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Story GW, Smith R, Moutoussis M, Berwian IM, Nolte T, Bilek E, Siegel JZ, Dolan RJ. A social inference model of idealization and devaluation. Psychol Rev 2024; 131:749-780. [PMID: 37602986 DOI: 10.1037/rev0000430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/22/2023]
Abstract
People often form polarized beliefs, imbuing objects (e.g., themselves or others) with unambiguously positive or negative qualities. In clinical settings, this is referred to as dichotomous thinking or "splitting" and is a feature of several psychiatric disorders. Here, we introduce a Bayesian model of splitting that parameterizes a tendency to rigidly categorize objects as either entirely "Bad" or "Good," rather than to flexibly learn dispositions along a continuous scale. Distinct from the previous descriptive theories, the model makes quantitative predictions about how dichotomous beliefs emerge and are updated in light of new information. Specifically, the model addresses how splitting is context-dependent, yet exhibits stability across time. A key model feature is that phases of devaluation and/or idealization are consolidated by rationally attributing counter-evidence to external factors. For example, when another person is idealized, their less-than-perfect behavior is attributed to unfavorable external circumstances. However, sufficient counter-evidence can trigger switches of polarity, producing bistable dynamics. We show that the model can be fitted to empirical data, to measure individual susceptibility to relational instability. For example, we find that a latent categorical belief that others are "Good" accounts for less changeable, and more certain, character impressions of benevolent as opposed to malevolent others among healthy participants. By comparison, character impressions made by participants with borderline personality disorder reveal significantly higher and more symmetric splitting. The generative framework proposed invites applications for modeling oscillatory relational and affective dynamics in psychotherapeutic contexts. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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Affiliation(s)
| | | | - Michael Moutoussis
- Max Planck-University College London Centre for Computational Psychiatry and Ageing Research, University College London
| | | | - Tobias Nolte
- Wellcome Centre for Human Neuroimaging, University College London
| | - Edda Bilek
- Wellcome Centre for Human Neuroimaging, University College London
| | - Jenifer Z Siegel
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University
| | - Raymond J Dolan
- Max Planck-University College London Centre for Computational Psychiatry and Ageing Research, University College London
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2
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Zheng XY, Hebart MN, Grill F, Dolan RJ, Doeller CF, Cools R, Garvert MM. Parallel cognitive maps for multiple knowledge structures in the hippocampal formation. Cereb Cortex 2024; 34:bhad485. [PMID: 38204296 PMCID: PMC10839836 DOI: 10.1093/cercor/bhad485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 11/27/2023] [Accepted: 11/30/2023] [Indexed: 01/12/2024] Open
Abstract
The hippocampal-entorhinal system uses cognitive maps to represent spatial knowledge and other types of relational information. However, objects can often be characterized by different types of relations simultaneously. How does the hippocampal formation handle the embedding of stimuli in multiple relational structures that differ vastly in their mode and timescale of acquisition? Does the hippocampal formation integrate different stimulus dimensions into one conjunctive map or is each dimension represented in a parallel map? Here, we reanalyzed human functional magnetic resonance imaging data from Garvert et al. (2017) that had previously revealed a map in the hippocampal formation coding for a newly learnt transition structure. Using functional magnetic resonance imaging adaptation analysis, we found that the degree of representational similarity in the bilateral hippocampus also decreased as a function of the semantic distance between presented objects. Importantly, while both map-like structures localized to the hippocampal formation, the semantic map was located in more posterior regions of the hippocampal formation than the transition structure and thus anatomically distinct. This finding supports the idea that the hippocampal-entorhinal system forms parallel cognitive maps that reflect the embedding of objects in diverse relational structures.
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Affiliation(s)
- Xiaochen Y Zheng
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, 6525 EN, Nijmegen, the Netherlands
| | - Martin N Hebart
- Max-Planck-Institute for Human Cognitive and Brain Sciences, 04103, Leipzig, Germany
- Department of Medicine, Justus Liebig University, 35390, Giessen, Germany
| | - Filip Grill
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, 6525 EN, Nijmegen, the Netherlands
- Radboud University Medical Center, Department of Neurology, 6525 GA, Nijmegen, the Netherlands
| | - Raymond J Dolan
- Wellcome Centre for Human Neuroimaging, University College London, London WC1N 3AR, United Kingdom
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London WC1B 5EH, United Kingdom
| | - Christian F Doeller
- Max-Planck-Institute for Human Cognitive and Brain Sciences, 04103, Leipzig, Germany
- Kavli Institute for Systems Neuroscience, Centre for Neural Computation, The Egil and Pauline Braathen and Fred Kavli Centre for Cortical Microcircuits, Jebsen Centre for Alzheimer's Disease, NTNU, 7491, Trondheim, Norway
- Wilhelm Wundt Institute of Psychology, Leipzig University, 04109, Leipzig, Germany
| | - Roshan Cools
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, 6525 EN, Nijmegen, the Netherlands
- Radboud University Medical Center, Department of Psychiatry, 6525 GA, Nijmegen, the Netherlands
| | - Mona M Garvert
- Max-Planck-Institute for Human Cognitive and Brain Sciences, 04103, Leipzig, Germany
- Max Planck Research Group NeuroCode, Max Planck Institute for Human Development, 14195, Berlin, Germany
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany
- Faculty of Human Sciences, Julius-Maximilians-Universität Würzburg, Würzburg, Germany
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González-García N, Buimer EEL, Moreno-López L, Sallie SN, Váša F, Lim S, Romero-Garcia R, Scheuplein M, Whitaker KJ, Jones PB, Dolan RJ, Fonagy P, Goodyer I, Bullmore ET, van Harmelen AL. Resilient functioning is associated with altered structural brain network topology in adolescents exposed to childhood adversity. Dev Psychopathol 2023; 35:2253-2263. [PMID: 37493043 DOI: 10.1017/s0954579423000901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/27/2023]
Abstract
Childhood adversity is one of the strongest predictors of adolescent mental illness. Therefore, it is critical that the mechanisms that aid resilient functioning in individuals exposed to childhood adversity are better understood. Here, we examined whether resilient functioning was related to structural brain network topology. We quantified resilient functioning at the individual level as psychosocial functioning adjusted for the severity of childhood adversity in a large sample of adolescents (N = 2406, aged 14-24). Next, we examined nodal degree (the number of connections that brain regions have in a network) using brain-wide cortical thickness measures in a representative subset (N = 275) using a sliding window approach. We found that higher resilient functioning was associated with lower nodal degree of multiple regions including the dorsolateral prefrontal cortex, the medial prefrontal cortex, and the posterior superior temporal sulcus (z > 1.645). During adolescence, decreases in nodal degree are thought to reflect a normative developmental process that is part of the extensive remodeling of structural brain network topology. Prior findings in this sample showed that decreased nodal degree was associated with age, as such our findings of negative associations between nodal degree and resilient functioning may therefore potentially resemble a more mature structural network configuration in individuals with higher resilient functioning.
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Affiliation(s)
- Nadia González-García
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Laboratory of Neurosciences, Hospital Infantil de México Federico Gómez, México City, Mexico
| | - Elizabeth E L Buimer
- Institute of Education and Child Studies, Leiden University, Leiden, The Netherlands
| | | | | | - František Váša
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Sol Lim
- Public health and Primary Care, Cardiovascular Epidemiology Unit (CEU), University of Cambridge, Cambridge, UK
| | - Rafael Romero-Garcia
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Dpto. de Fisiología Médica y Biofísica. Instituto de Biomedicina de Sevilla (IBiS) HUVR/CSIC/Universidad de Sevilla, Sevilla, Spain
| | - Maximilian Scheuplein
- Institute of Education and Child Studies, Leiden University, Leiden, The Netherlands
| | | | - Peter B Jones
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Raymond J Dolan
- Wellcome Trust Center for Neuroimaging, University College London, London, UK
| | - Peter Fonagy
- Department of Clinical, Educational and Health Psychology, University College London, London, UK
| | - Ian Goodyer
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | | | - Anne-Laura van Harmelen
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Institute of Education and Child Studies, Leiden University, Leiden, The Netherlands
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Reiter AMF, Hula A, Vanes L, Hauser TU, Kokorikou D, Goodyer IM, Fonagy P, Moutoussis M, Dolan RJ. Self-reported childhood family adversity is linked to an attenuated gain of trust during adolescence. Nat Commun 2023; 14:6920. [PMID: 37903767 PMCID: PMC10616102 DOI: 10.1038/s41467-023-41531-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 09/07/2023] [Indexed: 11/01/2023] Open
Abstract
A longstanding proposal in developmental research is that childhood family experiences provide a template that shapes a capacity for trust-based social relationships. We leveraged longitudinal data from a cohort of healthy adolescents (n = 570, aged 14-25), which included decision-making and psychometric data, to characterise normative developmental trajectories of trust behaviour and inter-individual differences therein. Extending on previous cross-sectional findings from the same cohort, we show that a task-based measure of trust increases longitudinally from adolescence into young adulthood. Computational modelling suggests this is due to a decrease in social risk aversion. Self-reported family adversity attenuates this developmental gain in trust behaviour, and within our computational model, this relates to a higher 'irritability' parameter in those reporting greater adversity. Unconditional trust at measurement time point T1 predicts the longitudinal trajectory of self-reported peer relation quality, particularly so for those with higher family adversity, consistent with trust acting as a resilience factor.
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Affiliation(s)
- Andrea M F Reiter
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK.
- Wellcome Centre for Human Neuroimaging, University College London, London, UK.
- Department of Child and Adolescence Psychiatry, Psychosomatics and Psychotherapy, Centre of Mental Health, University Hospital Würzburg, Würzburg, Germany.
- Department of Psychology, Julius-Maximilians-Universität Würzburg, Würzburg, Germany.
- CRC Cognitive Control, Faculty of Psychology, Technische Universität Dresden, Dresden, Germany.
| | - Andreas Hula
- Austrian Institute of Technology, Vienna, Austria
| | - Lucy Vanes
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Tobias U Hauser
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
- Department of Psychiatry and Psychotherapy, Medical School and University Hospital, Eberhard Karls University of Tübingen, Tübingen, Germany
- German Center for Mental Health (DZPG), Tübingen, Germany
| | - Danae Kokorikou
- Department of Clinical, Educational and Health Psychology, University College London, London, UK
| | - Ian M Goodyer
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Peter Fonagy
- Department of Clinical, Educational and Health Psychology, University College London, London, UK
| | - Michael Moutoussis
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - Raymond J Dolan
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
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Nour MM, McNamee DC, Liu Y, Dolan RJ. Trajectories through semantic spaces in schizophrenia and the relationship to ripple bursts. Proc Natl Acad Sci U S A 2023; 120:e2305290120. [PMID: 37816054 PMCID: PMC10589662 DOI: 10.1073/pnas.2305290120] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 07/31/2023] [Indexed: 10/12/2023] Open
Abstract
Human cognition is underpinned by structured internal representations that encode relationships between entities in the world (cognitive maps). Clinical features of schizophrenia-from thought disorder to delusions-are proposed to reflect disorganization in such conceptual representations. Schizophrenia is also linked to abnormalities in neural processes that support cognitive map representations, including hippocampal replay and high-frequency ripple oscillations. Here, we report a computational assay of semantically guided conceptual sampling and exploit this to test a hypothesis that people with schizophrenia (PScz) exhibit abnormalities in semantically guided cognition that relate to hippocampal replay and ripples. Fifty-two participants [26 PScz (13 unmedicated) and 26 age-, gender-, and intelligence quotient (IQ)-matched nonclinical controls] completed a category- and letter-verbal fluency task, followed by a magnetoencephalography (MEG) scan involving a separate sequence-learning task. We used a pretrained word embedding model of semantic similarity, coupled to a computational model of word selection, to quantify the degree to which each participant's verbal behavior was guided by semantic similarity. Using MEG, we indexed neural replay and ripple power in a post-task rest session. Across all participants, word selection was strongly influenced by semantic similarity. The strength of this influence showed sensitivity to task demands (category > letter fluency) and predicted performance. In line with our hypothesis, the influence of semantic similarity on behavior was reduced in schizophrenia relative to controls, predicted negative psychotic symptoms, and correlated with an MEG signature of hippocampal ripple power (but not replay). The findings bridge a gap between phenomenological and neurocomputational accounts of schizophrenia.
