Neuro-computational mechanisms and individual biases in action-outcome learning under moral conflict

TY - JOUR

T1 - Neuro-computational mechanisms and individual biases in action-outcome learning under moral conflict

AU - Fornari, Laura

AU - Ioumpa, Kalliopi

AU - Nostro, Alessandra D

AU - Evans, Nathan J

AU - De Angelis, Lorenzo

AU - Speer, Sebastian P H

AU - Paracampo, Riccardo

AU - Gallo, Selene

AU - Spezio, Michael

AU - Keysers, Christian

AU - Gazzola, Valeria

N1 - © 2023. The Author(s).

PY - 2023/3/6

Y1 - 2023/3/6

N2 - Learning to predict action outcomes in morally conflicting situations is essential for social decision-making but poorly understood. Here we tested which forms of Reinforcement Learning Theory capture how participants learn to choose between self-money and other-shocks, and how they adapt to changes in contingencies. We find choices were better described by a reinforcement learning model based on the current value of separately expected outcomes than by one based on the combined historical values of past outcomes. Participants track expected values of self-money and other-shocks separately, with the substantial individual difference in preference reflected in a valuation parameter balancing their relative weight. This valuation parameter also predicted choices in an independent costly helping task. The expectations of self-money and other-shocks were biased toward the favored outcome but fMRI revealed this bias to be reflected in the ventromedial prefrontal cortex while the pain-observation network represented pain prediction errors independently of individual preferences.

AB - Learning to predict action outcomes in morally conflicting situations is essential for social decision-making but poorly understood. Here we tested which forms of Reinforcement Learning Theory capture how participants learn to choose between self-money and other-shocks, and how they adapt to changes in contingencies. We find choices were better described by a reinforcement learning model based on the current value of separately expected outcomes than by one based on the combined historical values of past outcomes. Participants track expected values of self-money and other-shocks separately, with the substantial individual difference in preference reflected in a valuation parameter balancing their relative weight. This valuation parameter also predicted choices in an independent costly helping task. The expectations of self-money and other-shocks were biased toward the favored outcome but fMRI revealed this bias to be reflected in the ventromedial prefrontal cortex while the pain-observation network represented pain prediction errors independently of individual preferences.

U2 - 10.1038/s41467-023-36807-3

DO - 10.1038/s41467-023-36807-3

M3 - Article

C2 - 36878911

SN - 2041-1723

VL - 14

SP - 1218

JO - Nature Communications

JF - Nature Communications

IS - 1

ER -