Model-free decision making is prioritized when learning to avoid harming others
Research output: Contribution to journal › Article › peer-review
Colleges, School and Institutes
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.
|Number of pages||12|
|Journal||Proceedings of the National Academy of Sciences|
|Publication status||Published - 14 Oct 2020|
- learning, model-free, moral, neuroimaging, prediction error