1
|
Saad M, Bohon C, Weinbach N. Mechanisms underlying food devaluation after response inhibition to food. Appetite 2024; 199:107387. [PMID: 38692510 DOI: 10.1016/j.appet.2024.107387] [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: 02/06/2024] [Revised: 04/17/2024] [Accepted: 04/29/2024] [Indexed: 05/03/2024]
Abstract
Multiple studies reveal that a requirement to stop a response to appetitive food stimuli causes devaluation of these stimuli. However, the mechanism underlying food devaluation after stopping is still under debate. The immediate-affect theory suggests that an increase in negative affect after stopping a response is the driving force for food devaluation. A competing value-updating theory presumes that food devaluation after stopping occurs through the need to align behavior with goals. The current study assessed how food devaluation after response inhibition is influenced by negative emotional reactivity and behavior-goal alignment on a trial-by-trial basis. The study included 60 healthy participants who completed a Food-Stop-Signal-Emotion task. Participants categorized high vs. low-calorie food stimuli and stopped their response upon encountering a stop signal. Subsequently, participants made subjective negativity ratings of negative- or neutral-valenced emotional images, and rated their desire to eat the previously depicted food. In contrast to predictions made by the immediate-affect account, food devaluation after stopping was not mediated nor moderated via changes in negative emotional reactivity after stopping. In support of the value-updating account, food devaluation was modulated by behavior-goal alignment, indicated by larger food devaluation after successful vs. failed stopping. In agreement with this theory, the findings indicate that devaluation occurs more strongly when performance aligns with the task requirement. This study sheds light on the mechanism that likely underlies food devaluation after stopping. Implications regarding applied use of food-inhibition trainings are discussed.
Collapse
Affiliation(s)
- Maram Saad
- School of Psychological Sciences, University of Haifa, Haifa, Israel
| | - Cara Bohon
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Noam Weinbach
- School of Psychological Sciences, University of Haifa, Haifa, Israel.
| |
Collapse
|
2
|
Sohail A, Zhang L. Informing the treatment of social anxiety disorder with computational and neuroimaging data. PSYCHORADIOLOGY 2024; 4:kkae010. [PMID: 38841558 PMCID: PMC11152174 DOI: 10.1093/psyrad/kkae010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 04/15/2024] [Accepted: 04/25/2024] [Indexed: 06/07/2024]
Affiliation(s)
- Aamir Sohail
- Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, B15 2TT, UK
| | - Lei Zhang
- Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, B15 2TT, UK
- Institute for Mental Health, School of Psychology, University of Birmingham, Birmingham, B15 2TT, UK
| |
Collapse
|
3
|
Peng M, Duan Q, Yang X, Tang R, Zhang L, Zhang H, Li X. The influence of social feedback on reward learning in the Iowa gambling task. Front Psychol 2024; 15:1292808. [PMID: 38756493 PMCID: PMC11098015 DOI: 10.3389/fpsyg.2024.1292808] [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: 09/18/2023] [Accepted: 04/17/2024] [Indexed: 05/18/2024] Open
Abstract
Learning, an important activity for both human and animals, has long been a focal point of research. During the learning process, subjects assimilate not only their own information but also information from others, a phenomenon known as social learning. While numerous studies have explored the impact of social feedback as a reward/punishment during learning, few studies have investigated whether social feedback facilitates or inhibits the learning of environmental rewards/punishments. This study aims to test the effects of social feedback on economic feedback and its cognitive processes by using the Iowa Gambling Task (IGT). One hundred ninety-two participants were recruited and categorized into one non-social feedback group and four social feedback groups. Participants in the social feedback groups were informed that after the outcome of each choice, they would also receive feedback from an online peer. This peer was a fictitious entity, with variations in identity (novice or expert) and feedback type (random or effective). The Outcome-Representation Learning model (ORL model) was used to quantify the cognitive components of learning. Behavioral results showed that both the identity of the peer and the type of feedback provided significantly influenced the deck selection, with effective social feedback increasing the ratio of chosen good decks. Results in the ORL model showed that the four social feedback groups exhibited lower learning rates for gain and loss compared to the nonsocial feedback group, which suggested, in the social feedback groups, the impact of the recent outcome on the update of value decreased. Parameters such as forgetfulness, win frequency, and deck perseverance in the expert-effective feedback group were significantly higher than those in the non-social feedback and expert-random feedback groups. These findings suggest that individuals proactively evaluate feedback providers and selectively adopt effective feedback to enhance learning.
Collapse
Affiliation(s)
- Ming Peng
- Key Laboratory of Adolescent Cyberpsychology and Behavior (CCNU), Ministry of Education, Wuhan, China
- School of Psychology, Central China Normal University, Wuhan, China
- Key Laboratory of Human Development and Mental Health of Hubei Province, Wuhan, China
| | - Qiaochu Duan
- School of Psychology, Central China Normal University, Wuhan, China
| | - Xiaoying Yang
- School of Psychology, Central China Normal University, Wuhan, China
| | - Rui Tang
- School of Psychology, Central China Normal University, Wuhan, China
| | - Lei Zhang
- Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, United Kingdom
- Institute for Mental Health, School of Psychology, University of Birmingham, Birmingham, United Kingdom
| | - Hanshu Zhang
- Key Laboratory of Adolescent Cyberpsychology and Behavior (CCNU), Ministry of Education, Wuhan, China
- School of Psychology, Central China Normal University, Wuhan, China
- Key Laboratory of Human Development and Mental Health of Hubei Province, Wuhan, China
| | - Xu Li
- Key Laboratory of Adolescent Cyberpsychology and Behavior (CCNU), Ministry of Education, Wuhan, China
- School of Psychology, Central China Normal University, Wuhan, China
- Key Laboratory of Human Development and Mental Health of Hubei Province, Wuhan, China
| |
Collapse
|
4
|
Elster EM, Pauli R, Baumann S, De Brito SA, Fairchild G, Freitag CM, Konrad K, Roessner V, Brazil IA, Lockwood PL, Kohls G. Impaired Punishment Learning in Conduct Disorder. J Am Acad Child Adolesc Psychiatry 2024; 63:454-463. [PMID: 37414274 DOI: 10.1016/j.jaac.2023.05.032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 05/22/2023] [Accepted: 06/27/2023] [Indexed: 07/08/2023]
Abstract
OBJECTIVE Conduct disorder (CD) has been associated with deficits in the use of punishment to guide reinforcement learning (RL) and decision making. This may explain the poorly planned and often impulsive antisocial and aggressive behavior in affected youths. Here, we used a computational modeling approach to examine differences in RL abilities between CD youths and typically developing controls (TDCs). Specifically, we tested 2 competing hypotheses that RL deficits in CD reflect either reward dominance (also known as reward hypersensitivity) or punishment insensitivity (also known as punishment hyposensitivity). METHOD The study included 92 CD youths and 130 TDCs (aged 9-18 years, 48% girls) who completed a probabilistic RL task with reward, punishment, and neutral contingencies. Using computational modeling, we investigated the extent to which the 2 groups differed in their learning abilities to obtain reward and/or to avoid punishment. RESULTS RL model comparisons showed that a model with separate learning rates per contingency explained behavioral performance best. Importantly, CD youths showed lower learning rates than TDCs specifically for punishment, whereas learning rates for reward and neutral contingencies did not differ. Moreover, callous-unemotional (CU) traits did not correlate with learning rates in CD. CONCLUSION CD youths have a highly selective impairment in probabilistic punishment learning, regardless of their CU traits, whereas reward learning appears to be intact. In summary, our data suggest punishment insensitivity rather than reward dominance in CD. Clinically, the use of punishment-based intervention techniques to achieve effective discipline in patients with CD may be a less helpful strategy than reward-based techniques.
Collapse
Affiliation(s)
| | - Ruth Pauli
- University of Birmingham, Birmingham, United Kingdom
| | | | | | | | - Christine M Freitag
- University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany
| | - Kerstin Konrad
- University Hospital RWTH Aachen, Aachen, Germany; RWTH Aachen and Research Centre Juelich, Juelich, Germany
| | | | | | - Patricia L Lockwood
- University of Birmingham, Birmingham, United Kingdom; University of Oxford, Oxford, United Kingdom
| | | |
Collapse
|
5
|
Xu H, Luo L, Zhu R, Zhao Y, Zhang L, Zhang Y, Feng C, Guan Q. Common and distinct equity preferences in children and adults. Front Psychol 2024; 15:1330024. [PMID: 38420165 PMCID: PMC10899522 DOI: 10.3389/fpsyg.2024.1330024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Accepted: 01/30/2024] [Indexed: 03/02/2024] Open
Abstract
Fairness plays a crucial role in children's social life and has garnered considerable attention. However, previous research and theories primarily examined the development of children's fairness behaviors in the conflict between self-interest motivation and fairness-complying motivation, neglecting the influence of advantage-seeking motivation. Moreover, despite the well-established role of gain/loss frame in human decision-making, it remains largely unclear whether the framing effect modulates fairness behaviors in children. It was hypothesized that children would exhibit advantage-seeking motivation resulting in more selfish behaviors in the loss context. To examine the hypothesis, we combined an adapted dictator game and computational modeling to investigate various motivations underlying fairness behaviors of children in both loss and gain contexts and to explore the developmental directions by contrasting children and adults. In addition, the current design enabled the dissociation between fairness knowledge and behaviors by asking participants to decide for themselves (the first-party role) or for others (the third-party role). This study recruited a total of 34 children (9-10 years, Mage = 9.82, SDage = 0.38, 16 females) and 31 college students (Mage = 19.81, SDage = 1.40, 17 females). The behavioral results indicated that children behaved more selfishly in first-party and more fairly in third-party than adults, without any significant framing effects. The computational results revealed that both children and adults exhibited aversion to advantageous and disadvantageous inequity in third-party. However, they showed distinct preferences for advantageous inequity in first-party, with advantage-seeking preferences among children and aversion to advantageous inequity among adults. These findings contribute to a deeper understanding of children's social preferences and their developmental directions.
Collapse
Affiliation(s)
- Han Xu
- School of Psychology, Shenzhen University, Shenzhen, China
- Department of Psychology, University of Mannheim, Mannheim, Germany
| | - Lanxin Luo
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, 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
| | - Ruida Zhu
- Department of Psychology, Sun Yat-Sen University, Guangzhou, China
| | - Yue Zhao
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, 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
| | - Luansu Zhang
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, 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
| | - Yaqi Zhang
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, 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
| | - Chunliang Feng
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, 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
| | - Qing Guan
- School of Psychology, Shenzhen University, Shenzhen, China
- Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, China
| |
Collapse
|
6
|
Zhou M, Zhu S, Xu T, Wang J, Zhuang Q, Zhang Y, Becker B, Kendrick KM, Yao S. Neural and behavioral evidence for oxytocin's facilitatory effects on learning in volatile and stable environments. Commun Biol 2024; 7:109. [PMID: 38242969 PMCID: PMC10799007 DOI: 10.1038/s42003-024-05792-8] [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: 06/29/2023] [Accepted: 01/08/2024] [Indexed: 01/21/2024] Open
Abstract
Outcomes of past decisions profoundly shape our behavior. However, choice-outcome associations can become volatile and adaption to such changes is of importance. The present study combines pharmaco-electroencephalography with computational modeling to examine whether intranasal oxytocin can modulate reinforcement learning under a volatile vs. a stable association. Results show that oxytocin increases choice accuracy independent of learning context, which is paralleled by a larger N2pc and a smaller P300. Model-based analyses reveal that while oxytocin promotes learning by accelerating value update of outcomes in the volatile context, in the stable context it does so by improving choice consistency. These findings suggest that oxytocin's facilitatory effects on learning may be exerted via improving early attentional selection and late neural processing efficiency, although at the computational level oxytocin's actions are highly adaptive between learning contexts. Our findings provide proof of concept for oxytocin's therapeutic potential in mental disorders with adaptive learning dysfunction.
Collapse
Affiliation(s)
- Menghan Zhou
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 611731, China
- The MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Siyu Zhu
- School of Sport Training, Chengdu Sport University, Chengdu, 610041, Sichuan, China
| | - Ting Xu
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 611731, China
- The MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Jiayuan Wang
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 611731, China
- The MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Qian Zhuang
- The MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang Province, China
| | - Yuan Zhang
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 611731, China
- The MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Benjamin Becker
- The State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, Pokfulam, China
- Department of Psychology, The University of Hong Kong, Hong Kong, Pokfulam, China
| | - Keith M Kendrick
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 611731, China
- The MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Shuxia Yao
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 611731, China.