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Affiliation(s)
- Matthew M. Nour
- Department of Psychiatry, University of Oxford, OxfordOX3 7JX, United Kingdom
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, LondonWC1B 5EH, United Kingdom
| | - Daniel C. McNamee
- Champalimaud Research, Centre for the Unknown, 1400-038Lisbon, Portugal
| | - Yunzhe Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing100875, China
- Chinese Institute for Brain Research, Beijing102206, China
| | - Raymond J. Dolan
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, LondonWC1B 5EH, United Kingdom
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing100875, China
- Wellcome Centre for Human Neuroimaging, University College London, LondonWC1N 3AR, United Kingdom
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6
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Fradkin I, Simpson HB, Dolan RJ, Huppert JD. How computational psychiatry can advance the understanding and treatment of obsessive-compulsive disorder. World Psychiatry 2023; 22:472-473. [PMID: 37713564 PMCID: PMC10503894 DOI: 10.1002/wps.21116] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/17/2023] Open
Affiliation(s)
- Isaac Fradkin
- London Centre for Computational Psychiatry and Ageing Research, Max Planck University College, London, UK
- Department of Psychology, Hebrew University, Jerusalem, Israel
| | - Helen Blair Simpson
- Department of Psychiatry, Columbia University, New York, NY, USA
- New York State Psychiatric Institute, New York, NY, USA
| | - Raymond J Dolan
- London Centre for Computational Psychiatry and Ageing Research, Max Planck University College, London, UK
- Wellcome Trust Centre for Human Neuroimaging, University College London, London, UK
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
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7
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Fradkin I, Nour MM, Dolan RJ. Theory-Driven Analysis of Natural Language Processing Measures of Thought Disorder Using Generative Language Modeling. Biol Psychiatry Cogn Neurosci Neuroimaging 2023; 8:1013-1023. [PMID: 37257754 DOI: 10.1016/j.bpsc.2023.05.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 05/19/2023] [Accepted: 05/19/2023] [Indexed: 06/02/2023]
Abstract
BACKGROUND Natural language processing (NLP) holds promise to transform psychiatric research and practice. A pertinent example is the success of NLP in the automatic detection of speech disorganization in formal thought disorder (FTD). However, we lack an understanding of precisely what common NLP metrics measure and how they relate to theoretical accounts of FTD. We propose tackling these questions by using deep generative language models to simulate FTD-like narratives by perturbing computational parameters instantiating theory-based mechanisms of FTD. METHODS We simulated FTD-like narratives using Generative-Pretrained-Transformer-2 by either increasing word selection stochasticity or limiting the model's memory span. We then examined the sensitivity of common NLP measures of derailment (semantic distance between consecutive words or sentences) and tangentiality (how quickly meaning drifts away from the topic) in detecting and dissociating the 2 underlying impairments. RESULTS Both parameters led to narratives characterized by greater semantic distance between consecutive sentences. Conversely, semantic distance between words was increased by increasing stochasticity, but decreased by limiting memory span. An NLP measure of tangentiality was uniquely predicted by limited memory span. The effects of limited memory span were nonmonotonic in that forgetting the global context resulted in sentences that were semantically closer to their local, intermediate context. Finally, different methods for encoding the meaning of sentences varied dramatically in performance. CONCLUSIONS This work validates a simulation-based approach as a valuable tool for hypothesis generation and mechanistic analysis of NLP markers in psychiatry. To facilitate dissemination of this approach, we accompany the paper with a hands-on Python tutorial.
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Affiliation(s)
- Isaac Fradkin
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London, United Kingdom.
| | - Matthew M Nour
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London, United Kingdom; Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Raymond J Dolan
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London, United Kingdom; Wellcome Trust Centre for Human Neuroimaging, University College London, London, United Kingdom; State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
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8
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Michely J, Martin IM, Dolan RJ, Hauser TU. Boosting Serotonin Increases Information Gathering by Reducing Subjective Cognitive Costs. J Neurosci 2023; 43:5848-5855. [PMID: 37524494 PMCID: PMC10423044 DOI: 10.1523/jneurosci.1416-22.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 06/01/2023] [Accepted: 06/06/2023] [Indexed: 08/02/2023] Open
Abstract
Serotonin is implicated in the valuation of aversive costs, such as delay or physical effort. However, its role in governing sensitivity to cognitive effort, for example, deliberation costs during information gathering, is unclear. We show that treatment with a serotonergic antidepressant in healthy human individuals of either sex enhances a willingness to gather information when trying to maximize reward. Using computational modeling, we show this arises from a diminished sensitivity to subjective deliberation costs during the sampling process. This result is consistent with the notion that serotonin alleviates sensitivity to aversive costs in a domain-general fashion, with implications for its potential contribution to a positive impact on motivational deficits in psychiatric disorders.SIGNIFICANCE STATEMENT Gathering information about the world is essential for successfully navigating it. However, sampling information is costly, and we need to balance between gathering too little and too much information. The neurocomputational mechanisms underlying this arbitration between a putative gain, such as reward, and the associated costs, such as allocation of cognitive resources, remain unclear. In this study, we show that week-long daily treatment with a serotonergic antidepressant enhances a willingness to gather information when trying to maximize reward. Computational modeling indicates this arises from a reduced perception of aversive costs, rendering information gathering less cognitively effortful. This finding points to a candidate mechanism by which serotonergic treatment might help alleviate motivational deficits in a range of mental illnesses.
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Affiliation(s)
- Jochen Michely
- Department of Psychiatry and Neurosciences, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, 10117 Germany
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, BIH Charité Clinician Scientist Program, Berlin, 10117 Germany
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, WC1B 5EH, United Kingdom
- Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, United Kingdom
| | - Ingrid M Martin
- Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, United Kingdom
- Institute of Cognitive Neuroscience, University College London, London, WC1N 3AZ, United Kingdom
| | - Raymond J Dolan
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, WC1B 5EH, United Kingdom
- Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, United Kingdom
| | - Tobias U Hauser
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, WC1B 5EH, United Kingdom
- Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, United Kingdom
- Department of Psychiatry and Psychotherapy, Medical School and University Hospital, Eberhard Karls University of Tübingen, 72076 Tübingen, Germany
- German Center for Mental Health (DZPG)
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McFadyen J, Dolan RJ. Spatiotemporal Precision of Neuroimaging in Psychiatry. Biol Psychiatry 2023; 93:671-680. [PMID: 36376110 DOI: 10.1016/j.biopsych.2022.08.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 07/20/2022] [Accepted: 08/12/2022] [Indexed: 12/23/2022]
Abstract
Aberrant patterns of cognition, perception, and behavior seen in psychiatric disorders are thought to be driven by a complex interplay of neural processes that evolve at a rapid temporal scale. Understanding these dynamic processes in vivo in humans has been hampered by a trade-off between spatial and temporal resolutions inherent to current neuroimaging technology. A recent trend in psychiatric research has been the use of high temporal resolution imaging, particularly magnetoencephalography, often in conjunction with sophisticated machine learning decoding techniques. Developments here promise novel insights into the spatiotemporal dynamics of cognitive phenomena, including domains relevant to psychiatric illnesses such as reward and avoidance learning, memory, and planning. This review considers recent advances afforded by exploiting this increased spatiotemporal precision, with specific reference to applications that seek to drive a mechanistic understanding of psychopathology and the realization of preclinical translation.
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Affiliation(s)
- Jessica McFadyen
- UCL Max Planck Centre for Computational Psychiatry and Ageing Research and Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom; State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
| | - Raymond J Dolan
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
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10
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Bedder RL, Vaghi MM, Dolan RJ, Rutledge RB. Risk taking for potential losses but not gains increases with time of day. Sci Rep 2023; 13:5534. [PMID: 37015952 PMCID: PMC10073197 DOI: 10.1038/s41598-023-31738-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Accepted: 03/16/2023] [Indexed: 04/06/2023] Open
Abstract
Humans exhibit distinct risk preferences when facing choices involving potential gains and losses. These preferences are believed to be subject to neuromodulatory influence, particularly from dopamine and serotonin. As neuromodulators manifest circadian rhythms, this suggests decision making under risk might be affected by time of day. Here, in a large subject sample collected using a smartphone application, we found that risky options with potential losses were increasingly chosen over the course of the day. We observed this result in both a within-subjects design (N = 2599) comparing risky options chosen earlier and later in the day in the same individuals, and in a between-subjects design (N = 26,720) showing our effect generalizes across ages and genders. Using computational modelling, we show this diurnal change in risk preference reflects a decrease in sensitivity to increasing losses, but no change was observed in the relative impacts of gains and losses on choice (i.e., loss aversion). Thus, our findings reveal a striking diurnal modulation in human decision making, a pattern with potential importance for real-life decisions that include voting, medical decisions, and financial investments.
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Affiliation(s)
- Rachel L. Bedder
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - Matilde M. Vaghi
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
- School of Psychology, University of East Anglia, Norwich, UK
| | - Raymond J. Dolan
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Robb B. Rutledge
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
- Department of Psychology, Yale University, New Haven, USA
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11
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McFadyen J, Liu Y, Dolan RJ. Differential replay of reward and punishment paths predicts approach and avoidance. Nat Neurosci 2023; 26:627-637. [PMID: 37020116 DOI: 10.1038/s41593-023-01287-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Accepted: 02/16/2023] [Indexed: 04/07/2023]
Abstract
Neural replay is implicated in planning, where states relevant to a task goal are rapidly reactivated in sequence. It remains unclear whether, during planning, replay relates to an actual prospective choice. Here, using magnetoencephalography (MEG), we studied replay in human participants while they planned to either approach or avoid an uncertain environment containing paths leading to reward or punishment. We find evidence for forward sequential replay during planning, with rapid state-to-state transitions from 20 to 90 ms. Replay of rewarding paths was boosted, relative to aversive paths, before a decision to avoid and attenuated before a decision to approach. A trial-by-trial bias toward replaying prospective punishing paths predicted irrational decisions to approach riskier environments, an effect more pronounced in participants with higher trait anxiety. The findings indicate a coupling of replay with planned behavior, where replay prioritizes an online representation of a worst-case scenario for approaching or avoiding.
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Affiliation(s)
- Jessica McFadyen
- The UCL Max Planck Centre for Computational Psychiatry and Ageing Research, University College London, London, UK.
- Wellcome Centre for Human Neuroimaging, University College London, London, UK.
| | - Yunzhe Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
| | - Raymond J Dolan
- The UCL Max Planck Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
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12
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Sharp PB, Dolan RJ, Eldar E. Disrupted state transition learning as a computational marker of compulsivity. Psychol Med 2023; 53:2095-2105. [PMID: 37310326 PMCID: PMC10106291 DOI: 10.1017/s0033291721003846] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Revised: 08/28/2021] [Accepted: 09/02/2021] [Indexed: 11/07/2022]
Abstract
BACKGROUND Disorders involving compulsivity, fear, and anxiety are linked to beliefs that the world is less predictable. We lack a mechanistic explanation for how such beliefs arise. Here, we test a hypothesis that in people with compulsivity, fear, and anxiety, learning a probabilistic mapping between actions and environmental states is compromised. METHODS In Study 1 (n = 174), we designed a novel online task that isolated state transition learning from other facets of learning and planning. To determine whether this impairment is due to learning that is too fast or too slow, we estimated state transition learning rates by fitting computational models to two independent datasets, which tested learning in environments in which state transitions were either stable (Study 2: n = 1413) or changing (Study 3: n = 192). RESULTS Study 1 established that individuals with higher levels of compulsivity are more likely to demonstrate an impairment in state transition learning. Preliminary evidence here linked this impairment to a common factor comprising compulsivity and fear. Studies 2 and 3 showed that compulsivity is associated with learning that is too fast when it should be slow (i.e. when state transition are stable) and too slow when it should be fast (i.e. when state transitions change). CONCLUSIONS Together, these findings indicate that compulsivity is associated with a dysregulation of state transition learning, wherein the rate of learning is not well adapted to the task environment. Thus, dysregulated state transition learning might provide a key target for therapeutic intervention in compulsivity.
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Affiliation(s)
- Paul B. Sharp
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
- The Hebrew University of Jerusalem, Jerusalem, IL, USA
| | - Raymond J. Dolan
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - Eran Eldar
- The Hebrew University of Jerusalem, Jerusalem, IL, USA
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13
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Wimmer GE, Liu Y, McNamee DC, Dolan RJ. Distinct replay signatures for prospective decision-making and memory preservation. Proc Natl Acad Sci U S A 2023; 120:e2205211120. [PMID: 36719914 PMCID: PMC9963918 DOI: 10.1073/pnas.2205211120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 12/05/2022] [Indexed: 02/01/2023] Open
Abstract
Theories of neural replay propose that it supports a range of functions, most prominently planning and memory consolidation. Here, we test the hypothesis that distinct signatures of replay in the same task are related to model-based decision-making ("planning") and memory preservation. We designed a reward learning task wherein participants utilized structure knowledge for model-based evaluation, while at the same time had to maintain knowledge of two independent and randomly alternating task environments. Using magnetoencephalography and multivariate analysis, we first identified temporally compressed sequential reactivation, or replay, both prior to choice and following reward feedback. Before choice, prospective replay strength was enhanced for the current task-relevant environment when a model-based planning strategy was beneficial. Following reward receipt, and consistent with a memory preservation role, replay for the alternative distal task environment was enhanced as a function of decreasing recency of experience with that environment. Critically, these planning and memory preservation relationships were selective to pre-choice and post-feedback periods, respectively. Our results provide support for key theoretical proposals regarding the functional role of replay and demonstrate that the relative strength of planning and memory-related signals are modulated by ongoing computational and task demands.
