Our research covers many aspects of memory and perception, from working and long-term memory to mechanisms of perception and decision-making. We are especially interested in how the brain encodes individual experiences and transforms them into task-relevant representations. Our vision is to uncover how the brain transforms perceptual information into predictive memory representations that support flexible, adaptive behavior.
Research Line 1: Representational dynamics of naturalistic memories
Natural experiences require goal-directed actions within complex, sensory-rich environments. Memories of these experiences are inherently multidimensional, integrating perceptual features with abstract representations of goals, task-states, and spatiotemporal contexts. We aim to understand memory under such conditions, using an integrative framework that combines invasive electrophysiology with Deep Learning methods to explain how memory representations are formed, stored, and reinstated in the human brain.
Research Line 2: Multisensory integration and prediction
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