Dysfunction in the gene SCN2A, which encodes the voltage-gated sodium channel Na_v1.2, is strongly associated with neurodevelopmental disorders including autism spectrum disorder and intellectual disability (ASD/ID). This dysfunction typically manifests in these disorders as a haploinsufficiency, where loss of one copy of a gene cannot be compensated for by the other allele. Scn2a haploinsufficiency affects a range of cells and circuits across the brain, including associative neocortical circuits that are important for cognitive flexibility and decision-making behaviors. Here, we tested whether Scn2a haploinsufficiency has any effect on a dynamic foraging task that engages such circuits. Scn2a ^+/- mice and wild-type (WT) littermates were trained on a choice behavior where the probability of reward between two options varied dynamically across trials and where the location of the high reward underwent uncued reversals. Despite impairments in Scn2a-related neuronal excitability, we found that both male and female Scn2a ^+/- mice performed these tasks as well as wild-type littermates, with no behavioral difference across genotypes in learning or performance parameters. Varying the number of trials between reversals or probabilities of receiving reward did not result in an observable behavioral difference, either. These data suggest that, despite heterozygous loss of Scn2a, mice can perform relatively complex foraging tasks that make use of higher-order neuronal circuits.

Learning to predict rewards based on environmental cues is essential for survival. It is believed that animals learn to predict rewards by updating predictions whenever the outcome deviates from expectations, and that such reward prediction errors (RPEs) are signaled by the mesolimbic dopamine system-a key controller of learning. However, instead of learning prospective predictions from RPEs, animals can infer predictions by learning the retrospective cause of rewards. Hence, whether mesolimbic dopamine instead conveys a causal associative signal that sometimes resembles RPE remains unknown. We developed an algorithm for retrospective causal learning and found that mesolimbic dopamine release conveys causal associations but not RPE, thereby challenging the dominant theory of reward learning. Our results reshape the conceptual and biological framework for associative learning.