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Sazhin D, Wyngaarden JB, Dennison JB, Zaff O, Fareri D, McCloskey MS, Alloy LB, Jarcho JM, Smith DV. Trait Reward Sensitivity Modulates Connectivity with the Temporoparietal Junction and Anterior Insula during Strategic Decision Making. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.10.19.563125. [PMID: 37904967 PMCID: PMC10614961 DOI: 10.1101/2023.10.19.563125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/02/2023]
Abstract
Many decisions happen in social contexts such as negotiations, yet little is understood about how people balance fairness versus selfishness. Past investigations found that activation in brain areas involved in executive function and reward processing was associated with people offering less with no threat of rejection from their partner, compared to offering more when there was a threat of rejection. However, it remains unclear how trait reward sensitivity may modulate activation and connectivity patterns in these situations. To address this gap, we used task-based fMRI to examine the relation between reward sensitivity and the neural correlates of bargaining choices. Participants (N = 54) completed the Sensitivity to Punishment (SP)/Sensitivity to Reward (SR) Questionnaire and the Behavioral Inhibition System/Behavioral Activation System scales. Participants performed the Ultimatum and Dictator Games as proposers and exhibited strategic decisions by being fair when there was a threat of rejection, but being selfish when there was not a threat of rejection. We found that strategic decisions evoked activation in the Inferior Frontal Gyrus (IFG) and the Anterior Insula (AI). Next, we found elevated IFG connectivity with the Temporoparietal junction (TPJ) during strategic decisions. Finally, we explored whether trait reward sensitivity modulated brain responses while making strategic decisions. We found that people who scored lower in reward sensitivity made less strategic choices when they exhibited higher AI-Angular Gyrus connectivity. Taken together, our results demonstrate how trait reward sensitivity modulates neural responses to strategic decisions, potentially underscoring the importance of this factor within social and decision neuroscience.
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2
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Quinton JC, Gautheron F, Smeding A. Embodied sequential sampling models and dynamic neural fields for decision-making: Why hesitate between two when a continuum is the answer. Neural Netw 2024; 179:106526. [PMID: 39053301 DOI: 10.1016/j.neunet.2024.106526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2023] [Revised: 06/02/2024] [Accepted: 07/07/2024] [Indexed: 07/27/2024]
Abstract
As two alternative options in a forced choice task are separated by design, two classes of computational models of decision-making have thrived independently in the literature for nearly five decades. While sequential sampling models (SSM) focus on response times and keypresses in binary decisions in experimental paradigms, dynamic neural fields (DNF) focus on continuous sensorimotor dimensions and tasks found in perception and robotics. Recent attempts have been made to address limitations in their application to other domains, but strong similarities and compatibility between prominent models from both classes were hardly considered. This article is an attempt at bridging the gap between these classes of models, and simultaneously between disciplines and paradigms relying on binary or continuous responses. A unifying formulation of representative SSM and DNF equations is proposed, varying the number of units which interact and compete to reach a decision. The embodiment of decisions is also considered by coupling cognitive and sensorimotor processes, enabling the model to generate decision trajectories at trial level. The resulting mechanistic model is therefore able to target different paradigms (forced choices or continuous response scales) and measures (final responses or dynamics). The validity of the model is assessed statistically by fitting empirical distributions obtained from human participants in moral decision-making mouse-tracking tasks, for which both dichotomous and nuanced responses are meaningful. Comparing equations at the theoretical level, and model parametrizations at the empirical level, the implications for psychological decision-making processes, as well as the fundamental assumptions and limitations of models and paradigms are discussed.
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Affiliation(s)
| | - Flora Gautheron
- Univ. Grenoble Alpes, CNRS, Grenoble INP,(1) LJK, 38000 Grenoble, France; Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, LIP/PC2S, 38000 Grenoble, France.
| | - Annique Smeding
- Univ. Savoie Mont Blanc, Univ. Grenoble Alpes, LIP/PC2S, 73000 Chambéry, France.
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3
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Li Z, Jiang K, Zhu Y, Du H, Im H, Zhu Y, Feng L, Zhu W, Zhao G, Jia X, Hu Y, Zhu H, Yao Q, Wang H, Wang Q. Happy people are always similar: The evidence from brain morphological and functional inter-subject correlations. Neuroimage 2024; 297:120690. [PMID: 38880309 DOI: 10.1016/j.neuroimage.2024.120690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Revised: 06/13/2024] [Accepted: 06/14/2024] [Indexed: 06/18/2024] Open
Abstract
A fundamental question in the study of happiness is whether there is neural evidence to support a well-known hypothesis that happy people are always similar while unfortunate people have their own misfortunes. To investigate this, we employed several happiness-related questionnaires to identify potential components of happiness, and further investigated and confirmed their associations with personality, mood, aggressive behaviors, and amygdala reactivity to fearful faces within a substantial sample size of college students (n = 570). Additionally, we examined the functional and morphological similarities and differences among happy individuals using the inter-subject representational similarity analysis (IS-RSA). IS-RSA emphasizes the geometric properties in a high-dimensional space constructed by brain or behavioral patterns and focuses on individual subjects. Our behavioral findings unveiled two factors of happiness: individual and social, both of which mediated the effect of personality traits on individual aggression. Subsequently, mood mediated the impact of happiness on aggressive behaviors across two subgroup splits. Functional imaging data revealed that individuals with higher levels of happiness exhibited reduced amygdala reactivity to fearful faces, as evidenced by a conventional face-matching task (n = 104). Moreover, IS-RSA demonstrated that these participants manifested similar neural activation patterns when processing fearful faces within the visual pathway, but not within the emotional network (e.g., amygdala). Morphological observations (n = 425) indicated that individuals with similar high happiness levels exhibited comparable gray matter volume patterns within several networks, including the default mode network, fronto-parietal network, visual network, and attention network. Collectively, these findings offer early neural evidence supporting the proposition that happy individuals may share common neural characteristics.
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Affiliation(s)
- Zixi Li
- Faculty of Psychology, Tianjin Normal University, Tianjin 300387, China
| | - Keying Jiang
- Faculty of Psychology, Tianjin Normal University, Tianjin 300387, China
| | - Ye Zhu
- Faculty of Psychology, Tianjin Normal University, Tianjin 300387, China
| | - Hanxiao Du
- Faculty of Psychology, Tianjin Normal University, Tianjin 300387, China
| | | | - Yingying Zhu
- Faculty of Psychology, Tianjin Normal University, Tianjin 300387, China
| | - Lei Feng
- School of Mathematical Sciences, Tianjin Normal University, Tianjin 300387, China
| | - Wenwei Zhu
- School of Psychology, South China Normal University, Guangzhou 510631, China
| | - Guang Zhao
- Faculty of Psychology, Tianjin Normal University, Tianjin 300387, China
| | - Xuji Jia
- Faculty of Psychology, Tianjin Normal University, Tianjin 300387, China
| | - Ying Hu
- Faculty of Psychology, Tianjin Normal University, Tianjin 300387, China
| | - Haidong Zhu
- Normal College of Shihezi University, Shihezi University, Shihezi 832000, China
| | - Qiong Yao
- Key Laboratory of Philosophy and Social Science of Anhui Province on Adolescent Mental Health and Crisis Intelligence Intervention, Hefei 230601, China; School of Educational and Psychological Science, Hefei Normal University, Hefei 230601, China
| | - He Wang
- Institute of Biomedical Engineering, Chinese Academy of Medical Science & Peking Union Medical College, Tianjin, China.
| | - Qiang Wang
- Faculty of Psychology, Tianjin Normal University, Tianjin 300387, China; Key Laboratory of Philosophy and Social Science of Anhui Province on Adolescent Mental Health and Crisis Intelligence Intervention, Hefei 230601, China.
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4
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Galvan E, Sanfey A. Reciprocity in ambiguous situations: Default psychological strategies underlying ambiguity resolution in moral decision-making. PLoS One 2024; 19:e0300886. [PMID: 38574089 PMCID: PMC10994327 DOI: 10.1371/journal.pone.0300886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Accepted: 03/06/2024] [Indexed: 04/06/2024] Open
Abstract
When deciding whether to reciprocate trust, people are typically strongly influenced by how much trust their interaction partner has originally shown them. If a partner has placed a lot of trust in you, there is a strong motivation to reciprocate, and indeed this factor often outweighs pro-self considerations to maximize one's own financial payout. However, one important unanswered question in this regard is what people decide to do when this prior information is ambiguous; that is, when they do not know for sure exactly how trusting their partner has been. How then do people decide to reciprocate? This study utilizes a novel version of the Trust Game to directly address this question. Here, we develop, and validate, a computational model-based approach to quantify and categorize how participants assessed the trustworthiness of an unfamiliar partner when making reciprocity decisions. We find that participants spontaneously use their prior experience about the trustingness of game partners in general to inform their reciprocity decisions, even when they had the opportunity to strategically assume that their new, unfamiliar, partners were untrusting, and hence could have justified lower reciprocation rates.
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Affiliation(s)
- Elijah Galvan
- Behavioural Science Institute, Radboud University, Nijmegen, GE, Netherlands
- Donders Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, GE, Netherlands
| | - Alan Sanfey
- Behavioural Science Institute, Radboud University, Nijmegen, GE, Netherlands
- Donders Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, GE, Netherlands
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5
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Hsiao PYA, Kim MJ, Chou FCB, Chen PHA. Intersubject representational similarity analysis uncovers the impact of state anxiety on brain activation patterns in the human extrastriate cortex. Brain Imaging Behav 2024; 18:412-420. [PMID: 38324234 DOI: 10.1007/s11682-024-00854-1] [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] [Accepted: 01/16/2024] [Indexed: 02/08/2024]
Abstract
The current study used functional magnetic resonance imaging (fMRI) and showed that state anxiety modulated extrastriate cortex activity in response to emotionally-charged visual images. State anxiety and neuroimaging data from 53 individuals were subjected to an intersubject representational similarity analysis (ISRSA), wherein the geometries between neural and behavioral data were compared. This analysis identified the extrastriate cortex (fusiform gyrus and area MT) to be the sole regions whose activity patterns covaried with state anxiety. Importantly, we show that this brain-behavior association is revealed when treating state anxiety data as a multidimensional response pattern, rather than a single composite score. This suggests that ISRSA using multivariate distances may be more sensitive in identifying the shared geometries between self-report questionnaires and brain imaging data. Overall, our findings demonstrate that a transient state of anxiety may influence how visual information - especially those relevant to the valence dimension - is processed in the extrastriate cortex.
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Affiliation(s)
- Po-Yuan A Hsiao
- Department of Psychology, National Taiwan University, Taipei, Taiwan
| | - M Justin Kim
- Department of Psychology, Sungkyunkwan University, Seoul, South Korea
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, South Korea
| | - Feng-Chun B Chou
- Department of Psychology, National Taiwan University, Taipei, Taiwan
| | - Pin-Hao A Chen
- Department of Psychology, National Taiwan University, Taipei, Taiwan.
- Neurobiology and Cognitive Science Center, National Taiwan University, Taipei, Taiwan.
- Graduate Institute of Brain and Mind Sciences, National Taiwan University, Taipei, Taiwan.
