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McGovern HT, Grimmer HJ, Doss MK, Hutchinson BT, Timmermann C, Lyon A, Corlett PR, Laukkonen RE. An Integrated theory of false insights and beliefs under psychedelics. COMMUNICATIONS PSYCHOLOGY 2024; 2:69. [PMID: 39242747 PMCID: PMC11332244 DOI: 10.1038/s44271-024-00120-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Accepted: 07/23/2024] [Indexed: 09/09/2024]
Abstract
Psychedelics are recognised for their potential to re-orient beliefs. We propose a model of how psychedelics can, in some cases, lead to false insights and thus false beliefs. We first review experimental work on laboratory-based false insights and false memories. We then connect this to insights and belief formation under psychedelics using the active inference framework. We propose that subjective and brain-based alterations caused by psychedelics increases the quantity and subjective intensity of insights and thence beliefs, including false ones. We offer directions for future research in minimising the risk of false and potentially harmful beliefs arising from psychedelics. Ultimately, knowing how psychedelics may facilitate false insights and beliefs is crucial if we are to optimally leverage their therapeutic potential.
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Affiliation(s)
- H T McGovern
- School of Psychology, The University of Queensland, Brisbane, QLD, Australia.
- The Cairnmillar Institute, Melbourne, VIC, Australia.
| | - H J Grimmer
- School of Psychology, The University of Queensland, Brisbane, QLD, Australia
| | - M K Doss
- Department of Psychiatry and Behavioral Sciences, Center for Psychedelic Research & Therapy, The University of Texas at Austin Dell Medical School, Austin, TX, USA
| | - B T Hutchinson
- Faculty of Behavioural and Movement Sciences, Cognitive Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - C Timmermann
- Division of Psychiatry, Department of Brain Sciences, Centre for Psychedelic Research, Imperial College London, London, UK
| | - A Lyon
- Institute of Psychology, Leiden University, Leiden, The Netherlands
| | - P R Corlett
- Department of Psychiatry, Yale University, New Haven, CT, USA
- Wu Tsai Institute, Yale University, New Haven, CT, USA
| | - R E Laukkonen
- Faculty of Health, Southern Cross University, Gold Coast, QLD, Australia
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2
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Souter NE, de Freitas A, Zhang M, Shao X, del Jesus Gonzalez Alam TR, Engen H, Smallwood J, Krieger‐Redwood K, Jefferies E. Default mode network shows distinct emotional and contextual responses yet common effects of retrieval demands across tasks. Hum Brain Mapp 2024; 45:e26703. [PMID: 38716714 PMCID: PMC11077571 DOI: 10.1002/hbm.26703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Revised: 04/03/2024] [Accepted: 04/17/2024] [Indexed: 05/12/2024] Open
Abstract
The default mode network (DMN) lies towards the heteromodal end of the principal gradient of intrinsic connectivity, maximally separated from the sensory-motor cortex. It supports memory-based cognition, including the capacity to retrieve conceptual and evaluative information from sensory inputs, and to generate meaningful states internally; however, the functional organisation of DMN that can support these distinct modes of retrieval remains unclear. We used fMRI to examine whether activation within subsystems of DMN differed as a function of retrieval demands, or the type of association to be retrieved, or both. In a picture association task, participants retrieved semantic associations that were either contextual or emotional in nature. Participants were asked to avoid generating episodic associations. In the generate phase, these associations were retrieved from a novel picture, while in the switch phase, participants retrieved a new association for the same image. Semantic context and emotion trials were associated with dissociable DMN subnetworks, indicating that a key dimension of DMN organisation relates to the type of association being accessed. The frontotemporal and medial temporal DMN showed a preference for emotional and semantic contextual associations, respectively. Relative to the generate phase, the switch phase recruited clusters closer to the heteromodal apex of the principal gradient-a cortical hierarchy separating unimodal and heteromodal regions. There were no differences in this effect between association types. Instead, memory switching was associated with a distinct subnetwork associated with controlled internal cognition. These findings delineate distinct patterns of DMN recruitment for different kinds of associations yet common responses across tasks that reflect retrieval demands.