- The MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
| |
Collapse
|
7
|
Labutina N, Polyakov S, Nemtyreva L, Shuldishova A, Gizatullina O. Neural Correlates of Social Decision-Making. IRANIAN JOURNAL OF PSYCHIATRY 2024; 19:148-154. [PMID: 38420275 PMCID: PMC10896758 DOI: 10.18502/ijps.v19i1.14350] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/02/2023] [Revised: 08/13/2023] [Accepted: 09/02/2023] [Indexed: 03/02/2024]
Abstract
Objective: Recent studies have utilized innovative techniques to investigate the neural mechanisms underlying social and individual decision-making, aiming to understand how individuals respond to the world. Method : In this review, we summarized current scientific evidence concerning the neural underpinnings of social decision-making and their impact on social behavior. Results: Critical brain regions involved in social cognition and decision-making are integral to the process of social decision-making. Notably, the medial prefrontal cortex (mPFC) and temporoparietal junction (TPJ) contribute to the comprehension of others' mental states. Similarly, the posterior superior temporal sulcus (pSTS) shows heightened activity when individuals observe faces and movements. On the lateral surface of the brain, the inferior frontal gyrus (IFG) and inferior parietal sulcus (IPS) play a role in social cognition. Furthermore, the medial surface of the brain, including the amygdala, anterior cingulate cortex (ACC), and anterior insula (AI), also participates in social cognition processes. Regarding decision-making, functional magnetic resonance imaging (fMRI) studies have illuminated the involvement of a network of brain regions, encompassing the ventromedial prefrontal cortex (vmPFC), ventral striatum (VS), and nucleus accumbens (NAcc). Conclusion: Dysfunction in specific subregions of the prefrontal cortex (PFC) has been linked to various psychiatric conditions. These subregions play pivotal roles in cognitive, emotional, and social processing, and their impairment can contribute to the development and manifestation of psychiatric symptoms. A comprehensive understanding of the unique contributions of these PFC subregions to psychiatric disorders has the potential to inform the development of targeted interventions and treatments for affected individuals.
Collapse
Affiliation(s)
| | | | | | - Alina Shuldishova
- Peoples’ Friendship University of Russia (RUDN University), Moscow, Russia
| | - Olga Gizatullina
- Financial University under the Government of the Russian Federation, Moscow, Russia
| |
Collapse
|
8
|
Liu L, Liu D, Guo T, Schwieter JW, Liu H. The right superior temporal gyrus plays a role in semantic-rule learning: Evidence supporting a reinforcement learning model. Neuroimage 2023; 282:120393. [PMID: 37820861 DOI: 10.1016/j.neuroimage.2023.120393] [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: 05/02/2023] [Revised: 08/29/2023] [Accepted: 09/25/2023] [Indexed: 10/13/2023] Open
Abstract
In real-life communication, individuals use language that carries evident rewarding and punishing elements, such as praise and criticism. A common trend is to seek more praise while avoiding criticism. Furthermore, semantics is crucial for conveying information, but such semantic access to native and foreign languages is subtly distinct. To investigate how rule learning occurs in different languages and to highlight the importance of semantics in this process, we investigated both verbal and non-verbal rule learning in first (L1) and second (L2) languages using a reinforcement learning framework, including a semantic rule and a color rule. Our computational modeling on behavioral and brain imaging data revealed that individuals may be more motivated to learn and adhere to rules in an L1 compared to L2, with greater striatum activation during the outcome phase in the L1. Additionally, results on the learning rates and inverse temperature in the two rule learning tasks showed that individuals tend to be conservative and are reluctant to change their judgments regarding rule learning of semantic information. Moreover, the greater the prediction errors, the greater activation of the right superior temporal gyrus in the semantic-rule learning condition, demonstrating that such learning has differential neural correlates than symbolic rule learning. Overall, the findings provide insight into the neural mechanisms underlying rule learning in different languages, and indicate that rule learning involving verbal semantics is not a general symbolic learning that resembles a conditioned stimulus-response, but rather has its own specific characteristics.
Collapse
Affiliation(s)
- Linyan Liu
- Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, China; Key Laboratory of Brain and Cognitive Neuroscience, Liaoning Province, China
| | - Dongxue Liu
- Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, China; Key Laboratory of Brain and Cognitive Neuroscience, Liaoning Province, China
| | - Tingting Guo
- Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, China; Key Laboratory of Brain and Cognitive Neuroscience, Liaoning Province, China
| | - John W Schwieter
- Language Acquisition, Multilingualism, and Cognition Laboratory / Bilingualism Matters @ Wilfrid Laurier University, Canada; Department of Linguistics and Languages, McMaster University, Canada
| | - Huanhuan Liu
- Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, China; Key Laboratory of Brain and Cognitive Neuroscience, Liaoning Province, China.
| |
Collapse
|
9
|
Pan Y, Vinding MC, Zhang L, Lundqvist D, Olsson A. A Brain-To-Brain Mechanism for Social Transmission of Threat Learning. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2304037. [PMID: 37544901 PMCID: PMC10558655 DOI: 10.1002/advs.202304037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Indexed: 08/08/2023]
Abstract
Survival and adaptation in environments require swift and efficacious learning about what is dangerous. Across species, much of such threat learning is acquired socially, e.g., through the observation of others' ("demonstrators'") defensive behaviors. However, the specific neural mechanisms responsible for the integration of information shared between demonstrators and observers remain largely unknown. This dearth of knowledge is addressed by performing magnetoencephalography (MEG) neuroimaging in demonstrator-observer dyads. A set of stimuli are first shown to a demonstrator whose defensive responses are filmed and later presented to an observer, while neuronal activity is recorded sequentially from both individuals who never interacted directly. These results show that brain-to-brain coupling (BtBC) in the fronto-limbic circuit (including insula, ventromedial, and dorsolateral prefrontal cortex) within demonstrator-observer dyads predict subsequent expressions of learning in the observer. Importantly, the predictive power of BtBC magnifies when a threat is imminent to the demonstrator. Furthermore, BtBC depends on how observers perceive their social status relative to the demonstrator, likely driven by shared attention and emotion, as bolstered by dyadic pupillary coupling. Taken together, this study describes a brain-to-brain mechanism for social threat learning, involving BtBC, which reflects social relationships and predicts adaptive, learned behaviors.
Collapse
Affiliation(s)
- Yafeng Pan
- Department of Psychology and Behavioral SciencesZhejiang UniversityHangzhou310058China
- Department of Clinical NeuroscienceKarolinska InstitutetStockholm17165Sweden
| | - Mikkel C. Vinding
- Department of Clinical NeuroscienceKarolinska InstitutetStockholm17165Sweden
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and ResearchCopenhagen University Hospital ‐ Amager and HvidovreCopenhagen2650Denmark
| | - Lei Zhang
- Centre for Human Brain HealthSchool of PsychologyUniversity of BirminghamBirminghamB15 2TTUK
- Institute for Mental HealthSchool of PsychologyUniversity of BirminghamBirminghamB15 2TTUK
- SocialCognitive and Affective Neuroscience UnitDepartment of CognitionEmotionand Methods in PsychologyFaculty of PsychologyUniversity of ViennaVienna1010Austria
| | - Daniel Lundqvist
- Department of Clinical NeuroscienceKarolinska InstitutetStockholm17165Sweden
| | - Andreas Olsson
- Department of Clinical NeuroscienceKarolinska InstitutetStockholm17165Sweden
| |
Collapse
|
10
|
Jin Y, Gao Q, Wang Y, Dietz M, Xiao L, Cai Y, Bliksted V, Zhou Y. Impaired social learning in patients with major depressive disorder revealed by a reinforcement learning model. Int J Clin Health Psychol 2023; 23:100389. [PMID: 37829189 PMCID: PMC10564931 DOI: 10.1016/j.ijchp.2023.100389] [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: 03/14/2023] [Accepted: 05/03/2023] [Indexed: 10/14/2023] Open
Abstract
Background/objective Patients with major depressive disorder (MDD) have altered learning rates for rewards and losses in non-social learning paradigms. However, it is not well understood whether the ability to learn from social interactions is altered in MDD patients. Using reinforcement learning during the repeated Trust Game (rTG), we investigated how MDD patients learn to trust newly-met partners in MDD patients. Method Sixty-eight MDD patients and fifty-four controls each played as 'investor' and interacted with ten different partners. We manipulated both the level of trustworthiness by varying the chance of reciprocity (10, 30, 50, 70 and 90%) and reputation disclosure, where partners' reputation was either pre-disclosed or hidden. Results Our reinforcement learning model revealed that MDD patients had significantly higher learning rates for losses than the controls in both the reputation disclosure and non-disclosure condition. The difference was larger when reputation was not disclosed than disclosed. We observed no difference in learning rates for gains in either condition. Conclusions Our findings highlight that abnormal learning for losses underlies the social learning process in MDD patients. This abnormality is higher when situational unpredictability is high versus low. Our findings provide novel insights into social rehabilitation of MDD.
Collapse
Affiliation(s)
- Yuening Jin
- 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
| | - Qinglin Gao
- 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
| | - Yun Wang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
| | - Martin Dietz
- Center of Functionally Integrative Neuroscience, Institute of Clinical Medicine, Aarhus University, Universitetsbyen 3, Aarhus C 8000, Denmark
| | - Le Xiao
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
| | - Yuyang Cai
- 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
| | - Vibeke Bliksted
- Department of Clinical Medicine, Aarhus University, Palle Juul-Jensens Boulevard 82, Aarhus N 8200, Denmark
- Centre for Interacting Minds, Aarhus University, Jens Chr. Skous Vej 4, Building 1483, Aarhus C 8000, Denmark
| | - Yuan Zhou
- 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
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
| |
Collapse
|
11
|
Yao YW, Song KR, Schuck NW, Li X, Fang XY, Zhang JT, Heekeren HR, Bruckner R. The dorsomedial prefrontal cortex represents subjective value across effort-based and risky decision-making. Neuroimage 2023; 279:120326. [PMID: 37579997 DOI: 10.1016/j.neuroimage.2023.120326] [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: 03/16/2023] [Revised: 08/09/2023] [Accepted: 08/11/2023] [Indexed: 08/16/2023] Open
Abstract
Decisions that require taking effort costs into account are ubiquitous in real life. The neural common currency theory hypothesizes that a particular neural network integrates different costs (e.g., risk) and rewards into a common scale to facilitate value comparison. Although there has been a surge of interest in the computational and neural basis of effort-related value integration, it is still under debate if effort-based decision-making relies on a domain-general valuation network as implicated in the neural common currency theory. Therefore, we comprehensively compared effort-based and risky decision-making using a combination of computational modeling, univariate and multivariate fMRI analyses, and data from two independent studies. We found that effort-based decision-making can be best described by a power discounting model that accounts for both the discounting rate and effort sensitivity. At the neural level, multivariate decoding analyses indicated that the neural patterns of the dorsomedial prefrontal cortex (dmPFC) represented subjective value across different decision-making tasks including either effort or risk costs, although univariate signals were more diverse. These findings suggest that multivariate dmPFC patterns play a critical role in computing subjective value in a task-independent manner and thus extend the scope of the neural common currency theory.
Collapse
Affiliation(s)
- Yuan-Wei Yao
- Department of Education and Psychology, Freie Universität Berlin, Berlin, Germany; Einstein Center for Neurosciences Berlin, Charité - Universitätsmedizin Berlin, Germany; Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; Max Planck Research Group NeuroCode, Max Planck Institute for Human Development, Berlin, Germany.
| | - Kun-Ru Song
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Nicolas W Schuck
- Max Planck Research Group NeuroCode, Max Planck Institute for Human Development, Berlin, Germany; Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany; Institute of Psychology, Universität Hamburg, Hamburg, Germany
| | - Xin Li
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Xiao-Yi Fang
- Institute of Developmental Psychology, Beijing Normal University, Beijing, China
| | - Jin-Tao Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
| | - Hauke R Heekeren
- Department of Education and Psychology, Freie Universität Berlin, Berlin, Germany; Executive University Board, Universität Hamburg, Hamburg, Germany
| | - Rasmus Bruckner
- Department of Education and Psychology, Freie Universität Berlin, Berlin, Germany; Max Planck Research Group NeuroCode, Max Planck Institute for Human Development, Berlin, Germany
| |
Collapse
|
12
|
Björlin Avdic H, Strannegård C, Engberg H, Willfors C, Nordgren I, Frisén L, Hirschberg AL, Guath M, Nordgren A, Kleberg JL. Reduced effects of social feedback on learning in Turner syndrome. Sci Rep 2023; 13:15858. [PMID: 37739980 PMCID: PMC10516979 DOI: 10.1038/s41598-023-42628-7] [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: 03/31/2023] [Accepted: 09/12/2023] [Indexed: 09/24/2023] Open
Abstract
Turner syndrome is a genetic condition caused by a complete or partial loss of one of the X chromosomes. Previous studies indicate that Turner syndrome is associated with challenges in social skills, but the underlying mechanisms remain largely unexplored. A possible mechanism is a reduced social influence on learning. The current study examined the impact of social and non-social feedback on learning in women with Turner syndrome (n = 35) and a sex- and age-matched control group (n = 37). Participants were instructed to earn points by repeatedly choosing between two stimuli with unequal probabilities of resulting in a reward. Mastering the task therefore required participants to learn through feedback which of the two stimuli was more likely to be rewarded. Data were analyzed using computational modeling and analyses of choice behavior. Social feedback led to a more explorative choice behavior in the control group, resulting in reduced learning compared to non-social feedback. No effects of social feedback on learning were found in Turner syndrome. The current study thus indicates that women with Turner syndrome may be less sensitive to social influences on reinforcement learning, than the general population.
