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Zhou Y, Han S, Kang P, Tobler PN, Hein G. The social transmission of empathy relies on observational reinforcement learning. Proc Natl Acad Sci U S A 2024; 121:e2313073121. [PMID: 38381794 PMCID: PMC10907261 DOI: 10.1073/pnas.2313073121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Accepted: 01/12/2024] [Indexed: 02/23/2024] Open
Abstract
Theories of moral development propose that empathy is transmitted across individuals. However, the mechanisms through which empathy is socially transmitted remain unclear. Here, we combine computational learning models and functional MRI to investigate whether, and if so, how empathic and non-empathic responses observed in others affect the empathy of female observers. The results of three independent studies showed that watching empathic or non-empathic responses generates a learning signal that respectively increases or decreases empathy ratings of the observer. A fourth study revealed that the learning-related transmission of empathy is stronger when observing human rather than computer demonstrators. Finally, we show that the social transmission of empathy alters empathy-related responses in the anterior insula, i.e., the same region that correlated with empathy baseline ratings, as well as its functional connectivity with the temporoparietal junction. Together, our findings provide a computational and neural mechanism for the social transmission of empathy that accounts for changes in individual empathic responses in empathic and non-empathic social environments.
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Affiliation(s)
- Yuqing Zhou
- Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
- Translational Social Neuroscience Unit, Department of Psychiatry, Psychosomatics, and Psychotherapy, University of Würzburg, Würzburg 97080, Germany
| | - Shihui Han
- School of Psychological and Cognitive Sciences, Beijing Key Laboratory of Behavior and Mental Health, PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China
| | - Pyungwon Kang
- Department of Economics and Laboratory for Social and Neural Systems Research, University of Zurich and Neuroscience Center Zurich, University of Zurich and Swiss Federal Institute of Technology Zurich, Zurich CH-8006, Switzerland
| | - Philippe N. Tobler
- Department of Economics and Laboratory for Social and Neural Systems Research, University of Zurich and Neuroscience Center Zurich, University of Zurich and Swiss Federal Institute of Technology Zurich, Zurich CH-8006, Switzerland
| | - Grit Hein
- Translational Social Neuroscience Unit, Department of Psychiatry, Psychosomatics, and Psychotherapy, University of Würzburg, Würzburg 97080, Germany
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Xie J, Li L, Lu Y, Zhuang J, Wu Y, Li P, Zheng L. Learning from in-group and out-group models induces separative effects on human mate copying. Soc Cogn Affect Neurosci 2023; 18:nsad051. [PMID: 37757743 PMCID: PMC10547020 DOI: 10.1093/scan/nsad051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Revised: 07/27/2023] [Accepted: 09/18/2023] [Indexed: 09/29/2023] Open
Abstract
Mate copying is a social learning process in which individuals gather public information about potential mates by observing models' choices. Previous studies have reported that individual attributes of female models affect mate copying, yet little is known about whether and how the group attributes of models influence mate copying. In the current behavioral and functional magnetic resonance imaging studies, female participants were asked to rate their willingness to choose the depicted males as potential romantic partners before and after observing in-group or out-group female models accepting, rejecting or being undecided (baseline) about the males. Results showed that participants changed their ratings to align with the models' acceptance or rejection choices. Compared to rejection copying, the effect of acceptance copying was stronger and regulated by in- and out-group models, manifesting a discounting copying effect when learning from out-group models. At the neural level, for acceptance copying, stronger temporoparietal junction (TPJ) activity and connectivity between TPJ and anterior medial prefrontal cortex (amPFC) were observed when female models belonged to out-group members; meanwhile, the functional connection of TPJ and amPFC positively predicted the rating changes when learning from out-group models. The results indicated that participants might need more resources to infer out-group members' intentions to overcome the in-group bias during acceptance copying.