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Affiliation(s)
- G. Elliott Wimmer
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, LondonWC1B 5EH, UK
- Wellcome Centre for Human Neuroimaging, University College London, LondonWC1N 3BG, UK
| | - Yunzhe Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing100875, China
- Chinese Institute for Brain Research, Beijing100875, China
| | - Daniel C. McNamee
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, LondonWC1B 5EH, UK
- Wellcome Centre for Human Neuroimaging, University College London, LondonWC1N 3BG, UK
- Neuroscience Programme, Champalimaud Research, Lisbon1400-038, Portugal
| | - Raymond J. Dolan
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, LondonWC1B 5EH, UK
- Wellcome Centre for Human Neuroimaging, University College London, LondonWC1N 3BG, UK
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing100875, China
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14
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Nour MM, Liu Y, Higgins C, Woolrich MW, Dolan RJ. Reduced coupling between offline neural replay events and default mode network activation in schizophrenia. Brain Commun 2023; 5:fcad056. [PMID: 36950194 PMCID: PMC10026370 DOI: 10.1093/braincomms/fcad056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 11/11/2022] [Accepted: 03/01/2023] [Indexed: 03/06/2023] Open
Abstract
Schizophrenia is characterized by an abnormal resting state and default mode network brain activity. However, despite intense study, the mechanisms linking default mode network dynamics to neural computation remain elusive. During rest, sequential hippocampal reactivations, known as 'replay', are played out within default mode network activation windows, highlighting a potential role of replay-default mode network coupling in memory consolidation and model-based mental simulation. Here, we test a hypothesis of reduced replay-default mode network coupling in schizophrenia, using magnetoencephalography and a non-spatial sequence learning task designed to elicit off-task (i.e. resting state) neural replay. Participants with a diagnosis of schizophrenia (n = 28, mean age 28.2 years, range 20-40, 6 females, 13 not taking antipsychotic medication) and non-clinical control participants (n = 29, mean age 28.1 years, range 18-45, 6 females, matched at group level for age, intelligence quotient, gender, years in education and working memory) underwent a magnetoencephalography scan both during task completion and during a post-task resting state session. We used neural decoding to infer the time course of default mode network activation (time-delay embedding hidden Markov model) and spontaneous neural replay (temporally delayed linear modelling) in resting state magnetoencephalography data. Using multiple regression, we then quantified the extent to which default mode network activation was uniquely predicted by replay events that recapitulated the learned task sequences (i.e. 'task-relevant' replay-default mode network coupling). In control participants, replay-default mode network coupling was augmented following sequence learning, an augmentation that was specific for replay of task-relevant (i.e. learned) state transitions. This task-relevant replay-default mode network coupling effect was significantly reduced in schizophrenia (t(52) = 3.93, P = 0.018). Task-relevant replay-default mode network coupling predicted memory maintenance of learned sequences (ρ(52) = 0.31, P = 0.02). Importantly, reduced task-relevant replay-default mode network coupling in schizophrenia was not explained by differential replay or altered default mode network dynamics between groups nor by reference to antipsychotic exposure. Finally, task-relevant replay-default mode network coupling during rest correlated with stimulus-evoked default mode network modulation as measured in a separate task session. In the context of a proposed functional role of replay-default mode network coupling, our findings shed light on the functional significance of default mode network abnormalities in schizophrenia and provide for a consilience between task-based and resting state default mode network findings in this disorder.
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Affiliation(s)
- Matthew M Nour
- Correspondence to: Matthew M. Nour Department of Psychiatry, University of Oxford Warneford HospitalWarneford Ln, Headington Oxford OX3 7JX, UK E-mail:
| | - Yunzhe Liu
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London WC1B 5EH, UK
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
- Chinese Institute for Brain Research, Beijing 102206, China
| | - Cameron Higgins
- Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX9 9DU, UK
| | - Mark W Woolrich
- Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX9 9DU, UK
| | - Raymond J Dolan
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London WC1B 5EH, UK
- Wellcome Trust Centre for Human Neuroimaging, University College London, London WC1N 3AR, UK
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
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15
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Zech HG, Reichert M, Ebner-Priemer UW, Tost H, Rapp MA, Heinz A, Dolan RJ, Smolka MN, Deserno L. Mobile Data Collection of Cognitive-Behavioral Tasks in Substance Use Disorders: Where Are We Now? Neuropsychobiology 2022; 81:438-450. [PMID: 35350031 DOI: 10.1159/000523697] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Accepted: 02/11/2022] [Indexed: 11/19/2022]
Abstract
INTRODUCTION Over the last decades, our understanding of the cognitive, motivational, and neural processes involved in addictive behavior has increased enormously. A plethora of laboratory-based and cross-sectional studies has linked cognitive-behavioral measures to between-subject differences in drinking behavior. However, such laboratory-based studies inevitably suffer from small sample sizes and the inability to link temporal fluctuations in task measures to fluctuations in real-life substance use. To overcome these problems, several existing behavioral tasks have been transferred to smartphones to allow studying cognition in the field. METHOD In this narrative review, we first summarize studies that used existing behavioral tasks in the laboratory and self-reports of substance use with ecological momentary assessment (EMA) in the field. Next, we review studies on psychometric properties of smartphone-based behavioral tasks. Finally, we review studies that used both smartphone-based tasks and self-reports with EMA in the field. RESULTS Overall, studies were scarce and heterogenous both in tasks and in study outcomes. Nevertheless, existing findings are promising and point toward several methodological recommendations: concerning psychometrics, studies show that - although more systematic studies are necessary - task validity and reliability can be improved, for example, by analyzing several measurement sessions at once rather than analyzing sessions separately. Studies that use tasks in the field, moreover, show that power can be improved by choosing sampling schemes that combine time-based with event-based sampling, rather than relying on time-based sampling alone. Increasing sampling frequency can further increase power. However, as this also increases the burden to participants, more research is necessary to determine the ideal sampling frequency for each task. CONCLUSION Although more research is necessary to systematically study both the psychometrics of smartphone-based tasks and the frequency at which task measures fluctuate, existing studies are promising and reveal important methodological recommendations useful for researchers interested in implementing behavioral tasks in EMA studies.
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Affiliation(s)
- Hilmar G Zech
- Department of Psychiatry, Technische Universität Dresden, Dresden, Germany
| | - Markus Reichert
- Department of eHealth and Sports Analytics, Faculty of Sport Science, Ruhr-Universität Bochum (RUB), Bochum, Germany.,Institute of Sports and Sports Science, Karlsruhe Institute of Technology (KIT), Mental mHealth Lab, Karlsruhe, Germany.,Central Institute of Mental Health, Department of Psychiatry and Psychotherapy, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Ulrich W Ebner-Priemer
- Institute of Sports and Sports Science, Karlsruhe Institute of Technology (KIT), Mental mHealth Lab, Karlsruhe, Germany.,Central Institute of Mental Health, Department of Psychiatry and Psychotherapy, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Heike Tost
- Central Institute of Mental Health, Department of Psychiatry and Psychotherapy, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Michael A Rapp
- Department for Social and Preventive Medicine, University of Potsdam, Potsdam, Germany
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy, Charité Campus Mitte, Charité - Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Raymond J Dolan
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK.,Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - Michael N Smolka
- Department of Psychiatry, Technische Universität Dresden, Dresden, Germany
| | - Lorenz Deserno
- Department of Psychiatry, Technische Universität Dresden, Dresden, Germany.,Department of Child and Adolescent Psychiatry, Psychotherapy and Psychosomatics, University of Würzburg, Würzburg, Germany.,Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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16
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Sharp PB, Russek EM, Huys QJM, Dolan RJ, Eldar E. Correction: Humans perseverate on punishment avoidance goals in multigoal reinforcement learning. eLife 2022; 11:83998. [PMID: 36214798 PMCID: PMC9550222 DOI: 10.7554/elife.83998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
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17
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Wiedemann A, Stochl J, Neufeld SAS, Fritz J, Bhatti J, Hook RW, Goodyer IM, Dolan RJ, Bullmore ET, Chamberlain SR, Fonagy P, Perez J, Jones PB. The impact of the initial COVID-19 outbreak on young adults' mental health: a longitudinal study of risk and resilience factors. Sci Rep 2022; 12:16659. [PMID: 36198725 PMCID: PMC9533974 DOI: 10.1038/s41598-022-21053-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Accepted: 09/22/2022] [Indexed: 11/09/2022] Open
Abstract
Few studies assessing the effects of COVID-19 on mental health include prospective markers of risk and resilience necessary to understand and mitigate the combined impacts of the pandemic, lockdowns, and other societal responses. This population-based study of young adults includes individuals from the Neuroscience in Psychiatry Network (n = 2403) recruited from English primary care services and schools in 2012-2013 when aged 14-24. Participants were followed up three times thereafter, most recently during the initial outbreak of the COVID-19 outbreak when they were aged between 19 and 34. Repeated measures of psychological distress (K6) and mental wellbeing (SWEMWBS) were supplemented at the latest assessment by clinical measures of depression (PHQ-9) and anxiety (GAD-7). A total of 1000 participants, 42% of the original cohort, returned to take part in the COVID-19 follow-up; 737 completed all four assessments [mean age (SD), 25.6 (3.2) years; 65.4% female; 79.1% White]. Our findings show that the pandemic led to pronounced deviations from existing mental health-related trajectories compared to expected levels over approximately seven years. About three-in-ten young adults reported clinically significant depression (28.8%) or anxiety (27.6%) under current NHS guidelines; two-in-ten met clinical cut-offs for both. About 9% reported levels of psychological distress likely to be associated with serious functional impairments that substantially interfere with major life activities; an increase by 3% compared to pre-pandemic levels. Deviations from personal trajectories were not necessarily restricted to conventional risk factors; however, individuals with pre-existing health conditions suffered disproportionately during the initial outbreak of the COVID-19 pandemic. Resilience factors known to support mental health, particularly in response to adverse events, were at best mildly protective of individual psychological responses to the pandemic. Our findings underline the importance of monitoring the long-term effects of the ongoing pandemic on young adults' mental health, an age group at particular risk for the emergence of psychopathologies. Our findings further suggest that maintaining access to mental health care services during future waves, or potential new pandemics, is particularly crucial for those with pre-existing health conditions. Even though resilience factors known to support mental health were only mildly protective during the initial outbreak of the COVID-19 pandemic, it remains to be seen whether these factors facilitate mental health in the long term.
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Affiliation(s)
- Anna Wiedemann
- Department of Psychiatry, University of Cambridge, Douglas House, 18B Trumpington Road, Cambridge, CB2 8AH, UK. .,Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK. .,National Institute for Health Research, Applied Research Collaboration, East of England, Cambridge, UK.
| | - Jan Stochl
- Department of Psychiatry, University of Cambridge, Douglas House, 18B Trumpington Road, Cambridge, CB2 8AH, UK.,National Institute for Health Research, Applied Research Collaboration, East of England, Cambridge, UK.,Department of Kinanthropology and Humanities, Charles University, Prague, Czechia
| | - Sharon A S Neufeld
- Department of Psychiatry, University of Cambridge, Douglas House, 18B Trumpington Road, Cambridge, CB2 8AH, UK
| | - Jessica Fritz
- Department of Psychiatry, University of Cambridge, Douglas House, 18B Trumpington Road, Cambridge, CB2 8AH, UK.,Department of Clinical Psychology, Philipps University of Marburg, Marburg, Germany
| | - Junaid Bhatti
- Department of Psychiatry, University of Cambridge, Douglas House, 18B Trumpington Road, Cambridge, CB2 8AH, UK
| | - Roxanne W Hook
- Department of Psychiatry, University of Cambridge, Douglas House, 18B Trumpington Road, Cambridge, CB2 8AH, UK
| | | | - Ian M Goodyer
- Department of Psychiatry, University of Cambridge, Douglas House, 18B Trumpington Road, Cambridge, CB2 8AH, UK
| | - Raymond J Dolan
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, London, UK
| | - Edward T Bullmore
- Department of Psychiatry, University of Cambridge, Douglas House, 18B Trumpington Road, Cambridge, CB2 8AH, UK
| | - Samuel R Chamberlain
- Department of Psychiatry, Faculty of Medicine, University of Southampton, Southampton, UK.,Southern Health NHS Foundation Trust, Southampton, UK
| | - Peter Fonagy
- Research Department of Clinical, Educational and Health Psychology, University College London, London, UK
| | - Jesus Perez
- Department of Psychiatry, University of Cambridge, Douglas House, 18B Trumpington Road, Cambridge, CB2 8AH, UK.,Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK.,National Institute for Health Research, Applied Research Collaboration, East of England, Cambridge, UK.,Norwich Medical School, University of East Anglia, Norwich, UK.,Department of Medicine, Institute of Biomedical Research (IBSAL), University of Salamanca, Salamanca, Spain
| | - Peter B Jones
- Department of Psychiatry, University of Cambridge, Douglas House, 18B Trumpington Road, Cambridge, CB2 8AH, UK.,Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK.,National Institute for Health Research, Applied Research Collaboration, East of England, Cambridge, UK
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18
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Nour MM, Liu Y, Dolan RJ. Functional neuroimaging in psychiatry and the case for failing better. Neuron 2022; 110:2524-2544. [PMID: 35981525 DOI: 10.1016/j.neuron.2022.07.005] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Revised: 06/06/2022] [Accepted: 07/08/2022] [Indexed: 12/27/2022]
Abstract
Psychiatric disorders encompass complex aberrations of cognition and affect and are among the most debilitating and poorly understood of any medical condition. Current treatments rely primarily on interventions that target brain function (drugs) or learning processes (psychotherapy). A mechanistic understanding of how these interventions mediate their therapeutic effects remains elusive. From the early 1990s, non-invasive functional neuroimaging, coupled with parallel developments in the cognitive neurosciences, seemed to signal a new era of neurobiologically grounded diagnosis and treatment in psychiatry. Yet, despite three decades of intense neuroimaging research, we still lack a neurobiological account for any psychiatric condition. Likewise, functional neuroimaging plays no role in clinical decision making. Here, we offer a critical commentary on this impasse and suggest how the field might fare better and deliver impactful neurobiological insights.