Collapse
Affiliation(s)
- Hanna Björlin Avdic
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden.
| | - Claes Strannegård
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Division of Cognition and Communication, Department of Applied IT, University of Gothenburg, Gothenburg, Sweden
| | - Hedvig Engberg
- Department of Women's and Children's Health, Karolinska Institutet & Department of Gynaecology and Reproductive Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Charlotte Willfors
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Ida Nordgren
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Louise Frisén
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
| | - Angelica Lindén Hirschberg
- Department of Women's and Children's Health, Karolinska Institutet & Department of Gynaecology and Reproductive Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Mona Guath
- Department of Psychology, Uppsala University, Uppsala, Sweden
| | - Ann Nordgren
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Laboratory Medicine, Institute of Biomedicine, University of Gothenburg, Gothenburg, Sweden
- Department of Clinical Genetics and Genomics, Sahlgrenska University Hospital, Gothenburg, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Johan Lundin Kleberg
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
- Department of Psychology, Stockholm University, Stockholm, Sweden
| |
Collapse
|
13
|
Kutlikova HH, Zhang L, Eisenegger C, van Honk J, Lamm C. Testosterone eliminates strategic prosocial behavior through impacting choice consistency in healthy males. Neuropsychopharmacology 2023; 48:1541-1550. [PMID: 37012404 PMCID: PMC10425362 DOI: 10.1038/s41386-023-01570-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 02/24/2023] [Accepted: 03/13/2023] [Indexed: 04/05/2023]
Abstract
Humans are strategically more prosocial when their actions are being watched by others than when they act alone. Using a psychopharmacogenetic approach, we investigated the endocrinological and computational mechanisms of such audience-driven prosociality. One hundred and ninety-two male participants received either a single dose of testosterone (150 mg) or a placebo and performed a prosocial and self-benefitting reinforcement learning task. Crucially, the task was performed either in private or when being watched. Rival theories suggest that the hormone might either diminish or strengthen audience-dependent prosociality. We show that exogenous testosterone fully eliminated strategic, i.e., feigned, prosociality and thus decreased submission to audience expectations. We next performed reinforcement-learning drift-diffusion computational modeling to elucidate which latent aspects of decision-making testosterone acted on. The modeling revealed that testosterone compared to placebo did not deteriorate reinforcement learning per se. Rather, when being watched, the hormone altered the degree to which the learned information on choice value translated to action selection. Taken together, our study provides novel evidence of testosterone's effects on implicit reward processing, through which it counteracts conformity and deceptive reputation strategies.
Collapse
Affiliation(s)
- Hana H Kutlikova
- Department of Cognition, Emotion, and Methods in Psychology, University of Vienna, Vienna, Austria.
- Department of Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, the Netherlands.
| | - Lei Zhang
- Department of Cognition, Emotion, and Methods in Psychology, University of Vienna, Vienna, Austria
- Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, UK
- Institute for Mental Health, School of Psychology, University of Birmingham, Birmingham, UK
| | - Christoph Eisenegger
- Department of Cognition, Emotion, and Methods in Psychology, University of Vienna, Vienna, Austria
| | - Jack van Honk
- Department of Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, the Netherlands
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Claus Lamm
- Department of Cognition, Emotion, and Methods in Psychology, University of Vienna, Vienna, Austria
- Vienna Cognitive Science Hub, University of Vienna, Vienna, Austria
| |
Collapse
|
14
|
Haines N, Sullivan-Toole H, Olino T. From Classical Methods to Generative Models: Tackling the Unreliability of Neuroscientific Measures in Mental Health Research. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2023; 8:822-831. [PMID: 36997406 PMCID: PMC10333448 DOI: 10.1016/j.bpsc.2023.01.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 12/28/2022] [Accepted: 01/03/2023] [Indexed: 01/13/2023]
Abstract
Advances in computational statistics and corresponding shifts in funding initiatives over the past few decades have led to a proliferation of neuroscientific measures being developed in the context of mental health research. Although such measures have undoubtedly deepened our understanding of neural mechanisms underlying cognitive, affective, and behavioral processes associated with various mental health conditions, the clinical utility of such measures remains underwhelming. Recent commentaries point toward the poor reliability of neuroscientific measures to partially explain this lack of clinical translation. Here, we provide a concise theoretical overview of how unreliability impedes clinical translation of neuroscientific measures; discuss how various modeling principles, including those from hierarchical and structural equation modeling frameworks, can help to improve reliability; and demonstrate how to combine principles of hierarchical and structural modeling within the generative modeling framework to achieve more reliable, generalizable measures of brain-behavior relationships for use in mental health research.
Collapse
Affiliation(s)
- Nathaniel Haines
- Department of Data Science, Bayesian Beginnings LLC, Columbus, Ohio.
| | | | - Thomas Olino
- Department of Psychology, Temple University, Philadelphia, Pennsylvania
| |
Collapse
|
15
|
Vicente U, Ara A, Marco-Pallarés J. Intra- and inter-brain synchrony oscillations underlying social adjustment. Sci Rep 2023; 13:11211. [PMID: 37433866 DOI: 10.1038/s41598-023-38292-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Accepted: 07/06/2023] [Indexed: 07/13/2023] Open
Abstract
Humans naturally synchronize their behavior with other people. However, although it happens almost automatically, adjusting behavior and conformity to others is a complex phenomenon whose neural mechanisms are still yet to be understood entirely. The present experiment aimed to study the oscillatory synchronization mechanisms underlying automatic dyadic convergence in an EEG hyperscanning experiment. Thirty-six people performed a cooperative decision-making task where dyads had to guess the correct position of a point on a line. A reinforcement learning algorithm was used to model different aspects of the participants' behavior and their expectations of their peers. Intra- and inter-connectivity among electrode sites were assessed using inter-site phase clustering in three main frequency bands (theta, alpha, beta) using a two-level Bayesian mixed-effects modeling approach. The results showed two oscillatory synchronization dynamics related to attention and executive functions in alpha and reinforcement learning in theta. In addition, inter-brain synchrony was mainly driven by beta oscillations. This study contributes preliminary evidence on the phase-coherence mechanism underlying inter-personal behavioral adjustment.
Collapse
Affiliation(s)
- Unai Vicente
- Department of Cognition, Development and Educational Psychology, Faculty of Psychology, University of Barcelona, 08035, Barcelona, Spain.
- Cognition and Brain Plasticity Unit, Bellvitge Biomedical Research Institute, 08907, L'Hospitalet de Llobregat, Spain.
| | - Alberto Ara
- Cognitive Neuroscience Unit, Montreal Neurological Institute, McGill University, H3A 2B4, Montreal, Canada
- BRAMS: International Laboratory for Brain, Music and Sound Research, H3C 3J7, Montreal, Canada
| | - Josep Marco-Pallarés
- Department of Cognition, Development and Educational Psychology, Faculty of Psychology, University of Barcelona, 08035, Barcelona, Spain.
- Cognition and Brain Plasticity Unit, Bellvitge Biomedical Research Institute, 08907, L'Hospitalet de Llobregat, Spain.
| |
Collapse
|
16
|
Mikus N, Eisenegger C, Mathys C, Clark L, Müller U, Robbins TW, Lamm C, Naef M. Blocking D2/D3 dopamine receptors in male participants increases volatility of beliefs when learning to trust others. Nat Commun 2023; 14:4049. [PMID: 37422466 PMCID: PMC10329681 DOI: 10.1038/s41467-023-39823-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Accepted: 06/29/2023] [Indexed: 07/10/2023] Open
Abstract
The ability to learn about other people is crucial for human social functioning. Dopamine has been proposed to regulate the precision of beliefs, but direct behavioural evidence of this is lacking. In this study, we investigate how a high dose of the D2/D3 dopamine receptor antagonist sulpiride impacts learning about other people's prosocial attitudes in a repeated Trust game. Using a Bayesian model of belief updating, we show that in a sample of 76 male participants sulpiride increases the volatility of beliefs, which leads to higher precision weights on prediction errors. This effect is driven by participants with genetically conferred higher dopamine availability (Taq1a polymorphism) and remains even after controlling for working memory performance. Higher precision weights are reflected in higher reciprocal behaviour in the repeated Trust game but not in single-round Trust games. Our data provide evidence that the D2 receptors are pivotal in regulating prediction error-driven belief updating in a social context.
Collapse
Affiliation(s)
- Nace Mikus
- Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria.
- Interacting Minds Centre, Aarhus University, Aarhus, Denmark.
| | - Christoph Eisenegger
- Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria
- Behavioural and Clinical Neuroscience Institute and Department of Psychology, University of Cambridge, Cambridge, UK
| | - Christoph Mathys
- Interacting Minds Centre, Aarhus University, Aarhus, Denmark
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
- Scuola Internazionale Superiore di Studi Avanzati (SISSA), Trieste, Italy
| | - Luke Clark
- Centre for Gambling Research at UBC, Department of Psychology, University of British, Columbia, Vancouver, BC, Canada
- Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada
| | - Ulrich Müller
- Behavioural and Clinical Neuroscience Institute and Department of Psychology, University of Cambridge, Cambridge, UK
- Adult Neurodevelopmental Services, Health & Community Services, Government of Jersey, St Helier, Jersey
| | - Trevor W Robbins
- Behavioural and Clinical Neuroscience Institute and Department of Psychology, University of Cambridge, Cambridge, UK
| | - Claus Lamm
- Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria.
| | - Michael Naef
- Department of Economics, University of Durham, Durham, UK.
| |
Collapse
|
17
|
Rosenblau G, Frolichs K, Korn CW. A neuro-computational social learning framework to facilitate transdiagnostic classification and treatment across psychiatric disorders. Neurosci Biobehav Rev 2023; 149:105181. [PMID: 37062494 PMCID: PMC10236440 DOI: 10.1016/j.neubiorev.2023.105181] [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: 08/31/2022] [Revised: 03/14/2023] [Accepted: 04/13/2023] [Indexed: 04/18/2023]
Abstract
Social deficits are among the core and most striking psychiatric symptoms, present in most psychiatric disorders. Here, we introduce a novel social learning framework, which consists of neuro-computational models that combine reinforcement learning with various types of social knowledge structures. We outline how this social learning framework can help specify and quantify social psychopathology across disorders and provide an overview of the brain regions that may be involved in this type of social learning. We highlight how this framework can specify commonalities and differences in the social psychopathology of individuals with autism spectrum disorder (ASD), personality disorders (PD), and major depressive disorder (MDD) and improve treatments on an individual basis. We conjecture that individuals with psychiatric disorders rely on rigid social knowledge representations when learning about others, albeit the nature of their rigidity and the behavioral consequences can greatly differ. While non-clinical cohorts tend to efficiently adapt social knowledge representations to relevant environmental constraints, psychiatric cohorts may rigidly stick to their preconceived notions or overly coarse knowledge representations during learning.
