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Model-free decision making is prioritized when learning to avoid harming others

Moral behavior requires learning how our actions help or harm others. Theoretical accounts of learning propose a key division between “model-free” algorithms that cache outcome values in actions and “model-based” algorithms that map actions to outcomes. Here, we tested the engagement of these mechan...

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Detalles Bibliográficos
Autores principales: Lockwood, Patricia L., Klein-Flügge, Miriam C., Abdurahman, Ayat, Crockett, Molly J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7959560/
https://www.ncbi.nlm.nih.gov/pubmed/33055212
http://dx.doi.org/10.1073/pnas.2010890117
Descripción
Sumario:Moral behavior requires learning how our actions help or harm others. Theoretical accounts of learning propose a key division between “model-free” algorithms that cache outcome values in actions and “model-based” algorithms that map actions to outcomes. Here, we tested the engagement of these mechanisms and their neural basis as participants learned to avoid painful electric shocks for themselves and a stranger. We found that model-free decision making was prioritized when learning to avoid harming others compared to oneself. Model-free prediction errors for others relative to self were tracked in the thalamus/caudate. At the time of choice, neural activity consistent with model-free moral learning was observed in subgenual anterior cingulate cortex (sgACC), and switching after harming others was associated with stronger connectivity between sgACC and dorsolateral prefrontal cortex. Finally, model-free moral learning varied with individual differences in moral judgment. Our findings suggest moral learning favors efficiency over flexibility and is underpinned by specific neural mechanisms.