In our efforts to understand the psychology and neurobiology of learning, memory, and cognitive control, we adopt a multi-modal approach that combines behavior, including in virtual environments, with functional and structural magnetic resonance imaging (MRI) and with scalp and intracranial electroencephalography (EEG). Computational modeling and machine learning approaches –– multivariate pattern classification and pattern similarity analyses –– are leveraged to relate neural signals to cognition and behavior, providing quantitative assays of mnemonic mechanisms and representations.
Building and Retrieving Memories
Attention, Memory, and Multitasking
Stanford Aging & Memory Study
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