Near-Instantaneous Classification of Perceptual States from Cortical Surface Recordings

TitleNear-Instantaneous Classification of Perceptual States from Cortical Surface Recordings
Publication TypeBook Chapter
Year of Publication2015
AuthorsMiller, KJ, Schalk, G, Hermes, D, Ojemann, JG, Rao, RPN
Book TitleBrain-Computer Interface Research: A State-of-the-Art Summary
Pagination105-114
PublisherSpringer International Publishing
CityNew York City, NY
ISBN Number978-3-319-25188-2
ISBN978-3-319-25190-5
Keywordsbroadband power, Electrocorticography, event-related potential, fusiform cortex, human vision
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’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.

URLhttp://link.springer.com/chapter/10.1007/978-3-319-25190-5_10
DOI10.1007/978-3-319-25190-5_10
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