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Affiliation(s)
- Matthew M Nour
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London WC1B 5EH, UK; Wellcome Trust Centre for Human Neuroimaging, University College London, London WC1N 3AR, UK; Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK.
| | - Yunzhe Liu
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London WC1B 5EH, UK; State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China; Chinese Institute for Brain Research, Beijing 102206, China
| | - Raymond J Dolan
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London WC1B 5EH, UK; Wellcome Trust Centre for Human Neuroimaging, University College London, London WC1N 3AR, UK; State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China.
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19
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Michely J, Eldar E, Erdman A, Martin IM, Dolan RJ. Serotonin modulates asymmetric learning from reward and punishment in healthy human volunteers. Commun Biol 2022; 5:812. [PMID: 35962142 PMCID: PMC9374781 DOI: 10.1038/s42003-022-03690-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Accepted: 07/08/2022] [Indexed: 11/15/2022] Open
Abstract
Instrumental learning is driven by a history of outcome success and failure. Here, we examined the impact of serotonin on learning from positive and negative outcomes. Healthy human volunteers were assessed twice, once after acute (single-dose), and once after prolonged (week-long) daily administration of the SSRI citalopram or placebo. Using computational modelling, we show that prolonged boosting of serotonin enhances learning from punishment and reduces learning from reward. This valence-dependent learning asymmetry increases subjects’ tendency to avoid actions as a function of cumulative failure without leading to detrimental, or advantageous, outcomes. By contrast, no significant modulation of learning was observed following acute SSRI administration. However, differences between the effects of acute and prolonged administration were not significant. Overall, these findings may help explain how serotonergic agents impact on mood disorders. Two factors can drive learning: punishment of failures and reward of successes. Serotonin induces a valence-dependent learning asymmetry, as revealed by prolonged administering of SSRIs to healthy participants in a gambling task.
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Affiliation(s)
- Jochen Michely
- Department of Psychiatry and Neurosciences, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany. .,Berlin Institute of Health at Charité - Universitätsmedizin Berlin, BIH Charité Clinician Scientist Program, Berlin, Germany. .,Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK. .,Wellcome Centre for Human Neuroimaging, University College London, London, UK.
| | - Eran Eldar
- Psychology and Cognitive Sciences Departments, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Alon Erdman
- Psychology and Cognitive Sciences Departments, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Ingrid M Martin
- Wellcome Centre for Human Neuroimaging, University College London, London, UK.,Institute of Cognitive Neuroscience, University College London, London, UK
| | - Raymond J Dolan
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK.,Wellcome Centre for Human Neuroimaging, University College London, London, UK
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20
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Rouault M, Will GJ, Fleming SM, Dolan RJ. Low self-esteem and the formation of global self-performance estimates in emerging adulthood. Transl Psychiatry 2022; 12:272. [PMID: 35821225 PMCID: PMC9276660 DOI: 10.1038/s41398-022-02031-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 06/15/2022] [Accepted: 06/17/2022] [Indexed: 12/02/2022] Open
Abstract
High self-esteem, an overall positive evaluation of self-worth, is a cornerstone of mental health. Previously we showed that people with low self-esteem differentially construct beliefs about momentary self-worth derived from social feedback. However, it remains unknown whether these anomalies extend to constructing beliefs about self-performance in a non-social context, in the absence of external feedback. Here, we examined this question using a novel behavioral paradigm probing subjects' self-performance estimates with or without external feedback. We analyzed data from young adults (N = 57) who were selected from a larger community sample (N = 2402) on the basis of occupying the bottom or top 10% of a reported self-esteem distribution. Participants performed a series of short blocks involving two perceptual decision-making tasks with varying degrees of difficulty, with or without feedback. At the end of each block, they had to decide on which task they thought they performed best, and gave subjective task ratings, providing two measures of self-performance estimates. We found no robust evidence of differences in objective performance between high and low self-esteem participants. Nevertheless, low self-esteem participants consistently underestimated their performance as expressed in lower subjective task ratings relative to high self-esteem participants. These results provide an initial window onto how cognitive processes underpinning the construction of self-performance estimates across different contexts map on to global dispositions relevant to mental health such as self-esteem.
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Affiliation(s)
- Marion Rouault
- Institut Jean Nicod, Département d'études cognitives, ENS, EHESS, CNRS, PSL University, 75005, Paris, France.
- Laboratoire de neurosciences cognitives et computationnelles, Département d'études cognitives, ENS, INSERM, PSL University, 75005, Paris, France.
| | - Geert-Jan Will
- Department of Clinical Psychology, Utrecht University, Utrecht, The Netherlands
| | - Stephen M Fleming
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
- Department of Experimental Psychology, University College London, 26 Bedford Way, London, WC1H 0AP, UK
| | - Raymond J Dolan
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
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21
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Sharp PB, Russek EM, Huys QJM, Dolan RJ, Eldar E. Humans perseverate on punishment avoidance goals in multigoal reinforcement learning. eLife 2022; 11:e74402. [PMID: 35199640 PMCID: PMC8912924 DOI: 10.7554/elife.74402] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2021] [Accepted: 02/21/2022] [Indexed: 11/20/2022] Open
Abstract
Managing multiple goals is essential to adaptation, yet we are only beginning to understand computations by which we navigate the resource demands entailed in so doing. Here, we sought to elucidate how humans balance reward seeking and punishment avoidance goals, and relate this to variation in its expression within anxious individuals. To do so, we developed a novel multigoal pursuit task that includes trial-specific instructed goals to either pursue reward (without risk of punishment) or avoid punishment (without the opportunity for reward). We constructed a computational model of multigoal pursuit to quantify the degree to which participants could disengage from the pursuit goals when instructed to, as well as devote less model-based resources toward goals that were less abundant. In general, participants (n = 192) were less flexible in avoiding punishment than in pursuing reward. Thus, when instructed to pursue reward, participants often persisted in avoiding features that had previously been associated with punishment, even though at decision time these features were unambiguously benign. In a similar vein, participants showed no significant downregulation of avoidance when punishment avoidance goals were less abundant in the task. Importantly, we show preliminary evidence that individuals with chronic worry may have difficulty disengaging from punishment avoidance when instructed to seek reward. Taken together, the findings demonstrate that people avoid punishment less flexibly than they pursue reward. Future studies should test in larger samples whether a difficulty to disengage from punishment avoidance contributes to chronic worry.
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Affiliation(s)
- Paul B Sharp
- The Hebrew University of JerusalemJerusalemIsrael
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College LondonLondonUnited Kingdom
- Wellcome Centre for Human Neuroimaging, University College LondonLondonUnited Kingdom
| | - Evan M Russek
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College LondonLondonUnited Kingdom
- Wellcome Centre for Human Neuroimaging, University College LondonLondonUnited Kingdom
| | - Quentin JM Huys
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College LondonLondonUnited Kingdom
- Division of Psychiatry, University College LondonLondonUnited Kingdom
| | - Raymond J Dolan
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College LondonLondonUnited Kingdom
- Wellcome Centre for Human Neuroimaging, University College LondonLondonUnited Kingdom
| | - Eran Eldar
- The Hebrew University of JerusalemJerusalemIsrael
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22
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Nour MM, Dolan RJ. Synaptic Gain Abnormalities in Schizophrenia and the Potential Relevance for Cognition. Biol Psychiatry 2022; 91:167-169. [PMID: 34916028 DOI: 10.1016/j.biopsych.2021.10.017] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Accepted: 10/21/2021] [Indexed: 12/23/2022]
Affiliation(s)
- Matthew M Nour
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom; Wellcome Trust Centre for Human Neuroimaging, University College London, London, United Kingdom.
| | - Raymond J Dolan
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom; Wellcome Trust Centre for Human Neuroimaging, University College London, London, United Kingdom; State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China; Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charité-Universitätsmedizin, Berlin, Germany.
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23
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Nour MM, Beck K, Liu Y, Arumuham A, Veronese M, Howes OD, Dolan RJ. Relationship Between Replay-Associated Ripples and Hippocampal N-Methyl-D-Aspartate Receptors: Preliminary Evidence From a PET-MEG Study in Schizophrenia. Schizophr Bull Open 2022; 3:sgac044. [PMID: 35911846 PMCID: PMC9334566 DOI: 10.1093/schizbullopen/sgac044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Background and Hypotheses Hippocampal replay and associated high-frequency ripple oscillations are among the best-characterized phenomena in resting brain activity. Replay/ripples support memory consolidation and relational inference, and are regulated by N-methyl-D-aspartate receptors (NMDARs). Schizophrenia has been associated with both replay/ripple abnormalities and NMDAR hypofunction in both clinical samples and genetic mouse models, although the relationship between these 2 facets of hippocampal function has not been tested in humans. Study Design Here, we avail of a unique multimodal human neuroimaging data set to investigate the relationship between the availability of (intrachannel) NMDAR binding sites in hippocampus, and replay-associated ripple power, in 16 participants (7 nonclinical participants and 9 people with a diagnosis of schizophrenia, PScz). Each participant had both a [18F]GE-179 positron emission tomography (PET) scan (to measure NMDAR availability, V T ) and a magnetoencephalography (MEG) scan (to measure offline neural replay and associated high-frequency ripple oscillations, using Temporally Delayed Linear Modeling). Study Results We show a positive relationship between hippocampal NMDAR availability and replay-associated ripple power. This linkage was evident across control participants (r(5) = .94, P = .002) and PScz (r(7) = .70, P = .04), with no group difference. Conclusions Our findings provide preliminary evidence for a relationship between hippocampal NMDAR availability and replay-associated ripple power in humans, and haverelevance for NMDAR hypofunction theories of schizophrenia.
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Affiliation(s)
- Matthew M Nour
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London WC1B 5EH, UK
| | - Katherine Beck
- Department of Psychosis Studies, Institute of Psychiatry Psychology and Neuroscience, King's College London, London SE5 8AF, UK
| | - Yunzhe Liu
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London WC1B 5EH, UK
| | - Atheeshaan Arumuham
- Department of Psychosis Studies, Institute of Psychiatry Psychology and Neuroscience, King's College London, London SE5 8AF, UK
| | - Mattia Veronese
- Department of Psychosis Studies, Institute of Psychiatry Psychology and Neuroscience, King's College London, London SE5 8AF, UK
| | - Oliver D Howes
- Department of Psychosis Studies, Institute of Psychiatry Psychology and Neuroscience, King's College London, London SE5 8AF, UK
| | - Raymond J Dolan
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London WC1B 5EH, UK
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24
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Deserno L, Moran R, Michely J, Lee Y, Dayan P, Dolan RJ. Dopamine enhances model-free credit assignment through boosting of retrospective model-based inference. eLife 2021; 10:e67778. [PMID: 34882092 PMCID: PMC8758138 DOI: 10.7554/elife.67778] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Accepted: 12/08/2021] [Indexed: 11/13/2022] Open
Abstract
Dopamine is implicated in representing model-free (MF) reward prediction errors a as well as influencing model-based (MB) credit assignment and choice. Putative cooperative interactions between MB and MF systems include a guidance of MF credit assignment by MB inference. Here, we used a double-blind, placebo-controlled, within-subjects design to test an hypothesis that enhancing dopamine levels boosts the guidance of MF credit assignment by MB inference. In line with this, we found that levodopa enhanced guidance of MF credit assignment by MB inference, without impacting MF and MB influences directly. This drug effect correlated negatively with a dopamine-dependent change in purely MB credit assignment, possibly reflecting a trade-off between these two MB components of behavioural control. Our findings of a dopamine boost in MB inference guidance of MF learning highlight a novel DA influence on MB-MF cooperative interactions.
