Classification of EEG recordings without perfect time-locking
Date
2012
Authors
Zhu, Manli
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
It has been established that neural response is time-locked to stimulus; however, the latencyin between may vary because of stimulus strength, subject fatigue, distraction, etc.
Instead of assuming perfect time-locking between stimulus and its neural response, we proposed here a statistical model that admits latency variation.
We tested the approach on an EEG data set from an image Rapid Serial Visual Presentation (RSVP) experiment. Results show that the proposed approach consistently outperforms those relying on perfect time-locking.
In addition, our approach can predict the stimulus' onset time when this information is not available.
Description
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Keywords
discriminate, EEG, Gaussian distribution, neural response, stimulus, time-locking
Citation
Department
Electrical and Computer Engineering