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6
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Gu C, Peng Y, Nastase SA, Mayer RE, Li P. Onscreen presence of instructors in video lectures affects learners' neural synchrony and visual attention during multimedia learning. Proc Natl Acad Sci U S A 2024; 121:e2309054121. [PMID: 38466840 PMCID: PMC10963011 DOI: 10.1073/pnas.2309054121] [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: 06/01/2023] [Accepted: 01/20/2024] [Indexed: 03/13/2024] Open
Abstract
COVID-19 forced students to rely on online learning using multimedia tools, and multimedia learning continues to impact education beyond the pandemic. In this study, we combined behavioral, eye-tracking, and neuroimaging paradigms to identify multimedia learning processes and outcomes. College students viewed four video lectures including slides with either an onscreen human instructor, an animated instructor, or no onscreen instructor. Brain activity was recorded via fMRI, visual attention was recorded via eye-tracking, and learning outcome was assessed via post-tests. Onscreen presence of instructor, compared with no instructor presence, resulted in superior post-test performance, less visual attention on the slide, more synchronized eye movements during learning, and higher neural synchronization in cortical networks associated with socio-emotional processing and working memory. Individual variation in cognitive and socio-emotional abilities and intersubject neural synchronization revealed different levels of cognitive and socio-emotional processing in different learning conditions. The instructor-present condition evoked increased synchronization, likely reflecting extra processing demands in attentional control, working memory engagement, and socio-emotional processing. Although human instructors and animated instructors led to comparable learning outcomes, the effects were due to the dynamic interplay of information processing vs. attentional distraction. These findings reflect a benefit-cost trade-off where multimedia learning outcome is enhanced only when the cognitive benefits motivated by the social presence of onscreen instructor outweigh the cognitive costs brought about by concurrent attentional distraction unrelated to learning.
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Affiliation(s)
- Chanyuan Gu
- Department of Chinese and Bilingual Studies, Faculty of Humanities, The Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Yingying Peng
- Department of Chinese and Bilingual Studies, Faculty of Humanities, The Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Samuel A. Nastase
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ08540
| | - Richard E. Mayer
- Department of Psychological and Brain Sciences, University of California, Santa Barbara, CA93106
| | - Ping Li
- Department of Chinese and Bilingual Studies, Faculty of Humanities, The Hong Kong Polytechnic University, Hong Kong SAR, China
- Centre for Immersive Learning and Metaverse in Education, The Hong Kong Polytechnic University, Hong Kong SAR, China
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7
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Yu W, Chen J, Kong Z, Sun W, Zhou X, Lu L, Gao X, Sun H. Understanding the cognitive and neuroimaging bases underlying the detrimental impact of sleep deprivation on reciprocity. iScience 2024; 27:109155. [PMID: 38425845 PMCID: PMC10904273 DOI: 10.1016/j.isci.2024.109155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 11/24/2023] [Accepted: 02/02/2024] [Indexed: 03/02/2024] Open
Abstract
Although the impact of sleep loss on social behaviors has been widely observed in recent years, the mechanisms underpinning these impacts remain unclear. In this study, we explored the detrimental effects of sleep deprivation on reciprocity behavior as well as its underlying psychological and neuroimaging mechanisms by combining sleep manipulation, an interpersonal interactive game, computational modeling and neuroimaging. Our results suggested that after sleep deprivation, individuals showed reduced reciprocity behavior, mainly due to their reduced weights on communal concern when making social decisions. At neural level, we demonstrated that sleep deprivation's effects were observed in the precuneus (hyperactivity) and temporoparietal junction, dorsal lateral prefrontal cortex (DLPFC) (both hypoactivity), and reduced reciprocity was also accounted for by increased precuneus-thalamus connectivity and DLPFC-thalamus connectivity. Our findings contributed to the understanding of the psychological and neuroimaging bases underlying the deleterious impact of sleep deprivation on social behaviors.
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Affiliation(s)
- Wenwen Yu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Jie Chen
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Zhifei Kong
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Wei Sun
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Xiaolin Zhou
- Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, School of Psychology and Cognitive Science, East China Normal University, Shanghai 200062, China
- School of Business and Management, Shanghai International Studies University, Shanghai 200083, China
| | - Lin Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Xiaoxue Gao
- Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, School of Psychology and Cognitive Science, East China Normal University, Shanghai 200062, China
| | - Hongqiang Sun
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
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8
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Díaz-Gutiérrez P, Boone C, Vyas H, Declerck CH. Neural asymmetry in aligning with generous versus selfish descriptive norms in a charitable donation task. Sci Rep 2024; 14:5793. [PMID: 38461360 PMCID: PMC10924952 DOI: 10.1038/s41598-024-55688-0] [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: 09/28/2023] [Accepted: 02/26/2024] [Indexed: 03/11/2024] Open
Abstract
Social alignment is supported by the brain's reward system (ventral striatum), presumably because attaining synchrony generates feelings of connectedness. However, this may hold only for aligning with generous others, while aligning with selfishness might threaten social connectedness. We investigated this postulated asymmetry in an incentivized fMRI charitable donation task. Participants decided how much of their endowment to donate to real charities, and how much to keep for themselves. Compared to a baseline condition, donations significantly increased or decreased in function of the presence of descriptive norms. The fMRI data reveal that processing selfish norms (more than generous ones) recruited the amygdala and anterior insula. Aligning with selfish norms correlated on average with reduced activity in the lateral prefrontal cortex (LPFC) and, at the individual level, with decreasing activity in the ventral striatum (VS). Conversely, as participants aligned more with generous norms, they showed increasing activity in the LPFC and, on average, increased activity in the VS. This increase occurred beyond the increased VS activity which was also observed in the baseline condition. Taken together, this suggests that aligning with generosity, while effortful, provides a "warm glow of herding" associated with collective giving, but that aligning with selfishness does not.
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Affiliation(s)
| | - Christophe Boone
- Faculty of Business and Economics, University of Antwerp, Antwerp, Belgium
| | - Harshil Vyas
- Faculty of Business and Economics, University of Antwerp, Antwerp, Belgium
| | - Carolyn H Declerck
- Faculty of Business and Economics, University of Antwerp, Antwerp, Belgium
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9
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Cushman F. Computational Social Psychology. Annu Rev Psychol 2024; 75:625-652. [PMID: 37540891 DOI: 10.1146/annurev-psych-021323-040420] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/06/2023]
Abstract
Social psychologists attempt to explain how we interact by appealing to basic principles of how we think. To make good on this ambition, they are increasingly relying on an interconnected set of formal tools that model inference, attribution, value-guided decision making, and multi-agent interactions. By reviewing progress in each of these areas and highlighting the connections between them, we can better appreciate the structure of social thought and behavior, while also coming to understand when, why, and how formal tools can be useful for social psychologists.
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Affiliation(s)
- Fiery Cushman
- Department of Psychology, Harvard University, Cambridge, Massachusetts, USA;
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10
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Gao X, Jolly E, Yu H, Liu H, Zhou X, Chang LJ. The psychological, computational, and neural foundations of indebtedness. Nat Commun 2024; 15:68. [PMID: 38167846 PMCID: PMC10762097 DOI: 10.1038/s41467-023-44286-9] [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: 10/07/2020] [Accepted: 12/07/2023] [Indexed: 01/05/2024] Open
Abstract
Receiving a favor from another person may induce a negative feeling of indebtedness for the beneficiary. In this study, we explore these hidden costs by developing and validating a conceptual model of indebtedness across three studies that combine a large-scale online questionnaire, an interpersonal game, computational modeling, and neuroimaging. Our model captures how individuals perceive the altruistic and strategic intentions of the benefactor. These inferences produce distinct feelings of guilt and obligation that together comprise indebtedness and motivate reciprocity. Perceived altruistic intentions convey care and communal concern and are associated with activity in insula, ventromedial prefrontal cortex and dorsolateral prefrontal cortex, while inferred strategic intentions convey expectations of future reciprocity and are associated with activation in temporal parietal junction and dorsomedial prefrontal cortex. We further develop a neural utility model of indebtedness using multivariate patterns of brain activity that captures the tradeoff between these feelings and reliably predicts reciprocity behavior.
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Affiliation(s)
- Xiaoxue Gao
- Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, School of Psychology and Cognitive Science, East China Normal University, Shanghai, 200062, China.
- School of Psychological and Cognitive Sciences, Peking University, Beijing, 100871, China.
| | - Eshin Jolly
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, 03755, USA
| | - Hongbo Yu
- Department of Psychological and Brain Sciences, University of California Santa Barbara, Santa Barbara, CA, 93106-9660, USA
| | - Huiying Liu
- Mental Health Education Center, Zhengzhou University, Zhengzhou, 450001, Henan, China
| | - Xiaolin Zhou
- Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, School of Psychology and Cognitive Science, East China Normal University, Shanghai, 200062, China.
- School of Psychological and Cognitive Sciences, Peking University, Beijing, 100871, China.
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, 100871, China.
| | - Luke J Chang
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, 03755, USA.
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11
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Knyazev GG, Savostyanov AN, Bocharov AV, Saprigyn AE. Representational similarity analysis of self- versus other-processing: Effect of trait aggressiveness. Aggress Behav 2024; 50:e22125. [PMID: 38268387 DOI: 10.1002/ab.22125] [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: 03/02/2023] [Revised: 10/27/2023] [Accepted: 11/06/2023] [Indexed: 01/26/2024]
Abstract
In this study, using the self/other adjective judgment task, we aimed to explore how people perceive themselves in comparison to various other people, including friends, strangers, and those they dislike. Next, using representational similarity analysis, we sought to elucidate how these perceptual similarities and differences are represented in brain activity and how aggressiveness is related to these representations. Behavioral ratings show that, on average, people tend to consider themselves more like their friends than neutral strangers, and least like people they dislike. This pattern of similarity is positively correlated with neural representation in social and cognitive circuits of the brain and negatively correlated with neural representation in emotional centers that may represent emotional arousal associated with various social objects. Aggressiveness seems to predispose a person to a pattern of behavior that is the opposite of the average pattern, that is, a tendency to think of oneself as less like one's friends and more like one's enemies. This corresponds to an increase in the similarity of the behavioral representation with the representation in the emotional centers and a decrease in its similarity with the representation in the social and cognitive centers. This can be seen as evidence that in individuals prone to aggression, behavior in the social environment may depend to a greater extent on the representation of social objects in the emotional rather than social and cognitive brain circuits.
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Affiliation(s)
- Gennady G Knyazev
- Laboratory of Differential Psychophysiology, Institute of Neurosciences and Medicine, Novosibirsk, Russia
| | - Alexander N Savostyanov
- Laboratory of Differential Psychophysiology, Institute of Neurosciences and Medicine, Novosibirsk, Russia
- Laboratory of Psychological Genetics, Institute of Cytology and Genetics SB RAS, Novosibirsk, Russia
| | - Andrey V Bocharov
- Laboratory of Differential Psychophysiology, Institute of Neurosciences and Medicine, Novosibirsk, Russia
| | - Alexander E Saprigyn
- Laboratory of Differential Psychophysiology, Institute of Neurosciences and Medicine, Novosibirsk, Russia
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12
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Tang Y, Hu Y, Zhuang J, Feng C, Zhou X. Uncovering individual variations in bystander intervention of injustice through intrinsic brain connectivity patterns. Neuroimage 2024; 285:120468. [PMID: 38042393 DOI: 10.1016/j.neuroimage.2023.120468] [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: 08/03/2023] [Revised: 11/01/2023] [Accepted: 11/20/2023] [Indexed: 12/04/2023] Open
Abstract
When confronted with injustice, individuals often intervene as third parties to restore justice by either punishing the perpetrator or helping the victim, even at their own expense. However, little is known about how individual differences in third-party intervention propensity are related to inter-individual variability in intrinsic brain connectivity patterns and how these associations vary between help and punishment intervention. To address these questions, we employed a novel behavioral paradigm in combination with resting-state fMRI and inter-subject representational similarity analysis (IS-RSA). Participants acted as third-party bystanders and needed to decide whether to maintain the status quo or intervene by either helping the disadvantaged recipient (Help condition) or punishing the proposer (Punish condition) at a specific cost. Our analyses focused on three brain networks proposed in the third-party punishment (TPP) model: the salience (e.g., dorsal anterior cingulate cortex, dACC), central executive (e.g., dorsolateral prefrontal cortex, dlPFC), and default mode (e.g., dorsomedial prefrontal cortex, dmPFC; temporoparietal junction, TPJ) networks. IS-RSA showed that individual differences in resting-state functional connectivity (rs-FC) patterns within these networks were associated with the general third-party intervention propensity. Moreover, rs-FC patterns of the right dlPFC and right TPJ were more strongly associated with individual differences in the helping propensity rather than the punishment propensity, whereas the opposite pattern was observed for the dmPFC. Post-hoc predictive modeling confirmed the predictive power of rs-FC in these regions for intervention propensity across individuals. Collectively, these findings shed light on the shared and distinct roles of key regions in TPP brain networks at rest in accounting for individual variations in justice-restoring intervention behaviors.
