@inbook {3548,
	title = {Near-Instantaneous Classification of Perceptual States from Cortical Surface Recordings},
	booktitle = {Brain-Computer Interface Research: A State-of-the-Art Summary},
	year = {2015},
	pages = {105-114},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {New York City, NY},
	abstract = {Human visual processing is of such complexity that, despite decades of focused research, many basic questions remain unanswered. Although we know that the inferotemporal cortex is a key region in object recognition, we don{\textquoteright}t fully understand its physiologic role in brain function, nor do we have the full set of tools to explore this question. Here we show that electrical potentials from the surface of the human brain contain enough information to decode a subject{\textquoteright}s perceptual state accurately, and with fine temporal precision. Electrocorticographic (ECoG) arrays were placed over the inferotemporal cortical areas of seven subjects. Pictures of faces and houses were quickly presented while each subject performed a simple visual task. Results showed that two well-known types of brain signals{\textemdash}event-averaged broadband power and event-averaged raw potential{\textemdash}can independently or together be used to classify the presented image. When applied to continuously recorded brain activity, our decoding technique could accurately predict whether each stimulus was a face, house, or neither, with ~20 ms timing error. These results provide a roadmap for improved brain-computer interfacing tools to help neurosurgeons, research scientists, engineers, and, ultimately, patients.},
	keywords = {broadband power, Electrocorticography, event-related potential, fusiform cortex, human vision},
	isbn = {978-3-319-25188-2},
	issn = {978-3-319-25190-5},
	doi = {10.1007/978-3-319-25190-5_10},
	url = {http://link.springer.com/chapter/10.1007/978-3-319-25190-5_10},
	author = {Miller, Kai J and Gerwin Schalk and Hermes, Dora and Ojemann, Jeffrey G and Rao, Rajesh P N}
}
@conference {3438,
	title = {Three cases of feature correlation in an electrocorticographic BCI.},
	booktitle = {Engineering in Medicine and Biology Society, 2008.},
	year = {2008},
	month = {08/2008},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Vancouver, BC},
	abstract = {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.},
	keywords = {Adolescent, Adult, Algorithms, automated pattern recognition, control systems, decorrelation, Electrocardiography, Electrodes, Electroencephalography, evoked motor potentials, Feedback, Female, frequency, hospitals, Humans, Male, Middle Aged, Motor Cortex, Signal Processing, Statistics as Topic, Task Performance and Analysis, Tongue, User-Computer Interface},
	doi = {10.1109/IEMBS.2008.4650415},
	url = {http://www.ncbi.nlm.nih.gov/pubmed/19163918},
	author = {Miller, Kai J and Blakely, Timothy and Gerwin Schalk and den Nijs, Marcel and Rao, Rajesh PN and Ojemann, Jeffrey G}
}