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Affiliation(s)
- Nicholas E. Souter
- Department of PsychologyUniversity of YorkYorkUK
- School of PsychologyUniversity of SussexBrightonUK
| | - Antonia de Freitas
- Department of PsychologyUniversity of YorkYorkUK
- Experimental Psychology, Division of Psychology and Language SciencesUniversity College LondonLondonUK
| | - Meichao Zhang
- Department of PsychologyUniversity of YorkYorkUK
- CAS Key Laboratory of Behavioral ScienceInstitute of PsychologyBeijingChina
- Department of PsychologyUniversity of Chinese Academy of SciencesBeijingChina
| | - Ximing Shao
- Department of PsychologyUniversity of YorkYorkUK
- Experimental Psychology, Division of Psychology and Language SciencesUniversity College LondonLondonUK
| | | | - Haakon Engen
- Institute for Military Psychiatry, Joint Medical ServicesNorwegian Armed ForcesNorway
- Department of PsychologyUniversity of OsloOsloNorway
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3
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Rösler IK, Amodio DM. Neural Basis of Prejudice and Prejudice Reduction. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2022; 7:1200-1208. [PMID: 36402739 DOI: 10.1016/j.bpsc.2022.10.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 09/18/2022] [Accepted: 10/14/2022] [Indexed: 11/06/2022]
Abstract
Social prejudices, based on race, ethnicity, gender, or other identities, pervade how we perceive, think about, and act toward others. Research on the neural basis of prejudice seeks to illuminate its effects by investigating the neurocognitive processes through which prejudice is formed, represented in the mind, expressed in behavior, and potentially reduced. In this article, we review current knowledge about the social neuroscience of prejudice regarding its influence on rapid social perception, representation in memory, emotional expression and relation to empathy, and regulation, and we discuss implications of this work for prejudice reduction interventions.
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Affiliation(s)
- Inga K Rösler
- Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands
| | - David M Amodio
- Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands; Department of Psychology and Center for Neural Science, New York University, New York, New York.
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4
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Saylik R, Szameitat AJ, Williams AL, Murphy RA. Functional neuroanatomical correlates of contingency judgement. Neurosci Lett 2022; 791:136915. [DOI: 10.1016/j.neulet.2022.136915] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 09/30/2022] [Accepted: 10/11/2022] [Indexed: 11/30/2022]
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5
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Vijayakumar S, Hartstra E, Mars RB, Bekkering H. Neural mechanisms of predicting individual preferences based on group membership. Soc Cogn Affect Neurosci 2021; 16:1006-1017. [PMID: 33025007 PMCID: PMC8421698 DOI: 10.1093/scan/nsaa136] [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: 03/15/2019] [Revised: 08/26/2020] [Accepted: 09/28/2020] [Indexed: 11/17/2022] Open
Abstract
Successful social interaction requires humans to predict others’ behavior. To do so, internal models of others are generated based on previous observations. When predicting others’ preferences for objects, for example, observations are made at an individual level (5-year-old Rosie often chooses a pencil) or at a group level (kids often choose pencils). But previous research has focused either on already established group knowledge, i.e. stereotypes, or on the neural correlates of predicting traits and preferences of individuals. We identified the neural mechanisms underlying predicting individual behavior based on learned group knowledge using fMRI. We show that applying learned group knowledge hinges on both a network of regions commonly referred to as the mentalizing network, and a network of regions implicated in representing social knowledge. Additionally, we provide evidence for the presence of a gradient in the posterior temporal cortex and the medial frontal cortex, catering to different functions while applying learned group knowledge. This process is characterized by an increased connectivity between medial prefrontal cortex and other mentalizing network regions and increased connectivity between anterior temporal lobe and other social knowledge regions. Our study provides insights into the neural mechanisms underlying the application of learned group knowledge.
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Affiliation(s)
- Suhas Vijayakumar
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, HR, Nijmegen, The Netherlands
| | - Egbert Hartstra
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, HR, Nijmegen, The Netherlands
| | - Rogier B Mars
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, HR, Nijmegen, The Netherlands.,Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Harold Bekkering
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, HR, Nijmegen, The Netherlands
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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: 48] [Impact Index Per Article: 12.0] [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.
