Luke T. Coddington

The paper derives a scaling law for biological learning by linking inductive bias to learning speed and validates it using human and mouse datasets.

The paper develops an algorithm inspired by mouse behavior to rapidly infer navigational goals through Bayesian inference and trajectory composition.

The paper shows that male and female mice use different synaptic plasticity mechanisms for fear extinction, with males showing structural remodeling and GRIN2B dependence, while females do not.

This study shows that mesolimbic dopamine adjusts the rate of learning from action in mice, supporting a model where dopamine signals set an adaptive learning rate rather than serving as an error signal.

This study shows that dopamine neuron activity in early learning reflects reward expectation based on sensory and action initiation cues rather than reward prediction errors.