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The nucleus accumbens shell (NAcSh) integrates reward information through diverse and specialized neuronal ensembles, influencing decision-making. By training rats in a probabilistic choice task and recording NAcSh neuronal activity, we found that rats adapt their choices based solely on the presence or absence of a sucrose reward, suggesting they build an internal representation of reward likelihood. We further demonstrate that NAcSh ensembles dynamically process different aspects of reward-guided behavior, with changes in composition and functional connections observed throughout the reinforcement learning process. The NAcSh forms a highly connected network characterized by a heavy-tailed distribution and the presence of neuronal hubs, facilitating efficient information flow. Reward delivery enhances mutual information, indicating increased communication between ensembles and network synchronization, whereas reward omission decreases it. Our findings reveal how reward information flows through dynamic NAcSh ensembles, whose flexible membership adapts as the rat learns to obtain rewards (energy) in an ever-changing environment. [Display omitted] • NAcSh neuronal ensembles act as distinct modules to process reward-guided behavior • NAcSh network exhibits hubs and small-world and heavy-tailed distribution properties • Sucrose evokes higher mutual information (MI) in the NAcSh network than omission • Learning strengthens MI during reward delivery and weakens it during reward omission Arroyo et al. show that NAcSh neuronal ensembles are distinct modules, each processing specific aspects of reward-guided behavior. These ensembles adapt during learning, forming different functional connections based on reward outcomes. The NAcSh network has a heavy-tailed distribution and central hubs that facilitate reward information flow. [ABSTRACT FROM AUTHOR]

We provide a proof of principle for an evolutionary systems theory (EST) of depression. This theory suggests that normative depressive symptoms counter socioenvironmental volatility by increasing interpersonal support via social signalling and that this response depends upon the encoding of uncertainty about social contingencies, which can be targeted by neuromodulatory antidepressants. We simulated agents that committed to a series of decisions in a social two-arm bandit task before and after social adversity, which precipitated depressive symptoms. Responses to social adversity were modelled under various combinations of social support and pharmacotherapy. The normative depressive phenotype responded positively to social support and simulated treatments with antidepressants. Attracting social support and administering antidepressants also alleviated anhedonia and social withdrawal, speaking to improvements in interpersonal relationships. These results support the EST of depression by demonstrating that following adversity, normative depressed mood preserved social inclusion with appropriate interpersonal support or pharmacotherapy.

We provide a proof of principle for an evolutionary systems theory (EST) of depression. This theory suggests that normative depressive symptoms counter socioenvironmental volatility by increasing interpersonal support via social signalling and that this response depends upon the encoding of uncertainty about social contingencies, which can be targeted by neuromodulatory antidepressants. We simulated agents that committed to a series of decisions in a social two-arm bandit task before and after social adversity, which precipitated depressive symptoms. Responses to social adversity were modelled under various combinations of social support and pharmacotherapy. The normative depressive phenotype responded positively to social support and simulated treatments with antidepressants. Attracting social support and administering antidepressants also alleviated anhedonia and social withdrawal, speaking to improvements in interpersonal relationships. These results support the EST of depression by demonstrating that following adversity, normative depressed mood preserved social inclusion with appropriate interpersonal support or pharmacotherapy. [ABSTRACT FROM AUTHOR]

Abstract: Adaptive designs are effective mechanisms for flexibly allocating experimental resources. In clinical trials particularly, such designs allow researchers to balance short- and long-term goals. Unfortunately, fully sequential strategies require outcomes from all previous allocations prior to the next allocation. This can prolong an experiment unduly. As a result, we seek designs for models that specifically incorporate delays. We utilize a delay model in which patients arrive according to a Poisson process and their response times are exponential. We examine three designs with an eye towards minimizing patient losses: a delayed two-armed bandit rule which is optimal for the model and objective of interest; a newly proposed hyperopic rule; and a randomized play-the-winner rule. The results show that, except when the delay rate is several orders of magnitude different than the patient arrival rate, the delayed response bandit is nearly as efficient as the immediate response bandit. The delayed hyperopic design also performs extremely well throughout the range of delays, despite the fact that the rate of delay is not one of its design parameters. The delayed randomized play-the-winner rule is far less efficient than either of the other methods. [Copyright &y& Elsevier]