A Rao, Rajesh P N %K broadband power %K Electrocorticography %K event-related potential %K fusiform cortex %K human vision %X Human visual processing is of such complexity that, despite decades of focused research, many basic questions remain unanswered. Although we know that the inferotemporal cortex is a key region in object recognition, we don’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. %B Brain-Computer Interface Research: A State-of-the-Art Summary %I Springer International Publishing %C New York City, NY %P 105-114 %@ 978-3-319-25188-2 %G eng %U http://link.springer.com/chapter/10.1007/978-3-319-25190-5_10 %R 10.1007/978-3-319-25190-5_10 %0 Journal Article %J Proc Natl Acad Sci U S A %D 2010 %T Cortical activity during motor execution, motor imagery, and imagery-based online feedback. %A Miller, K.J. %A Gerwin Schalk %A Fetz, Eberhard E %A den Nijs, Marcel %A Ojemann, J G %A Rao, Rajesh P N %K Adolescent %K Adult %K Biofeedback, Psychology %K Cerebral Cortex %K Child %K Electric Stimulation %K Electrocardiography %K Female %K Humans %K Male %K Middle Aged %K Motor Activity %K Young Adult %X

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.

%B Proc Natl Acad Sci U S A %V 107 %P 4430-5 %8 03/2010 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/20160084 %N 9 %R 10.1073/pnas.0913697107 %0 Conference Proceedings %B Conf Proc IEEE Eng Med Biol Soc %D 2009 %T Detection of spontaneous class-specific visual stimuli with high temporal accuracy in human electrocorticography. %A Miller, John W %A Hermes, Dora %A Gerwin Schalk %A Ramsey, Nick F %A Jagadeesh, Bharathi %A den Nijs, Marcel %A Ojemann, J G %A Rao, Rajesh P N %K Algorithms %K Electrocardiography %K Evoked Potentials, Visual %K Humans %K Male %K Pattern Recognition, Automated %K Pattern Recognition, Visual %K Photic Stimulation %K Reproducibility of Results %K Sensitivity and Specificity %K User-Computer Interface %K Visual Cortex %X Most 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. %B Conf Proc IEEE Eng Med Biol Soc %V 2009 %P 6465-8 %8 2009 %G eng %R 10.1109/IEMBS.2009.5333546 %0 Conference Proceedings %B Conf Proc IEEE Eng Med Biol Soc %D 2008 %T Three cases of feature correlation in an electrocorticographic BCI. %A Miller, John W %A Blakely, Timothy %A Gerwin Schalk %A den Nijs, Marcel %A Rao, Rajesh P N %A Ojemann, J G %K Adolescent %K Adult %K Algorithms %K Electrocardiography %K Evoked Potentials, Motor %K Female %K Humans %K Male %K Middle Aged %K Motor Cortex %K Pattern Recognition, Automated %K Statistics as Topic %K Task Performance and Analysis %K User-Computer Interface %X Three 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. %B Conf Proc IEEE Eng Med Biol Soc %P 5318-21 %8 2008 %G eng %R 10.1109/IEMBS.2008.4650415 %0 Journal Article %J J Neurosci %D 2007 %T Spectral Changes in Cortical Surface Potentials During Motor Movement. %A Miller, John W %A Leuthardt, E C %A Gerwin Schalk %A Rao, Rajesh P N %A Nicholas R Anderson %A Moran, D %A Miller, John W %A Ojemann, J G %K Adult %K Brain Mapping %K Female %K Humans %K Male %K Middle Aged %K Motor Cortex %K Movement %X

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.

%B J Neurosci %V 27 %P 2424-32 %8 02/2007 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/17329441 %N 9 %R 10.1523/JNEUROSCI.3886-06.2007 %0 Journal Article %J IEEE Trans Neural Syst Rehabil Eng %D 2006 %T Electrocorticography-based brain computer interface--the Seattle experience. %A Leuthardt, E C %A Miller, John W %A Gerwin Schalk %A Rao, Rajesh P N %A Ojemann, J G %K Cerebral Cortex %K Electroencephalography %K Epilepsy %K Evoked Potentials %K Humans %K Therapy, Computer-Assisted %K User-Computer Interface %K Washington %X

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.

%B IEEE Trans Neural Syst Rehabil Eng %V 14 %P 194-8 %8 06/2006 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/16792292 %N 2 %R 10.1109/TNSRE.2006.875536