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Affiliation(s)
- Yancheng Tang
- Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai, China
| | - Yang Hu
- School of Psychology and Cognitive Science, Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, East China Normal University, Shanghai, China.
| | - Jie Zhuang
- School of Psychology, Shanghai University of Sport, Shanghai, China
| | - Chunliang Feng
- School of Psychology, Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, Center for Studies of Psychological Application, Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, China
| | - Xiaolin Zhou
- Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai, China; School of Psychology and Cognitive Science, Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, East China Normal University, Shanghai, China.
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13
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She MHC, Sanfey AG. An experimental study of information transparency and social preferences on donation behaviors: the self-signaling model. Front Psychol 2023; 14:1258808. [PMID: 38022993 PMCID: PMC10667727 DOI: 10.3389/fpsyg.2023.1258808] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 10/27/2023] [Indexed: 12/01/2023] Open
Abstract
Certain segments of the population reply on charitable or other non-governmental organizations as their main source of support, with these organizations largely funded by those in society who can afford to give. The present study investigated to what extent information transparency influences donation decisions, and whether specific preferences for charities influences information seeking behavior. We recruited 114 participants via Prolific and employed a binary online Dictator Game to address these two study objectives. The results showed that participants' actual donation behavior was not influenced by their charity preference or the level of information transparency. However, they were more prone to seek out additional information when deciding about the most preferred category of charity. These results raise important questions as to whether the perceived anonymity of online choices may differ from choices carried out in person.
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Affiliation(s)
- Minnie H. C. She
- Behavioural Science Institute, Radboud University, Nijmegen, Netherlands
| | - Alan G. Sanfey
- Behavioural Science Institute, Radboud University, Nijmegen, Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands
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14
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Cheong JH, Molani Z, Sadhukha S, Chang LJ. Synchronized affect in shared experiences strengthens social connection. Commun Biol 2023; 6:1099. [PMID: 37898664 PMCID: PMC10613250 DOI: 10.1038/s42003-023-05461-2] [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: 01/20/2020] [Accepted: 10/13/2023] [Indexed: 10/30/2023] Open
Abstract
People structure their days to experience events with others. We gather to eat meals, watch TV, and attend concerts together. What constitutes a shared experience and how does it manifest in dyadic behavior? The present study investigates how shared experiences-measured through emotional, motoric, physiological, and cognitive alignment-promote social bonding. We recorded the facial expressions and electrodermal activity (EDA) of participants as they watched four episodes of a TV show for a total of 4 h with another participant. Participants displayed temporally synchronized and spatially aligned emotional facial expressions and the degree of synchronization predicted the self-reported social connection ratings between viewing partners. We observed a similar pattern of results for dyadic physiological synchrony measured via EDA and their cognitive impressions of the characters. All four of these factors, temporal synchrony of positive facial expressions, spatial alignment of expressions, EDA synchrony, and character impression similarity, contributed to a latent factor of a shared experience that predicted social connection. Our findings suggest that the development of interpersonal affiliations in shared experiences emerges from shared affective experiences comprising synchronous processes and demonstrate that these complex interpersonal processes can be studied in a holistic and multi-modal framework leveraging naturalistic experimental designs.
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Affiliation(s)
- Jin Hyun Cheong
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA
| | - Zainab Molani
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA
| | - Sushmita Sadhukha
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA
| | - Luke J Chang
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA.
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15
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Xu J, Hu L, Qiao R, Hu Y, Tian Y. Music-emotion EEG coupling effects based on representational similarity. J Neurosci Methods 2023; 398:109959. [PMID: 37661055 DOI: 10.1016/j.jneumeth.2023.109959] [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: 06/19/2023] [Revised: 08/05/2023] [Accepted: 08/30/2023] [Indexed: 09/05/2023]
Abstract
BACKGROUND Music can evoke intense emotions and music emotion is a complex cognitive process. However, we know little about the cognitive mechanisms underlying these processes, and there are significant individual differences in the emotional responses to the same musical stimuli. NEW METHOD We used the inter-subject representational similarity analysis (IS-RSA) method to investigate the shared music emotion responses across multiple participants. In addition, we extended IS-RSA to estimate the group cross-frequency coupling effects of music emotion. Based on the cross-frequency coupling IS-RSA, we analyzed the differences in cross-frequency coupling patterns under different music emotions using MI. Comparison of existing methods: most current IS-RSA analyses focus on within-frequency band analysis. However, the cognitive processing of music emotion involves not only activation and brain network connections differences within frequency bands but also information communication between frequency bands. RESULTS The results of the within-frequency band IS-RSA analysis showed that the theta and gamma frequency bands play important roles in the inter-participant consistency of music emotion. The inter-frequency band IS-RSA analysis showed that the theta-beta coupling pattern exhibited stronger inter-participant consistency compared to the theta-gamma coupling pattern, and the theta-beta coupling had significant consistent representation across various music conditions. Through the significant regions of cross-frequency coupling representation similarity analysis, we performed phase-amplitude coupling analysis on FC4-C6 and FC4-Pz connections. For the theta-beta coupling pattern, we found that the MI of these two connections exhibited different coupling patterns under different music conditions, and they showed a significant decrease compared to the baseline period.
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Affiliation(s)
- Jiayang Xu
- School of Bioinformatics, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
| | - Liangliang Hu
- School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China; West China institute of children's brain and cognition, Chongqing university of education, Chongqing 400065, China
| | - Rui Qiao
- School of Bioinformatics, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
| | - Yilin Hu
- School of Bioinformatics, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
| | - Yin Tian
- School of Bioinformatics, Chongqing University of Posts and Telecommunications, Chongqing 400065, China; School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China; Institute for Advanced Sciences,Chongqing University of Posts and Telecommunications, Chongqing 400065, China; Chongqing Institute for Brain and Intelligence, Guangyang Bay Laboratory, Chongqing 400064, China.
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16
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Wu X, Wang X, Lu XJ, Kong YZ, Hu L. Enhanced neural synchrony associated with long-term ballroom dance training. Neuroimage 2023; 278:120301. [PMID: 37524169 DOI: 10.1016/j.neuroimage.2023.120301] [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: 03/06/2023] [Revised: 07/25/2023] [Accepted: 07/28/2023] [Indexed: 08/02/2023] Open
Abstract
Long-term dance training offers numerous benefits, including improvements in physical health, posture, body coordination, and mental health and well-being. Since dance is an art form of body-to-body communication, professional dancers may share feelings and thoughts on dance with their partners, owing to their shared training experiences. Considering this perspective, one may expect that professional dancers would demonstrate pronounced neural similarities when viewing dancing videos, which could be associated with their training duration. To test these hypotheses, we collected functional magnetic resonance imaging (fMRI) data while presenting ballroom dancing and neutral video clips with long durations (∼100 s each) to 41 professional ballroom dancers (19 pairs of dance partners) and 39 age- and sex-matched nondancers. Our findings revealed that dancers exhibited broader and stronger neural similarities across the whole brain when watching dancing video clips, as compared to the control group. These increased neural similarities could be interpreted in at least two distinct ways. First, neural similarities in certain brain regions within the motor control circuit (i.e., frontal cortical-basal ganglia-thalamic circuit) were significantly correlated with dance-related information (e.g., dance partners' cooperation duration), which reinforced the impact of long-term dance training on neural synchronization. Second, neural similarities in other brain regions (e.g., memory-related brain regions) were significantly correlated with subjects' impression of the viewed videos (i.e., whether they have watched before, familiarity, and liking), which may not necessarily be directly linked to long-term dance training. Altogether, our study provided solid evidence for synchronized neural mechanisms in professional dancers due to long-term dance training.
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Affiliation(s)
- Xiao Wu
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China; CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
| | - Xiao Wang
- School of Art, Beijing Sport University, Beijing 100084, China
| | - Xue-Jing Lu
- Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China; CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
| | - Ya-Zhuo Kong
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Li Hu
- Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China; CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China.
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17
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Houlihan SD, Kleiman-Weiner M, Hewitt LB, Tenenbaum JB, Saxe R. Emotion prediction as computation over a generative theory of mind. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2023; 381:20220047. [PMID: 37271174 DOI: 10.1098/rsta.2022.0047] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 03/16/2023] [Indexed: 06/06/2023]
Abstract
From sparse descriptions of events, observers can make systematic and nuanced predictions of what emotions the people involved will experience. We propose a formal model of emotion prediction in the context of a public high-stakes social dilemma. This model uses inverse planning to infer a person's beliefs and preferences, including social preferences for equity and for maintaining a good reputation. The model then combines these inferred mental contents with the event to compute 'appraisals': whether the situation conformed to the expectations and fulfilled the preferences. We learn functions mapping computed appraisals to emotion labels, allowing the model to match human observers' quantitative predictions of 20 emotions, including joy, relief, guilt and envy. Model comparison indicates that inferred monetary preferences are not sufficient to explain observers' emotion predictions; inferred social preferences are factored into predictions for nearly every emotion. Human observers and the model both use minimal individualizing information to adjust predictions of how different people will respond to the same event. Thus, our framework integrates inverse planning, event appraisals and emotion concepts in a single computational model to reverse-engineer people's intuitive theory of emotions. This article is part of a discussion meeting issue 'Cognitive artificial intelligence'.
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Affiliation(s)
- Sean Dae Houlihan
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Max Kleiman-Weiner
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Psychology, Harvard University, Cambridge, MA, USA
| | - Luke B Hewitt
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Joshua B Tenenbaum
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Rebecca Saxe
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
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18
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Li Z, Dong Q, Hu B, Wu H. Every individual makes a difference: A trinity derived from linking individual brain morphometry, connectivity and mentalising ability. Hum Brain Mapp 2023; 44:3343-3358. [PMID: 37051692 PMCID: PMC10171537 DOI: 10.1002/hbm.26285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 02/01/2023] [Accepted: 03/08/2023] [Indexed: 04/14/2023] Open
Abstract
Mentalising ability, indexed as the ability to understand others' beliefs, feelings, intentions, thoughts and traits, is a pivotal and fundamental component of human social cognition. However, considering the multifaceted nature of mentalising ability, little research has focused on characterising individual differences in different mentalising components. And even less research has been devoted to investigating how the variance in the structural and functional patterns of the amygdala and hippocampus, two vital subcortical regions of the "social brain", are related to inter-individual variability in mentalising ability. Here, as a first step toward filling these gaps, we exploited inter-subject representational similarity analysis (IS-RSA) to assess relationships between amygdala and hippocampal morphometry (surface-based multivariate morphometry statistics, MMS), connectivity (resting-state functional connectivity, rs-FC) and mentalising ability (interactive mentalisation questionnaire [IMQ] scores) across the participants ( N = 24 $$ N=24 $$ ). In IS-RSA, we proposed a novel pipeline, that is, computing patching and pooling operations-based surface distance (CPP-SD), to obtain a decent representation for high-dimensional MMS data. On this basis, we found significant correlations (i.e., second-order isomorphisms) between these three distinct modalities, indicating that a trinity existed in idiosyncratic patterns of brain morphometry, connectivity and mentalising ability. Notably, a region-related mentalising specificity emerged from these associations: self-self and self-other mentalisation are more related to the hippocampus, while other-self mentalisation shows a closer link with the amygdala. Furthermore, by utilising the dyadic regression analysis, we observed significant interactions such that subject pairs with similar morphometry had even greater mentalising similarity if they were also similar in rs-FC. Altogether, we demonstrated the feasibility and illustrated the promise of using IS-RSA to study individual differences, deepening our understanding of how individual brains give rise to their mentalising abilities.