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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
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Gosztyla ML, Kwong L, Murray NA, Williams CE, Behnke N, Curry P, Corbett KD, DSouza KN, Gala de Pablo J, Gicobi J, Javidnia M, Lotay N, Prescott SM, Quinn JP, Rivera ZMG, Smith MA, Tang KTY, Venkat A, Yamoah MA. Responses to 10 common criticisms of anti-racism action in STEMM. PLoS Comput Biol 2021; 17:e1009141. [PMID: 34264941 PMCID: PMC8282043 DOI: 10.1371/journal.pcbi.1009141] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Affiliation(s)
- Maya L. Gosztyla
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, California, United States of America
| | - Lydia Kwong
- Bioethics and Science Policy Program, Duke University, Durham, North Carolina, United States of America
| | - Naomi A. Murray
- Ecology, Evolution, and Biodiversity Program, University of California Davis, Davis, California, United States of America
| | - Claire E. Williams
- Department of Biology, Northeastern University, Boston, Massachusetts, United States of America
| | - Nicholas Behnke
- Department of Food, Agricultural, and Biological Engineering, The Ohio State University, Columbus, Ohio, United States of America
| | - Porsia Curry
- Porsia Curry, Black Resource Center, University of California San Diego, La Jolla, California, United States of America
| | - Kevin D. Corbett
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, California, United States of America
| | - Karen N. DSouza
- Mayo Clinic Graduate School of Biomedical Science, Rochester, Minnesota, United States of America
| | | | - Joanina Gicobi
- Department of Immunology, Mayo Clinic, Rochester, Minnesota, United States of America
| | - Monica Javidnia
- Department of Neurology, University of Rochester, Rochester, New York, United States of America
| | - Navina Lotay
- Department of Chemistry, University of Toronto, Toronto, Canada
| | - Sidney Madison Prescott
- Executive Women’s MBA Cohort, Women’s College, Brenau University, Gainesville, Georgia, United States of America
- Department of Graduate Studies, Master of Science in Legal Studies Program, Cornell Law School, Ithaca, New York, United States of America
| | - James P. Quinn
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Zeena M. G. Rivera
- Neurosciences Interdepartmental Program, University of California Los Angeles, Los Angeles, California, United States of America
| | - Markia A. Smith
- Department of Pathology and Laboratory Medicine, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Karen T. Y. Tang
- Department of Psychology and Neuroscience, Dalhousie University, Halifax, Canada
| | - Aarya Venkat
- Department of Biochemistry, University of Georgia, Athens, Georgia, United States of America
| | - Megan A. Yamoah
- Department of Physics, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
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8
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Chao CM, McGregor A, Sanderson DJ. Uncertainty and predictiveness modulate attention in human predictive learning. J Exp Psychol Gen 2021; 150:1177-1202. [PMID: 33252980 PMCID: PMC8515774 DOI: 10.1037/xge0000991] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2019] [Revised: 09/06/2020] [Accepted: 09/09/2020] [Indexed: 11/08/2022]
Abstract
[Correction Notice: An Erratum for this article was reported online in Journal of Experimental Psychology: General on Jan 14 2021 (see record 2021-07705-001). In the article, formatting for UK Research Councils funding was omitted. The author note and copyright line now reflect the standard acknowledgment of and formatting for the funding received for this article. All versions of this article have been corrected.] Attention determines which cues receive processing and are learned about. Learning, however, leads to attentional biases. In the study of animal learning, in some circumstances, cues that have been previously predictive of their consequences are subsequently learned about more than are nonpredictive cues, suggesting that they receive more attention. In other circumstances, cues that have previously led to uncertain consequences are learned about more than are predictive cues. In human learning, there is a clear role for predictiveness, but a role for uncertainty has been less clear. Here, in a human learning task, we show that cues that led to uncertain outcomes were subsequently learned about more than were cues that were previously predictive of their outcomes. This effect occurred when there were few uncertain cues. When the number of uncertain cues was increased, attention switched to predictive cues. This pattern of results was found for cues (1) that were uncertain because they led to 2 different outcomes equally often in a nonpredictable manner and (2) that were used in a nonlinear discrimination and were not predictive individually but were predictive in combination with other cues. This suggests that both the opposing predictiveness and uncertainty effects were determined by the relationship between individual cues and outcomes rather than the predictive strength of combined cues. These results demonstrate that learning affects attention; however, the precise nature of the effect on attention depends on the level of task complexity, which reflects a potential switch between exploration and exploitation of cues. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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Weigl M, Pham HH, Mecklinger A, Rosburg T. The effect of shared distinctiveness on source memory: An event-related potential study. COGNITIVE, AFFECTIVE & BEHAVIORAL NEUROSCIENCE 2020; 20:1027-1040. [PMID: 32839959 PMCID: PMC7497493 DOI: 10.3758/s13415-020-00817-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
