Unraveling the Role of the Hippocampus in Reversal Learning. - Vila-Ballo, Adria; Mas-Herrero, Ernest; Ripollés, Pablo; Simó, Marta; Miró, Júlia; Cucurell, David; López-Barroso, Diana; Juncadella, Montserrat; Marco-Pallarés, Josep; Falip, Mercé; Rodríguez-Fornells, Antoni (Society for Neuroscience (SfN), 2017)
Research in reversal learning has mainly focused on the functional role of dopamine and striatal structures in driving behavior on the basis of classic reinforcement learning mechanisms. However, recent evidence indicates that, beyond classic reinforcement learning adaptations, individuals may also learn the inherent task structure and anticipate the occurrence of reversals. A candidate structure to support such task representation is the hippocampus, which might create a flexible representation of the environment that can be adaptively applied to goaldirected behavior.Toinvestigate the functional role of thehippocampusin the implementation of anticipatory strategies in reversal learning,we first studied, in 20 healthy individuals (11 women), whether the gray matter anatomy and volume of the hippocampus were related to anticipatory strategies in a reversal learning task. Second,wetested 20 refractory temporal lobe epileptic patients (11women)with unilateral hippocampal sclerosis, who served as a hippocampal lesion model. Our results indicate that healthy participants were able to learn the task structure and useit toguidetheirbehaviorandoptimizetheirperformance.Participants’ ability toadoptanticipatory strategies correlatedwiththegraymatter volumeof the hippocampus. In contrast, hippocampal patients were unable to grasp the higher-order structure of the task with thesamesuccess than controls. Present results indicate that the hippocampus is necessary to respond in an appropriately flexible manner to high-order environments, and disruptions in this structure can render behavior habitual and inflexible.
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Keywords: Epilepsia; Hipocampo (Cerebro); Aprendizaje; Neurociencias; Epilepsy; Flexible behavior; Hippocampus; Model-based strategies; Reinforcement learning; Reversal learning