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Affiliation(s)
- Zhaoning Li
- Centre for Cognitive and Brain Sciences and Department of Psychology, University of Macau, Taipa, China
| | - Qunxi Dong
- School of Medical Technology, Beijing Institute of Technology, Beijing, China
| | - Bin Hu
- School of Medical Technology, Beijing Institute of Technology, Beijing, China
| | - Haiyan Wu
- Centre for Cognitive and Brain Sciences and Department of Psychology, University of Macau, Taipa, China
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19
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Vives ML, Heffner J, FeldmanHall O. Conceptual representations of uncertainty predict risky decision-making. COGNITIVE, AFFECTIVE & BEHAVIORAL NEUROSCIENCE 2023:10.3758/s13415-023-01090-8. [PMID: 37029276 DOI: 10.3758/s13415-023-01090-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 03/13/2023] [Indexed: 04/09/2023]
Abstract
Decisions made under uncertainty often are considered according to their perceived subjective value. We move beyond this traditional framework to explore the hypothesis that conceptual representations of uncertainty influence risky choice. Results reveal that uncertainty concepts are represented along a dimension that jointly captures probabilistic and valenced features of the conceptual space. These uncertainty representations predict the degree to which an individual engages in risky decision-making. Moreover, we find that most individuals have two largely distinct representations: one for uncertainty and another for certainty. In contrast, a minority of individuals exhibit substantial overlap between their representations of uncertainty and certainty. Together, these findings reveal the relationship between the conceptualization of uncertainty and risky decisions.
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Affiliation(s)
- Marc-Lluís Vives
- Department of Cognitive, Linguistic, Psychological Sciences, Brown University, Providence, RI, USA
- Institute of Psychology, Leiden University, Leiden, The Netherlands
| | - Joseph Heffner
- Department of Cognitive, Linguistic, Psychological Sciences, Brown University, Providence, RI, USA
- Department of Psychology, Yale University, New Haven, CT, USA
| | - Oriel FeldmanHall
- Department of Cognitive, Linguistic, Psychological Sciences, Brown University, Providence, RI, USA.
- Carney Institute for Brain Science, Brown University, Providence, RI, USA.
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20
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de Bruin D, van Baar JM, Rodríguez PL, FeldmanHall O. Shared neural representations and temporal segmentation of political content predict ideological similarity. SCIENCE ADVANCES 2023; 9:eabq5920. [PMID: 36724226 PMCID: PMC9891706 DOI: 10.1126/sciadv.abq5920] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 01/03/2023] [Indexed: 06/18/2023]
Abstract
Despite receiving the same sensory input, opposing partisans often interpret political content in disparate ways. Jointly analyzing controlled and naturalistic functional magnetic resonance imaging data, we uncover the neurobiological mechanisms explaining how these divergent political viewpoints arise. Individuals who share an ideology have more similar neural representations of political words, experience greater neural synchrony during naturalistic political content, and temporally segment real-world information into the same meaningful units. In the striatum and amygdala, increasing intersubject similarity in neural representations of political concepts during a word reading task predicts enhanced synchronization of blood oxygen level-dependent time courses when viewing real-time, inflammatory political videos, revealing that polarization can arise from differences in the brain's affective valuations of political concepts. Together, this research shows that political ideology is shaped by semantic representations of political concepts processed in an environment free of any polarizing agenda and that these representations bias how real-world political information is construed into a polarized perspective.
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Affiliation(s)
- Daantje de Bruin
- Department of Cognitive, Linguistic, Psychological Sciences, Brown University, Providence, RI, USA
| | - Jeroen M. van Baar
- Department of Cognitive, Linguistic, Psychological Sciences, Brown University, Providence, RI, USA
- Trimbos Institute, Netherlands Institute of Mental Health and Addiction, Utrecht, Netherlands
| | - Pedro L. Rodríguez
- Center for Data Science, New York University, New York, NY, USA
- International Faculty, Instituto de Estudios Superiores de Administración, Caracas, Venezuela
| | - Oriel FeldmanHall
- Department of Cognitive, Linguistic, Psychological Sciences, Brown University, Providence, RI, USA
- Carney Institute for Brain Science, Brown University, Providence, RI, USA
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21
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Haselager P, Schraffenberger H, Thill S, Fischer S, Lanillos P, van de Groes S, van Hooff M. Reflection Machines: Supporting Effective Human Oversight Over Medical Decision Support Systems. Camb Q Healthc Ethics 2023:1-10. [PMID: 36624620 DOI: 10.1017/s0963180122000718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Human decisions are increasingly supported by decision support systems (DSS). Humans are required to remain "on the loop," by monitoring and approving/rejecting machine recommendations. However, use of DSS can lead to overreliance on machines, reducing human oversight. This paper proposes "reflection machines" (RM) to increase meaningful human control. An RM provides a medical expert not with suggestions for a decision, but with questions that stimulate reflection about decisions. It can refer to data points or suggest counterarguments that are less compatible with the planned decision. RMs think against the proposed decision in order to increase human resistance against automation complacency. Building on preliminary research, this paper will (1) make a case for deriving a set of design requirements for RMs from EU regulations, (2) suggest a way how RMs could support decision-making, (3) describe the possibility of how a prototype of an RM could apply to the medical domain of chronic low back pain, and (4) highlight the importance of exploring an RM's functionality and the experiences of users working with it.
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Affiliation(s)
- Pim Haselager
- Donders Institute for Brain, Cognition and Behaviour, Department of AI, Radboud University, Nijmegen, The Netherlands
| | | | - Serge Thill
- Donders Institute for Brain, Cognition and Behaviour, Department of AI, Radboud University, Nijmegen, The Netherlands
| | - Simon Fischer
- Donders Institute for Brain, Cognition and Behaviour, Department of AI, Radboud University, Nijmegen, The Netherlands
| | - Pablo Lanillos
- Donders Institute for Brain, Cognition and Behaviour, Department of AI, Radboud University, Nijmegen, The Netherlands
| | | | - Miranda van Hooff
- Health Sciences, Radboud UMC, Nijmegen, The Netherlands
- St Maartenskliniek, Nijmegen, The Netherlands
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22
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Jolly E, Farrens M, Greenstein N, Eisenbarth H, Reddan MC, Andrews E, Wager TD, Chang LJ. Recovering Individual Emotional States from Sparse Ratings Using Collaborative Filtering. AFFECTIVE SCIENCE 2022; 3:799-817. [PMID: 36519147 PMCID: PMC9743951 DOI: 10.1007/s42761-022-00161-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 10/03/2022] [Indexed: 11/21/2022]
Abstract
A fundamental challenge in emotion research is measuring feeling states with high granularity and temporal precision without disrupting the emotion generation process. Here we introduce and validate a new approach in which responses are sparsely sampled and the missing data are recovered using a computational technique known as collaborative filtering (CF). This approach leverages structured covariation across individual experiences and is available in Neighbors, an open-source Python toolbox. We validate our approach across three different experimental contexts by recovering dense individual ratings using only a small subset of the original data. In dataset 1, participants (n=316) separately rated 112 emotional images on 6 different discrete emotions. In dataset 2, participants (n=203) watched 8 short emotionally engaging autobiographical stories while simultaneously providing moment-by-moment ratings of the intensity of their affective experience. In dataset 3, participants (n=60) with distinct social preferences made 76 decisions about how much money to return in a hidden multiplier trust game. Across all experimental contexts, CF was able to accurately recover missing data and importantly outperformed mean and multivariate imputation, particularly in contexts with greater individual variability. This approach will enable new avenues for affective science research by allowing researchers to acquire high dimensional ratings from emotional experiences with minimal disruption to the emotion-generation process. Supplementary Information The online version contains supplementary material available at 10.1007/s42761-022-00161-2.
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Affiliation(s)
- Eshin Jolly
- Department of Psychological and Brain Sciences, Computational Social and Affective Neuroscience Laboratory, Dartmouth College, 6207 Moore Hall, Hanover, NH 03755 USA
| | - Max Farrens
- Department of Psychological and Brain Sciences, Computational Social and Affective Neuroscience Laboratory, Dartmouth College, 6207 Moore Hall, Hanover, NH 03755 USA
| | - Nathan Greenstein
- Department of Psychological and Brain Sciences, Computational Social and Affective Neuroscience Laboratory, Dartmouth College, 6207 Moore Hall, Hanover, NH 03755 USA
| | - Hedwig Eisenbarth
- School of Psychology, Victoria University of Wellington, Wellington, New Zealand
| | | | - Eric Andrews
- Department of Psychology, University of Arizona, Tucson, AZ USA
| | - Tor D. Wager
- Department of Psychological and Brain Sciences, Computational Social and Affective Neuroscience Laboratory, Dartmouth College, 6207 Moore Hall, Hanover, NH 03755 USA
| | - Luke J. Chang
- Department of Psychological and Brain Sciences, Computational Social and Affective Neuroscience Laboratory, Dartmouth College, 6207 Moore Hall, Hanover, NH 03755 USA
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23
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How do children adapt their fairness norm? Evidence from computational modeling. PLoS One 2022; 17:e0277508. [PMID: 36383514 PMCID: PMC9668110 DOI: 10.1371/journal.pone.0277508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 10/28/2022] [Indexed: 11/17/2022] Open
Abstract
Adequate social functioning during childhood requires context-appropriate social decision-making. To make such decisions, children rely on their social norms, conceptualized as cognitive models of shared expectations. Since social norms are dynamic, children must adapt their models of shared expectations and modify their behavior in line with their social environment. This study aimed to investigate children's abilities to use social information to adapt their fairness norm and to identify the computational mechanism governing this process. Thirty children (7-11 years, M = 7.9 SD = 0.85, 11 girls) played the role of Responder in a modified version of the Ultimatum Game-a two-player game based on the fairness norm-in which they had to choose to accept or reject offers from different Proposers. Norm adaptation was assessed by comparing rejection rates before and after a conditioning block in which children received several low offers. Computational models were compared to test which best explains children's behavior during the game. Mean rejection rate decreased significantly after receiving several low offers suggesting that children have the ability to dynamically update their fairness norm and adapt to changing social environments. Model-based analyses suggest that this process involves the computation of norm-prediction errors. This is the first study on norm adaptation capacities in school-aged children that uses a computational approach. Children use implicit social information to adapt their fairness norm to changing environments and this process appears to be supported by a computational mechanism in which norm-prediction errors are used to update norms.
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24
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Social Economic Decision-Making and Psychopathy: A Systematic Review and Meta-Analysis. Neurosci Biobehav Rev 2022; 143:104966. [DOI: 10.1016/j.neubiorev.2022.104966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Revised: 11/12/2022] [Accepted: 11/15/2022] [Indexed: 11/19/2022]
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25
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Yu H, Contreras-Huerta LS, Prosser AMB, Apps MAJ, Hofmann W, Sinnott-Armstrong W, Crockett MJ. Neural and Cognitive Signatures of Guilt Predict Hypocritical Blame. Psychol Sci 2022; 33:1909-1927. [PMID: 36201792 DOI: 10.1177/09567976221122765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
A common form of moral hypocrisy occurs when people blame others for moral violations that they themselves commit. It is assumed that hypocritical blamers act in this manner to falsely signal that they hold moral standards that they do not really accept. We tested this assumption by investigating the neurocognitive processes of hypocritical blamers during moral decision-making. Participants (62 adult UK residents; 27 males) underwent functional MRI scanning while deciding whether to profit by inflicting pain on others and then judged the blameworthiness of others' identical decisions. Observers (188 adult U.S. residents; 125 males) judged participants who blamed others for making the same harmful choice to be hypocritical, immoral, and untrustworthy. However, analyzing hypocritical blamers' behaviors and neural responses shows that hypocritical blame was positively correlated with conflicted feelings, neural responses to moral standards, and guilt-related neural responses. These findings demonstrate that hypocritical blamers may hold the moral standards that they apply to others.
