The penumbra of learning


December 6, 2016 - 12:00pm - 1:00pm
Northwest 243
About the Speaker
Sam Gershman
Speaker Affiliation: 

Abstract: In noisy, dynamic environments, organisms must distinguish genuine change (e.g., the movement of prey) from noise (e.g., the rustling of leaves). Expectations should be updated only when the organism believes genuine change has occurred. Although individual variables can be highly unreliable, organisms can take advantage of the fact that changes tend to be correlated (e.g., movement of prey will tend to produce changes in both visual and olfactory modalities). Thus, observing a change in one variable provides information about the rate of change for other variables. This is the penumbra of learning. At the neural level, the penumbra of learning may offer an explanation for why strong plasticity in one synapse can rescue weak plasticity at another (synaptic tagging and capture). At the behavioral level, it has been observed that weak learning of one task can be rescued by novelty exposure before or after the learning task. I will describe a computational theory of synaptic tagging and capture based on the penumbra of learning, and then summarize novel behavioral evidence for the theory in humans.