Goal-directed, habitual and pavlovian prosocial behavior

Filip Gȩsiarz, Molly J. Crockett

Research output: Contribution to journalArticlepeer-review

27 Scopus citations

Abstract

Although prosocial behaviors have been widely studied across disciplines, the mechanisms underlying them are not fully understood. Evidence from psychology, biology and economics suggests that prosocial behaviors can be driven by a variety of seemingly opposing factors: altruism or egoism, intuition or deliberation, inborn instincts or learned dispositions, and utility derived from actions or their outcomes. Here we propose a framework inspired by research on reinforcement learning and decision making that links these processes and explains characteristics of prosocial behaviors in different contexts. More specifically, we suggest that prosocial behaviors inherit features of up to three decision-making systems employed to choose between self- and other- regarding acts: a goal-directed system that selects actions based on their predicted consequences, a habitual system that selects actions based on their reinforcement history, and a Pavlovian system that emits reflexive responses based on evolutionarily prescribed priors. This framework, initially described in the field of cognitive neuroscience and machine learning, provides insight into the potential neural circuits and computations shaping prosocial behaviors. Furthermore, it identifies specific conditions in which each of these three systems should dominate and promote other- or self- regarding behavior.

Original languageEnglish (US)
Article number135
Pages (from-to)1-16
Number of pages16
JournalFrontiers in Behavioral Neuroscience
Volume9
Issue numberMAY
DOIs
StatePublished - May 27 2015
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Neuropsychology and Physiological Psychology
  • Cognitive Neuroscience
  • Behavioral Neuroscience

Keywords

  • Altruism
  • Dictator game
  • Model-based
  • Model-free
  • Pavlovian
  • Prosocial behavior
  • Reinforcement learning
  • Warm-glow

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