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Affiliation(s)
- Jiajia Xie
- Department of Psychology, Normal College, Qingdao University, Qingdao 266071, China
| | - Lin Li
- Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, School of Psychology and Cognitive Science, East China Normal University, Shanghai 200062, China
| | - Yang Lu
- Fudan Institute on Ageing, Fudan University, Shanghai 200433, China
- MOE Laboratory for National Development and Intelligent Governance, Fudan University, Shanghai 200433, China
| | - Jinying Zhuang
- School of Psychology and Cognitive Science, East China Normal University, Shanghai 200062, China
| | - Yuyan Wu
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai 200062, China
| | - Peng Li
- School of Psychology and Cognitive Science, East China Normal University, Shanghai 200062, China
| | - Li Zheng
- Fudan Institute on Ageing, Fudan University, Shanghai 200433, China
- MOE Laboratory for National Development and Intelligent Governance, Fudan University, Shanghai 200433, China
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Flechsenhar A, Kanske P, Krach S, Korn C, Bertsch K. The (un)learning of social functions and its significance for mental health. Clin Psychol Rev 2022; 98:102204. [PMID: 36216722 DOI: 10.1016/j.cpr.2022.102204] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Revised: 08/11/2022] [Accepted: 09/23/2022] [Indexed: 01/27/2023]
Abstract
Social interactions are dynamic, context-dependent, and reciprocal events that influence prospective strategies and require constant practice and adaptation. This complexity of social interactions creates several research challenges. We propose a new framework encouraging future research to investigate not only individual differences in capacities relevant for social functioning and their underlying mechanisms, but also the flexibility to adapt or update one's social abilities. We suggest three key capacities relevant for social functioning: (1) social perception, (2) sharing emotions or empathizing, and (3) mentalizing. We elaborate on how adaptations in these capacities may be investigated on behavioral and neural levels. Research on these flexible adaptations of one's social behavior is needed to specify how humans actually "learn to be social". Learning to adapt implies plasticity of the relevant brain networks involved in the underlying social processes, indicating that social abilities are malleable for different contexts. To quantify such measures, researchers need to find ways to investigate learning through dynamic changes in adaptable social paradigms and examine several factors influencing social functioning within the three aformentioned social key capacities. This framework furthers insight concerning individual differences, provides a holistic approach to social functioning, and may improve interventions for ameliorating social abilities in patients.
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Affiliation(s)
- Aleya Flechsenhar
- Department Clinical Psychology and Psychotherapy, Ludwig-Maximilians-University Munich, Germany.
| | - Philipp Kanske
- Institute of Clinical Psychology and Psychotherapy, Technische Universität Dresden, Germany
| | - Sören Krach
- Department of Psychiatry and Psychotherapy, University of Lübeck, Germany
| | - Christoph Korn
- Section Social Neuroscience, Department of General Psychiatry, Center for Psychosocial Medicine, Heidelberg University, Heidelberg, Germany
| | - Katja Bertsch
- Department Clinical Psychology and Psychotherapy, Ludwig-Maximilians-University Munich, Germany; NeuroImaging Core Unit Munich (NICUM), University Hospital LMU, Munich, Germany; Department of General Psychiatry, Center for Psychosocial Medicine, Heidelberg University, Heidelberg, Germany
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Adaptive learning strategies in purely observational learning. CURRENT PSYCHOLOGY 2022. [DOI: 10.1007/s12144-022-03904-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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Incorporating social knowledge structures into computational models. Nat Commun 2022; 13:6205. [PMID: 36266284 PMCID: PMC9584930 DOI: 10.1038/s41467-022-33418-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Accepted: 09/16/2022] [Indexed: 12/24/2022] Open
Abstract
To navigate social interactions successfully, humans need to continuously learn about the personality traits of other people (e.g., how helpful or aggressive is the other person?). However, formal models that capture the complexities of social learning processes are currently lacking. In this study, we specify and test potential strategies that humans can employ for learning about others. Standard Rescorla-Wagner (RW) learning models only capture parts of the learning process because they neglect inherent knowledge structures and omit previously acquired knowledge. We therefore formalize two social knowledge structures and implement them in hybrid RW models to test their usefulness across multiple social learning tasks. We name these concepts granularity (knowledge structures about personality traits that can be utilized at different levels of detail during learning) and reference points (previous knowledge formalized into representations of average people within a social group). In five behavioural experiments, results from model comparisons and statistical analyses indicate that participants efficiently combine the concepts of granularity and reference points-with the specific combinations in models depending on the people and traits that participants learned about. Overall, our experiments demonstrate that variants of RW algorithms, which incorporate social knowledge structures, describe crucial aspects of the dynamics at play when people interact with each other.