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Affiliation(s)
- Hongbo Yu
- Department of Psychology, Yale University.,Department of Psychological and Brain Sciences, University of California Santa Barbara
| | - Luis Sebastian Contreras-Huerta
- Department of Experimental Psychology, University of Oxford.,Wellcome Centre for Integrative Neuroimaging, University of Oxford.,Centre for Human Brain Health, School of Psychology, University of Birmingham
| | - Annayah M B Prosser
- Department of Psychology, Yale University.,Department of Experimental Psychology, University of Oxford.,Department of Psychology, University of Bath
| | - Matthew A J Apps
- Department of Experimental Psychology, University of Oxford.,Centre for Human Brain Health, School of Psychology, University of Birmingham
| | | | - Walter Sinnott-Armstrong
- Center for Cognitive Neuroscience, Duke University.,Department of Philosophy, Duke University.,Kenan Institute for Ethics, Duke University.,Duke Institute for Brain Sciences, Duke University
| | - Molly J Crockett
- Department of Psychology, Yale University.,Department of Psychology, Princeton University
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26
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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: 0] [Impact Index Per Article: 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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Wang R, Yu R, Tian Y, Wu H. Individual variation in the neurophysiological representation of negative emotions in virtual reality is shaped by sociability. Neuroimage 2022; 263:119596. [PMID: 36041644 DOI: 10.1016/j.neuroimage.2022.119596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Revised: 08/24/2022] [Accepted: 08/26/2022] [Indexed: 01/10/2023] Open
Abstract
Negative emotions play a dominant role in daily human life, and mentalizing and empathy are also basic sociability in social life. However, little is known regards the neurophysiological pattern of negative experiences in immersive environments and how people with different sociabilities respond to the negative emotional stimuli at behavioral and neural levels. The present study investigated the neurophysiological representation of negative affective experiences and whether such variations are associated with one's sociability. To address this question, we examined four types of negative emotions that frequently occurred in real life: angry, anxious, fearful, and helpless. We combined naturalistic neuroimaging under virtual reality, multimodal neurophysiological recording, and behavioral measures. Inter-subject representational similarity analysis was conducted to capture the individual differences in the neurophysiological representations of negative emotional experiences. The behavioral and neurophysiological indices revealed that although the emotion ratings were uniquely different, a similar electroencephalography response pattern across these negative emotions was found over the parieto-occipital electrodes. Furthermore, the neurophysiological representations indeed reflected interpersonal variations regarding mentalizing and empathic abilities. Our findings yielded a common pattern of neurophysiological responses toward different negative affective experiences in VR. Moreover, the current results indicate the potential of taking a sociability perspective for understanding the interpersonal variations in the neurophysiological representation of emotion.
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Affiliation(s)
- Ruien Wang
- Centre for Cognitive and Brain Sciences and Department of Psychology, University of Macau, Taipa, Macau SAR, China
| | - Runquan Yu
- Centre for Cognitive and Brain Sciences and Department of Psychology, University of Macau, Taipa, Macau SAR, China
| | - Yan Tian
- Centre for Cognitive and Brain Sciences and Department of Psychology, University of Macau, Taipa, Macau SAR, China
| | - Haiyan Wu
- Centre for Cognitive and Brain Sciences and Department of Psychology, University of Macau, Taipa, Macau SAR, China.
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28
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Kim KI, Jung WH, Woo CW, Kim H. Neural signatures of individual variability in context-dependent perception of ambiguous facial expression. Neuroimage 2022; 258:119355. [PMID: 35660000 DOI: 10.1016/j.neuroimage.2022.119355] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Revised: 05/28/2022] [Accepted: 05/31/2022] [Indexed: 11/25/2022] Open
Abstract
How do we incorporate contextual information to infer others' emotional state? Here we employed a naturalistic context-dependent facial expression estimation task where participants estimated pleasantness levels of others' ambiguous expression faces when sniffing different contextual cues (e.g., urine, fish, water, and rose). Based on their pleasantness rating data, we placed participants on a context-dependency continuum and mapped the individual variability in the context-dependency onto the neural representation using a representational similarity analysis. We found that the individual variability in the context-dependency of facial expression estimation correlated with the activity level of the pregenual anterior cingulate cortex (pgACC) and the amygdala and was also decoded by the neural representation of the ventral anterior insula (vAI). A dynamic causal modeling revealed that those with higher context-dependency exhibited a greater degree of the modulation from vAI to the pgACC. These findings provide novel insights into the neural circuitry associated with the individual variability in context-dependent facial expression estimation and the first empirical evidence for individual variability in the predictive accounts of affective states.
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Affiliation(s)
- Kun Il Kim
- School of Psychology, Korea University, Seoul, Republic of Korea
| | - Wi Hoon Jung
- Department of Psychology, Gachon University, Seongnam, Republic of Korea
| | - Choong-Wan Woo
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Sungkyunkwan University, Suwon, Republic of Korea; Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea; Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Republic of Korea
| | - Hackjin Kim
- School of Psychology, Korea University, Seoul, Republic of Korea.
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29
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Chen H, Dong Y, Jiang S, Li Z, Krueger F, Wu Y. Fragile promise: The role of justification in
promise‐breaking. ASIAN JOURNAL OF SOCIAL PSYCHOLOGY 2022. [DOI: 10.1111/ajsp.12542] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- He Chen
- Department of Psychology, College of Hengyi Jing Education Hangzhou Normal University Hangzhou China
- Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairment Hangzhou Normal University Hangzhou China
| | - Yuxuan Dong
- Department of Psychology, College of Hengyi Jing Education Hangzhou Normal University Hangzhou China
- Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairment Hangzhou Normal University Hangzhou China
| | - Shaohan Jiang
- Department of Psychology, College of Hengyi Jing Education Hangzhou Normal University Hangzhou China
- Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairment Hangzhou Normal University Hangzhou China
| | - Zenghui Li
- Department of Psychology, College of Hengyi Jing Education Hangzhou Normal University Hangzhou China
- Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairment Hangzhou Normal University Hangzhou China
| | - Frank Krueger
- School of Systems Biology George Mason University Fairfax Virginia USA
- Department of Psychology University of Mannheim Mannheim Germany
| | - Yan Wu
- Department of Psychology, College of Hengyi Jing Education Hangzhou Normal University Hangzhou China
- Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairment Hangzhou Normal University Hangzhou China
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30
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Musz E, Chen J. Neural signatures associated with temporal compression in the verbal retelling of past events. Commun Biol 2022; 5:489. [PMID: 35606497 PMCID: PMC9126919 DOI: 10.1038/s42003-022-03418-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 04/26/2022] [Indexed: 11/17/2022] Open
Abstract
When we retell our past experiences, we aim to reproduce some version of the original events; this reproduced version is often temporally compressed relative to the original. However, it is currently unclear how this compression manifests in brain activity. One possibility is that a compressed retrieved memory manifests as a neural pattern which is more dissimilar to the original, relative to a more detailed or vivid memory. However, we argue that measuring raw dissimilarity alone is insufficient, as it confuses a variety of interesting and uninteresting changes. To address this problem, we examine brain pattern changes that are consistent across people. We show that temporal compression in individuals’ retelling of past events predicts systematic encoding-to-recall transformations in several higher associative regions. These findings elucidate how neural representations are not simply reactivated, but can also be transformed due to temporal compression during a universal form of human memory expression: verbal retelling. Brain patterns measured while participants first watched a movie in the fMRI scanner, then recalled the movie’s key narrative features, demonstrate that temporal compression in individuals’ retelling of past events predicts encoding-to-recall transformations.
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Affiliation(s)
- Elizabeth Musz
- Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD, 21218, USA.
| | - Janice Chen
- Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD, 21218, USA
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31
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A Model of Trust. GAMES 2022. [DOI: 10.3390/g13030039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Trust is central to a large variety of social interactions. Different research fields have empirically and theoretically investigated trust, observing trusting behaviors in different situations and pinpointing their different components and constituents. However, a unifying, computational formalization of those diverse components and constituents of trust is still lacking. Previous work has mainly used computational models borrowed from other fields and developed for other purposes to explain trusting behaviors in empirical paradigms. Here, I computationally formalize verbal models of trust in a simple model (i.e., vulnerability model) that combines current and prospective action values with beliefs and expectancies about a partner’s behavior. By using the classic investment game (IG)—an economic game thought to capture some important features of trusting behaviors in social interactions—I show how variations of a single parameter of the vulnerability model generates behaviors that can be interpreted as different “trust attitudes”. I then show how these behavioral patterns change as a function of an individual’s loss aversion and expectations of the partner’s behavior. I finally show how the vulnerability model can be easily extended in a novel IG paradigm to investigate inferences on different traits of a partner. In particular, I will focus on benevolence and competence—two character traits that have previously been described as determinants of trustworthiness impressions central to trust. The vulnerability model can be employed as is or as a utility function within more complex Bayesian frameworks to fit participants’ behavior in different social environments where actions are associated with subjective values and weighted by individual beliefs about others’ behaviors. Hence, the vulnerability model provides an important building block for future theoretical and empirical work across a variety of research fields.
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32
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Xie E, Liu M, Liu J, Gao X, Li X. Neural mechanisms of the mood effects on third‐party responses to injustice after unfair experiences. Hum Brain Mapp 2022; 43:3646-3661. [PMID: 35426965 PMCID: PMC9294295 DOI: 10.1002/hbm.25874] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2021] [Revised: 03/26/2022] [Accepted: 04/02/2022] [Indexed: 12/01/2022] Open
Abstract
Behavioral decision theory argues that humans can adjust their third‐party responses (e.g., punishment and compensation) to injustice by integrating unfair experiences. Typically, the mood plays an important role in such a decision‐making process. However, the underlying neurocognitive bases remain largely unclear. We first employ a modified third‐party justice game in which an allocator split an amount of money between oneself and a receiver. The participants can reapportion the money as observers by choosing from the following three costly options: compensate the receiver, accept the current allocation, or punish the allocator. Then, a second‐party pseudo interaction is conducted where participants receive more (i.e., advantageous unfair experience) or less (i.e., disadvantageous unfair experience) than others. Finally, participants perform the third‐party justice game again after unfair experiences. Here, we use functional near‐infrared spectroscopy (fNIRS) to measure participants' brain activities during third‐party responses to injustice. We find participants compensate more to the receiver after advantageous unfair experience, which involved enhanced positive emotion, weakened sense of unfairness, and is linked with increased activity in the right dorsolateral prefrontal cortex (rDLPFC). In contrast, participants punish more on the allocator after disadvantageous unfair experience, which might primarily stem from their negative emotional responses, strong sense of unfairness, and is associated with significantly decreased activity in the rDLPFC. Our results suggest that third‐party compensation and punishment involved differential psychological and neural bases. Our findings highlight the crucial roles of second‐party unfair experiences and the corresponding mood responses in third‐party responses to unfairness, and unravel the intermediate neural architecture.
