Biology subjects

Donoso, J. R.

Publications and source records attributed to Donoso, J. R..

4 recordsLinked to original sources

bioRxiv2025

Place cell activity and behaviour during task acquisition and extinction learning predict renewal outcome

Extinction learning (EL) and the subsequent renewal of learned behaviours are crucial for adaptive responding, yet the underlying neural mechanisms that differentiate successful renewal from its absence remain unclear. Here, we explored the behavioral and neurophysiological basis of spatial appetitive EL, as well as renewal failure and renewal success. We recorded place cell activity from hippocampal area CA1 in male rats that performed a context-dependent spatial appetitive learning task in a T-maze (rewarded context A), followed by EL (unrewarded context B), and subsequent renewal testing (unrewarded context A). Half of the animals exhibited significant renewal ("renewers") and the other half failed to renew ("non-renewers"). Our findings reveal fundamental differences in learning strategies between groups revealed by differences in both spatial behavior and in place cell activity during both initial acquisition and subsequent EL. Specifically, renewers exhibited a context-based EL strategy, whereas non-renewers followed a goal-directed strategy. The spatial distribution of hippocampal place cell activity differed significantly between groups, indicating the hippocampus role in the learning processes. Furthermore, renewers exhibited a greater extent of global remapping of place cells compared to non-renewers, consistent with predictions by our computational modeling. This suggests that global remapping serves as a key neural mechanism underlying effective renewal, allowing for the segregation of distinct memories and preventing the generalization of extinction. Our results highlight how hippocampal place cell dynamics during acquisition and EL predict later behavioral renewal outcomes, providing critical insights into the neural basis of memory updating and contextual control over learned behaviors. Significance StatementThis study reveals that individual differences in associative learning strategies determine the outcome of memory renewal/re-activation. After first learning, and then extinguishing, a spatial learning task in two different contexts, some animals renewed their behavior when returned to the acquisition context ("renewers"), while others did not ("non-renewers"). Intriguingly, hippocampal place cell activity during acquisition and extinction learning predicted the subsequent renewal efficacy in these distinct animal groups. In particular, renewers exhibited more global remapping than non-renewers, a neural mechanism that segregates memories from different contexts and prevents over-generalization of extinction. These findings provide critical insights into how the hippocampus supports context-dependent memory acquisition and updating, providing new insights into the physiological basis of individual differences in behavioral flexibility.

neuroscience↗

bioRxiv2025

Divide and conquer: How avian 'prefrontal' and hippocampal neurons process extinction learning in complementary ways

Context-dependent extinction learning enables organisms to acquire an inhibition of responding to cues that no longer signal reward in specific environmental settings. Both the hippocampus and the prefrontal cortex play key but complementary roles in encoding extinction. To understand what drives the differential contributions of these two structures, we recorded single-unit responses from the pigeon hippocampus (HPC) and the prefrontal nidopallium caudolaterale (NCL), while the animals were engaged in a repeated appetitive ABA extinction learning paradigm. HPC carried more information about experimental phases (acquisition (context A), extinction (context B), and renewal (context A)) than NCL. In addition, hippocampal neurons with mixed selectivity integrated all contextual stimuli and conditioned cues, thereby possibly enabling context integration into phase-dependent extinction events. The mixed selectivity pattern of NCL neurons differed: They encoded all relevant task parameters separately, thereby possibly enabling the weighing and deciding between response alternatives. Repeatedly testing the same animals over many months enabled us to reveal that the activity of NCL neurons increasingly became predictive of the number of responses that animals made during renewal. Thus, NCL neurons possibly assumed a meta-learning ability that enabled a behavioral adaption to the deeper task structure that always followed the sequence of acquisition[->]extinction[->]renewal. Our results make it likely that different processing strategies of hippocampus and prefrontal NCL enable a differential encoding of experimental phase, context, decision-making, and meta-learning during extinction learning.

neuroscience↗

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↗