An illusory correlation (IC) is the erroneous perception that two actually uncorrelated categories are correlated. The Shared Distinctiveness Approach (SDA) explains ICs with heightened accessibility of distinctive category combinations in episodic memory. However, empirical evidence for this approach is heterogeneous. In the present event-related potential (ERP) study, we exploited the fact that more distinctive items elicit larger P300 responses than less distinctive items, which potentially predict subsequent memory performance differences for such items. Distinctiveness at encoding was created by presenting words that differed from frequently presented, positive words in valence, font color, or both. We hypothesized that shared distinctiveness (deviation in both color and valence) would lead to an enhanced P300 subsequent memory effect (SME), better source memory performance, and an overestimation of the frequency of shared distinctive items. Behavioral results indicated the presence of shared distinctiveness effects on source memory and frequency estimation. Unexpectedly, memory also was enhanced for positive items in the frequent color. This pattern also was reflected in the P300 for highly positive and negative items. However, shared distinctiveness did not modulate the P300 SME, indicating that the processing of distinctive features might only indirectly contribute to better encoding. This study shows that shared distinctiveness indeed is associated with better source memory and ICs. Because effects were observed for the most frequent and the least frequent category combination, our results imply that the processing of distinctiveness might involve attention allocation to diametrical category combinations, thereby accentuating the differences between the categories.
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Affiliation(s)
- Michael Weigl
- Department of Psychology, Experimental Neuropsychology Unit, Saarland University, D-66041, Saarbrücken, Germany.
- Department of Psychology, Experimental Neuropsychology Unit, Saarland University, Campus, Building A2.4, D-66123, Saarbrücken, Germany.
| | - Hong Hanh Pham
- Department of Psychology, Experimental Neuropsychology Unit, Saarland University, D-66041, Saarbrücken, Germany
| | - Axel Mecklinger
- Department of Psychology, Experimental Neuropsychology Unit, Saarland University, D-66041, Saarbrücken, Germany
| | - Timm Rosburg
- Department of Psychology, Experimental Neuropsychology Unit, Saarland University, D-66041, Saarbrücken, Germany
- Department of Clinical Research, Evidence-based Insurance Medicine, University of Basel, University Hospital, CH-4031, Basel, Switzerland
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Abstract
The social neuroscience approach to prejudice investigates the psychology of intergroup bias by integrating models and methods of neuroscience with the social psychology of prejudice, stereotyping, and discrimination. Here, we review major contemporary lines of inquiry, including current accounts of group-based categorization; formation and updating of prejudice and stereotypes; effects of prejudice on perception, emotion, and decision making; and the self-regulation of prejudice. In each section, we discuss key social neuroscience findings, consider interpretational challenges and connections with the behavioral literature, and highlight how they advance psychological theories of prejudice. We conclude by discussing the next-generation questions that will continue to guide the social neuroscience approach toward addressing major societal issues of prejudice and discrimination.
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Affiliation(s)
- David M Amodio
- Department of Psychology, New York University, New York, NY 10003, USA; .,Department of Psychology, University of Amsterdam, 1001 NK Amsterdam, The Netherlands
| | - Mina Cikara
- Department of Psychology, Harvard University, Cambridge, Massachusetts 02138, USA
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12
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Abstract
How do we learn what we know about others? Answering this question requires understanding the perceptual mechanisms with which we recognize individuals and their actions, and the processes by which the resulting perceptual representations lead to inferences about people's mental states and traits. This review discusses recent behavioral, neural, and computational studies that have contributed to this broad research program, encompassing both social perception and social cognition.