Collapse
Affiliation(s)
- Gabriela Rosenblau
- Department of Psychological and Brain Sciences, George Washington University, Washington DC, USA; Autism and Neurodevelopmental Disorders Institute, George Washington University, Washington DC, USA.
| | - Koen Frolichs
- Section Social Neuroscience, Department of General Psychiatry, University of Heidelberg, Heidelberg, Germany; Institute for Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Christoph W Korn
- Section Social Neuroscience, Department of General Psychiatry, University of Heidelberg, Heidelberg, Germany; Institute for Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
| |
Collapse
|
18
|
Elder JJ, Davis TH, Hughes BL. A Fluid Self-Concept: How the Brain Maintains Coherence and Positivity across an Interconnected Self-Concept While Incorporating Social Feedback. J Neurosci 2023; 43:4110-4128. [PMID: 37156606 PMCID: PMC10255005 DOI: 10.1523/jneurosci.1951-22.2023] [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: 10/12/2022] [Revised: 02/16/2023] [Accepted: 04/04/2023] [Indexed: 05/10/2023] Open
Abstract
People experience instances of social feedback as interdependent with potential implications for their entire self-concept. How do people maintain positivity and coherence across the self-concept while updating self-views from feedback? We present a network model describing how the brain represents the semantic dependency relations among traits and uses this information to avoid an overall loss of positivity and coherence. Both male and female human participants received social feedback during a self-evaluation task while undergoing functional magnetic resonance imaging. We modeled self-belief updating by incorporating a reinforcement learning model within the network structure. Participants learned more rapidly from positive than negative feedback and were less likely to change self-views for traits with more dependencies in the network. Further, participants back propagated feedback across network relations while retrieving prior feedback on the basis of network similarity to inform ongoing self-views. Activation in ventromedial prefrontal cortex (vmPFC) reflected the constrained updating process such that positive feedback led to higher activation and negative feedback to less activation for traits with more dependencies. Additionally, vmPFC was associated with the novelty of a trait relative to previously self-evaluated traits in the network, and angular gyrus was associated with greater certainty for self-beliefs given the relevance of prior feedback. We propose that neural computations that selectively enhance or attenuate social feedback and retrieve past relevant experiences to guide ongoing self-evaluations may support an overall positive and coherent self-concept.SIGNIFICANCE STATEMENT We humans experience social feedback throughout our lives, but we do not dispassionately incorporate feedback into our self-concept. The implications of feedback for our entire self-concept plays a role in how we either change or retain our prior self-beliefs. In a neuroimaging study, we find that people are less likely to change their beliefs from feedback when the feedback has broader implications for the self-concept. This resistance to change is reflected in processing in the ventromedial prefrontal cortex, a region that is central to self-referential and social cognition. These results are broadly applicable given the role that maintaining a positive and coherent self-concept plays in promoting mental health and development throughout the lifespan.
Collapse
Affiliation(s)
- Jacob J Elder
- Department of Psychology, University of California, Riverside, Riverside, California 92521
| | | | - Brent L Hughes
- Department of Psychology, University of California, Riverside, Riverside, California 92521
| |
Collapse
|
19
|
Barnes SA, Dillon DG, Young JW, Thomas ML, Faget L, Yoo JH, Der-Avakian A, Hnasko TS, Geyer MA, Ramanathan DS. Modulation of ventromedial orbitofrontal cortical glutamatergic activity affects the explore-exploit balance and influences value-based decision-making. Cereb Cortex 2023; 33:5783-5796. [PMID: 36472411 PMCID: PMC10183731 DOI: 10.1093/cercor/bhac459] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Revised: 10/26/2022] [Accepted: 10/27/2022] [Indexed: 12/12/2022] Open
Abstract
The balance between exploration and exploitation is essential for decision-making. The present study investigated the role of ventromedial orbitofrontal cortex (vmOFC) glutamate neurons in mediating value-based decision-making by first using optogenetics to manipulate vmOFC glutamate activity in rats during a probabilistic reversal learning (PRL) task. Rats that received vmOFC activation during informative feedback completed fewer reversals and exhibited reduced reward sensitivity relative to rats. Analysis with a Q-learning computational model revealed that increased vmOFC activity did not affect the learning rate but instead promoted maladaptive exploration. By contrast, vmOFC inhibition increased the number of completed reversals and increased exploitative behavior. In a separate group of animals, calcium activity of vmOFC glutamate neurons was recorded using fiber photometry. Complementing our results above, we found that suppression of vmOFC activity during the latter part of rewarded trials was associated with improved PRL performance, greater win-stay responding and selecting the correct choice on the next trial. These data demonstrate that excessive vmOFC activity during reward feedback disrupted value-based decision-making by increasing the maladaptive exploration of lower-valued options. Our findings support the premise that pharmacological interventions that normalize aberrant vmOFC glutamate activity during reward feedback processing may attenuate deficits in value-based decision-making.
Collapse
Affiliation(s)
- Samuel A Barnes
- Department of Psychiatry, University of California San Diego, 9500 Gilman Dr, La Jolla, CA 92093, United States
- Department of Mental Health, VA San Diego Healthcare System, 3350 La Jolla Village Dr, La Jolla, CA 92093, United States
| | - Daniel G Dillon
- Center for Depression, Anxiety and Stress Research, McLean Hospital, 115 Mill St, Belmont, MA 02478, United States
- Department of Psychiatry, Harvard Medical School, 401 Park Drive, Boston, MA 02115, United States
| | - Jared W Young
- Department of Psychiatry, University of California San Diego, 9500 Gilman Dr, La Jolla, CA 92093, United States
- Department of Mental Health, VA San Diego Healthcare System, 3350 La Jolla Village Dr, La Jolla, CA 92093, United States
| | - Michael L Thomas
- Department of Psychiatry, University of California San Diego, 9500 Gilman Dr, La Jolla, CA 92093, United States
- Department of Psychology, 1876 Campus Delivery, Colorado State University, Fort Collins, CO 80523, United States
| | - Lauren Faget
- Department of Neurosciences, University of California San Diego, 9500 Gilman Dr, La Jolla, CA 92093, United States
| | - Ji Hoon Yoo
- Department of Neurosciences, University of California San Diego, 9500 Gilman Dr, La Jolla, CA 92093, United States
| | - Andre Der-Avakian
- Department of Psychiatry, University of California San Diego, 9500 Gilman Dr, La Jolla, CA 92093, United States
| | - Thomas S Hnasko
- Department of Neurosciences, University of California San Diego, 9500 Gilman Dr, La Jolla, CA 92093, United States
- Research Service, VA San Diego Healthcare System, San Diego, CA, 92161, United States
| | - Mark A Geyer
- Department of Psychiatry, University of California San Diego, 9500 Gilman Dr, La Jolla, CA 92093, United States
- Department of Mental Health, VA San Diego Healthcare System, 3350 La Jolla Village Dr, La Jolla, CA 92093, United States
| | - Dhakshin S Ramanathan
- Department of Psychiatry, University of California San Diego, 9500 Gilman Dr, La Jolla, CA 92093, United States
- Department of Mental Health, VA San Diego Healthcare System, 3350 La Jolla Village Dr, La Jolla, CA 92093, United States
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, 3350 La Jolla Village Dr, La Jolla, CA 92093, United States
| |
Collapse
|
20
|
Sandhu TR, Xiao B, Lawson RP. Transdiagnostic computations of uncertainty: towards a new lens on intolerance of uncertainty. Neurosci Biobehav Rev 2023; 148:105123. [PMID: 36914079 DOI: 10.1016/j.neubiorev.2023.105123] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 02/21/2023] [Accepted: 03/08/2023] [Indexed: 03/13/2023]
Abstract
People radically differ in how they cope with uncertainty. Clinical researchers describe a dispositional characteristic known as "intolerance of uncertainty", a tendency to find uncertainty aversive, reported to be elevated across psychiatric and neurodevelopmental conditions. Concurrently, recent research in computational psychiatry has leveraged theoretical work to characterise individual differences in uncertainty processing. Under this framework, differences in how people estimate different forms of uncertainty can contribute to mental health difficulties. In this review, we briefly outline the concept of intolerance of uncertainty within its clinical context, and we argue that the mechanisms underlying this construct may be further elucidated through modelling how individuals make inferences about uncertainty. We will review the evidence linking psychopathology to different computationally specified forms of uncertainty and consider how these findings might suggest distinct mechanistic routes towards intolerance of uncertainty. We also discuss the implications of this computational approach for behavioural and pharmacological interventions, as well as the importance of different cognitive domains and subjective experiences in studying uncertainty processing.
Collapse
Affiliation(s)
- Timothy R Sandhu
- Department of Psychology, Downing Place, University of Cambridge, CB2 3EB, UK; MRC Cognition and Brain Sciences Unit, 15 Chaucer Road, CB2 7EF, UK.
| | - Bowen Xiao
- Department of Psychology, Downing Place, University of Cambridge, CB2 3EB, UK
| | - Rebecca P Lawson
- Department of Psychology, Downing Place, University of Cambridge, CB2 3EB, UK; MRC Cognition and Brain Sciences Unit, 15 Chaucer Road, CB2 7EF, UK
| |
Collapse
|
21
|
Jansen M, Lockwood PL, Cutler J, de Bruijn ERA. l-DOPA and oxytocin influence the neurocomputational mechanisms of self-benefitting and prosocial reinforcement learning. Neuroimage 2023; 270:119983. [PMID: 36848972 DOI: 10.1016/j.neuroimage.2023.119983] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 02/03/2023] [Accepted: 02/23/2023] [Indexed: 02/27/2023] Open
Abstract
Humans learn through reinforcement, particularly when outcomes are unexpected. Recent research suggests similar mechanisms drive how we learn to benefit other people, that is, how we learn to be prosocial. Yet the neurochemical mechanisms underlying such prosocial computations remain poorly understood. Here, we investigated whether pharmacological manipulation of oxytocin and dopamine influence the neurocomputational mechanisms underlying self-benefitting and prosocial reinforcement learning. Using a double-blind placebo-controlled cross-over design, we administered intranasal oxytocin (24 IU), dopamine precursor l-DOPA (100 mg + 25 mg carbidopa), or placebo over three sessions. Participants performed a probabilistic reinforcement learning task with potential rewards for themselves, another participant, or no one, during functional magnetic resonance imaging. Computational models of reinforcement learning were used to calculate prediction errors (PEs) and learning rates. Participants behavior was best explained by a model with different learning rates for each recipient, but these were unaffected by either drug. On the neural level, however, both drugs blunted PE signaling in the ventral striatum and led to negative signaling of PEs in the anterior mid-cingulate cortex, dorsolateral prefrontal cortex, inferior parietal gyrus, and precentral gyrus, compared to placebo, and regardless of recipient. Oxytocin (versus placebo) administration was additionally associated with opposing tracking of self-benefitting versus prosocial PEs in dorsal anterior cingulate cortex, insula and superior temporal gyrus. These findings suggest that both l-DOPA and oxytocin induce a context-independent shift from positive towards negative tracking of PEs during learning. Moreover, oxytocin may have opposing effects on PE signaling when learning to benefit oneself versus another.
Collapse
Affiliation(s)
- Myrthe Jansen
- Department of Clinical Psychology, Leiden University, the Netherlands; Leiden Institute for Brain and Cognition (LIBC), Leiden, the Netherlands.
| | - Patricia L Lockwood
- Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, UK; Institute for Mental Health, School of Psychology, University of Birmingham, Birmingham, UK; Centre for Developmental Science, School of Psychology, University of Birmingham, UK
| | - Jo Cutler
- Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, UK; Institute for Mental Health, School of Psychology, University of Birmingham, Birmingham, UK; Centre for Developmental Science, School of Psychology, University of Birmingham, UK
| | - Ellen R A de Bruijn
- Department of Clinical Psychology, Leiden University, the Netherlands; Leiden Institute for Brain and Cognition (LIBC), Leiden, the Netherlands
| |
Collapse
|
22
|
Kreis I, Zhang L, Mittner M, Syla L, Lamm C, Pfuhl G. Aberrant uncertainty processing is linked to psychotic-like experiences, autistic traits, and is reflected in pupil dilation during probabilistic learning. COGNITIVE, AFFECTIVE & BEHAVIORAL NEUROSCIENCE 2023:10.3758/s13415-023-01088-2. [PMID: 36977966 PMCID: PMC10390366 DOI: 10.3758/s13415-023-01088-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 03/07/2023] [Indexed: 03/30/2023]
Abstract
Aberrant belief updating due to misestimation of uncertainty and an increased perception of the world as volatile (i.e., unstable) has been found in autism and psychotic disorders. Pupil dilation tracks events that warrant belief updating, likely reflecting the adjustment of neural gain. However, whether subclinical autistic or psychotic symptoms affect this adjustment and how they relate to learning in volatile environments remains to be unraveled. We investigated the relationship between behavioral and pupillometric markers of subjective volatility (i.e., experience of the world as unstable), autistic traits, and psychotic-like experiences in 52 neurotypical adults with a probabilistic reversal learning task. Computational modeling revealed that participants with higher psychotic-like experience scores overestimated volatility in low-volatile task periods. This was not the case for participants scoring high on autistic-like traits, who instead showed a diminished adaptation of choice-switching behavior in response to risk. Pupillometric data indicated that individuals with higher autistic- or psychotic-like trait and experience scores differentiated less between events that warrant belief updating and those that do not when volatility was high. These findings are in line with misestimation of uncertainty accounts of psychosis and autism spectrum disorders and indicate that aberrancies are already present at the subclinical level.
Collapse
Affiliation(s)
- Isabel Kreis
- Department of Psychology, UiT - The Arctic University of Norway, Tromsø, Norway.
