Reinforcement Learning during Adolescence in Rats.

The most dynamic period of postnatal brain development occurs during adolescence, the period between childhood and adulthood. Neuroimaging studies have observed morphologic and functional changes during adolescence, and it is believed that these changes serve to improve the functions of circuits that underlie decision-making. Direct evidence in support of this hypothesis, however, has been limited because most preclinical decision-making paradigms are not readily translated to humans. Here, we developed a reversal-learning protocol for the rapid assessment of adaptive choice behavior in dynamic environments in rats as young as postnatal day 30. A computational framework was used to elucidate the reinforcement-learning mechanisms that change in adolescence and into adulthood. Using a cross-sectional and longitudinal design, we provide the first evidence that value-based choice behavior in a reversal-learning task improves during adolescence in male and female Long-Evans rats and demonstrate that the increase in reversal performance is due to alterations in value updating for positive outcomes. Furthermore, we report that reversal-learning trajectories in adolescence reliably predicted reversal performance in adulthood. This novel behavioral protocol provides a unique platform for conducting biological and systems-level analyses of the neurodevelopmental mechanisms of decision-making.SIGNIFICANCE STATEMENT The neurodevelopmental adaptations that occur during adolescence are hypothesized to underlie age-related improvements in decision-making, but evidence to support this hypothesis has been limited. Here, we describe a novel behavioral protocol for rapidly assessing adaptive choice behavior in adolescent rats with a reversal-learning paradigm. Using a computational approach, we demonstrate that age-related changes in reversal-learning performance in male and female Long-Evans rats are linked to specific reinforcement-learning mechanisms and are predictive of reversal-learning performance in adulthood. Our behavioral protocol provides a unique platform for elucidating key components of adolescent brain function.

Orbitofrontal Circuits Control Multiple Reinforcement-Learning Processes.

Adaptive decision making in dynamic environments requires multiple reinforcement-learning steps that may be implemented by dissociable neural circuits. Here, we used a novel directionally specific viral ablation approach to investigate the function of several anatomically defined orbitofrontal cortex (OFC) circuits during adaptive, flexible decision making in rats trained on a probabilistic reversal learning task. Ablation of OFC neurons projecting to the nucleus accumbens selectively disrupted performance following a reversal, by disrupting the use of negative outcomes to guide subsequent choices. Ablation of amygdala neurons projecting to the OFC also impaired reversal performance, but due to disruptions in the use of positive outcomes to guide subsequent choices. Ablation of OFC neurons projecting to the amygdala, by contrast, enhanced reversal performance by destabilizing action values. Our data are inconsistent with a unitary function of the OFC in decision making. Rather, distinct OFC-amygdala-striatal circuits mediate distinct components of the action-value updating and maintenance necessary for decision making.