Literature DB >> 32839234

When Implicit Prosociality Trumps Selfishness: The Neural Valuation System Underpins More Optimal Choices When Learning to Avoid Harm to Others Than to Oneself.

Lukas L Lengersdorff1, Isabella C Wagner1, Patricia L Lockwood2,3, Claus Lamm4.   

Abstract

Humans learn quickly which actions cause them harm. As social beings, we also need to learn to avoid actions that hurt others. It is currently unknown whether humans are as good at learning to avoid others' harm (prosocial learning) as they are at learning to avoid self-harm (self-relevant learning). Moreover, it remains unclear how the neural mechanisms of prosocial learning differ from those of self-relevant learning. In this fMRI study, 96 male human participants learned to avoid painful stimuli either for themselves or for another individual. We found that participants performed more optimally when learning for the other than for themselves. Computational modeling revealed that this could be explained by an increased sensitivity to subjective values of choice alternatives during prosocial learning. Increased value sensitivity was further associated with empathic traits. On the neural level, higher value sensitivity during prosocial learning was associated with stronger engagement of the ventromedial PFC during valuation. Moreover, the ventromedial PFC exhibited higher connectivity with the right temporoparietal junction during prosocial, compared with self-relevant, choices. Our results suggest that humans are particularly adept at learning to protect others from harm. This ability appears implemented by neural mechanisms overlapping with those supporting self-relevant learning, but with the additional recruitment of structures associated to the social brain. Our findings contrast with recent proposals that humans are egocentrically biased when learning to obtain monetary rewards for self or others. Prosocial tendencies may thus trump egocentric biases in learning when another person's physical integrity is at stake.SIGNIFICANCE STATEMENT We quickly learn to avoid actions that cause us harm. As "social animals," we also need to learn and consider the harmful consequences our actions might have for others. Here, we investigated how learning to protect others from pain (prosocial learning) differs from learning to protect oneself (self-relevant learning). We found that human participants performed better during prosocial learning than during self-relevant learning, as they were more sensitive toward the information they collected when making choices for the other. Prosocial learning recruited similar brain areas as self-relevant learning, but additionally involved parts of the "social brain" that underpin perspective-taking and self-other distinction. Our findings suggest that people show an inherent tendency toward "intuitive" prosociality.
Copyright © 2020 the authors.

Entities:  

Keywords:  computational modeling; empathy; fMRI; learning; prosocial behavior; valuation

Year:  2020        PMID: 32839234      PMCID: PMC7534918          DOI: 10.1523/JNEUROSCI.0842-20.2020

Source DB:  PubMed          Journal:  J Neurosci        ISSN: 0270-6474            Impact factor:   6.167


  62 in total

Review 1.  Imaging empathy and prosocial emotions.

Authors:  Claus Lamm; Markus Rütgen; Isabella C Wagner
Journal:  Neurosci Lett       Date:  2017-06-29       Impact factor: 3.046

2.  Harm to others outweighs harm to self in moral decision making.

Authors:  Molly J Crockett; Zeb Kurth-Nelson; Jenifer Z Siegel; Peter Dayan; Raymond J Dolan
Journal:  Proc Natl Acad Sci U S A       Date:  2014-11-17       Impact factor: 11.205

3.  Lower level mediation in multilevel models.

Authors:  David A Kenny; Josephine D Korchmaros; Niall Bolger
Journal:  Psychol Methods       Date:  2003-06

4.  Revealing Neurocomputational Mechanisms of Reinforcement Learning and Decision-Making With the hBayesDM Package.

Authors:  Woo-Young Ahn; Nathaniel Haines; Lei Zhang
Journal:  Comput Psychiatr       Date:  2017-10-01

5.  Striatal structure and function predict individual biases in learning to avoid pain.

Authors:  Eran Eldar; Tobias U Hauser; Peter Dayan; Raymond J Dolan
Journal:  Proc Natl Acad Sci U S A       Date:  2016-04-11       Impact factor: 11.205

6.  Dopaminergic Control of the Exploration-Exploitation Trade-Off via the Basal Ganglia.

Authors:  Mark D Humphries; Mehdi Khamassi; Kevin Gurney
Journal:  Front Neurosci       Date:  2012-02-06       Impact factor: 4.677

Review 7.  The neurobiology of decision: consensus and controversy.

Authors:  Joseph W Kable; Paul W Glimcher
Journal:  Neuron       Date:  2009-09-24       Impact factor: 18.688

8.  Models of morality.

Authors:  Molly J Crockett
Journal:  Trends Cogn Sci       Date:  2013-07-08       Impact factor: 20.229

9.  Representation of aversive prediction errors in the human periaqueductal gray.

Authors:  Mathieu Roy; Daphna Shohamy; Nathaniel Daw; Marieke Jepma; G Elliott Wimmer; Tor D Wager
Journal:  Nat Neurosci       Date:  2014-10-05       Impact factor: 24.884

10.  Valuation in major depression is intact and stable in a non-learning environment.

Authors:  Dongil Chung; Kelly Kadlec; Jason A Aimone; Katherine McCurry; Brooks King-Casas; Pearl H Chiu
Journal:  Sci Rep       Date:  2017-03-10       Impact factor: 4.379

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  1 in total

1.  Birth order and prosociality in the early adolescent brain.

Authors:  Naohiro Okada; Yu Yamamoto; Noriaki Yahata; Susumu Morita; Daisuke Koshiyama; Kentaro Morita; Kingo Sawada; Sho Kanata; Shinya Fujikawa; Noriko Sugimoto; Rie Toriyama; Mio Masaoka; Shinsuke Koike; Tsuyoshi Araki; Yukiko Kano; Kaori Endo; Syudo Yamasaki; Shuntaro Ando; Atsushi Nishida; Mariko Hiraiwa-Hasegawa; Charles Yokoyama; Kiyoto Kasai
Journal:  Sci Rep       Date:  2021-11-08       Impact factor: 4.379

  1 in total

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