Dissociation between private and social counterfactual value signals following ventromedial prefrontal cortex damage

Nadège Bault, Giuseppe Di Pellegrino, Martina Puppi, Gaëlle Opolczynski, Alessia Monti, Davide Braghittoni, Florence Thibaut, Aldo Rustichini, Giorgio Coricelli

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

Individuals learn by comparing the outcome of chosen and unchosen actions. A negative counterfactual value signal is generated when this comparison is unfavorable. This can happen in private as well as in social settings—where the foregone outcome results from the choice of another person. We hypothesized that, despite sharing similar features such as supporting learning, these two counterfactual signals might implicate distinct brain networks. We conducted a neuropsychological study on the role of private and social counterfactual value signals in risky decision-making. Patients with lesions in the ventromedial prefrontal cortex (vmPFC), lesion controls, and healthy controls repeatedly chose between lotteries. In private trials, participants could observe the out-out-comes of their choices and the outcomes of the unselected lotteries. In social trials, participants could also see the other player’s choices and outcome. At the time of outcome, vmPFC patients were insensitive to private counterfactual value signals, whereas their responses to social comparison were similar to those of control participants.Atthetimeofchoice, intact vmPFC was necessary to integrate counterfactual signals in decisions, although amelioration was observed during the course of the task, possibly driven by social trials. We conclude that if the vmPFC is critical in processing private counterfactual signals and in integrating those signals in decision-making, then distinct brain areas might support the processing comes of social counterfactual signals.

Original languageEnglish (US)
Pages (from-to)639-656
Number of pages18
JournalJournal of cognitive neuroscience
Volume31
Issue number5
DOIs
StatePublished - 2019

PubMed: MeSH publication types

  • Journal Article
  • Research Support, Non-U.S. Gov't

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