A Neuro-computational Account of Arbitration between Choice Imitation and Goal Emulation during Human Observational Learning - Charpentier, Caroline J.; Iigaya, Kiyohito; O’Doherty, John P. (Neuron (Cambridge, Mass.), 2020)
When individuals learn from observing the behavior of others, they deploy at least two distinct strategies. Choice imitation involves repeating other agents’ previous actions, whereas emulation proceeds from inferring their goals and intentions. Despite the prevalence of observational learning in humans and other social animals, a fundamental question remains unaddressed: how does the brain decide which strategy to use in a given situation? In two fMRI studies (the second a pre-registered replication of the first), we identify a neuro-computational mechanism underlying arbitration between choice imitation and goal emulation. Computational modeling, combined with a behavioral task that dissociated the two strategies, revealed that control over behavior was adaptively and dynamically weighted toward the most reliable strategy. Emulation reliability, the model’s arbitration signal, was represented in the ventrolateral prefrontal cortex, temporoparietal junction, and rostral cingulate cortex. Our replicated findings illuminate the computations by which the brain decides to imitate or emulate others. •Replicable evidence of arbitration between choice imitation and goal emulation•Control over behavior is adaptively weighted toward the most reliable strategy•Distinct brain networks implement each strategy’s learning signals in parallel•Arbitration is driven by variations in emulation reliability in rvlPFC, ACC, and TPJ Charpentier et al. show, in two independent studies, that people learn from observing others by flexibly deploying one of two strategies, imitation or emulation, depending on the conditions of the environment. By tracking changes in the reliability of emulation, fronto-parietal brain regions assign control to the most reliable strategy.