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Affiliation(s)
- Lorenz Deserno
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College LondonLondonUnited Kingdom
- The Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College LondonLondonUnited Kingdom
- Department of Child and Adolescent Psychiatry, Psychotherapy and Psychosomatics, University of WürzburgWürzburgGermany
- Department of Psychiatry and Psychotherapy, Technische Universität DresdenDresdenGermany
| | - Rani Moran
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College LondonLondonUnited Kingdom
- The Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College LondonLondonUnited Kingdom
| | - Jochen Michely
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College LondonLondonUnited Kingdom
- The Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College LondonLondonUnited Kingdom
- Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin BerlinBerlinGermany
| | - Ying Lee
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College LondonLondonUnited Kingdom
- The Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College LondonLondonUnited Kingdom
- Department of Psychiatry and Psychotherapy, Technische Universität DresdenDresdenGermany
| | - Peter Dayan
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College LondonLondonUnited Kingdom
- Max Planck Institute for Biological CyberneticsTübingenGermany
- University of TübingenTübingenGermany
| | - Raymond J Dolan
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College LondonLondonUnited Kingdom
- The Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College LondonLondonUnited Kingdom
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25
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Shahar N, Hauser TU, Moran R, Moutoussis M, Bullmore ET, Dolan RJ. Correction: Assigning the right credit to the wrong action: compulsivity in the general population is associated with augmented outcome-irrelevant value-based learning. Transl Psychiatry 2021; 11:610. [PMID: 34857737 PMCID: PMC8640043 DOI: 10.1038/s41398-021-01734-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/01/2022] Open
Affiliation(s)
- Nitzan Shahar
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London, WC1B 5EH, UK. .,Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK. .,Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel. .,Psychology Department, Tel Aviv University, Tel Aviv, Israel.
| | - Tobias U. Hauser
- grid.83440.3b0000000121901201Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London, WC1B 5EH UK ,grid.83440.3b0000000121901201Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG UK
| | - Rani Moran
- grid.83440.3b0000000121901201Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London, WC1B 5EH UK ,grid.83440.3b0000000121901201Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG UK
| | - Michael Moutoussis
- grid.83440.3b0000000121901201Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London, WC1B 5EH UK ,grid.83440.3b0000000121901201Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG UK
| | | | - Edward T. Bullmore
- grid.5335.00000000121885934Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Raymond J. Dolan
- grid.83440.3b0000000121901201Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London, WC1B 5EH UK ,grid.83440.3b0000000121901201Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG UK
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26
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Shahar N, Hauser TU, Moran R, Moutoussis M, Bullmore ET, Dolan RJ. Assigning the right credit to the wrong action: compulsivity in the general population is associated with augmented outcome-irrelevant value-based learning. Transl Psychiatry 2021; 11:564. [PMID: 34741013 PMCID: PMC8571313 DOI: 10.1038/s41398-021-01642-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Revised: 09/01/2021] [Accepted: 09/21/2021] [Indexed: 11/08/2022] Open
Abstract
Compulsive behavior is enacted under a belief that a specific act controls the likelihood of an undesired future event. Compulsive behaviors are widespread in the general population despite having no causal relationship with events they aspire to influence. In the current study, we tested whether there is an increased tendency to assign value to aspects of a task that do not predict an outcome (i.e., outcome-irrelevant learning) among individuals with compulsive tendencies. We studied 514 healthy individuals who completed self-report compulsivity, anxiety, depression, and schizotypal measurements, and a well-established reinforcement-learning task (i.e., the two-step task). As expected, we found a positive relationship between compulsivity and outcome-irrelevant learning. Specifically, individuals who reported having stronger compulsive tendencies (e.g., washing, checking, grooming) also tended to assign value to response keys and stimuli locations that did not predict an outcome. Controlling for overall goal-directed abilities and the co-occurrence of anxious, depressive, or schizotypal tendencies did not impact these associations. These findings indicate that outcome-irrelevant learning processes may contribute to the expression of compulsivity in a general population setting. We highlight the need for future research on the formation of non-veridical action-outcome associations as a factor related to the occurrence and maintenance of compulsive behavior.
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Affiliation(s)
- Nitzan Shahar
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London, WC1B 5EH, UK.
- Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK.
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.
- Psychology Department, Tel Aviv University, Tel Aviv, Israel.
| | - Tobias U Hauser
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London, WC1B 5EH, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK
| | - Rani Moran
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London, WC1B 5EH, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK
| | - Michael Moutoussis
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London, WC1B 5EH, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK
| | | | - Raymond J Dolan
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London, WC1B 5EH, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK
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27
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Story GW, Chowdhury R, Kurth-Nelson Z, Crockett M, Vlaev I, Darzi A, Dolan RJ. Dreading the pain of others? Altruistic responses to others' pain underestimate dread. J Exp Anal Behav 2021; 116:359-378. [PMID: 34643955 DOI: 10.1002/jeab.721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 09/03/2021] [Accepted: 09/22/2021] [Indexed: 11/08/2022]
Abstract
A dislike of waiting for pain, aptly termed 'dread', is so great that people will increase pain to avoid delaying it. However, despite many accounts of altruistic responses to pain in others, no previous studies have tested whether people take delay into account when attempting to ameliorate others' pain. We examined the impact of delay in 2 experiments where participants (total N = 130) specified the intensity and delay of pain either for themselves or another person. Participants were willing to increase the experimental pain of another participant to avoid delaying it, indicative of dread, though did so to a lesser extent than was the case for their own pain. We observed a similar attenuation in dread when participants chose the timing of a hypothetical painful medical treatment for a close friend or relative, but no such attenuation when participants chose for a more distant acquaintance. A model in which altruism is biased to privilege pain intensity over the dread of pain parsimoniously accounts for these findings. We refer to this underestimation of others' dread as a 'Dread Empathy Gap'.
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Affiliation(s)
- Giles W Story
- Max Planck UCL Centre for Computational Psychiatry and Ageing, London, UK.,Centre for Health Policy, Institute of Global Health Innovation, Imperial College London, UK.,Wellcome Centre for Human Neuroimaging, London, UK
| | | | - Zeb Kurth-Nelson
- Max Planck UCL Centre for Computational Psychiatry and Ageing, London, UK.,DeepMind, London, UK
| | | | - Ivo Vlaev
- Warwick Business School, The University of Warwick, Coventry, UK
| | - Ara Darzi
- Centre for Health Policy, Institute of Global Health Innovation, Imperial College London, UK
| | - Raymond J Dolan
- Max Planck UCL Centre for Computational Psychiatry and Ageing, London, UK
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28
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Hula A, Moutoussis M, Will GJ, Kokorikou D, Reiter AM, Ziegler G, Bullmore ED, Jones PB, Goodyer I, Fonagy P, Montague PR, Dolan RJ. Multi-Round Trust Game Quantifies Inter-Individual Differences in Social Exchange from Adolescence to Adulthood. Comput Psychiatr 2021; 5:102-118. [PMID: 35656356 PMCID: PMC7612797 DOI: 10.5334/cpsy.65] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Investing in strangers in a socio-economic exchange is risky, as we may be uncertain whether they will reciprocate. Nevertheless, the potential rewards for cooperating can be great. Here, we used a cross sectional sample (n = 784) to study how the challenges of cooperation versus defection are negotiated across an important period of the lifespan: from adolescence to young adulthood (ages 14 to 25). We quantified social behaviour using a multi round investor-trustee task, phenotyping individuals using a validated model whose parameters characterise patterns of real exchange and constitute latent social characteristics. We found highly significant differences in investment behaviour according to age, sex, socio-economic status and IQ. Consistent with the literature, we showed an overall trend towards higher trust from adolescence to young adulthood but, in a novel finding, we characterized key cognitive mechanisms explaining this, especially regarding socio-economic risk aversion. Males showed lower risk-aversion, associated with greater investments. We also found that inequality aversion was higher in females and, in a novel relation, that socio-economic deprivation was associated with more risk averse play.
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Affiliation(s)
- Andreas Hula
- Austrian Insitute of Technology, Vienna, Austria
| | - Michael Moutoussis
- Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom
| | - Geert-Jan Will
- Institute of Psychology, Leiden University, Leiden, the Netherlands
| | | | - Andrea M Reiter
- Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom; Lifespan Developmental Neuroscience, Faculty of Psychology, Technische Universität Dresden, Germany; Department of Neurology, Max-Planck-Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Gabriel Ziegler
- Centre for Cognitive Neurology and Dementia Research, Magdeburg, Germany; German Center for Neurodegenerative Diseases, Magdeburg, Germany
| | - E D Bullmore
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom; Cambridgeshire and Peterborough National Health Service Foundation Trust, Cambridge, United Kingdom; Medical Research Council/Wellcome Trust Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, United Kingdom; Max Planck University College London Centre for Computational Psychiatry, London, United Kingdom
| | - Peter B Jones
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom; Cambridgeshire and Peterborough National Health Service Foundation Trust, Cambridge, United Kingdom
| | - Ian Goodyer
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom; Cambridgeshire and Peterborough National Health Service Foundation Trust, Cambridge, United Kingdom
| | - Peter Fonagy
- Anna Freud Centre, London, United Kingdom; Research Department of Clinical, Educational and Health Psychology, University College London, United Kingdom
| | - P Read Montague
- Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom; Human Neuroimaging Laboratory, Virginia Tech Carilion Research Institute, Roanoke, Virginia, United States of America; Department of Physics, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, United States of America
| | - Raymond J Dolan
- Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom; Max Planck University College London Centre for Computational Psychiatry, London, United Kingdom
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29
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Liu S, Müller S, Dolan RJ, Zhao X, Zheng JC, Heinz A. Opportunities, risks and challenges in global mental health and population neuroscience: a case of Sino-German cooperation. Eur Arch Psychiatry Clin Neurosci 2021; 271:1027-1034. [PMID: 32729097 PMCID: PMC8354880 DOI: 10.1007/s00406-020-01176-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Accepted: 07/22/2020] [Indexed: 01/10/2023]
Abstract
Large scale prospective cohorts have now been established across several countries, and continents, and among the aims include an assessment of the developmental trajectory of mental disorders. This level of international cooperation helps transfer research findings to new social contexts as well as enabling an assessment of which findings can be replicated, and which interventions are most effective, in different social and cultural settings. However, data sharing across different regional and national health care systems requires a careful consideration of different standards in ethical research, data protection and patient care, including respect for patients' rights, in cooperating jurisdictions. In our review, we discuss ethical, legal and practical challenges associated with such cooperation with a focus on research participants, specifically patient recruitment, by considering the instance of China and Germany. Our broader aim is to promote international cooperation by identifying key challenges that arise in international cooperation, and to facilitate an exchange in relation to legal and practical approaches.
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Affiliation(s)
- Shuyan Liu
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin (Campus Charité Mitte), Berlin, Germany.
| | - Sabine Müller
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin (Campus Charité Mitte), Berlin, Germany
| | - Raymond J Dolan
- Max Planck Centre for Computational Psychiatry and Ageing Research & Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - Xudong Zhao
- Pudong Mental Health Centre, Tongji University School of Medicine, Shanghai, China
| | - Jialin C Zheng
- Center for Translational Neurodegeneration and Regenerative Therapy, Shanghai Tenth People's Hospital affiliated to Tongji University School of Medicine, Shanghai, China
- Collaborative Innovation Center for Brain Science, Tongji University, Shanghai, China
- Department of Pharmacology and Experimental Neuroscience, University of Nebraska Medical Center, Omaha, USA
- Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, USA
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin (Campus Charité Mitte), Berlin, Germany
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30
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Affiliation(s)
- Shuyan Liu
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin (Campus Charité Mitte), Berlin, Germany
| | - Stephan Heinzel
- 2Clinical Psychology and Psychotherapy, Department of Education and Psychology, Freie Universität Berlin, Berlin, Germany
| | - Raymond J Dolan
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin (Campus Charité Mitte), Berlin, Germany.,Max Planck Centre for Computational Psychiatry and Ageing Research & Wellcome Centre for Human Neuroimaging, University College London, London, England.,State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
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31
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Nour MM, Liu Y, Arumuham A, Kurth-Nelson Z, Dolan RJ. Impaired neural replay of inferred relationships in schizophrenia. Cell 2021; 184:4315-4328.e17. [PMID: 34197734 PMCID: PMC8357425 DOI: 10.1016/j.cell.2021.06.012] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 04/09/2021] [Accepted: 06/10/2021] [Indexed: 12/19/2022]
Abstract
An ability to build structured mental maps of the world underpins our capacity to imagine relationships between objects that extend beyond experience. In rodents, such representations are supported by sequential place cell reactivations during rest, known as replay. Schizophrenia is proposed to reflect a compromise in structured mental representations, with animal models reporting abnormalities in hippocampal replay and associated ripple activity during rest. Here, utilizing magnetoencephalography (MEG), we tasked patients with schizophrenia and control participants to infer unobserved relationships between objects by reorganizing visual experiences containing these objects. During a post-task rest session, controls exhibited fast spontaneous neural reactivation of presented objects that replayed inferred relationships. Replay was coincident with increased ripple power in hippocampus. Patients showed both reduced replay and augmented ripple power relative to controls, convergent with findings in animal models. These abnormalities are linked to impairments in behavioral acquisition and subsequent neural representation of task structure.