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Affiliation(s)
- Enhui Xie
- Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science East China Normal University Shanghai China
| | - Mengdie Liu
- Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science East China Normal University Shanghai China
| | - Jieqiong Liu
- Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science East China Normal University Shanghai China
| | - Xiaoxue Gao
- Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, School of Psychology and Cognitive Science East China Normal University Shanghai China
| | - Xianchun Li
- Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science East China Normal University Shanghai China
- Shanghai Changning Mental Health Center Shanghai China
- Institute of Wisdom in China East China Normal University Shanghai China
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33
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Awad E, Levine S, Anderson M, Anderson SL, Conitzer V, Crockett MJ, Everett JAC, Evgeniou T, Gopnik A, Jamison JC, Kim TW, Liao SM, Meyer MN, Mikhail J, Opoku-Agyemang K, Borg JS, Schroeder J, Sinnott-Armstrong W, Slavkovik M, Tenenbaum JB. Computational ethics. Trends Cogn Sci 2022; 26:388-405. [PMID: 35365430 DOI: 10.1016/j.tics.2022.02.009] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 02/14/2022] [Accepted: 02/25/2022] [Indexed: 12/11/2022]
Abstract
Technological advances are enabling roles for machines that present novel ethical challenges. The study of 'AI ethics' has emerged to confront these challenges, and connects perspectives from philosophy, computer science, law, and economics. Less represented in these interdisciplinary efforts is the perspective of cognitive science. We propose a framework - computational ethics - that specifies how the ethical challenges of AI can be partially addressed by incorporating the study of human moral decision-making. The driver of this framework is a computational version of reflective equilibrium (RE), an approach that seeks coherence between considered judgments and governing principles. The framework has two goals: (i) to inform the engineering of ethical AI systems, and (ii) to characterize human moral judgment and decision-making in computational terms. Working jointly towards these two goals will create the opportunity to integrate diverse research questions, bring together multiple academic communities, uncover new interdisciplinary research topics, and shed light on centuries-old philosophical questions.
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Affiliation(s)
- Edmond Awad
- Department of Economics, University of Exeter, Exeter, UK; Institute for Data Science and AI, University of Exeter, Exeter, UK; Center for Humans and Machines, Max-Planck Institute for Human Development, Berlin, Germany.
| | - Sydney Levine
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA; Department of Psychology, Harvard University, Cambridge, MA, USA.
| | - Michael Anderson
- Department of Computer Science, University of Hartford, West Hartford, CT, USA
| | | | - Vincent Conitzer
- Department of Computer Science, Duke University, Durham, NC, USA; Department of Economics, Duke University, Durham, NC, USA; Department of Philosophy, Duke University, Durham, NC, USA; Institute for Ethics in AI, University of Oxford, Oxford, UK
| | - M J Crockett
- Department of Psychology, Yale University, New Haven, CT, USA
| | | | | | - Alison Gopnik
- Department of Psychology, University of California, Berkeley, CA, USA
| | - Julian C Jamison
- Department of Economics, University of Exeter, Exeter, UK; Global Priorities Institute, Oxford University, Oxford, UK
| | - Tae Wan Kim
- Ethics Group, Tepper School of Business, Carnegie Mellon University, Pittsburgh, PA, USA
| | - S Matthew Liao
- Center for Bioethics, New York University, New York, NY, USA
| | - Michelle N Meyer
- Center for Translational Bioethics and Health Care Policy, Geisinger Health System, Danville, PA, USA; Steele Institute for Health Innovation, Geisinger Health System, Danville, PA, USA; Geisinger Commonwealth School of Medicine, Scranton, PA, USA
| | - John Mikhail
- Georgetown University Law Center, Washington, DC, USA
| | - Kweku Opoku-Agyemang
- International Growth Centre, London School of Economics, London, UK; Machine Learning X Doing, Toronto, ON, Canada; Development Economics X, Toronto, ON, Canada
| | - Jana Schaich Borg
- Social Science Research Institute, Duke University, Durham, NC, USA; Duke Institute for Brain Sciences, Duke University, Durham, NC, USA
| | - Juliana Schroeder
- Haas School of Business, University of California, Berkeley, CA, USA
| | - Walter Sinnott-Armstrong
- Department of Philosophy, Duke University, Durham, NC, USA; Duke Institute for Brain Sciences, Duke University, Durham, NC, USA; Kenan Institute for Ethics, Duke University, Durham, NC, USA
| | - Marija Slavkovik
- Department of Information Science and Media Studies, University of Bergen, Bergen, Norway
| | - Josh B Tenenbaum
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA; Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA, USA; Center for Brains, Minds, and Machines, MIT, Cambridge, MA, USA
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34
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van Baar JM, Nassar MR, Deng W, FeldmanHall O. Latent motives guide structure learning during adaptive social choice. Nat Hum Behav 2022; 6:404-414. [PMID: 34750584 DOI: 10.1038/s41562-021-01207-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Accepted: 09/01/2021] [Indexed: 11/09/2022]
Abstract
Predicting the behaviour of others is an essential part of social cognition. Despite its ubiquity, social prediction poses a poorly understood generalization problem: we cannot assume that others will repeat past behaviour in new settings or that their future actions are entirely unrelated to the past. We demonstrate that humans solve this challenge using a structure learning mechanism that uncovers other people's latent, unobservable motives, such as greed and risk aversion. In four studies, participants (N = 501) predicted other players' decisions across four economic games, each with different social tensions (for example, Prisoner's Dilemma and Stag Hunt). Participants achieved accurate social prediction by learning the stable motivational structure underlying a player's changing actions across games. This motive-based abstraction enabled participants to attend to information diagnostic of the player's next move and disregard irrelevant contextual cues. Participants who successfully learned another's motives were more strategic in a subsequent competitive interaction with that player in entirely new contexts, reflecting that social structure learning supports adaptive social behaviour.
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Affiliation(s)
- Jeroen M van Baar
- Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, RI, USA.,Trimbos Institute, Netherlands Institute of Mental Health and Addiction, Utrecht, the Netherlands
| | - Matthew R Nassar
- Department of Neuroscience, Brown University, Providence, RI, USA.,Carney Institute for Brain Science, Brown University, Providence, RI, USA
| | - Wenning Deng
- Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, RI, USA
| | - Oriel FeldmanHall
- Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, RI, USA. .,Carney Institute for Brain Science, Brown University, Providence, RI, USA.
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35
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Hevia-Orozco JC, Reyes-Aguilar A, Hernández-Pérez R, González-Santos L, Pasaye EH, Barrios FA. Personality Traits Induce Different Brain Patterns When Processing Social and Valence Information. Front Psychol 2022; 12:782754. [PMID: 35153905 PMCID: PMC8833229 DOI: 10.3389/fpsyg.2021.782754] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Accepted: 12/28/2021] [Indexed: 11/28/2022] Open
Abstract
This paper shows the brain correlates of Cloninger’s personality model during the presentation of social scenarios under positive or negative valence situations. Social scenarios were constructed when participants played the Dictator game with two confederates that had two opposites roles as the cooperator (Coop) and non-cooperator (NoCoop). Later the same day during a fMRI scanning session, participants read negative (Neg) and positive (Pos) situations that happened to confederates in the past. Participants were asked to think “how do you think those people felt during that situation?” A dissimilarity matrix between stimuli were obtained from fMRI results. Results shown that Harm Avoidance trait people make use of right middle frontal gyrus and left superior frontal gyrus to discriminate between Coop and NoCoop. Cooperation as a trait makes use of the right superior temporal gyrus and the right precuneus to discriminate between Coop and NoCoop in positive social scenarios. Finally, Self-directedness trait people make use of the right inferior parietal lobe to discriminate between Coop and NoCoop in negative social scenarios and the right precuneus to discriminate between Coop and Strangers. An intuitive link between discrimination findings and behavioral patterns of those personality traits is proposed.
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Affiliation(s)
- Jorge Carlos Hevia-Orozco
- Escuela de Psicología, Universidad Anáhuac Mayab, Mérida, Mexico
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Santiago de Querétaro, Mexico
| | - Azalea Reyes-Aguilar
- Facultad de Psicología, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Raúl Hernández-Pérez
- Department of Ethology, Institute of Biology, Eötvös Loránd University, Budapest, Hungary
| | - Leopoldo González-Santos
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Santiago de Querétaro, Mexico
| | - Erick H Pasaye
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Santiago de Querétaro, Mexico
| | - Fernando A Barrios
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Santiago de Querétaro, Mexico
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36
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Lo Presti S, Mattavelli G, Canessa N, Gianelli C. Risk perception and behaviour during the COVID-19 pandemic: Predicting variables of compliance with lockdown measures. PLoS One 2022; 17:e0262319. [PMID: 34986209 PMCID: PMC8730439 DOI: 10.1371/journal.pone.0262319] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 12/22/2021] [Indexed: 01/10/2023] Open
Abstract
The COVID-19 pandemic and the measures to counteract it have highlighted the role of individual differences in evaluating and reacting to emergencies, and the challenges inherent in promoting precautionary behaviours. We aimed to explore the psychological and cognitive factors modulating behaviour and intentions during the national lockdown in Italy. We administered an online questionnaire (N = 244) that included tests for assessing personality traits (Temperament and Character Inventory; Locus of Control of Behaviour) and moral judgment (Moral Foundations Questionnaire), alongside behavioural economics tasks addressing different facets of risk attitude (loss aversion, risk aversion and delay discounting). We then assessed the extent to which individual variations in these dimensions modulated participants' compliance with the lockdown norms. When assessing their joint contribution via multiple regressions, lockdown adherence was mostly predicted by internal locus of control, psycho-economic dimensions suggestive of long-sighted and loss-averse attitudes, as well as personality traits related to cautionary behaviour, such as harm avoidance, and the authority moral concern. These findings show that a multi-domain assessment of the factors underlying personal intentions, and thus driving compliance with government measures, can help predict individuals' actions during health emergencies. This evidence points to factors that should be considered when developing interventions and communication strategies to promote precautionary behaviours.
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Affiliation(s)
- Sara Lo Presti
- IUSS Cognitive Neuroscience (ICON) Center, Scuola Universitaria Superiore IUSS, Pavia, Italy
| | - Giulia Mattavelli
- IUSS Cognitive Neuroscience (ICON) Center, Scuola Universitaria Superiore IUSS, Pavia, Italy
- Istituti Clinici Scientifici Maugeri IRCCS, Cognitive Neuroscience Laboratory of Pavia Institute, Pavia, Italy
| | - Nicola Canessa
- IUSS Cognitive Neuroscience (ICON) Center, Scuola Universitaria Superiore IUSS, Pavia, Italy
- Istituti Clinici Scientifici Maugeri IRCCS, Cognitive Neuroscience Laboratory of Pavia Institute, Pavia, Italy
| | - Claudia Gianelli
- IUSS Cognitive Neuroscience (ICON) Center, Scuola Universitaria Superiore IUSS, Pavia, Italy
- Istituti Clinici Scientifici Maugeri IRCCS, Cognitive Neuroscience Laboratory of Pavia Institute, Pavia, Italy
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37
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Influence of reputational concern and social distance on moral decision-making under the harmful dilemma: Evidence from behavioral and ERPs study. ACTA PSYCHOLOGICA SINICA 2022. [DOI: 10.3724/sp.j.1041.2022.00613] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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38
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Zoh Y, Chang SWC, Crockett MJ. The prefrontal cortex and (uniquely) human cooperation: a comparative perspective. Neuropsychopharmacology 2022; 47:119-133. [PMID: 34413478 PMCID: PMC8617274 DOI: 10.1038/s41386-021-01092-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Revised: 06/03/2021] [Accepted: 06/24/2021] [Indexed: 02/07/2023]
Abstract
Humans have an exceptional ability to cooperate relative to many other species. We review the neural mechanisms supporting human cooperation, focusing on the prefrontal cortex. One key feature of human social life is the prevalence of cooperative norms that guide social behavior and prescribe punishment for noncompliance. Taking a comparative approach, we consider shared and unique aspects of cooperative behaviors in humans relative to nonhuman primates, as well as divergences in brain structure that might support uniquely human aspects of cooperation. We highlight a medial prefrontal network common to nonhuman primates and humans supporting a foundational process in cooperative decision-making: valuing outcomes for oneself and others. This medial prefrontal network interacts with lateral prefrontal areas that are thought to represent cooperative norms and modulate value representations to guide behavior appropriate to the local social context. Finally, we propose that more recently evolved anterior regions of prefrontal cortex play a role in arbitrating between cooperative norms across social contexts, and suggest how future research might fruitfully examine the neural basis of norm arbitration.
