Topic: reward locations

Long-term potentiation (LTP) is thought to be a key plasticity mechanism underlying the formation and maintenance of hippocampal place codes. It is unclear, however, which properties of these neural codes are inherited from upstream processing and which are learned through plasticity. To disentangle these influences on place codes, we utilized a method for abolishing LTP specifically in hippocampal region CA1 of the adult mouse without affecting basal synaptic processing: conditional genetic deletion of a necessary component of the postsynaptic membrane fusion machinery, Syntaxin3 (Stx3). Surp

When rodents learn to navigate in a new environment, high place field density emerge at reward locations, fields elongate against the trajectory, and individual fields change spatial selectivity or drift while demonstrating stable behavior. Why place fields demonstrate these characteristic phenomena during learning remains elusive. We develop a model that optimizes for a normative goal, which is to maximize cumulative rewards. Place fields are modelled using Gaussian basis functions to represent spatial information of an environment, and directly synapse to an actor-critic for policy learning

Animals can learn to repeat actions that lead to rewards (model-free learning). However, animals can also learn about environmental structure without receiving immediate and explicit rewards (latent learning), and then use this knowledge to guide future reward-seeking behavior efficiently. How the brain accomplishes this is not clear, in part due to limitations in existing behavioral tasks to study latent learning in rodents. In particular, traditional latent learning tasks suffer from their “one-shot” characteristics, such that learning is typically performed and tested in one environment, pr