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Affiliation(s)
- Matthew M Nour
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London WC1B 5EH, UK; Wellcome Centre for Human Neuroimaging (WCHN), University College London, London WC1N 3AR, UK; Department of Psychosis Studies, Institute of Psychiatry Psychology and Neuroscience, King's College London, London SE5 8AF, UK.
| | - Yunzhe Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China; Chinese Institute for Brain Research, Beijing 102206, China
| | - Atheeshaan Arumuham
- Department of Psychosis Studies, Institute of Psychiatry Psychology and Neuroscience, King's College London, London SE5 8AF, UK
| | - Zeb Kurth-Nelson
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London WC1B 5EH, UK; Deepmind, London NC1 4AG, UK
| | - Raymond J Dolan
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London WC1B 5EH, UK; Wellcome Centre for Human Neuroimaging (WCHN), University College London, London WC1N 3AR, UK; State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China; BIH Visiting Professor, Stiftung Charité, Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charité - Universitätsmedizin, Berlin, Germany
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32
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Moran R, Dayan P, Dolan RJ. Efficiency and prioritization of inference-based credit assignment. Curr Biol 2021; 31:2747-2756.e6. [PMID: 33887181 PMCID: PMC8279739 DOI: 10.1016/j.cub.2021.03.091] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 02/11/2021] [Accepted: 03/29/2021] [Indexed: 11/16/2022]
Abstract
Organisms adapt to their environments by learning to approach states that predict rewards and avoid states associated with punishments. Knowledge about the affective value of states often relies on credit assignment (CA), whereby state values are updated on the basis of reward feedback. Remarkably, humans assign credit to states that are not observed but are instead inferred based on a cognitive map that represents structural knowledge of an environment. A pertinent example is authors attempting to infer the identity of anonymous reviewers to assign them credit or blame and, on this basis, inform future referee recommendations. Although inference is cognitively costly, it is unknown how it influences CA or how it is apportioned between hidden and observable states (for example, both anonymous and revealed reviewers). We addressed these questions in a task that provided choices between lotteries where each led to a unique pair of occasionally rewarding outcome states. On some trials, both states were observable (rendering inference nugatory), whereas on others, the identity of one of the states was concealed. Importantly, by exploiting knowledge of choice-state associations, subjects could infer the identity of this hidden state. We show that having to perform inference reduces state-value updates. Strikingly, and in violation of normative theories, this reduction in CA was selective for the observed outcome alone. These findings have implications for the operation of putative cognitive maps.
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Affiliation(s)
- Rani Moran
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, 10-12 Russell Square, London WC1B 5EH, UK; Wellcome Centre for Human Neuroimaging, University College London, London WC1N 3BG, UK.
| | - Peter Dayan
- Max Planck Institute for Biological Cybernetics, Max Planck-Ring 8, 72076 Tübingen, Germany; University of Tübingen, 72074 Tübingen, Germany
| | - Raymond J Dolan
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, 10-12 Russell Square, London WC1B 5EH, UK; Wellcome Centre for Human Neuroimaging, University College London, London WC1N 3BG, UK
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33
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Atiya NAA, Huys QJM, Dolan RJ, Fleming SM. Explaining distortions in metacognition with an attractor network model of decision uncertainty. PLoS Comput Biol 2021; 17:e1009201. [PMID: 34310613 PMCID: PMC8341696 DOI: 10.1371/journal.pcbi.1009201] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Revised: 08/05/2021] [Accepted: 06/18/2021] [Indexed: 11/21/2022] Open
Abstract
Metacognition is the ability to reflect on, and evaluate, our cognition and behaviour. Distortions in metacognition are common in mental health disorders, though the neural underpinnings of such dysfunction are unknown. One reason for this is that models of key components of metacognition, such as decision confidence, are generally specified at an algorithmic or process level. While such models can be used to relate brain function to psychopathology, they are difficult to map to a neurobiological mechanism. Here, we develop a biologically-plausible model of decision uncertainty in an attempt to bridge this gap. We first relate the model's uncertainty in perceptual decisions to standard metrics of metacognition, namely mean confidence level (bias) and the accuracy of metacognitive judgments (sensitivity). We show that dissociable shifts in metacognition are associated with isolated disturbances at higher-order levels of a circuit associated with self-monitoring, akin to neuropsychological findings that highlight the detrimental effect of prefrontal brain lesions on metacognitive performance. Notably, we are able to account for empirical confidence judgements by fitting the parameters of our biophysical model to first-order performance data, specifically choice and response times. Lastly, in a reanalysis of existing data we show that self-reported mental health symptoms relate to disturbances in an uncertainty-monitoring component of the network. By bridging a gap between a biologically-plausible model of confidence formation and observed disturbances of metacognition in mental health disorders we provide a first step towards mapping theoretical constructs of metacognition onto dynamical models of decision uncertainty. In doing so, we provide a computational framework for modelling metacognitive performance in settings where access to explicit confidence reports is not possible.
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Affiliation(s)
- Nadim A. A. Atiya
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom
| | - Quentin J. M. Huys
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom
- Division of Psychiatry, University College London, London, United Kingdom
| | - Raymond J. Dolan
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom
| | - Stephen M. Fleming
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom
- Department of Experimental Psychology, University College London, London, United Kingdom
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Wise T, Liu Y, Chowdhury F, Dolan RJ. Model-based aversive learning in humans is supported by preferential task state reactivation. Sci Adv 2021; 7:eabf9616. [PMID: 34321205 PMCID: PMC8318377 DOI: 10.1126/sciadv.abf9616] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 06/10/2021] [Indexed: 06/13/2023]
Abstract
Harm avoidance is critical for survival, yet little is known regarding the neural mechanisms supporting avoidance in the absence of trial-and-error experience. Flexible avoidance may be supported by a mental model (i.e., model-based), a process for which neural reactivation and sequential replay have emerged as candidate mechanisms. During an aversive learning task, combined with magnetoencephalography, we show prospective and retrospective reactivation during planning and learning, respectively, coupled to evidence for sequential replay. Specifically, when individuals plan in an aversive context, we find preferential reactivation of subsequently chosen goal states. Stronger reactivation is associated with greater hippocampal theta power. At outcome receipt, unchosen goal states are reactivated regardless of outcome valence. Replay of paths leading to goal states was modulated by outcome valence, with aversive outcomes associated with stronger reverse replay than safe outcomes. Our findings are suggestive of avoidance involving simulation of unexperienced states through hippocampally mediated reactivation and replay.
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Affiliation(s)
- Toby Wise
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK.
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
- Division of the Humanities and Social Sciences, California Institute of Technology, Pasadena, CA, USA
| | - Yunzhe Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
| | - Fatima Chowdhury
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, London, UK
| | - Raymond J Dolan
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
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Moutoussis M, Garzón B, Neufeld S, Bach DR, Rigoli F, Goodyer I, Bullmore E, Guitart-Masip M, Dolan RJ. Decision-making ability, psychopathology, and brain connectivity. Neuron 2021; 109:2025-2040.e7. [PMID: 34019810 PMCID: PMC8221811 DOI: 10.1016/j.neuron.2021.04.019] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2020] [Revised: 02/16/2021] [Accepted: 04/19/2021] [Indexed: 12/11/2022]
Abstract
Decision-making is a cognitive process of central importance for the quality of our lives. Here, we ask whether a common factor underpins our diverse decision-making abilities. We obtained 32 decision-making measures from 830 young people and identified a common factor that we call "decision acuity," which was distinct from IQ and reflected a generic decision-making ability. Decision acuity was decreased in those with aberrant thinking and low general social functioning. Crucially, decision acuity and IQ had dissociable brain signatures, in terms of their associated neural networks of resting-state functional connectivity. Decision acuity was reliably measured, and its relationship with functional connectivity was also stable when measured in the same individuals 18 months later. Thus, our behavioral and brain data identify a new cognitive construct that underpins decision-making ability across multiple domains. This construct may be important for understanding mental health, particularly regarding poor social function and aberrant thought patterns.
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Affiliation(s)
- Michael Moutoussis
- Wellcome Centre for Human Neuroimaging, University College London, London WC1N 3BG, UK; Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London WC1B 5EH, UK.
| | - Benjamín Garzón
- Aging Research Centre, Karolinska Institute, Stockholm, Sweden
| | - Sharon Neufeld
- Department of Psychiatry, University of Cambridge, Cambridge CB2 0SZ, UK
| | - Dominik R Bach
- Wellcome Centre for Human Neuroimaging, University College London, London WC1N 3BG, UK; Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London WC1B 5EH, UK; Computational Psychiatry Research, Department of Psychiatry, Psychotherapy, and Psychosomatics, Psychiatric Hospital, University of Zurich, 8032 Zurich, Switzerland
| | | | - Ian Goodyer
- Department of Psychiatry, University of Cambridge, Cambridge CB2 0SZ, UK
| | - Edward Bullmore
- Department of Psychiatry, University of Cambridge, Cambridge CB2 0SZ, UK
| | - Marc Guitart-Masip
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London WC1B 5EH, UK; Aging Research Centre, Karolinska Institute, Stockholm, Sweden
| | - Raymond J Dolan
- Wellcome Centre for Human Neuroimaging, University College London, London WC1N 3BG, UK; Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London WC1B 5EH, UK
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Liu Y, Dolan RJ, Higgins C, Penagos H, Woolrich MW, Ólafsdóttir HF, Barry C, Kurth-Nelson Z, Behrens TE. Temporally delayed linear modelling (TDLM) measures replay in both animals and humans. eLife 2021; 10:e66917. [PMID: 34096501 PMCID: PMC8318595 DOI: 10.7554/elife.66917] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Accepted: 06/06/2021] [Indexed: 12/25/2022] Open
Abstract
There are rich structures in off-task neural activity which are hypothesized to reflect fundamental computations across a broad spectrum of cognitive functions. Here, we develop an analysis toolkit - temporal delayed linear modelling (TDLM) - for analysing such activity. TDLM is a domain-general method for finding neural sequences that respect a pre-specified transition graph. It combines nonlinear classification and linear temporal modelling to test for statistical regularities in sequences of task-related reactivations. TDLM is developed on the non-invasive neuroimaging data and is designed to take care of confounds and maximize sequence detection ability. Notably, as a linear framework, TDLM can be easily extended, without loss of generality, to capture rodent replay in electrophysiology, including in continuous spaces, as well as addressing second-order inference questions, for example, its temporal and spatial varying pattern. We hope TDLM will advance a deeper understanding of neural computation and promote a richer convergence between animal and human neuroscience.
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Affiliation(s)
- Yunzhe Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal UniversityBeijingChina
- Chinese Institute for Brain ResearchBeijingChina
- Max Planck University College London Centre for Computational Psychiatry and Ageing ResearchLondonUnited Kingdom
| | - Raymond J Dolan
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal UniversityBeijingChina
- Max Planck University College London Centre for Computational Psychiatry and Ageing ResearchLondonUnited Kingdom
- Wellcome Centre for Human Neuroimaging, University College LondonLondonUnited Kingdom
| | - Cameron Higgins
- Wellcome Centre for Integrative Neuroimaging, University of OxfordOxfordUnited Kingdom
| | - Hector Penagos
- Center for Brains, Minds and Machines, Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Mark W Woolrich
- Wellcome Centre for Integrative Neuroimaging, University of OxfordOxfordUnited Kingdom
| | - H Freyja Ólafsdóttir
- Donders Institute for Brain Cognition and Behaviour, Radboud UniversityNijmegenNetherlands
| | - Caswell Barry
- Research Department of Cell and Developmental Biology, University College LondonLondonUnited Kingdom
| | - Zeb Kurth-Nelson
- Max Planck University College London Centre for Computational Psychiatry and Ageing ResearchLondonUnited Kingdom
- DeepMindLondonUnited Kingdom
| | - Timothy E Behrens
- Wellcome Centre for Human Neuroimaging, University College LondonLondonUnited Kingdom
- Wellcome Centre for Integrative Neuroimaging, University of OxfordOxfordUnited Kingdom
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37
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Liu Y, Mattar MG, Behrens TEJ, Daw ND, Dolan RJ. Experience replay is associated with efficient nonlocal learning. Science 2021; 372:372/6544/eabf1357. [PMID: 34016753 DOI: 10.1126/science.abf1357] [Citation(s) in RCA: 48] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Accepted: 04/15/2021] [Indexed: 01/08/2023]
Abstract
To make effective decisions, people need to consider the relationship between actions and outcomes. These are often separated by time and space. The neural mechanisms by which disjoint actions and outcomes are linked remain unknown. One promising hypothesis involves neural replay of nonlocal experience. Using a task that segregates direct from indirect value learning, combined with magnetoencephalography, we examined the role of neural replay in human nonlocal learning. After receipt of a reward, we found significant backward replay of nonlocal experience, with a 160-millisecond state-to-state time lag, which was linked to efficient learning of action values. Backward replay and behavioral evidence of nonlocal learning were more pronounced for experiences of greater benefit for future behavior. These findings support nonlocal replay as a neural mechanism for solving complex credit assignment problems during learning.
