Publications

Survival requires balancing reward seeking and threat avoidance, yet how distinct dopamine systems coordinate to support this remains unclear. Using a naturalistic foraging paradigm in which mice pursue water reward under threat from a monster object, we...

Animals, including humans, use coordinated facial movements to sample the environment, ingest nutrients, and communicate. Rodents, in particular, produce rhythmic facial movements during spontaneous behavior and cognitive tasks. Measuring these movements...

Postural control circuitry performs the essential function of maintaining balance and body position in response to perturbations that are either self-generated (e.g., reaching to pick up an object) or externally delivered (e.g., being pushed by another...

Animals exposed to pairings of a neutral stimulus with reward acquire a conditioned response to the neutral stimulus. A prominent hypothesis, formalized in the Temporal Difference (TD) learning algorithm, is that animals learn to predict the future reward...

The ability to estimate the value associated with a specific stimulus or action is essential for adaptive behavior. Value can be updated either incrementally through experience or rapidly by inference based on latent environmental structure. Yet, how the...

Caloric depletion induces behavioral changes that help an animal find food and restore its homeostatic balance. Hunger increases exploration and risk-taking behavior, allowing an animal to forage for food despite risks; however, it is unknown which neural...

The capacity to adapt behavior across different contexts is a fundamental feature of intelligence and is crucial for animal life, yet the mechanisms by which neural circuits are contextually reconfigured to alter their function are poorly understood. As a...

The neurotransmitter dopamine plays a major role in learning by acting as a teaching signal to update the brain’s predictions about rewards. A leading theory proposes that this process is analogous to a reinforcement learning algorithm called temporal...

Patch foraging is a ubiquitous decision-making process in which animals decide when to abandon a resource patch of diminishing value to pursue an alternative. We developed a virtual foraging task in which mouse behavior varied systematically with patch...

A hallmark of various psychiatric disorders is biased future predictions. Here we examined the mechanisms for biased value learning using reinforcement learning models incorporating recent findings on synaptic plasticity and opponent circuit mechanisms in...

To thrive in complex environments, animals and artificial agents must learn to act adaptively to maximize fitness and rewards. Such adaptive behaviour can be learned through reinforcement learning, a class of algorithms that has been successful at...

The widespread adoption of deep learning to model neural activity often relies on “black-box” approaches that lack an interpretable connection between neural activity and network parameters. Here, we propose using algorithm unrolling, a method for...