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
| | - Lei Zhang
- Department of Psychology, UiT - The Arctic University of Norway, Tromsø, Norway
- Institute for Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, UK
- Institute for Mental Health, School of Psychology, University of Birmingham, Birmingham, UK
- Social, Cognitive and Affective Neuroscience Unit, Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria
| | - Matthias Mittner
- Department of Psychology, UiT - The Arctic University of Norway, Tromsø, Norway
| | - Leonard Syla
- Department of Psychology, UiT - The Arctic University of Norway, Tromsø, Norway
| | - Claus Lamm
- Social, Cognitive and Affective Neuroscience Unit, Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria
- Vienna Cognitive Science Hub, University of Vienna, Vienna, Austria
| | - Gerit Pfuhl
- Department of Psychology, UiT - The Arctic University of Norway, Tromsø, Norway
- Department of Psychology, Norwegian University of Science and Technology, Trondheim, Norway
| |
Collapse
|
23
|
Fornari L, Ioumpa K, Nostro AD, Evans NJ, De Angelis L, Speer SPH, Paracampo R, Gallo S, Spezio M, Keysers C, Gazzola V. Neuro-computational mechanisms and individual biases in action-outcome learning under moral conflict. Nat Commun 2023; 14:1218. [PMID: 36878911 PMCID: PMC9988878 DOI: 10.1038/s41467-023-36807-3] [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: 11/25/2021] [Accepted: 02/17/2023] [Indexed: 03/08/2023] Open
Abstract
Learning to predict action outcomes in morally conflicting situations is essential for social decision-making but poorly understood. Here we tested which forms of Reinforcement Learning Theory capture how participants learn to choose between self-money and other-shocks, and how they adapt to changes in contingencies. We find choices were better described by a reinforcement learning model based on the current value of separately expected outcomes than by one based on the combined historical values of past outcomes. Participants track expected values of self-money and other-shocks separately, with the substantial individual difference in preference reflected in a valuation parameter balancing their relative weight. This valuation parameter also predicted choices in an independent costly helping task. The expectations of self-money and other-shocks were biased toward the favored outcome but fMRI revealed this bias to be reflected in the ventromedial prefrontal cortex while the pain-observation network represented pain prediction errors independently of individual preferences.
Collapse
Affiliation(s)
- Laura Fornari
- Netherlands Institute for Neuroscience, KNAW, Meibergdreef 47, 1105BA, Amsterdam, The Netherlands
| | - Kalliopi Ioumpa
- Netherlands Institute for Neuroscience, KNAW, Meibergdreef 47, 1105BA, Amsterdam, The Netherlands
| | - Alessandra D Nostro
- Netherlands Institute for Neuroscience, KNAW, Meibergdreef 47, 1105BA, Amsterdam, The Netherlands
| | - Nathan J Evans
- School of Psychology, University of Queensland, Brisbane, QLD, Australia
| | - Lorenzo De Angelis
- Netherlands Institute for Neuroscience, KNAW, Meibergdreef 47, 1105BA, Amsterdam, The Netherlands
| | - Sebastian P H Speer
- Netherlands Institute for Neuroscience, KNAW, Meibergdreef 47, 1105BA, Amsterdam, The Netherlands
| | - Riccardo Paracampo
- Netherlands Institute for Neuroscience, KNAW, Meibergdreef 47, 1105BA, Amsterdam, The Netherlands
| | - Selene Gallo
- Netherlands Institute for Neuroscience, KNAW, Meibergdreef 47, 1105BA, Amsterdam, The Netherlands
| | - Michael Spezio
- Psychology, Neuroscience, & Data Science, Scripps College, 1030 Columbia Ave, CA 91711, Claremont, CA, USA
| | - Christian Keysers
- Netherlands Institute for Neuroscience, KNAW, Meibergdreef 47, 1105BA, Amsterdam, The Netherlands.,Department of Psychology, University of Amsterdam, Nieuwe Achtergracht 129-B, 1018 WT, Amsterdam, The Netherlands
| | - Valeria Gazzola
- Netherlands Institute for Neuroscience, KNAW, Meibergdreef 47, 1105BA, Amsterdam, The Netherlands. .,Department of Psychology, University of Amsterdam, Nieuwe Achtergracht 129-B, 1018 WT, Amsterdam, The Netherlands.
| |
Collapse
|
24
|
Xu T, Zhou X, Kanen JW, Wang L, Li J, Chen Z, Zhang R, Jiao G, Zhou F, Zhao W, Yao S, Becker B. Angiotensin blockade enhances motivational reward learning via enhancing striatal prediction error signaling and frontostriatal communication. Mol Psychiatry 2023; 28:1692-1702. [PMID: 36810437 DOI: 10.1038/s41380-023-02001-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 02/09/2023] [Accepted: 02/10/2023] [Indexed: 02/23/2023]
Abstract
Adaptive human learning utilizes reward prediction errors (RPEs) that scale the differences between expected and actual outcomes to optimize future choices. Depression has been linked with biased RPE signaling and an exaggerated impact of negative outcomes on learning which may promote amotivation and anhedonia. The present proof-of-concept study combined computational modeling and multivariate decoding with neuroimaging to determine the influence of the selective competitive angiotensin II type 1 receptor antagonist losartan on learning from positive or negative outcomes and the underlying neural mechanisms in healthy humans. In a double-blind, between-subjects, placebo-controlled pharmaco-fMRI experiment, 61 healthy male participants (losartan, n = 30; placebo, n = 31) underwent a probabilistic selection reinforcement learning task incorporating a learning and transfer phase. Losartan improved choice accuracy for the hardest stimulus pair via increasing expected value sensitivity towards the rewarding stimulus relative to the placebo group during learning. Computational modeling revealed that losartan reduced the learning rate for negative outcomes and increased exploitatory choice behaviors while preserving learning for positive outcomes. These behavioral patterns were paralleled on the neural level by increased RPE signaling in orbitofrontal-striatal regions and enhanced positive outcome representations in the ventral striatum (VS) following losartan. In the transfer phase, losartan accelerated response times and enhanced VS functional connectivity with left dorsolateral prefrontal cortex when approaching maximum rewards. These findings elucidate the potential of losartan to reduce the impact of negative outcomes during learning and subsequently facilitate motivational approach towards maximum rewards in the transfer of learning. This may indicate a promising therapeutic mechanism to normalize distorted reward learning and fronto-striatal functioning in depression.
Collapse
Affiliation(s)
- Ting Xu
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.,MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Xinqi Zhou
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.,MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Jonathan W Kanen
- Department of Psychology, University of Cambridge, Cambridge, UK.,Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK
| | - Lan Wang
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.,MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Jialin Li
- Max Planck School of Cognition, Leipzig, Germany
| | - Zhiyi Chen
- Faculty of Psychology, Southwest University, Chongqing, China.,Key Laboratory of Cognition and Personality, Ministry of Education, Chongqing, China
| | - Ran Zhang
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.,MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Guojuan Jiao
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.,MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Feng Zhou
- Faculty of Psychology, Southwest University, Chongqing, China.,Key Laboratory of Cognition and Personality, Ministry of Education, Chongqing, China
| | - Weihua Zhao
- MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Shuxia Yao
- MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Benjamin Becker
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China. .,MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
| |
Collapse
|
25
|
Kleberg JL, Willfors C, Björlin Avdic H, Riby D, Galazka MA, Guath M, Nordgren A, Strannegård C. Social feedback enhances learning in Williams syndrome. Sci Rep 2023; 13:164. [PMID: 36599864 PMCID: PMC9813264 DOI: 10.1038/s41598-022-26055-8] [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: 08/12/2022] [Accepted: 12/08/2022] [Indexed: 01/06/2023] Open
Abstract
Williams syndrome (WS) is a rare genetic condition characterized by high social interest and approach motivation as well as intellectual disability and anxiety. Despite the fact that social stimuli are believed to have an increased intrinsic reward value in WS, it is not known whether this translates to learning and decision making. Genes homozygously deleted in WS are linked to sociability in the general population, making it a potential model condition for understanding the social brain. Probabilistic reinforcement learning was studied with either social or non-social rewards for correct choices. Social feedback improved learning in individuals with Williams syndrome but not in typically developing controls or individuals with other intellectual disabilities. Computational modeling indicated that these effects on social feedback were mediated by a shift towards higher weight given to rewards relative to punishments and increased choice consistency. We conclude that reward learning in WS is characterized by high volatility and a tendency to learn how to avoid punishment rather than how to gain rewards. Social feedback can partly normalize this pattern and promote adaptive reward learning.
Collapse
Affiliation(s)
- Johan Lundin Kleberg
- grid.10548.380000 0004 1936 9377Department of Psychology, Stockholm University, Stockholm, Sweden ,grid.4714.60000 0004 1937 0626Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institute, Stockholm, Sweden
| | - Charlotte Willfors
- grid.4714.60000 0004 1937 0626Department of Molecular Medicine and Surgery, Karolinska Institute, Stockholm, Sweden
| | - Hanna Björlin Avdic
- grid.4714.60000 0004 1937 0626Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institute, Stockholm, Sweden
| | - Deborah Riby
- grid.8250.f0000 0000 8700 0572Department of Psychology, Centre for Developmental Disorders, Durham University, Durham, UK
| | - Martyna A. Galazka
- grid.8761.80000 0000 9919 9582Gillberg Neuropsychiatry Centre, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Mona Guath
- grid.8993.b0000 0004 1936 9457Department of Psychology, Uppsala University, Uppsala, Sweden
| | - Ann Nordgren
- grid.4714.60000 0004 1937 0626Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institute, Stockholm, Sweden ,grid.24381.3c0000 0000 9241 5705Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden ,grid.8761.80000 0000 9919 9582Department of Laboratory Medicine, Institute of Biomedicine, University of Gothenburg, Gothenburg, Sweden ,grid.1649.a000000009445082XDepartment of Clinical Genetics and Genomics, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Claes Strannegård
- grid.4714.60000 0004 1937 0626Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institute, Stockholm, Sweden ,grid.8761.80000 0000 9919 9582Division of Cognition and Communication, Department of Applied IT, University of Gothenburg, Gothenburg, Sweden
| |
Collapse
|
26
|
Comparing gratitude and pride: evidence from brain and behavior. COGNITIVE, AFFECTIVE & BEHAVIORAL NEUROSCIENCE 2022; 22:1199-1214. [PMID: 35437682 DOI: 10.3758/s13415-022-01006-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 03/30/2022] [Indexed: 01/27/2023]
Abstract
Gratitude and pride are both positive emotions. Yet gratitude motivates people to help others and build up relationships, whereas pride motivates people to pursue achievements and build on self-esteem. Although these social outcomes are crucial for humans to be evolutionarily adaptive, no study so far has systematically compared gratitude and pride to understand why and how they can motivate humans differently. In this review, we compared gratitude and pride from their etymologies, cognitive prerequisites, motivational functions, and brain regions involved. By integrating the evidence from brain and behavior, we suggest that gratitude and pride share a common reward basis, yet gratitude is more related to theory of mind, while pride is more related to self-referential processing. Moreover, we proposed a cognitive neuroscientific model to explain the dynamics in gratitude and pride under a reinforcement learning framework.
Collapse
|
27
|
Nitschke JP, Forbes PA, Lamm C. Does stress make us more—or less—prosocial? A systematic review and meta-analysis of the effects of acute stress on prosocial behaviours using economic games. Neurosci Biobehav Rev 2022; 142:104905. [DOI: 10.1016/j.neubiorev.2022.104905] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 09/16/2022] [Accepted: 10/02/2022] [Indexed: 01/10/2023]
|
28
|
Zhang Y, Zhai Y, Zhou X, Zhang Z, Gu R, Luo Y, Feng C. Loss context enhances preferences for generosity but reduces preferences for honesty: Evidence from a combined behavioural‐computational approach. EUROPEAN JOURNAL OF SOCIAL PSYCHOLOGY 2022. [DOI: 10.1002/ejsp.2896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Affiliation(s)
- Yijie Zhang
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University) Ministry of Education 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
| | - Yuzhu Zhai
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University) Ministry of Education 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
| | - Xingmei Zhou
- Center of Brain Disorder and Cognitive Sciences College of Psychology and Sociology Shenzhen Key Laboratory of Affective and Social Cognitive Science Shenzhen University Center for Emotion and Brain Shenzhen Institute of Neuroscience Shenzhen China
| | - Zhixin Zhang
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University) Ministry of Education 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
| | - Ruolei Gu
- Key Laboratory of Behavioral Science Institute of Psychology Chinese Academy of Sciences Department of Psychology University of Chinese Academy of Sciences Beijing China
| | - Yue‐jia Luo
- The State Key Lab of Cognitive and Learning Faculty of Psychology Beijing Normal University Beijing China
- The Research Center of Brain Science and Visual Cognition Kunming University of Science and Technology Kunming China
- College of Teacher Education Qilu Normal University Jinan China
| | - Chunliang Feng
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University) Ministry of Education 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
| |
Collapse
|
29
|
Adaptive learning strategies in purely observational learning. CURRENT PSYCHOLOGY 2022. [DOI: 10.1007/s12144-022-03904-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
|
30
|
Incorporating social knowledge structures into computational models. Nat Commun 2022; 13:6205. [PMID: 36266284 PMCID: PMC9584930 DOI: 10.1038/s41467-022-33418-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Accepted: 09/16/2022] [Indexed: 12/24/2022] Open
Abstract
To navigate social interactions successfully, humans need to continuously learn about the personality traits of other people (e.g., how helpful or aggressive is the other person?). However, formal models that capture the complexities of social learning processes are currently lacking. In this study, we specify and test potential strategies that humans can employ for learning about others. Standard Rescorla-Wagner (RW) learning models only capture parts of the learning process because they neglect inherent knowledge structures and omit previously acquired knowledge. We therefore formalize two social knowledge structures and implement them in hybrid RW models to test their usefulness across multiple social learning tasks. We name these concepts granularity (knowledge structures about personality traits that can be utilized at different levels of detail during learning) and reference points (previous knowledge formalized into representations of average people within a social group). In five behavioural experiments, results from model comparisons and statistical analyses indicate that participants efficiently combine the concepts of granularity and reference points-with the specific combinations in models depending on the people and traits that participants learned about. Overall, our experiments demonstrate that variants of RW algorithms, which incorporate social knowledge structures, describe crucial aspects of the dynamics at play when people interact with each other.
