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Explore advanced EEG analysis techniques for understanding memory processing through this 30-minute webinar presented by Dr. Virginia de Sa from UC San Diego. Learn how single-trial classification methods can predict memory formation from EEG signals recorded before and during picture presentation in episodic memory tasks. Discover how discriminative dimensionality reduction enables projection of untrained data to reveal novel electrophysiological distinctions between behavioral states. Examine EEG analysis during memory testing phases, where researchers demonstrate modeling of 13 different trial classes combining objective memory performance (correct rejects, false alarms) with perceived performance (sure new, maybe new) using only three basis classifiers. Understand how projecting untrained classes onto classifiers trained on other classes helps decompose EEG signals and uncover new electrophysiological correlates of behavior. Gain insights into computational approaches that bridge machine learning, neuroscience, and cognitive science for advancing our understanding of human memory and perception. The presentation includes opportunities to earn PACE credits and provides practical applications for EEG-based brain-computer interface development.
