Research
Our goal is to gain a quantitative circuit-level understanding of neuronal mechanisms that subserve learning and decision-making. Specifically, we are interested in how the brain integrates external sensory signals with internal reward and motivational signals for making decisions, and how the brain learns to make decisions under uncertainty. We particularly focus on understanding the roles that frontostriatal circuits play during decision-making, and how neuromodulators, in particular the dopamine system, shape learning and decision-making under uncertainty.
We employ a multi-disciplinary approach including high-count electrophysiology (Neuropixels probes), cell type-specific multi-photon imaging, optogenetic manipulations, highly-controlled behavioural tasks in mice, and computational modelling of behavioural and neuronal data.
We employ a multi-disciplinary approach including high-count electrophysiology (Neuropixels probes), cell type-specific multi-photon imaging, optogenetic manipulations, highly-controlled behavioural tasks in mice, and computational modelling of behavioural and neuronal data.