Collapse
|
31
|
Colas JT, Dundon NM, Gerraty RT, Saragosa‐Harris NM, Szymula KP, Tanwisuth K, Tyszka JM, van Geen C, Ju H, Toga AW, Gold JI, Bassett DS, Hartley CA, Shohamy D, Grafton ST, O'Doherty JP. Reinforcement learning with associative or discriminative generalization across states and actions: fMRI at 3 T and 7 T. Hum Brain Mapp 2022; 43:4750-4790. [PMID: 35860954 PMCID: PMC9491297 DOI: 10.1002/hbm.25988] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Revised: 05/20/2022] [Accepted: 06/10/2022] [Indexed: 11/12/2022] Open
Abstract
The model-free algorithms of "reinforcement learning" (RL) have gained clout across disciplines, but so too have model-based alternatives. The present study emphasizes other dimensions of this model space in consideration of associative or discriminative generalization across states and actions. This "generalized reinforcement learning" (GRL) model, a frugal extension of RL, parsimoniously retains the single reward-prediction error (RPE), but the scope of learning goes beyond the experienced state and action. Instead, the generalized RPE is efficiently relayed for bidirectional counterfactual updating of value estimates for other representations. Aided by structural information but as an implicit rather than explicit cognitive map, GRL provided the most precise account of human behavior and individual differences in a reversal-learning task with hierarchical structure that encouraged inverse generalization across both states and actions. Reflecting inference that could be true, false (i.e., overgeneralization), or absent (i.e., undergeneralization), state generalization distinguished those who learned well more so than action generalization. With high-resolution high-field fMRI targeting the dopaminergic midbrain, the GRL model's RPE signals (alongside value and decision signals) were localized within not only the striatum but also the substantia nigra and the ventral tegmental area, including specific effects of generalization that also extend to the hippocampus. Factoring in generalization as a multidimensional process in value-based learning, these findings shed light on complexities that, while challenging classic RL, can still be resolved within the bounds of its core computations.
Collapse
Affiliation(s)
- Jaron T. Colas
- Department of Psychological and Brain SciencesUniversity of CaliforniaSanta BarbaraCaliforniaUSA
- Division of the Humanities and Social SciencesCalifornia Institute of TechnologyPasadenaCaliforniaUSA
- Computation and Neural Systems Program, California Institute of TechnologyPasadenaCaliforniaUSA
| | - Neil M. Dundon
- Department of Psychological and Brain SciencesUniversity of CaliforniaSanta BarbaraCaliforniaUSA
- Department of Child and Adolescent Psychiatry, Psychotherapy, and PsychosomaticsUniversity of FreiburgFreiburg im BreisgauGermany
| | - Raphael T. Gerraty
- Department of PsychologyColumbia UniversityNew YorkNew YorkUSA
- Zuckerman Mind Brain Behavior Institute, Columbia UniversityNew YorkNew YorkUSA
- Center for Science and SocietyColumbia UniversityNew YorkNew YorkUSA
| | - Natalie M. Saragosa‐Harris
- Department of PsychologyNew York UniversityNew YorkNew YorkUSA
- Department of PsychologyUniversity of CaliforniaLos AngelesCaliforniaUSA
| | - Karol P. Szymula
- Department of BioengineeringUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Koranis Tanwisuth
- Division of the Humanities and Social SciencesCalifornia Institute of TechnologyPasadenaCaliforniaUSA
- Department of PsychologyUniversity of CaliforniaBerkeleyCaliforniaUSA
| | - J. Michael Tyszka
- Division of the Humanities and Social SciencesCalifornia Institute of TechnologyPasadenaCaliforniaUSA
| | - Camilla van Geen
- Zuckerman Mind Brain Behavior Institute, Columbia UniversityNew YorkNew YorkUSA
- Department of PsychologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Harang Ju
- Neuroscience Graduate GroupUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Arthur W. Toga
- Laboratory of Neuro ImagingUSC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Joshua I. Gold
- Department of NeuroscienceUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Dani S. Bassett
- Department of BioengineeringUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Department of Electrical and Systems EngineeringUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Department of PsychiatryUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Department of Physics and AstronomyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Santa Fe InstituteSanta FeNew MexicoUSA
| | - Catherine A. Hartley
- Department of PsychologyNew York UniversityNew YorkNew YorkUSA
- Center for Neural ScienceNew York UniversityNew YorkNew YorkUSA
| | - Daphna Shohamy
- Department of PsychologyColumbia UniversityNew YorkNew YorkUSA
- Zuckerman Mind Brain Behavior Institute, Columbia UniversityNew YorkNew YorkUSA
- Kavli Institute for Brain ScienceColumbia UniversityNew YorkNew YorkUSA
| | - Scott T. Grafton
- Department of Psychological and Brain SciencesUniversity of CaliforniaSanta BarbaraCaliforniaUSA
| | - John P. O'Doherty
- Division of the Humanities and Social SciencesCalifornia Institute of TechnologyPasadenaCaliforniaUSA
- Computation and Neural Systems Program, California Institute of TechnologyPasadenaCaliforniaUSA
| |
Collapse
|
32
|
Latuske P, von Heimendahl M, Deiana S, Wotjak CT, du Hoffmann J. Sustained MK-801 induced deficit in a novel probabilistic reversal learning task. Front Pharmacol 2022; 13:898548. [PMID: 36313373 PMCID: PMC9614101 DOI: 10.3389/fphar.2022.898548] [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: 03/17/2022] [Accepted: 08/02/2022] [Indexed: 12/01/2022] Open
Abstract
Cognitive flexibility, the ability to adapt to unexpected changes, is critical for healthy environmental and social interactions, and thus to everyday functioning. In neuropsychiatric diseases, cognitive flexibility is often impaired and treatment options are lacking. Probabilistic reversal learning (PRL) is commonly used to measure cognitive flexibility in rodents and humans. In PRL tasks, subjects must sample choice options and, from probabilistic feedback, find the current best choice which then changes without warning. However, in rodents, pharmacological models of human cognitive impairment tend to disrupt only the first (or few) of several contingency reversals, making quantitative assessment of behavioral effects difficult. To address this limitation, we developed a novel rat PRL where reversals occur at relatively long intervals in time that demonstrates increased sensitivity to the non-competitive NMDA receptor antagonist MK-801. Here, we quantitively compare behavior in time-based PRL with a widely used task where reversals occur based on choice behavior. In time-based PRL, MK-801 induced sustained reversal learning deficits both in time and across reversal blocks but, at the same dose, only transient weak effects in performance-based PRL. Moreover, time-based PRL yielded better estimates of behavior and reinforcement learning model parameters, which opens meaningful pharmacological windows to efficiently test and develop novel drugs preclinically with the goal of improving cognitive impairment in human patients.
Collapse
|
33
|
How go/no-go training changes behavior: A value-based decision-making perspective. Curr Opin Behav Sci 2022. [DOI: 10.1016/j.cobeha.2022.101206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
|
34
|
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.
Collapse
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
| |
Collapse
|
35
|
Impaired Outcome Evaluation During Risky Decision-Making in Individuals with Methamphetamine Use Disorder. Int J Ment Health Addict 2022. [DOI: 10.1007/s11469-022-00873-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/09/2022] Open
|
36
|
Jiang Y, Wu H, Mi Q, Zhu L. Neurocomputations of strategic behavior: From iterated to novel interactions. WIRES COGNITIVE SCIENCE 2022; 13:e1598. [PMID: 35441465 PMCID: PMC9542218 DOI: 10.1002/wcs.1598] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 03/27/2022] [Accepted: 03/29/2022] [Indexed: 11/15/2022]
Abstract
Strategic interactions, where an individual's payoff depends on the decisions of multiple intelligent agents, are ubiquitous among social animals. They span a variety of important social behaviors such as competition, cooperation, coordination, and communication, and often involve complex, intertwining cognitive operations ranging from basic reward processing to higher‐order mentalization. Here, we review the progress and challenges in probing the neural and cognitive mechanisms of strategic behavior of interacting individuals, drawing an analogy to recent developments in studies of reward‐seeking behavior, in particular, how research focuses in the field of strategic behavior have been expanded from adaptive behavior based on trial‐and‐error to flexible decisions based on limited prior experience. We highlight two important research questions in the field of strategic behavior: (i) How does the brain exploit past experience for learning to behave strategically? and (ii) How does the brain decide what to do in novel strategic situations in the absence of direct experience? For the former, we discuss the utility of learning models that have effectively connected various types of neural data with strategic learning behavior and helped elucidate the interplay among multiple learning processes. For the latter, we review the recent evidence and propose a neural generative mechanism by which the brain makes novel strategic choices through simulating others' goal‐directed actions according to rational or bounded‐rational principles obtained through indirect social knowledge. This article is categorized under:Economics > Interactive Decision‐Making Psychology > Reasoning and Decision Making Neuroscience > Cognition
Collapse
Affiliation(s)
- Yaomin Jiang
- School of Psychological and Cognitive Sciences, Beijing Key Laboratory of Behavior and Mental Health, IDG/McGovern Institute for Brain Research, Peking‐Tsinghua Center for Life Sciences Peking University Beijing China
| | - Hai‐Tao Wu
- School of Psychological and Cognitive Sciences, Beijing Key Laboratory of Behavior and Mental Health, IDG/McGovern Institute for Brain Research, Peking‐Tsinghua Center for Life Sciences Peking University Beijing China
| | - Qingtian Mi
- School of Psychological and Cognitive Sciences, Beijing Key Laboratory of Behavior and Mental Health, IDG/McGovern Institute for Brain Research, Peking‐Tsinghua Center for Life Sciences Peking University Beijing China
| | - Lusha Zhu
- School of Psychological and Cognitive Sciences, Beijing Key Laboratory of Behavior and Mental Health, IDG/McGovern Institute for Brain Research, Peking‐Tsinghua Center for Life Sciences Peking University Beijing China
| |
Collapse
|
37
|
Bhattacharyya SS. Monetization of customer futures through machine learning and artificial intelligence based persuasive technologies. JOURNAL OF SCIENCE AND TECHNOLOGY POLICY MANAGEMENT 2022. [DOI: 10.1108/jstpm-09-2021-0136] [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
Purpose
The purpose of this study was to ascertain how real options investment perspective could be applied towards monetization of customer futures through the deployment of machine learning (ML) and artificial intelligence (AI)-based persuasive technologies.
Design/methodology/approach
The authors embarked on a theoretical treatise as advocated by scholars (Cornelissen, 2019; Barney, 2018; Cornelissen, 2017; Smithey Fulmer, 2012; Bacharach, 1989; Whetten, 1989; Weick,1989). Towards this end, theoretical argumentative logic was incrementally used to build an integrated perspective on the deployment of learning and AI-based persuasive technologies. This was carried out with strategic real options investment perspective to secure customer futures on m-commerce apps and e-commerce sites.