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Affiliation(s)
- Yunzhe Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China. .,Chinese Institute for Brain Research, Beijing, China.,Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, UK.,Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - Marcelo G Mattar
- Department of Cognitive Science, University of California, San Diego, CA, USA.
| | - Timothy E J Behrens
- Wellcome Centre for Human Neuroimaging, University College London, London, UK. .,Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Nathaniel D Daw
- Princeton Neuroscience Institute and Department of Psychology, Princeton University, Princeton, NJ, USA.
| | - Raymond J Dolan
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China. .,Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, UK.,Wellcome Centre for Human Neuroimaging, University College London, London, UK.,Department of Psychiatry, Universitätsmedizin Berlin (Campus Charité Mitte), Berlin, Germany
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38
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Vanes LD, Dolan RJ. Transdiagnostic neuroimaging markers of psychiatric risk: A narrative review. Neuroimage Clin 2021; 30:102634. [PMID: 33780864 PMCID: PMC8022867 DOI: 10.1016/j.nicl.2021.102634] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Revised: 03/03/2021] [Accepted: 03/12/2021] [Indexed: 02/07/2023]
Abstract
We review the literature on neural correlates of a general psychopathology factor General psychopathology relates to structural and functional neurodevelopment Disrupted network connectivity maturation may underlie psychiatric vulnerability
Several decades of neuroimaging research in psychiatry have shed light on structural and functional neural abnormalities associated with individual psychiatric disorders. However, there is increasing evidence for substantial overlap in the patterns of neural dysfunction seen across disorders, suggesting that risk for psychiatric illness may be shared across diagnostic boundaries. Gaining insights on the existence of shared neural mechanisms which may transdiagnostically underlie psychopathology is important for psychiatric research in order to tease apart the unique and common aspects of different disorders, but also clinically, so as to help identify individuals early on who may be biologically vulnerable to psychiatric disorder in general. In this narrative review, we first evaluate recent studies investigating the functional and structural neural correlates of a general psychopathology factor, which is thought to reflect the shared variance across common mental health symptoms and therefore index psychiatric vulnerability. We then link insights from this research to existing meta-analytic evidence for shared patterns of neural dysfunction across categorical psychiatric disorders. We conclude by providing an integrative account of vulnerability to mental illness, whereby delayed or disrupted maturation of large-scale networks (particularly default-mode, executive, and sensorimotor networks), and more generally between-network connectivity, results in a compromised ability to integrate and switch between internally and externally focused tasks.
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Affiliation(s)
- Lucy D Vanes
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, King's College London, United Kingdom.
| | - Raymond J Dolan
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom
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39
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Abstract
Action is invigorated in the presence of reward-predicting stimuli and inhibited in the presence of punishment-predicting stimuli. Although valuable as a heuristic, this Pavlovian bias can also lead to maladaptive behaviour and is implicated in addiction. Here we explore whether Pavlovian bias can be overcome through training. Across five experiments, we find that Pavlovian bias is resistant to unlearning under most task configurations. However, we demonstrate that when subjects engage in instrumental learning in a verbal semantic space, as opposed to a motoric space, not only do they exhibit the typical Pavlovian bias, but this Pavlovian bias diminishes with training. Our results suggest that learning within the semantic space is necessary, but not sufficient, for subjects to unlearn their Pavlovian bias, and that other task features, such as gamification and spaced stimulus presentation may also be necessary. In summary, we show that Pavlovian bias, whilst robust, is susceptible to change with experience, but only under specific environmental conditions.
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Affiliation(s)
- Sam Ereira
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, UCL, London, WC1B 5EH, UK.
- Wellcome Centre for Human Neuroimaging, UCL, London, WC1N 3BG, UK.
| | - Marine Pujol
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, UCL, London, WC1B 5EH, UK
- Sorbonne Université, Paris, France
| | - Marc Guitart-Masip
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, UCL, London, WC1B 5EH, UK
- Aging Research Centre, Karolinska Institute, 171 65, Stockholm, Sweden
| | - Raymond J Dolan
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, UCL, London, WC1B 5EH, UK
- Wellcome Centre for Human Neuroimaging, UCL, London, WC1N 3BG, UK
| | - Zeb Kurth-Nelson
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, UCL, London, WC1B 5EH, UK
- DeepMind, London, N1C 4AG, UK
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Moran R, Keramati M, Dolan RJ. Model based planners reflect on their model-free propensities. PLoS Comput Biol 2021; 17:e1008552. [PMID: 33411724 PMCID: PMC7817042 DOI: 10.1371/journal.pcbi.1008552] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Revised: 01/20/2021] [Accepted: 11/23/2020] [Indexed: 12/19/2022] Open
Abstract
Dual-reinforcement learning theory proposes behaviour is under the tutelage of a retrospective, value-caching, model-free (MF) system and a prospective-planning, model-based (MB), system. This architecture raises a question as to the degree to which, when devising a plan, a MB controller takes account of influences from its MF counterpart. We present evidence that such a sophisticated self-reflective MB planner incorporates an anticipation of the influences its own MF-proclivities exerts on the execution of its planned future actions. Using a novel bandit task, wherein subjects were periodically allowed to design their environment, we show that reward-assignments were constructed in a manner consistent with a MB system taking account of its MF propensities. Thus, in the task participants assigned higher rewards to bandits that were momentarily associated with stronger MF tendencies. Our findings have implications for a range of decision making domains that includes drug abuse, pre-commitment, and the tension between short and long-term decision horizons in economics.
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Affiliation(s)
- Rani Moran
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom
| | - Mehdi Keramati
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom
- Department of Psychology, City, University of London, London, United Kingdom
| | - Raymond J. Dolan
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom
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Abstract
When knowledge is scarce, it is adaptive to seek further information to resolve uncertainty and obtain a more accurate worldview. Biases in such information-seeking behavior can contribute to the maintenance of inaccurate views. Here, we investigate whether predispositions for uncertainty-guided information seeking relate to individual differences in dogmatism, a phenomenon linked to entrenched beliefs in political, scientific, and religious discourse. We addressed this question in a perceptual decision-making task, allowing us to rule out motivational factors and isolate the role of uncertainty. In two independent general population samples (n = 370 and n = 364), we show that more dogmatic participants are less likely to seek out new information to refine an initial perceptual decision, leading to a reduction in overall belief accuracy despite similar initial decision performance. Trial-by-trial modeling revealed that dogmatic participants placed less reliance on internal signals of uncertainty (confidence) to guide information search, rendering them less likely to seek additional information to update beliefs derived from weak or uncertain initial evidence. Together, our results highlight a cognitive mechanism that may contribute to the formation of dogmatic worldviews.
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Affiliation(s)
- Lion Schulz
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London WC1N 3BG, United Kingdom;
- Department of Experimental Psychology, University College London, London WC1H 0AP, United Kingdom
- Department of Computational Neuroscience, Max Planck Institute for Biological Cybernetics, 72076 Tübingen, Germany
| | - Max Rollwage
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London WC1N 3BG, United Kingdom
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, Institute of Neurology, University College London, London WC1B 5EH, United Kingdom
| | - Raymond J Dolan
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London WC1N 3BG, United Kingdom
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, Institute of Neurology, University College London, London WC1B 5EH, United Kingdom
| | - Stephen M Fleming
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London WC1N 3BG, United Kingdom;
- Department of Experimental Psychology, University College London, London WC1H 0AP, United Kingdom
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, Institute of Neurology, University College London, London WC1B 5EH, United Kingdom
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Affiliation(s)
- Shuyan Liu
- Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin (Campus Charité Mitte), Berlin, Germany
| | - Raymond J Dolan
- Max Planck Centre for Computational Psychiatry and Ageing Research & Wellcome Centre for Human Neuroimaging, University College London, London, England
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin (Campus Charité Mitte), Berlin, Germany
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Vaghi MM, Moutoussis M, Váša F, Kievit RA, Hauser TU, Vértes PE, Shahar N, Romero-Garcia R, Kitzbichler MG, Bullmore ET, Dolan RJ. Compulsivity is linked to reduced adolescent development of goal-directed control and frontostriatal functional connectivity. Proc Natl Acad Sci U S A 2020; 117:25911-25922. [PMID: 32989168 PMCID: PMC7568330 DOI: 10.1073/pnas.1922273117] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
A characteristic of adaptive behavior is its goal-directed nature. An ability to act in a goal-directed manner is progressively refined during development, but this refinement can be impacted by the emergence of psychiatric disorders. Disorders of compulsivity have been framed computationally as a deficit in model-based control, and have been linked also to abnormal frontostriatal connectivity. However, the developmental trajectory of model-based control, including an interplay between its maturation and an emergence of compulsivity, has not been characterized. Availing of a large sample of healthy adolescents (n = 569) aged 14 to 24 y, we show behaviorally that over the course of adolescence there is a within-person increase in model-based control, and this is more pronounced in younger participants. Using a bivariate latent change score model, we provide evidence that the presence of higher compulsivity traits is associated with an atypical profile of this developmental maturation in model-based control. Resting-state fMRI data from a subset of the behaviorally assessed subjects (n = 230) revealed that compulsivity is associated with a less pronounced change of within-subject developmental remodeling of functional connectivity, specifically between the striatum and a frontoparietal network. Thus, in an otherwise clinically healthy population sample, in early development, individual differences in compulsivity are linked to the developmental trajectory of model-based control and a remodeling of frontostriatal connectivity.
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Affiliation(s)
- Matilde M Vaghi
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, WC1 B5EH London, United Kingdom;
- Wellcome Centre for Human Neuroimaging, University College London, WC1N 3AR London, United Kingdom
| | - Michael Moutoussis
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, WC1 B5EH London, United Kingdom
- Wellcome Centre for Human Neuroimaging, University College London, WC1N 3AR London, United Kingdom
| | - František Váša
- Department of Psychiatry, University of Cambridge, CB2 2QQ Cambridge, United Kingdom
- Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, SE5 8AF London, United Kingdom
| | - Rogier A Kievit
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, WC1 B5EH London, United Kingdom
- Medical Research Council Cognition and Brain Sciences Unit, Cambridge, CB2 7EF Cambridge, United Kingdom
| | - Tobias U Hauser
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, WC1 B5EH London, United Kingdom
- Wellcome Centre for Human Neuroimaging, University College London, WC1N 3AR London, United Kingdom
| | - Petra E Vértes
- Department of Psychiatry, University of Cambridge, CB2 2QQ Cambridge, United Kingdom
- The Alan Turing Institute, NW1 2DB London, United Kingdom
- School of Mathematical Sciences, Queen Mary University of London, E1 4NS London, United Kingdom
| | - Nitzan Shahar
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, WC1 B5EH London, United Kingdom
- Wellcome Centre for Human Neuroimaging, University College London, WC1N 3AR London, United Kingdom
| | - Rafael Romero-Garcia
- Department of Psychiatry, University of Cambridge, CB2 2QQ Cambridge, United Kingdom
| | - Manfred G Kitzbichler
- Department of Psychiatry, University of Cambridge, CB2 2QQ Cambridge, United Kingdom
| | - Edward T Bullmore
- Department of Psychiatry, University of Cambridge, CB2 2QQ Cambridge, United Kingdom
| | - Raymond J Dolan
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, WC1 B5EH London, United Kingdom
- Wellcome Centre for Human Neuroimaging, University College London, WC1N 3AR London, United Kingdom
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44
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Story GW, Kurth-Nelson Z, Crockett M, Vlaev I, Darzi A, Dolan RJ. Social discounting of pain. J Exp Anal Behav 2020; 114:308-325. [PMID: 33026113 PMCID: PMC8436752 DOI: 10.1002/jeab.631] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Revised: 08/19/2020] [Accepted: 09/04/2020] [Indexed: 12/28/2022]
Abstract
Impatience can be formalized as a delay discount rate, describing how the subjective value of reward decreases as it is delayed. By analogy, selfishness can be formalized as a social discount rate, representing how the subjective value of rewarding another person decreases with increasing social distance. Delay and social discount rates for reward are correlated across individuals. However no previous work has examined whether this relationship also holds for aversive outcomes. Neither has previous work described a functional form for social discounting of pain in humans. This is a pertinent question, since preferences over aversive outcomes formally diverge from those for reward. We addressed this issue in an experiment in which healthy adult participants (N = 67) chose the timing and intensity of hypothetical pain for themselves and others. In keeping with previous studies, participants showed a strong preference for immediate over delayed pain. Participants showed greater concern for pain in close others than for their own pain, though this hyperaltruism was steeply discounted with increasing social distance. Impatience for pain and social discounting of pain were weakly correlated across individuals. Our results extend a link between impatience and selfishness to the aversive domain.
