We study how animals infer patterns and priors from their environment and use them to guide their behaviour. Our work focuses on:
Sensory inference and memory organisation
Neuronal computations underlying learning across timescales
Integration of priors with sensory inputs and internal models
Our approach combines:
High-throughput behavioural training
Circuit-level monitoring and manipulation
Theory-driven hypotheses and computational modelling
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