Findings
M-commerce apps and e-commerce sites have been deploying ML and AI-based tools (referred to as persuasive technologies), to nudge customers for increased and quicker purchase. The primary objective was to increase engagement time of customers (at an individual level), grow the number of customers (at market level) and increase firm revenue (at an organizational level). The deployment of any persuasive technology entailed increased investment (cash outflow) but was also expected to increase the level of revenue and margin (cash inflow). Given the dynamics of market and the emergent nature of persuasive technologies, ascertaining favourable cash flow was challenging. Real options strategy provided a robust theoretical perspective to time the persuasive technology-related investment in stages. This helped managers to be on time with loading customer purchase with increased temporal immediacy. A real options investment space involving six spaces has also been developed in this conceptual work. These were Never Invest, Immediately Investment, Present-day Investment Possibility, Possibly Invest Later, Invest Probably Later and Possibly Never Invest.
Research limitations/implications
The foundations of this study domain encompassed work done by an eclectic mix of scholars like from technology management (Siggelkow and Terwiesch, 2019a; Porter and Heppelmann, 2014), real options (Trigeorgis and Reuer, 2017; Luehrman, 1998a, 1998b), marketing intelligence and planning (Appel et al., 2020; Thaichon et al., 2019; Thaichon et al., 2020; Ye et al., 2019) and strategy from a demand positioning school of thought (Adner and Zemsky, 2006).
Practical implications
The findings would help managers to comprehend what level of investments need to be done in a staggered manner. The phased way of investing towards the deployment of ML and AI-based persuasive technologies would enable better monetization of customer futures. This would aid marketing managers for increased customer engagement at the individual level, fast monetization of customer futures and increased number of customers and consumption on m-commerce apps and e-commerce sites.
Originality/value
This was one of the first studies to apply real options investment perspective towards the deployment of ML and AI-based persuasive technologies for monetizing customer futures.
Collapse
|
38
|
Kreis I, Zhang L, Moritz S, Pfuhl G. Spared performance but increased uncertainty in schizophrenia: Evidence from a probabilistic decision-making task. Schizophr Res 2022; 243:414-423. [PMID: 34272122 DOI: 10.1016/j.schres.2021.06.038] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Revised: 03/30/2021] [Accepted: 06/23/2021] [Indexed: 10/20/2022]
Abstract
Aberrant attribution of salience to in fact little informative events might explain the emergence of positive symptoms in schizophrenia and has been linked to belief uncertainty. Uncertainty is thought to be encoded by neuromodulators, including norepinephrine. However, norepinephrinergic encoding of uncertainty, measured as task-related pupil dilation, has rarely been explored in schizophrenia. Here, we addressed this question by comparing individuals with a disorder from the schizophrenia spectrum to a non-psychiatric control group on behavioral and pupillometric measures in a probabilistic prediction task, where different levels of uncertainty were introduced. Behaviorally, patients performed similar to controls, but their belief uncertainty was higher, particularly when instability of the task environment was high, suggesting an increased sensitivity to this instability. Furthermore, while pupil dilation scaled positively with uncertainty, this was less the case for patients, suggesting aberrant neuromodulatory regulation of neural gain, which may hinder the reduction of uncertainty in the long run. Together, the findings point to abnormal uncertainty processing and norepinephrinergic signaling in schizophrenia, potentially informing future development of both psychopharmacological therapies and psychotherapeutic approaches that deal with the processing of uncertain information.
Collapse
Affiliation(s)
- Isabel Kreis
- Department of Psychology, Faculty of Health Sciences, UiT The Arctic University of Norway, 9037 Tromsø, Norway.
| | - Lei Zhang
- Department of Psychology, Faculty of Health Sciences, UiT The Arctic University of Norway, 9037 Tromsø, Norway; Social, Cognitive and Affective Neuroscience Unit, Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Liebiggasse 5, 1010 Vienna, Austria
| | - Steffen Moritz
- Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
| | - Gerit Pfuhl
- Department of Psychology, Faculty of Health Sciences, UiT The Arctic University of Norway, 9037 Tromsø, Norway
| |
Collapse
|
39
|
Elder J, Davis T, Hughes BL. Learning About the Self: Motives for Coherence and Positivity Constrain Learning From Self-Relevant Social Feedback. Psychol Sci 2022; 33:629-647. [PMID: 35343826 DOI: 10.1177/09567976211045934] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
People learn about themselves from social feedback, but desires for coherence and positivity constrain how feedback is incorporated into the self-concept. We developed a network-based model of the self-concept and embedded it in a reinforcement-learning framework to provide a computational account of how motivations shape self-learning from feedback. Participants (N = 46 adult university students) received feedback while evaluating themselves on traits drawn from a causal network of trait semantics. Network-defined communities were assigned different likelihoods of positive feedback. Participants learned from positive feedback but dismissed negative feedback, as reflected by asymmetries in computational parameters that represent the incorporation of positive versus negative outcomes. Furthermore, participants were constrained in how they incorporated feedback: Self-evaluations changed less for traits that have more implications and are thus more important to the coherence of the network. We provide a computational explanation of how motives for coherence and positivity jointly constrain learning about the self from feedback, an explanation that makes testable predictions for future clinical research.
Collapse
Affiliation(s)
- Jacob Elder
- Department of Psychology, University of California, Riverside
| | - Tyler Davis
- Department of Psychological Sciences, Texas Tech University
| | - Brent L Hughes
- Department of Psychology, University of California, Riverside
| |
Collapse
|
40
|
Learning from gain and loss: Links to suicide risk. J Psychiatr Res 2022; 147:126-134. [PMID: 35032945 DOI: 10.1016/j.jpsychires.2021.12.016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Revised: 11/27/2021] [Accepted: 12/10/2021] [Indexed: 11/21/2022]
Abstract
Despite preliminary evidence that people with suicide attempt histories demonstrate deficits in processing feedback, no studies have examined the interrelations of learning from feedback and emotional state on suicide risk. This study examined the influence of suicide risk and negative emotions on learning accuracy and rates among individuals with a range of borderline personality features (N = 145). Participants completed a reinforcement learning task after neutral and negative emotion inductions. Results revealed interactions between suicide risk and emotion condition, with elevated risk linked to greater increases in loss learning rate (training phase models) and gain learning rate (test phase models) post-negative emotion induction. Emotion-dependent fluctuations in learning performance may be markers of decision-making that are associated with greater suicide risk. This line of work has the potential to identify the contexts that confer greater risk for suicidal behaviors.
Collapse
|
41
|
Shamay-Tsoory SG, Hertz U. Adaptive Empathy: A Model for Learning Empathic Responses in Response to Feedback. PERSPECTIVES ON PSYCHOLOGICAL SCIENCE 2022; 17:1008-1023. [PMID: 35050819 DOI: 10.1177/17456916211031926] [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] [Indexed: 01/10/2023]
Abstract
Empathy is usually deployed in social interactions. Nevertheless, common measures and examinations of empathy study this construct in isolation from the person in distress. In this article we seek to extend the field of examination to include both empathizer and target to determine whether and how empathic responses are affected by feedback and learned through interaction. Building on computational approaches in feedback-based adaptations (e.g., no feedback, model-free and model-based learning), we propose a framework for understanding how empathic responses are learned on the basis of feedback. In this framework, adaptive empathy, defined as the ability to adapt one's empathic responses, is a central aspect of empathic skills and can provide a new dimension to the evaluation and investigation of empathy. By extending existing neural models of empathy, we suggest that adaptive empathy may be mediated by interactions between the neural circuits associated with valuation, shared distress, observation-execution, and mentalizing. Finally, we propose that adaptive empathy should be considered a prominent facet of empathic capabilities with the potential to explain empathic behavior in health and psychopathology.
Collapse
Affiliation(s)
- Simone G Shamay-Tsoory
- Department of Psychology, University of Haifa.,Integrated Brain and Behavior Research Center (IBBRC), University of Haifa
| | - Uri Hertz
- Integrated Brain and Behavior Research Center (IBBRC), University of Haifa.,Department of Cognitive Sciences, University of Haifa
| |
Collapse
|
42
|
Mikus N, Korb S, Massaccesi C, Gausterer C, Graf I, Willeit M, Eisenegger C, Lamm C, Silani G, Mathys C. Effects of dopamine D2/3 and opioid receptor antagonism on the trade-off between model-based and model-free behaviour in healthy volunteers. eLife 2022; 11:79661. [PMID: 36468832 PMCID: PMC9721617 DOI: 10.7554/elife.79661] [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: 04/21/2022] [Accepted: 11/22/2022] [Indexed: 12/11/2022] Open
Abstract
Human behaviour requires flexible arbitration between actions we do out of habit and actions that are directed towards a specific goal. Drugs that target opioid and dopamine receptors are notorious for inducing maladaptive habitual drug consumption; yet, how the opioidergic and dopaminergic neurotransmitter systems contribute to the arbitration between habitual and goal-directed behaviour is poorly understood. By combining pharmacological challenges with a well-established decision-making task and a novel computational model, we show that the administration of the dopamine D2/3 receptor antagonist amisulpride led to an increase in goal-directed or 'model-based' relative to habitual or 'model-free' behaviour, whereas the non-selective opioid receptor antagonist naltrexone had no appreciable effect. The effect of amisulpride on model-based/model-free behaviour did not scale with drug serum levels in the blood. Furthermore, participants with higher amisulpride serum levels showed higher explorative behaviour. These findings highlight the distinct functional contributions of dopamine and opioid receptors to goal-directed and habitual behaviour and support the notion that even small doses of amisulpride promote flexible application of cognitive control.
Collapse
Affiliation(s)
- Nace Mikus
- Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of ViennaViennaAustria,Interacting Minds Centre, Aarhus UniversityAarhusDenmark
| | - Sebastian Korb
- Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of ViennaViennaAustria,Department of Psychology, University of EssexColchesterUnited Kingdom
| | - Claudia Massaccesi
- Department of Clinical and Health Psychology, Faculty of Psychology, University of ViennaViennaAustria
| | - Christian Gausterer
- FDZ‐Forensisches DNA Zentrallabor GmbH, Medical University of ViennaViennaAustria
| | - Irene Graf
- Department of Psychiatry and Psychotherapy, Medical University of ViennaViennaAustria
| | - Matthäus Willeit
- Department of Psychiatry and Psychotherapy, Medical University of ViennaViennaAustria
| | - Christoph Eisenegger
- Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of ViennaViennaAustria
| | - Claus Lamm
- Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of ViennaViennaAustria
| | - Giorgia Silani
- Department of Clinical and Health Psychology, Faculty of Psychology, University of ViennaViennaAustria
| | - Christoph Mathys
- Interacting Minds Centre, Aarhus UniversityAarhusDenmark,Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and ETH ZurichZurichSwitzerland,Scuola Internazionale Superiore di Studi Avanzati (SISSA)TriesteItaly
| |
Collapse
|
43
|
Zhou L, Zou T, Zhang L, Lin JM, Zhang YY, Liang ZY. "Carpe Diem?": Disjunction Effect of Incidental Affect on Intertemporal Choice. Front Psychol 2021; 12:782472. [PMID: 34956000 PMCID: PMC8702439 DOI: 10.3389/fpsyg.2021.782472] [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: 09/24/2021] [Accepted: 11/22/2021] [Indexed: 11/13/2022] Open
Abstract
Incidental affect has an important impact on intertemporal choice (IC). This research aimed to test how positive incidental affect influences IC and its underlying mechanisms. We assumed that positive incidental affect may have a disjunction effect on IC that includes or excludes immediate time. Moreover, we examined the role of time perception for the effect of affect on IC. In Study 1, after undergoing affect priming by video clips, participants completed the IC task using a multiple staircase paradigm. Using Hierarchical Bayesian Modeling, we estimated the discount rate parameter by distinguishing “immediate” and “non-immediate” conditions of IC. The participants’ time perception was also measured. In Study 2, apart from the choice preference of IC, we additionally investigated the differences in the participants’ attention to delay and reward attributes before decision making. The results of the two studies indicated that positive incidental affect leads to longer time perception (Study 1) and prior and more attention to the delay attribute of IC (Study 2), which leads individuals to prefer immediate options in the IC (Studies 1 and 2). Moreover, there is a disjunction effect of affect; in other words, the incidental affect did not influence IC excluding immediate time (Studies 1 and 2). This study improves our understanding of the disjunctive effect and its mechanism of inducing a positive incidental affect on IC and thus provides a new perspective on how related decision making can be improved.