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Affiliation(s)
- Giles W Story
- Max Planck UCL Centre for Computational Psychiatry and Ageing, London, UK.,Centre for Health Policy, Institute of Global Health Innovation, Imperial College London, UK.,Wellcome Centre for Human Neuroimaging, University College London, UK
| | - Zeb Kurth-Nelson
- Max Planck UCL Centre for Computational Psychiatry and Ageing, London, UK.,DeepMind, London, UK
| | | | - Ivo Vlaev
- Warwick Business School, The University of Warwick, Coventry, UK
| | - Ara Darzi
- Centre for Health Policy, Institute of Global Health Innovation, Imperial College London, UK
| | - Raymond J Dolan
- Max Planck UCL Centre for Computational Psychiatry and Ageing, London, UK
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45
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Abstract
BACKGROUND A dominant methodology in contemporary clinical neuroscience is the use of dimensional self-report questionnaires to measure features such as psychological traits (e.g., trait anxiety) and states (e.g., depressed mood). These dimensions are then mapped to biological measures and computational parameters. Researchers pursuing this approach tend to equate a symptom inventory score (plus noise) with some latent psychological trait. MAIN TEXT We argue this approach implies weak, tacit, models of traits that provide fixed predictions of individual symptoms, and thus cannot account for symptom trajectories within individuals. This problem persists because (1) researchers are not familiarized with formal models that relate internal traits to within-subject symptom variation and (2) rely on an assumption that trait self-report inventories accurately indicate latent traits. To address these concerns, we offer a computational model of trait depression that demonstrates how parameters instantiating a given trait remain stable while manifest symptom expression varies predictably. We simulate patterns of mood variation from both the computational model and the standard self-report model and describe how to quantify the relative validity of each model using a Bayesian procedure. CONCLUSIONS Ultimately, we would urge a tempering of a reliance on self-report inventories and recommend a shift towards developing mechanistic trait models that can explain within-subject symptom dynamics.
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Affiliation(s)
- Paul B Sharp
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK.
- Wellcome Centre for Human Neuroimaging, University College London, London, UK.
| | - Gregory A Miller
- University of California, Los Angeles, USA
- University of Illinois at Urbana-Champaign, Champaign, USA
| | - Raymond J Dolan
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - Eran Eldar
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
- The Hebrew University of Jerusalem, Jerusalem, IL, Israel
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46
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Wise T, Dolan RJ. Associations between aversive learning processes and transdiagnostic psychiatric symptoms in a general population sample. Nat Commun 2020; 11:4179. [PMID: 32826918 PMCID: PMC7443146 DOI: 10.1038/s41467-020-17977-w] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Accepted: 07/13/2020] [Indexed: 11/09/2022] Open
Abstract
Symptom expression in psychiatric conditions is often linked to altered threat perception, however how computational mechanisms that support aversive learning relate to specific psychiatric symptoms remains undetermined. We answer this question using an online game-based aversive learning task together with measures of common psychiatric symptoms in 400 subjects. We show that physiological symptoms of anxiety and a transdiagnostic compulsivity-related factor are associated with enhanced safety learning, as measured using a probabilistic computational model, while trait cognitive anxiety symptoms are associated with enhanced learning from danger. We use data-driven partial least squares regression to identify two separable components across behavioural and questionnaire data: one linking enhanced safety learning and lower estimated uncertainty to physiological anxiety, compulsivity, and impulsivity; the other linking enhanced threat learning and heightened uncertainty estimation to symptoms of depression and social anxiety. Our findings implicate aversive learning processes in the expression of psychiatric symptoms that transcend diagnostic boundaries.
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Affiliation(s)
- Toby Wise
- Wellcome Centre for Human Neuroimaging, University College London, London, UK.
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK.
- Division of the Humanities and Social Sciences, California Institute of Technology, Pasadena, CA, USA.
| | - Raymond J Dolan
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
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47
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Romero-Garcia R, Seidlitz J, Whitaker KJ, Morgan SE, Fonagy P, Dolan RJ, Jones PB, Goodyer IM, Suckling J, Vértes PE, Bullmore ET. Schizotypy-Related Magnetization of Cortex in Healthy Adolescence Is Colocated With Expression of Schizophrenia-Related Genes. Biol Psychiatry 2020; 88:248-259. [PMID: 32029217 PMCID: PMC7369635 DOI: 10.1016/j.biopsych.2019.12.005] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/09/2019] [Revised: 11/21/2019] [Accepted: 12/03/2019] [Indexed: 12/03/2022]
Abstract
BACKGROUND Genetic risk is thought to drive clinical variation on a spectrum of schizophrenia-like traits, but the underlying changes in brain structure that mechanistically link genomic variation to schizotypal experience and behavior are unclear. METHODS We assessed schizotypy using a self-reported questionnaire and measured magnetization transfer as a putative microstructural magnetic resonance imaging marker of intracortical myelination in 68 brain regions in 248 healthy young people (14-25 years of age). We used normative adult brain gene expression data and partial least squares analysis to find the weighted gene expression pattern that was most colocated with the cortical map of schizotypy-related magnetization. RESULTS Magnetization was significantly correlated with schizotypy in the bilateral posterior cingulate cortex and precuneus (and for disorganized schizotypy, also in medial prefrontal cortex; all false discovery rate-corrected ps < .05), which are regions of the default mode network specialized for social and memory functions. The genes most positively weighted on the whole-genome expression map colocated with schizotypy-related magnetization were enriched for genes that were significantly downregulated in two prior case-control histological studies of brain gene expression in schizophrenia. Conversely, the most negatively weighted genes were enriched for genes that were transcriptionally upregulated in schizophrenia. Positively weighted (downregulated) genes were enriched for neuronal, specifically interneuronal, affiliations and coded a network of proteins comprising a few highly interactive "hubs" such as parvalbumin and calmodulin. CONCLUSIONS Microstructural magnetic resonance imaging maps of intracortical magnetization can be linked to both the behavioral traits of schizotypy and prior histological data on dysregulated gene expression in schizophrenia.
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Affiliation(s)
| | - Jakob Seidlitz
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Kirstie J Whitaker
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom; Alan Turing Institute, London, United Kingdom
| | - Sarah E Morgan
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Peter Fonagy
- Research Department of Clinical, Educational and Health Psychology, London, United Kingdom
| | - Raymond J Dolan
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom; Wellcome Trust Centre for Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Peter B Jones
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom; Cambridgeshire and Peterborough NHS Foundation Trust, Huntingdon, United Kingdom
| | - Ian M Goodyer
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom; Cambridgeshire and Peterborough NHS Foundation Trust, Huntingdon, United Kingdom
| | - John Suckling
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Petra E Vértes
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom; Alan Turing Institute, London, United Kingdom; School of Mathematical Sciences, Queen Mary University of London, London, United Kingdom
| | - Edward T Bullmore
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom; Cambridgeshire and Peterborough NHS Foundation Trust, Huntingdon, United Kingdom
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48
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Michely J, Viswanathan S, Hauser TU, Delker L, Dolan RJ, Grefkes C. The role of dopamine in dynamic effort-reward integration. Neuropsychopharmacology 2020; 45:1448-1453. [PMID: 32268344 PMCID: PMC7360543 DOI: 10.1038/s41386-020-0669-0] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Revised: 02/16/2020] [Accepted: 03/20/2020] [Indexed: 01/08/2023]
Abstract
When deciding to act, the neurotransmitter dopamine is implicated in a valuation of prospective effort and reward. However, its role in dynamic effort-reward integration during action, a process central to everyday behaviour, remains unclear. In a placebo-controlled, within-subject, study, we probed the impact of increasing brain dopamine levels (150 mg of levodopa) and blocking dopamine receptors (1.5 mg of haloperidol) in the context of a novel dynamic effort task in healthy human subjects. We show that modulating homoeostatic dopamine balance distinctly alters implicit and explicit effort allocation as a function of instantaneous reward. Pharmacologically boosting dopamine enhanced motor vigour, reflected in an implicit increase in effort allocation for high rewards. Conversely, pharmacological blockade of dopamine attenuated sensitivity to differences in reward context, reflected in reduced strategic effort discounting. These findings implicate dopamine in an integration of momentary physical experience and instantaneous reward, suggesting a key role of dopamine in acting to maximise reward on the fly.
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Affiliation(s)
- Jochen Michely
- 0000000121901201grid.83440.3bWellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG UK ,0000000121901201grid.83440.3bMax Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, WC1B 5EH UK ,0000 0000 8852 305Xgrid.411097.aMedical Faculty, University of Cologne and Department of Neurology, University Hospital Cologne, 50937 Cologne, Germany
| | - Shivakumar Viswanathan
- 0000 0001 2297 375Xgrid.8385.6Cognitive Neuroscience, Institute of Neuroscience & Medicine (INM-3), Research Centre Juelich, 52425 Juelich, Germany
| | - Tobias U. Hauser
- 0000000121901201grid.83440.3bWellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG UK ,0000000121901201grid.83440.3bMax Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, WC1B 5EH UK
| | - Laura Delker
- 0000 0000 8852 305Xgrid.411097.aMedical Faculty, University of Cologne and Department of Neurology, University Hospital Cologne, 50937 Cologne, Germany
| | - Raymond J. Dolan
- 0000000121901201grid.83440.3bWellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG UK ,0000000121901201grid.83440.3bMax Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, WC1B 5EH UK
| | - Christian Grefkes
- Medical Faculty, University of Cologne and Department of Neurology, University Hospital Cologne, 50937, Cologne, Germany. .,Cognitive Neuroscience, Institute of Neuroscience & Medicine (INM-3), Research Centre Juelich, 52425, Juelich, Germany.
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49
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Wimmer GE, Liu Y, Vehar N, Behrens TEJ, Dolan RJ. Episodic memory retrieval success is associated with rapid replay of episode content. Nat Neurosci 2020; 23:1025-1033. [PMID: 32514135 PMCID: PMC7610376 DOI: 10.1038/s41593-020-0649-z] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2019] [Accepted: 04/28/2020] [Indexed: 12/18/2022]
Abstract
Retrieval of everyday experiences is fundamental for informing our future decisions. The fine-grained neurophysiological mechanisms that support such memory retrieval are largely unknown. We studied participants who first experienced, without repetition, unique multicomponent 40-80-s episodes. One day later, they engaged in cued retrieval of these episodes while undergoing magnetoencephalography. By decoding individual episode elements, we found that trial-by-trial successful retrieval was supported by the sequential replay of episode elements, with a temporal compression factor of >60. The direction of replay supporting retrieval, either backward or forward, depended on whether the task goal was to retrieve elements of an episode that followed or preceded, respectively, a retrieval cue. This sequential replay was weaker in very-high-performing participants, in whom instead we found evidence for simultaneous clustered reactivation. Our results demonstrate that memory-mediated decisions are supported by a rapid replay mechanism that can flexibly shift in direction in response to task goals.
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Affiliation(s)
- G Elliott Wimmer
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, UK.
- Wellcome Centre for Human Neuroimaging, University College London, London, UK.
| | - Yunzhe Liu
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - Neža Vehar
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - Timothy E J Behrens
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional Magnetic Resonance Imaging of the Brain, University of Oxford, Oxford, UK
| | - Raymond J Dolan
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
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50
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Abstract
During adolescence and early adulthood, learning when to avoid threats and when to pursue rewards becomes crucial. Using a risky foraging task, we investigated individual differences in this dynamic across 781 individuals aged 14-24 years who were split into a hypothesis-generating discovery sample and a hold-out confirmation sample. Sex was the most important predictor of cautious behaviour and performance. Males earned one standard deviation (or 20%) more reward than females, collected more reward when there was little to lose and reduced foraging to the same level as females when potential losses became high. Other independent predictors of cautiousness and performance were self-reported daringness, IQ and self-reported cognitive complexity. We found no evidence for an impact of age or maturation. Thus, maleness, a high IQ or self-reported cognitive complexity, and self-reported daringness predicted greater success in risky foraging, possibly due to better exploitation of low-risk opportunities in high-risk environments.
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Affiliation(s)
- Dominik R Bach
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK.
- Wellcome Centre for Human Neuroimaging, University College London, London, UK.
- Computational Psychiatry Research, Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Zurich, Switzerland.
| | - Michael Moutoussis
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - Aislinn Bowler
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - Raymond J Dolan
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
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