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Affiliation(s)
- Stefano Anzellotti
- Department of Psychology, Boston College, Boston, Massachusetts 02467, USA; ,
| | - Liane L Young
- Department of Psychology, Boston College, Boston, Massachusetts 02467, USA; ,
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13
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The social neuroscience of race-based and status-based prejudice. Curr Opin Psychol 2018; 24:27-34. [DOI: 10.1016/j.copsyc.2018.04.010] [Citation(s) in RCA: 59] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2018] [Revised: 04/10/2018] [Accepted: 04/11/2018] [Indexed: 11/20/2022]
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14
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Changing our minds: the neural bases of dynamic impression updating. Curr Opin Psychol 2018; 24:72-76. [DOI: 10.1016/j.copsyc.2018.08.007] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2018] [Revised: 08/14/2018] [Accepted: 08/21/2018] [Indexed: 11/22/2022]
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Ma DS, Correll J, Wittenbrink B. The effects of category and physical features on stereotyping and evaluation. JOURNAL OF EXPERIMENTAL SOCIAL PSYCHOLOGY 2018. [DOI: 10.1016/j.jesp.2018.06.008] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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16
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Mattan BD, Kubota JT, Li T, Dang TP, Cloutier J. Motivation Modulates Brain Networks in Response to Faces Varying in Race and Status: A Multivariate Approach. eNeuro 2018; 5:ENEURO.0039-18.2018. [PMID: 30225341 PMCID: PMC6140103 DOI: 10.1523/eneuro.0039-18.2018] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2018] [Revised: 08/05/2018] [Accepted: 08/06/2018] [Indexed: 01/27/2023] Open
Abstract
Previous behavioral and neuroimaging work indicates that individuals who are externally motivated to respond without racial prejudice tend not to spontaneously regulate their prejudice and prefer to focus on nonracial attributes when evaluating others. This fMRI multivariate analysis used partial least squares analysis to examine the distributed neural processing of race and a relevant but ostensibly nonracial attribute (i.e., socioeconomic status) as a function of the perceiver's external motivation. Sixty-one white male participants (Homo sapiens) privately formed impressions of black and white male faces ascribed with high or low status. Across all conditions, greater external motivation was associated with reduced coactivation of brain regions believed to support emotion regulation (rostral anterior cingulate cortex), introspection (middle cingulate), and social cognition (temporal pole, medial prefrontal cortex). The reduced involvement of this network irrespective of target race and status suggests that external motivation is related to the participant's overall approach to impression formation in an interracial context. The findings highlight the importance of examining network coactivation in understanding the role of external motivation in impression formation, among other interracial social processes.
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Affiliation(s)
- Bradley D. Mattan
- Department of Psychological and Brain Sciences, University of Delaware, Newark, Delaware 19716
| | - Jennifer T. Kubota
- Department of Psychological and Brain Sciences, University of Delaware, Newark, Delaware 19716
- Department of Political Science and International Relations, University of Delaware, Newark, Delaware 19716
| | - Tianyi Li
- College of Business Administration, University of Illinois at Chicago, Chicago, Illinois 60607
| | - Tzipporah P. Dang
- Department of Psychological and Brain Sciences, University of Delaware, Newark, Delaware 19716
| | - Jasmin Cloutier
- Department of Psychological and Brain Sciences, University of Delaware, Newark, Delaware 19716
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Illusory correlations despite equated category frequencies: A test of the information loss account. Conscious Cogn 2018; 63:11-28. [PMID: 29909350 DOI: 10.1016/j.concog.2018.06.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2017] [Revised: 04/28/2018] [Accepted: 06/03/2018] [Indexed: 11/23/2022]
Abstract
Illusory correlations (IC) are the perception of covariation, where none exists. For example, people associate majorities with frequent behavior and minorities with infrequent behavior even in the absence of such an association. According to the information loss account, ICs result from greater fading of infrequent group-behavior combinations in memory. We conducted computer simulations based on this account which showed that ICs are expected under standard conditions with skewed category frequencies (i.e. 2:1 ratio for positive and negative descriptions), but not under conditions with equated category frequencies (i.e. 1:1 ratio for positive and negative descriptions). Contrary to these simulations, our behavioral experiments revealed an IC under both conditions, which did not decrease over time. Thus, information loss alone is not sufficient as an explanation for the formation of ICs. These results imply that negative items contribute to ICs not only due to their infrequency, but also due to their emotional salience.
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