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Affiliation(s)
- Yoonseo Zoh
- grid.47100.320000000419368710Department of Psychology, Yale University, New Haven, USA
| | - Steve W. C. Chang
- grid.47100.320000000419368710Department of Psychology, Yale University, New Haven, USA
| | - Molly J. Crockett
- grid.47100.320000000419368710Department of Psychology, Yale University, New Haven, USA
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39
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Gao X, Yu H, Peng L, Gong X, Xiang Y, Jiang C, Zhou X. The mutuality of social emotions: How the victim's reactive attitude influences the transgressor's emotional responses. Neuroimage 2021; 244:118631. [PMID: 34601131 DOI: 10.1016/j.neuroimage.2021.118631] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Revised: 09/08/2021] [Accepted: 09/29/2021] [Indexed: 11/25/2022] Open
Abstract
Would a transgressor be guiltier or less after receiving the victim's forgiving or blaming attitude? Everyday intuitions and empirical evidence are mixed in this regard, leaving how interpersonal attitudes shape the transgressor's reactive social emotions an open question. We combined a social interactive game with multivariate pattern analysis of fMRI data to address this question. Participants played an interactive game in an fMRI scanner where their incorrect responses could cause either high or low pain stimulation to an anonymous co-player. Following incorrect responses, participants were presented with the co-player's (i.e., the victim's) attitude towards the harm (Blame, Forgive, or Neutral). Behaviorally, the victim's attitude and the severity of harm interactively modulated the transgressor's social emotions, with expectation violation serving as a mediator. While unexpected forgiveness following severe harm amplified the participants' guilt, unexpected blame following minor harm reduced the participants' guilt and increased their anger. This role of expectation violation was supported by multivariate pattern analysis of fMRI, revealing a shared neural representation in ventral striatum in the processing of victim's attitude-induced guilt and anger. Moreover, we identified a neural re-appraisal process of guilt in the transgressor, with the involvement of area related to self-conscious processing (i.e., perigenual anterior cingulate cortex) before knowing the victim's attitude transiting to the involvement of other-regarding related area (i.e., temporoparietal junction) after knowing the victim's attitude. These findings uncover the neurocognitive bases underlying the transgressor's social emotional responses, and highlight the importance of the mutuality of social emotions.
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Affiliation(s)
- Xiaoxue Gao
- Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, School of Psychology and Cognitive Science, East China Normal University, Shanghai 200062, China; School of Psychological and Cognitive Sciences, Peking University, Beijing 100871, China.
| | - Hongbo Yu
- Department of Psychological and Brain Sciences, University of California Santa Barbara, Santa Barbara, CA, 93106-9660, USA.
| | - Lu Peng
- School of Psychological and Cognitive Sciences, Peking University, Beijing 100871, China
| | - Xiaoliang Gong
- Key Laboratory of Embedded System and Service Computing (Ministry of Education), Tongji University, Shanghai 201804, China
| | - Yang Xiang
- Key Laboratory of Embedded System and Service Computing (Ministry of Education), Tongji University, Shanghai 201804, China
| | - Changjun Jiang
- Key Laboratory of Embedded System and Service Computing (Ministry of Education), Tongji University, Shanghai 201804, China
| | - Xiaolin Zhou
- Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, School of Psychology and Cognitive Science, East China Normal University, Shanghai 200062, China; School of Psychological and Cognitive Sciences, Peking University, Beijing 100871, China; School of Business and Management, Shanghai International Studies University, Shanghai 200083, China; Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing 100871, China; PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China.
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Functional Connectivity Basis and Underlying Cognitive Mechanisms for Gender Differences in Guilt Aversion. eNeuro 2021; 8:ENEURO.0226-21.2021. [PMID: 34819311 PMCID: PMC8675089 DOI: 10.1523/eneuro.0226-21.2021] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Revised: 11/05/2021] [Accepted: 11/18/2021] [Indexed: 11/21/2022] Open
Abstract
Prosocial behavior is pivotal to our society. Guilt aversion, which describes the tendency to reduce the discrepancy between a partner's expectation and his/her actual outcome, drives human prosocial behavior as does well-known inequity aversion. Although women are reported to be more inequity averse than men, gender differences in guilt aversion remain unexplored. Here, we conducted a functional magnetic resonance imaging (fMRI) study (n = 52) and a large-scale online behavioral study (n = 4723) of a trust game designed to investigate guilt and inequity aversions. The fMRI study demonstrated that men exhibited stronger guilt aversion and recruited right dorsolateral prefrontal cortex (DLPFC)-ventromedial PFC (VMPFC) connectivity more for guilt aversion than women, while VMPFC-dorsal medial PFC (DMPFC) connectivity was commonly used in both genders. Furthermore, our regression analysis of the online behavioral data collected with Big Five and demographic factors replicated the gender differences and revealed that Big Five Conscientiousness (rule-based decision) correlated with guilt aversion only in men, but Agreeableness (empathetic consideration) correlated with guilt aversion in both genders. Thus, this study suggests that gender differences in prosocial behavior are heterogeneous depending on underlying motives in the brain and that the consideration of social norms plays a key role in the stronger guilt aversion in men.
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Neurocomputational mechanisms engaged in moral choices and moral learning. Neurosci Biobehav Rev 2021; 132:50-60. [PMID: 34826508 DOI: 10.1016/j.neubiorev.2021.11.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 11/15/2021] [Accepted: 11/16/2021] [Indexed: 11/20/2022]
Abstract
The neural circuitry involved in moral decisions has been studied since the early days of cognitive neuroscience, mainly using moral dilemma. However, the neurocomputational mechanisms describing how the human brain makes moral decisions and learns in various moral contexts are only starting to be established. Here we review recent results from an emerging field using model-based fMRI, which describes moral choices at a mechanistic level. These findings unify the field of moral decision making, extend a conceptual framework previously developed for value-based decision making and characterize how moral processes are computed in the brain. Moral dilemma can be modeled as value-based decisions that weigh self-interests against moral costs/harm to others and different types of prediction errors can be distinguished in different aspects of moral learning. These key computational signals help to describe moral choices and moral learning at an algorithmic level and to reveal how these cognitive operations are implemented in the brain. This researches provide a foundation to account for the neurocomputational mechanisms underlying moral decision making.
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42
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Hilger K, Markett S. Personality network neuroscience: Promises and challenges on the way toward a unifying framework of individual variability. Netw Neurosci 2021; 5:631-645. [PMID: 34746620 PMCID: PMC8567832 DOI: 10.1162/netn_a_00198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2020] [Accepted: 04/22/2021] [Indexed: 11/21/2022] Open
Abstract
We propose that the application of network theory to established psychological personality conceptions has great potential to advance a biologically plausible model of human personality. Stable behavioral tendencies are conceived as personality “traits.” Such traits demonstrate considerable variability between individuals, and extreme expressions represent risk factors for psychological disorders. Although the psychometric assessment of personality has more than hundred years tradition, it is not yet clear whether traits indeed represent “biophysical entities” with specific and dissociable neural substrates. For instance, it is an open question whether there exists a correspondence between the multilayer structure of psychometrically derived personality factors and the organizational properties of traitlike brain systems. After a short introduction into fundamental personality conceptions, this article will point out how network neuroscience can enhance our understanding about human personality. We will examine the importance of intrinsic (task-independent) brain connectivity networks and show means to link brain features to stable behavioral tendencies. Questions and challenges arising from each discipline itself and their combination are discussed and potential solutions are developed. We close by outlining future trends and by discussing how further developments of network neuroscience can be applied to personality research.
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Affiliation(s)
- Kirsten Hilger
- Department of Psychology I, Julius-Maximilians University Würzburg, Würzburg, Germany
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43
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Li S, Hao X, Mei Y, Cheng Y, Sun N, Qu C. How Adolescents and Adults Learn About Changes in the Trustworthiness of Others Through Dynamic Interaction. Front Psychol 2021; 12:690494. [PMID: 34484041 PMCID: PMC8416302 DOI: 10.3389/fpsyg.2021.690494] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2021] [Accepted: 07/21/2021] [Indexed: 11/24/2022] Open
Abstract
Whether to trust or distrust another individual is a complex interpersonal challenge, especially when such individuals behave inconsistently. It is still unclear as to how individuals learn and adapt to fluctuations in the trustworthiness of others and how this process changes from adolescence to adulthood. To address these issues, we implemented repeated rounds of a trust game within the context of a complicated and changeable interpersonal environment. Specifically, adolescents and adults played the role of trustors who had to decide whether to invest money in two anonymous partners carrying the risk of no reciprocation. Unbeknownst to participants, these two partners had different trustworthiness profiles: one partner initially yielded a higher initial return rate (70%) while the other initially yielded a lower initial return rate (30%). Crucially, over repeated rounds, these two partners gradually changed their responses to the point where, finally, return rates were both neutral (50%). Results indicated that all participants showed less updating in the negative direction in response to good-to-neutral partners while more updating in the positive direction in response to the bad-to-neutral partner. Compared to adults, this behavioral disparity in responses to good-to-neutral and bad-to-neutral partners was less pronounced in adolescents. Based on the computational modeling approach, the potential mechanisms underlying their behavioral patterns were revealed: the higher learning rate promoted flexible adaptions in participants to untrustworthy trustees as they changed to neutral. The less pronounced distinction between good-to-neutral and bad-to-neutral partners in adolescents was related to their lower learning rate. Overall, our study extends the understanding of trust behavior to a fluctuating social context and highlights the role of social learning in social emotion and interaction.
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Affiliation(s)
- Siying Li
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, South China Normal University, Guangzhou, China.,School of Psychology, South China Normal University, Guangzhou, China.,Center for Studies of Psychological Application, South China Normal University, Guangzhou, China.,Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, China
| | - Xinmin Hao
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, South China Normal University, Guangzhou, China.,School of Psychology, South China Normal University, Guangzhou, China.,Center for Studies of Psychological Application, South China Normal University, Guangzhou, China.,Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, China
| | - Yueqi Mei
- Guangdong Country Garden School, Foshan, China
| | - Yinyi Cheng
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, South China Normal University, Guangzhou, China.,School of Psychology, South China Normal University, Guangzhou, China.,Center for Studies of Psychological Application, South China Normal University, Guangzhou, China.,Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, China
| | - Nan Sun
- School of Education, Guangzhou University, Guangzhou, China
| | - Chen Qu
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, South China Normal University, Guangzhou, China.,School of Psychology, South China Normal University, Guangzhou, China.,Center for Studies of Psychological Application, South China Normal University, Guangzhou, China.,Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, China
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44
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Russ BE, Petkov CI, Kwok SC, Zhu Q, Belin P, Vanduffel W, Hamed SB. Common functional localizers to enhance NHP & cross-species neuroscience imaging research. Neuroimage 2021; 237:118203. [PMID: 34048898 PMCID: PMC8529529 DOI: 10.1016/j.neuroimage.2021.118203] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Revised: 05/15/2021] [Accepted: 05/24/2021] [Indexed: 11/25/2022] Open
Abstract
Functional localizers are invaluable as they can help define regions of interest, provide cross-study comparisons, and most importantly, allow for the aggregation and meta-analyses of data across studies and laboratories. To achieve these goals within the non-human primate (NHP) imaging community, there is a pressing need for the use of standardized and validated localizers that can be readily implemented across different groups. The goal of this paper is to provide an overview of the value of localizer protocols to imaging research and we describe a number of commonly used or novel localizers within NHPs, and keys to implement them across studies. As has been shown with the aggregation of resting-state imaging data in the original PRIME-DE submissions, we believe that the field is ready to apply the same initiative for task-based functional localizers in NHP imaging. By coming together to collect large datasets across research group, implementing the same functional localizers, and sharing the localizers and data via PRIME-DE, it is now possible to fully test their robustness, selectivity and specificity. To do this, we reviewed a number of common localizers and we created a repository of well-established localizer that are easily accessible and implemented through the PRIME-RE platform.