Collapse
Affiliation(s)
- Lei Zhou
- School of Management, Guangdong University of Technology, Guangzhou, China
| | - Tong Zou
- School of Management, Guangdong University of Technology, Guangzhou, China
| | - Lei Zhang
- Social, Cognitive and Affective Neuroscience Unit, Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria
| | - Jiao-Min Lin
- School of Management, Guangdong University of Technology, Guangzhou, China
| | - Yang-Yang Zhang
- School of Psychology, Shaanxi Normal University, Xi'an, China
| | - Zhu-Yuan Liang
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| |
Collapse
|
44
|
FeldmanHall O, Nassar MR. The computational challenge of social learning. Trends Cogn Sci 2021; 25:1045-1057. [PMID: 34583876 PMCID: PMC8585698 DOI: 10.1016/j.tics.2021.09.002] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Revised: 08/31/2021] [Accepted: 09/01/2021] [Indexed: 10/20/2022]
Abstract
The complex reward structure of the social world and the uncertainty endemic to social contexts poses a challenge for modeling. For example, during social interactions, the actions of one person influence the internal states of another. These social dependencies make it difficult to formalize social learning problems in a mathematically tractable way. While it is tempting to dispense with these complexities, they are a defining feature of social life. Because the structure of social interactions challenges the simplifying assumptions often made in models, they make an ideal testbed for computational models of cognition. By adopting a framework that embeds existing social knowledge into the model, we can go beyond explaining behaviors in laboratory tasks to explaining those observed in the wild.
Collapse
Affiliation(s)
- Oriel FeldmanHall
- Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, RI 02912, USA; Carney Institute for Brain Sciences, Brown University, Providence, RI 02912, USA.
| | - Matthew R Nassar
- Carney Institute for Brain Sciences, Brown University, Providence, RI 02912, USA; Department of Neuroscience, Brown University, Providence, RI 02912, USA
| |
Collapse
|
45
|
Asutay E, Västfjäll D. The goal-relevance of affective stimuli is dynamically represented in affective experience. ROYAL SOCIETY OPEN SCIENCE 2021; 8:211548. [PMID: 34849249 PMCID: PMC8611340 DOI: 10.1098/rsos.211548] [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: 09/27/2021] [Accepted: 11/01/2021] [Indexed: 06/13/2023]
Abstract
Affect is a continuous and temporally dependent process that represents an individual's ongoing relationship with its environment. However, there is a lack of evidence on how factors defining the dynamic sensory environment modulate changes in momentary affective experience. Here, we show that goal-dependent relevance of stimuli is a key factor shaping momentary affect in a dynamic context. Participants (N = 83) viewed sequentially presented images and reported their momentary affective experience after every fourth stimulus. Relevance was manipulated through an attentional task that rendered each image either task-relevant or task-irrelevant. Computational models were fitted to trial-by-trial affective responses to capture the key dynamic parameters explaining momentary affective experience. The findings from statistical analyses and computational models showed that momentary affective experience was shaped by the temporal integration of the affective impact of recently encountered stimuli, and that task-relevant stimuli, independent of stimulus affect, prompted larger changes in experienced pleasantness compared with task-irrelevant stimuli. These findings clearly show that dynamics of affective experience reflect goal-relevance of stimuli in our surroundings.
Collapse
Affiliation(s)
- Erkin Asutay
- Department of Behavioral Sciences and Learning, Linköping University, Sweden
| | - Daniel Västfjäll
- Department of Behavioral Sciences and Learning, Linköping University, Sweden
- Decision Research, Eugene, OR, USA
| |
Collapse
|
46
|
Riels K, Ramos Campagnoli R, Thigpen N, Keil A. Oscillatory brain activity links experience to expectancy during associative learning. Psychophysiology 2021; 59:e13946. [PMID: 34622471 PMCID: PMC10150413 DOI: 10.1111/psyp.13946] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 08/20/2021] [Accepted: 08/30/2021] [Indexed: 01/23/2023]
Abstract
Associating a novel situation with a specific outcome involves a cascade of cognitive processes, including selecting relevant stimuli, forming predictions regarding expected outcomes, and updating memorized predictions based on experience. The present manuscript uses computational modeling and machine learning to test the hypothesis that alpha-band (8-12 Hz) oscillations are involved in the updating of expectations based on experience. Participants learned that a visual cue predicted an aversive loud noise with a probability of 50%. The Rescorla-Wagner model of associative learning explained trial-wise changes in self-reported noise expectancy as well as alpha power changes. Experience in the past trial and self-reported expectancy for the subsequent trial were accurately decoded based on the topographical distribution of alpha power at specific latencies. Decodable information during initial association formation and contingency report recurred when viewing the conditioned cue. Findings support the idea that alpha oscillations have multiple, temporally specific, roles in the formation of associations between cues and outcomes.
Collapse
Affiliation(s)
- Kierstin Riels
- Department of Psychology, University of Florida, Gainesville, Florida, USA
| | - Rafaela Ramos Campagnoli
- Department of Neurobiology, Institute of Biology, Universidade Federal Fluminense, Niterói, Brazil
| | - Nina Thigpen
- Department of Psychology, University of Florida, Gainesville, Florida, USA
| | - Andreas Keil
- Department of Psychology, University of Florida, Gainesville, Florida, USA
| |
Collapse
|
47
|
Lockwood PL, Klein-Flügge MC. Computational modelling of social cognition and behaviour-a reinforcement learning primer. Soc Cogn Affect Neurosci 2021; 16:761-771. [PMID: 32232358 PMCID: PMC8343561 DOI: 10.1093/scan/nsaa040] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2019] [Revised: 02/07/2020] [Accepted: 03/18/2020] [Indexed: 02/06/2023] Open
Abstract
Social neuroscience aims to describe the neural systems that underpin social cognition and behaviour. Over the past decade, researchers have begun to combine computational models with neuroimaging to link social computations to the brain. Inspired by approaches from reinforcement learning theory, which describes how decisions are driven by the unexpectedness of outcomes, accounts of the neural basis of prosocial learning, observational learning, mentalizing and impression formation have been developed. Here we provide an introduction for researchers who wish to use these models in their studies. We consider both theoretical and practical issues related to their implementation, with a focus on specific examples from the field.
Collapse
Affiliation(s)
- Patricia L Lockwood
- Department of Experimental Psychology, University of Oxford, Oxford OX1 3PH, United Kingdom
- Department of Experimental Psychology, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX1 3PH, United Kingdom
| | - Miriam C Klein-Flügge
- Department of Experimental Psychology, University of Oxford, Oxford OX1 3PH, United Kingdom
- Department of Experimental Psychology, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX1 3PH, United Kingdom
| |
Collapse
|
48
|
Tusche A, Bas LM. Neurocomputational models of altruistic decision-making and social motives: Advances, pitfalls, and future directions. WILEY INTERDISCIPLINARY REVIEWS. COGNITIVE SCIENCE 2021; 12:e1571. [PMID: 34340256 PMCID: PMC9286344 DOI: 10.1002/wcs.1571] [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: 02/06/2021] [Revised: 06/23/2021] [Accepted: 07/01/2021] [Indexed: 01/09/2023]
Abstract
This article discusses insights from computational models and social neuroscience into motivations, precursors, and mechanisms of altruistic decision-making and other-regard. We introduce theoretical and methodological tools for researchers who wish to adopt a multilevel, computational approach to study behaviors that promote others' welfare. Using examples from recent studies, we outline multiple mental and neural processes relevant to altruism. To this end, we integrate evidence from neuroimaging, psychology, economics, and formalized mathematical models. We introduce basic mechanisms-pertinent to a broad range of value-based decisions-and social emotions and cognitions commonly recruited when our decisions involve other people. Regarding the latter, we discuss how decomposing distinct facets of social processes can advance altruistic models and the development of novel, targeted interventions. We propose that an accelerated synthesis of computational approaches and social neuroscience represents a critical step towards a more comprehensive understanding of altruistic decision-making. We discuss the utility of this approach to study lifespan differences in social preference in late adulthood, a crucial future direction in aging global populations. Finally, we review potential pitfalls and recommendations for researchers interested in applying a computational approach to their research. This article is categorized under: Economics > Interactive Decision-Making Psychology > Emotion and Motivation Neuroscience > Cognition Economics > Individual Decision-Making.
Collapse
Affiliation(s)
- Anita Tusche
- Department of Psychology, Queen's University, Ontario, Kingston, Canada.,Department of Economics, Queen's University, Ontario, Kingston, Canada.,Division of the Humanities and Social Sciences, California Institute of Technology, Pasadena, California, USA
| | - Lisa M Bas
- Department of Psychology, Queen's University, Ontario, Kingston, Canada
| |
Collapse
|
49
|
Veselic S, Jocham G, Gausterer C, Wagner B, Ernhoefer-Reßler M, Lanzenberger R, Eisenegger C, Lamm C, Losecaat Vermeer A. A causal role of estradiol in human reinforcement learning. Horm Behav 2021; 134:105022. [PMID: 34273676 DOI: 10.1016/j.yhbeh.2021.105022] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2020] [Revised: 06/12/2021] [Accepted: 06/22/2021] [Indexed: 10/20/2022]
Abstract
The sex hormone estradiol is hypothesized to play a key role in human cognition, and reward processing specifically, via increased dopamine D1-receptor signalling. However, the effect of estradiol on reward processing in men has never been established. To fill this gap, we performed a double-blind placebo-controlled study in which men (N = 100) received either a single dose of estradiol (2 mg) or a placebo. Subjects performed a probabilistic reinforcement learning task where they had to choose between two options with varying reward probabilities to maximize monetary reward. Results showed that estradiol administration increased reward sensitivity compared to placebo. This effect was observed in subjects' choices, how much weight they assigned to their previous choices, and subjective reports about the reward probabilities. Furthermore, effects of estradiol were moderated by reward sensitivity, as measured through the BIS/BAS questionnaire. Using reinforcement learning models, we found that behavioral effects of estradiol were reflected in increased learning rates. These results demonstrate a causal role of estradiol within the framework of reinforcement learning, by enhancing reward sensitivity and learning. Furthermore, they provide preliminary evidence for dopamine-related genetic variants moderating the effect of estradiol on reward processing.
Collapse
Affiliation(s)
- Sebastijan Veselic
- Neuropsychopharmacology and Biopsychology Unit, Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Austria; Department of Clinical and Movement Neurosciences, University College London, London, UK; Wellcome Centre for Human Neuroimaging, University College London, London, UK.
| | - Gerhard Jocham
- Biological Psychology of Decision Making, Institute of Experimental Psychology, Heinrich Heine University Düsseldorf, Germany
| | - Christian Gausterer
- FDZ-Forensisches DNA Zentrallabor GmbH, Medical University of Vienna, Austria
| | - Bernhard Wagner
- Laboratory for Chromatographic & Spectrometric Analysis, FH JOANNEUM, Graz, Austria
| | | | - Rupert Lanzenberger
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Christoph Eisenegger
- Neuropsychopharmacology and Biopsychology Unit, Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Austria
| | - Claus Lamm
- Neuropsychopharmacology and Biopsychology Unit, Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Austria; Vienna Cognitive Science Hub, University of Vienna, Austria
| | - Annabel Losecaat Vermeer
- Neuropsychopharmacology and Biopsychology Unit, Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Austria; Department of Decision Neuroscience and Nutrition, German Institute of Human Nutrition Potsdam-Rehbrücke, Germany; Charité-Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.
| |
Collapse
|
50
|
Kozakevich Arbel E, Shamay-Tsoory SG, Hertz U. Adaptive Empathy: Empathic Response Selection as a Dynamic, Feedback-Based Learning Process. Front Psychiatry 2021; 12:706474. [PMID: 34366937 PMCID: PMC8339423 DOI: 10.3389/fpsyt.2021.706474] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Accepted: 06/29/2021] [Indexed: 01/10/2023] Open
Abstract
Empathy allows us to respond to the emotional state of another person. Considering that an empathic interaction may last beyond the initial response, learning mechanisms may be involved in dynamic adaptation of the reaction to the changing emotional state of the other person. However, traditionally, empathy is assessed through sets of isolated reactions to another's distress. Here we address this gap by focusing on adaptive empathy, defined as the ability to learn and adjust one's empathic responses based on feedback. For this purpose, we designed a novel paradigm of associative learning in which participants chose one of two empathic strategies (reappraisal or distraction) to attenuate the distress of a target person, where one strategy had a higher probability of relieving distress. After each choice, participants received feedback about the success of their chosen strategy in relieving the target person's distress, which they could use to inform their future decisions. The results show that the participants made more accurate choices in the adaptive empathy condition than in a non-social control condition, pointing to an advantage for learning from social feedback. We found a correlation between adaptive empathy and a trait measure of cognitive empathy. These findings indicate that the ability to learn about the effectiveness of empathic responses may benefit from incorporating mentalizing abilities. Our findings provide a lab-based model for studying adaptive empathy and point to the potential contribution of learning theory to enhancing our understanding of the dynamic nature of empathy.
Collapse
Affiliation(s)
| | - Simone G. Shamay-Tsoory
- Department of Psychology, University of Haifa, Haifa, Israel
- Integrated Brain and Behavior Research Center, Haifa, Israel
| | - Uri Hertz
- Integrated Brain and Behavior Research Center, Haifa, Israel
- Department of Cognitive Sciences, University of Haifa, Haifa, Israel
| |
Collapse
|