Mechanisms of flexible behaviour in complex environments

I aim to understand brain mechanisms of flexible behaviour in complex environments, focusing on how predictive models of the environment's structure are used for action selection. The key questions are:

- What is the computational structure of the model used for planning? Does it store local relationships between locations and use step-by-step simulation to evaluate options, or store long-range relationships allowing rapid action selection at the cost of reduced flexibility?

- What is the differential contribution of, and interaction between, medial frontal cortex and hippocampus in model-based action? Do these regions represent different levels of hierarchically organised behaviour?

- How does information in the model get translated into action? Do dopaminergic reward prediction errors, or short-term memory by recurrent cortical activity, store the output of model-based evaluations to guide choices?

I will answer these questions using a novel behavioural assay for mice, in which they choose among goals, and plan routes, in a complex maze environment ideally suited to mathematically modelling planning computations. I will characterise activity in frontal cortex and hippocampus using high-density silicon probes, and in the dopamine system using photometry, including simultaneous recordings to study the interaction between regions and optogenetic manipulations to test causality.