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Affiliation(s)
- Brian E Russ
- Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, Orangeburg, NY, United States; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York City, NY, United States; Department of Psychiatry, New York University at Langone, New York City, NY, United States.
| | - Christopher I Petkov
- Biosciences Institute, Newcastle University Medical School, Newcastle upon Tyne, United Kingdom
| | - Sze Chai Kwok
- Shanghai Key Laboratory of Brain Functional Genomics, Key Laboratory of Brain Functional Genomics Ministry of Education, Shanghai Key Laboratory of Magnetic Resonance, Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, Shanghai, China; Division of Natural and Applied Sciences, Duke Kunshan University, Kunshan, Jiangsu, China; NYU-ECNU Institute of Brain and Cognitive Science at NYU Shanghai, Shanghai, China
| | - Qi Zhu
- Cognitive Neuroimaging Unit, INSERM, CEA, Université Paris-Saclay, NeuroSpin Center, 91191 Gif/Yvette, France; Laboratory for Neuro-and Psychophysiology, Department of Neurosciences, KU Leuven Medical School, Leuven, 3000, Belgium
| | - Pascal Belin
- Institut de Neurosciences de La Timone, Aix-Marseille Université et CNRS, Marseille, 13005, France
| | - Wim Vanduffel
- Laboratory for Neuro-and Psychophysiology, Department of Neurosciences, KU Leuven Medical School, Leuven, 3000, Belgium; Leuven Brain Institute, KU Leuven, Leuven, 3000, Belgium; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, United States; Department of Radiology, Harvard Medical School, Boston, MA 02144, United States.
| | - Suliann Ben Hamed
- Institut des Sciences Cognitives Marc Jeannerod, UMR 5229, Université de Lyon - CNRS, France.
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van Baar JM, Halpern DJ, FeldmanHall O. Intolerance of uncertainty modulates brain-to-brain synchrony during politically polarized perception. Proc Natl Acad Sci U S A 2021; 118:e2022491118. [PMID: 33986114 PMCID: PMC8157931 DOI: 10.1073/pnas.2022491118] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Political partisans see the world through an ideologically biased lens. What drives political polarization? Although it has been posited that polarization arises because of an inability to tolerate uncertainty and a need to hold predictable beliefs about the world, evidence for this hypothesis remains elusive. We examined the relationship between uncertainty tolerance and political polarization using a combination of brain-to-brain synchrony and intersubject representational similarity analysis, which measured committed liberals' and conservatives' (n = 44) subjective interpretation of naturalistic political video material. Shared ideology between participants increased neural synchrony throughout the brain during a polarizing political debate filled with provocative language but not during a neutrally worded news clip on polarized topics or a nonpolitical documentary. During the political debate, neural synchrony in mentalizing and valuation networks was modulated by one's aversion to uncertainty: Uncertainty-intolerant individuals experienced greater brain-to-brain synchrony with politically like-minded peers and lower synchrony with political opponents-an effect observed for liberals and conservatives alike. Moreover, the greater the neural synchrony between committed partisans, the more likely that two individuals formed similar, polarized attitudes about the debate. These results suggest that uncertainty attitudes gate the shared neural processing of political narratives, thereby fueling polarized attitude formation about hot-button issues.
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Affiliation(s)
- Jeroen M van Baar
- Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, RI 02912
| | - David J Halpern
- Department of Psychology, New York University, New York, NY 10002
- Department of Psychology, University of Pennsylvania, Philadelphia, PA 19104
| | - Oriel FeldmanHall
- Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, RI 02912;
- Carney Institute for Brain Science, Brown University, Providence, RI 02912
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46
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When my wrongs are worse than yours: Behavioral and neural asymmetries in first-person and third-person perspectives of accidental harms. JOURNAL OF EXPERIMENTAL SOCIAL PSYCHOLOGY 2021. [DOI: 10.1016/j.jesp.2021.104102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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47
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Donnarumma F, Pezzulo G. Moral decisions in the age of COVID-19: Your choices really matter. SOCIAL SCIENCES & HUMANITIES OPEN 2021; 4:100149. [PMID: 34927057 PMCID: PMC8665354 DOI: 10.1016/j.ssaho.2021.100149] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Revised: 03/27/2021] [Accepted: 04/01/2021] [Indexed: 12/21/2022]
Abstract
The moral decisions we make during this period, such as deciding whether to comply with quarantine rules, have unprecedented societal effects. We simulate the "escape from Milan" that occurred on March 7th-8th 2020, when many travelers moved from a high-risk zone (Milan) to southern regions of Italy (Campania and Lazio) immediately after an imminent lockdown was announced. Our simulations show that fewer than 50 active cases might have caused the sudden spread of the virus observed afterwards in these regions. The surprising influence of the actions of few individuals on societal dynamics challenges our cognitive expectations - as in normal conditions, collective dynamics are rather robust to the decisions of few "cheaters". This situation therefore requires novel educational strategies that increase our awareness and understanding of the unprecedented effects of our individual moral decisions.
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Affiliation(s)
- Francesco Donnarumma
- Institute of Cognitive Sciences and Technologies, National Research Council, Via S. Martino Della Battaglia 44, 00185, Rome, Italy
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Via S. Martino Della Battaglia 44, 00185, Rome, Italy
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48
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Finn ES, Bandettini PA. Movie-watching outperforms rest for functional connectivity-based prediction of behavior. Neuroimage 2021; 235:117963. [PMID: 33813007 PMCID: PMC8204673 DOI: 10.1016/j.neuroimage.2021.117963] [Citation(s) in RCA: 84] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 02/23/2021] [Accepted: 03/08/2021] [Indexed: 01/31/2023] Open
Abstract
A major goal of human neuroscience is to relate differences in brain function to differences in behavior across people. Recent work has established that whole-brain functional connectivity patterns are relatively stable within individuals and unique across individuals, and that features of these patterns predict various traits. However, while functional connectivity is most often measured at rest, certain tasks may enhance individual signals and improve sensitivity to behavior differences. Here, we show that compared to the resting state, functional connectivity measured during naturalistic viewing—i.e., movie watching—yields more accurate predictions of trait-like phenotypes in the domains of both cognition and emotion. Traits could be predicted using less than three minutes of data from single video clips, and clips with highly social content gave the most accurate predictions. Results suggest that naturalistic stimuli amplify individual differences in behaviorally relevant brain networks.
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Affiliation(s)
- Emily S Finn
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD, United States; Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, United States.
| | - Peter A Bandettini
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD, United States
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49
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Hu Y, Hu C, Derrington E, Corgnet B, Qu C, Dreher JC. Neural basis of corruption in power-holders. eLife 2021; 10:63922. [PMID: 33759762 PMCID: PMC7990503 DOI: 10.7554/elife.63922] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2020] [Accepted: 03/09/2021] [Indexed: 11/27/2022] Open
Abstract
Corruption often involves bribery, when a briber suborns a power-holder to gain advantages usually at a cost of moral transgression. Despite its wide presence in human societies, the neurocomputational basis of bribery remains elusive. Here, using model-based fMRI, we investigated the neural substrates of how a power-holder decides to accept or reject a bribe. Power-holders considered two types of moral cost brought by taking bribes: the cost of conniving with a fraudulent briber, encoded in the anterior insula, and the harm brought to a third party, represented in the right temporoparietal junction. These moral costs were integrated into a value signal in the ventromedial prefrontal cortex. The dorsolateral prefrontal cortex was selectively engaged to guide anti-corrupt behaviors when a third party would be harmed. Multivariate and connectivity analyses further explored how these neural processes depend on individual differences. These findings advance our understanding of the neurocomputational mechanisms underlying corrupt behaviors.
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Affiliation(s)
- Yang Hu
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, China; School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, China.,Laboratory of Neuroeconomics, Institut des Sciences Cognitives Marc Jeannerod, CNRS, Lyon, France
| | - Chen Hu
- Motivation, Brain & Behavior (MBB) Team, Institut du Cerveau et Moelle Epiniere, Hôpital de la Pitié-Salpêtrière, Paris, France.,Sorbonne Université, Paris, France
| | - Edmund Derrington
- Laboratory of Neuroeconomics, Institut des Sciences Cognitives Marc Jeannerod, CNRS, Lyon, France.,Université Claude Bernard Lyon 1, Lyon, France
| | | | - Chen Qu
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, China; School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, China
| | - Jean-Claude Dreher
- Laboratory of Neuroeconomics, Institut des Sciences Cognitives Marc Jeannerod, CNRS, Lyon, France.,Université Claude Bernard Lyon 1, Lyon, France
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50
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Computational and Neurobiological Substrates of Cost-Benefit Integration in Altruistic Helping Decision. J Neurosci 2021; 41:3545-3561. [PMID: 33674417 DOI: 10.1523/jneurosci.1939-20.2021] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Revised: 02/21/2021] [Accepted: 02/23/2021] [Indexed: 12/30/2022] Open
Abstract
Although altruistic behaviors, e.g., sacrificing one's own interests to alleviate others' suffering, are widely observed in human society, altruism varies greatly across individuals. Such individual differences in altruistic preference have been hypothesized to arise from both individuals' dispositional empathic concern for others' welfare and context-specific cost-benefit integration processes. However, how cost-benefit integration is implemented in the brain and how it is linked to empathy remain unclear. Here, we combine a novel paradigm with the model-based functional magnetic resonance imaging (fMRI) approach to examine the neurocomputational basis of altruistic behaviors. Thirty-seven adults (16 females) were tested. Modeling analyses suggest that individuals are likely to integrate their own monetary costs with nonlinearly transformed recipients' benefits. Neuroimaging results demonstrate the involvement of an extended common currency system during decision-making by showing that selfish and other-regarding motives were processed in dorsal anterior cingulate cortex (ACC) and right inferior parietal lobe in a domain-general manner. Importantly, a functional dissociation of adjacent but different subregions within anterior insular cortex (aINS) was observed for different subprocesses underlying altruistic behaviors. While dorsal aINS (daINS) and inferior frontal gyrus (IFG) were involved in valuation of benefactors' costs, ventral aINS and middle INS (vaINS/mINS), as empathy-related regions, reflected individual variations in valuating recipients' benefits. Multivariate analyses further suggest that both vaINS/mINS and dorsolateral prefrontal cortex (DLPFC) reflect individual variations in general altruistic preferences which account for both dispositional empathy and context-specific other-regarding tendency. Together, these findings provide valuable insights into our understanding of psychological and neurobiological basis of altruistic behaviors.SIGNIFICANCE STATEMENT Altruistic behaviors play a crucial role in facilitating solidarity and development of human society, but the mechanisms of the cost-benefit integration underlying these behaviors are still unclear. Using model-based neuroimaging approaches, we clarify that people integrate personal costs and non-linearly transformed other's benefits during altruistic decision-making and the implementations of the integration processes are supported by an extended common currency neural network. Importantly, multivariate analyses reveal that both empathy-related and cognitive control-related brain regions are involved in modulating individual variations of altruistic preference, which implicate complex psychological and computational processes. Our results provide a neurocomputational account of how people weigh between different attributes to make altruistic decisions and why altruistic preference varies to a great extent across individuals.
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