Donoso, J. R. | Search bioRxiv

bioRxiv2020

Context-dependent extinction learning emerging from raw sensory inputs: A reinforcement learning approach

The context-dependence of extinction learning has been well studied and requires the hippocampus. However, the underlying neural mechanisms are still poorly understood. Using memory-driven reinforcement learning and deep neural networks, we developed a model that learns to navigate autonomously in biologically realistic VR environments based on raw camera inputs alone. Neither is context represented explicitly in our model, nor is context change signaled. We find that memory-intact agents learn distinct context representations, and develop ABA renewal, whereas memory-impaired agents do not. These findings reproduce the behavior of control and hippocampal animals, respectively. We therefore propose that the role of the hippocampus in the context-dependence of extinction learning might stem from its function in episodic-like memory and not in context-representation per se. We conclude that context-dependence can emerge from raw visual inputs.

neuroscience↗

bioRxiv2020

Complex dynamics of choice during operant extinction and a simple associative learning account

Extinction learning, the process of ceasing an acquired behavior in response to altered reinforcement contingencies, is not only essential for survival in a changing environment, but also plays a fundamental role in the treatment of pathological behaviors. During therapy and other forms of training involving extinction, subjects are typically exposed to several sessions with a similar structure. The effects of this repeated exposure are not well understood. Here, we studied the behavior of pigeons across several sessions of a discrimination learning task in context A, extinction in context B, and a return to context A to test the context-dependent return of the learned responses (ABA renewal). By focusing on individual learning curves across animals, we uncovered a session-dependent variability of behavior: (1) During extinction, pigeons preferred the unrewarded alternative choice in one-third of the sessions, predominantly during the first one. (2) In later sessions, abrupt transitions of behavior at the onset of context B emerged, and (3) the renewal effect decayed as sessions progressed. We show that the observed results can be parsimoniously accounted for by a computational model based only on associative learning between stimuli and actions. Our work thus demonstrates the critical importance of studying the trial-by-trial dynamics of learning in individual sessions, and the power of "simple" associative learning processes.

animal behavior and cognition↗