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Zhou Y, Lindström B, Soutschek A, Kang P, Tobler PN, Hein G. Learning from Ingroup Experiences Changes Intergroup Impressions. J Neurosci 2022; 42:6931-6945. [PMID: 35906067 PMCID: PMC9464015 DOI: 10.1523/jneurosci.0027-22.2022] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 06/29/2022] [Accepted: 07/11/2022] [Indexed: 11/21/2022] Open
Abstract
Humans form impressions toward individuals of their own social groups (ingroup members) and of different social groups (outgroup members). Outgroup-focused theories predict that intergroup impressions are mainly shaped by experiences with outgroup individuals, while ingroup-focused theories predict that ingroup experiences play a dominant role. Here we test predictions from these two psychological theories by estimating how intergroup impressions are dynamically shaped when people learn from both ingroup and outgroup experiences. While undergoing fMRI, male participants had identical experiences with different ingroup or outgroup members and rated their social closeness and impressions toward the ingroup and the outgroup. Behavioral results showed an initial ingroup bias in impression ratings which was significantly reduced over the course of learning, with larger effects in individuals with stronger ingroup identification. Computational learning models revealed that these changes in intergroup impressions were predicted by the weight given to ingroup prediction errors. Neurally, the individual weight for ingroup prediction errors was related to the coupling between the left inferior parietal lobule and the left anterior insula, which, in turn, predicted learning-related changes in intergroup impressions. Our findings provide computational and neural evidence for ingroup-focused theories, highlighting the importance of ingroup experiences in shaping social impressions in intergroup settings.SIGNIFICANCE STATEMENT Living in multicultural societies, humans interact with individuals of their own social groups (ingroup members) and of different social groups (outgroup members). However, little is known about how people learn from the mixture of ingroup and outgroup interactions, the most natural experiences in current societies. Here, participants had identical, intermixed experiences with different ingroup and outgroup individuals and rated their closeness and impressions toward the ingroup and the outgroup. Combining computational models and fMRI, we find that the weight given to ingroup experiences (ingroup prediction errors) is the main source of intergroup impression change, captured by changes in connectivity between the parietal lobe and insula. These findings highlight the importance of ingroup experiences in shaping intergroup impressions in complex social environments.
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Affiliation(s)
- Yuqing Zhou
- Translational Social Neuroscience Unit, Department of Psychiatry, Psychosomatics, and Psychotherapy, University of Würzburg, Würzburg 97080, Germany
| | - Björn Lindström
- Department of Experimental and Applied Psychology, Vrije Universiteit Amsterdam, Amsterdam, 1081 HV, The Netherlands
| | - Alexander Soutschek
- Department of Psychology, Ludwig Maximilian University, Munich 80802, Germany
| | - Pyungwon Kang
- Department of Economics and Laboratory for Social and Neural Systems Research, University of Zurich and Neuroscience Center Zurich, University of Zurich and Swiss Federal Institute of Technology Zurich, Zurich, CH-8006, Switzerland
| | - Philippe N Tobler
- Department of Economics and Laboratory for Social and Neural Systems Research, University of Zurich and Neuroscience Center Zurich, University of Zurich and Swiss Federal Institute of Technology Zurich, Zurich, CH-8006, Switzerland
| | - Grit Hein
- Translational Social Neuroscience Unit, Department of Psychiatry, Psychosomatics, and Psychotherapy, University of Würzburg, Würzburg 97080, Germany
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Neural basis of in-group bias and prejudices: A systematic meta-analysis. Neurosci Biobehav Rev 2021; 131:1214-1227. [PMID: 34715150 DOI: 10.1016/j.neubiorev.2021.10.027] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2021] [Revised: 10/14/2021] [Accepted: 10/24/2021] [Indexed: 01/06/2023]
Abstract
In-group favoritism and prejudices relate to discriminatory behaviors but, despite decades of research, understanding of their neural correlates has been limited. A systematic coordinate-based meta-analysis of functional magnetic resonance imaging (fMRI) studies (altogether 87 original datasets, n = 2328) was conducted to investigate neural inter-group biases, i.e., responses toward in-group vs. out-group in different contexts. We found inter-group biases in some previously identified brain regions (e.g., the medial prefrontal cortex, insula) but also in many previously non-identified brain regions (e.g., the cerebellum, precentral gyrus). Sub-group analyses indicated that neural correlates of inter-group biases may be mostly context-specific. Regarding different types of group memberships, inter-group bias toward trivial groups was evident only in the cingulate cortex, while inter-group biases toward "real" groups (ethnic, national, or political groups) involved broader sets of brain regions. Additionally, there were heightened neural threat responses toward out-groups' faces and stronger neural empathic responses toward in-groups' suffering. We did not obtain significant publication bias. Overall, the findings provide novel implications for theory and prejudice-reduction interventions.
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