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      Ventral striatum’s role in learning from gains and losses

      , , ,
      Proceedings of the National Academy of Sciences
      Proceedings of the National Academy of Sciences

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          Abstract

          Adaptive behavior requires animals to learn from experience. Ideally, learning should both promote choices that lead to rewards and reduce choices that lead to losses. Because the ventral striatum (VS) contains neurons that respond to aversive stimuli and aversive stimuli can drive dopamine release in the VS, it is possible that the VS contributes to learning about aversive outcomes, including losses. However, other work suggests that the VS may play a specific role in learning to choose among rewards, with other systems mediating learning from aversive outcomes. To examine the role of the VS in learning from gains and losses, we compared the performance of macaque monkeys with VS lesions and unoperated controls on a reinforcement learning task. In the task, the monkeys gained or lost tokens, which were periodically cashed out for juice, as outcomes for choices. They learned over trials to choose cues associated with gains, and not choose cues associated with losses. We found that monkeys with VS lesions had a deficit in learning to choose between cues that differed in reward magnitude. By contrast, monkeys with VS lesions performed as well as controls when choices involved a potential loss. We also fit reinforcement learning models to the behavior and compared learning rates between groups. Relative to controls, the monkeys with VS lesions had reduced learning rates for gain cues. Therefore, in this task, the VS plays a specific role in learning to choose between rewarding options.

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          Most cited references21

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          A Circuit Mechanism for Differentiating Positive and Negative Associations

          The ability to differentiate stimuli predicting positive or negative outcomes is critical for survival, and perturbations of emotional processing underlie many psychiatric disease states. Synaptic plasticity in the basolateral amygdala complex (BLA) mediates the acquisition of associative memories, both positive 1,2 and negative 3–7 . Different populations of BLA neurons may encode fearful or rewarding associations 8–10 , but the identifying features of these populations and the synaptic mechanisms of differentiating positive and negative emotional valence have remained an enigma. Here, we show that BLA neurons projecting to the nucleus accumbens (NAc projectors) or the centromedial amygdala (CeM projectors) underwent opposing synaptic changes following fear or reward conditioning. We found that photostimulation of NAc projectors supports positive reinforcement while photostimulation of CeM projectors mediates negative reinforcement. Photoinhibition of CeM projectors impaired fear conditioning and enhanced reward conditioning. We then characterized these functionally-distinct neuronal populations by comparing their electrophysiological, morphological and genetic features. We provide a mechanistic explanation for the representation of positive and negative associations within the amygdala.
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            Divergent Routing of Positive and Negative Information from the Amygdala during Memory Retrieval.

            Although the basolateral amygdala (BLA) is known to play a critical role in the formation of memories of both positive and negative valence, the coding and routing of valence-related information is poorly understood. Here, we recorded BLA neurons during the retrieval of associative memories and used optogenetic-mediated phototagging to identify populations of neurons that synapse in the nucleus accumbens (NAc), the central amygdala (CeA), or ventral hippocampus (vHPC). We found that despite heterogeneous neural responses within each population, the proportions of BLA-NAc neurons excited by reward predictive cues and of BLA-CeA neurons excited by aversion predictive cues were higher than within the entire BLA. Although the BLA-vHPC projection is known to drive behaviors of innate negative valence, these neurons did not preferentially code for learned negative valence. Together, these findings suggest that valence encoding in the BLA is at least partially mediated via divergent activity of anatomically defined neural populations.
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              Basolateral amygdala neurons facilitate reward-seeking behavior by exciting nucleus accumbens neurons.

              Both the nucleus accumbens (NAc) and basolateral amygdala (BLA) contribute to learned behavioral choice. Neurons in both structures that encode reward-predictive cues may underlie the decision to respond to such cues, but the neural circuits by which the BLA influences reward-seeking behavior have not been established. Here, we test the hypothesis that the BLA drives NAc neuronal responses to reward-predictive cues. First, using a disconnection experiment, we show that the BLA and dopamine projections to the NAc interact to promote the reward-seeking behavioral response. Next, we demonstrate that BLA neuronal responses to cues precede those of NAc neurons and that cue-evoked excitation of NAc neurons depends on BLA input. These results indicate that BLA input is required for dopamine to enhance the cue-evoked firing of NAc neurons and that this enhanced firing promotes reward-seeking behavior.
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                Author and article information

                Journal
                Proceedings of the National Academy of Sciences
                Proc Natl Acad Sci USA
                Proceedings of the National Academy of Sciences
                0027-8424
                1091-6490
                December 26 2018
                December 26 2018
                December 26 2018
                December 13 2018
                : 115
                : 52
                : E12398-E12406
                Article
                10.1073/pnas.1809833115
                6310791
                30545910
                27d7beac-9d1b-43e3-a5c0-f15437f78977
                © 2018

                Free to read

                http://www.pnas.org/site/misc/userlicense.xhtml

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