Topic: rapid learning

Rapid learning confers significant advantages to animals in ecological environments. Despite the need for speed, animals appear to only slowly learn to associate rewarded actions with predictive cues. This slow learning is thought to be supported by a gradual expansion of predictive cue representation in the sensory cortex. However, evidence is growing that animals learn more rapidly than classical performance measures suggest, challenging the prevailing model of sensory cortical plasticity. Here, we investigated the relationship between learning and sensory cortical representations. We traine

Animals quickly learn to navigate to rewarding or salient landmarks in their environments. However, existing models often require thousands of trials to learn contingencies that animals learn within tens of trials, and they do so via unstructured sequences of actions that do not mimic real behavior. In this work, we study rapid learning in a hidden-target foraging task for mice in which animals learn to intercept an uncued target location within an open arena. To study the computational underpinnings of this learning, we build an agent that controls its speed and heading over time via a pre-sp