1
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Powers A, Angelos PA, Bond A, Farina E, Fredericks C, Gandhi J, Greenwald M, Hernandez-Busot G, Hosein G, Kelley M, Mourgues C, Palmer W, Rodriguez-Sanchez J, Seabury R, Toribio S, Vin R, Weleff J, Woods S, Benrimoh D. A computational account of the development and evolution of psychotic symptoms. Biol Psychiatry 2024:S0006-3223(24)01584-1. [PMID: 39260466 DOI: 10.1016/j.biopsych.2024.08.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/10/2024] [Revised: 08/08/2024] [Accepted: 08/13/2024] [Indexed: 09/13/2024]
Abstract
The mechanisms of psychotic symptoms like hallucinations and delusions are often investigated in fully-formed illness, well after symptoms emerge. These investigations have yielded key insights, but are not well-positioned to reveal the dynamic forces underlying symptom formation itself. Understanding symptom development over time would allow us to identify steps in the pathophysiological process leading to psychosis, shifting the focus of psychiatric intervention from symptom alleviation to prevention. We propose a model for understanding the emergence of psychotic symptoms within the context of an adaptive, developing neural system. We will make the case for a pathophysiological process that begins with cortical hyperexcitability and bottom-up noise transmission, which engenders inappropriate belief formation via aberrant prediction error signaling. We will argue that this bottom-up noise drives learning about the (im)precision of new incoming sensory information because of diminished signal-to-noise ratio, causing a compensatory relative over-reliance on prior beliefs. This over-reliance on priors predisposes to hallucinations and covaries with hallucination severity. An over-reliance on priors may also lead to increased conviction in the beliefs generated by bottom-up noise and drive movement toward conversion to psychosis. We will identify predictions of our model at each stage, examine evidence to support or refute those predictions, and propose experiments that could falsify or help select between alternative elements of the overall model. Nesting computational abnormalities within longitudinal development allows us to account for hidden dynamics among the mechanisms driving symptom formation and to view established symptomatology as a point of equilibrium among competing biological forces.
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Affiliation(s)
- Albert Powers
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA.
| | - P A Angelos
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Alexandria Bond
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Emily Farina
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Carolyn Fredericks
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Jay Gandhi
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Maximillian Greenwald
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | | | - Gabriel Hosein
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Megan Kelley
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Catalina Mourgues
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - William Palmer
- Yale University Department of Psychology, New Haven, CT, USA
| | | | - Rashina Seabury
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Silmilly Toribio
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Raina Vin
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Jeremy Weleff
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Scott Woods
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - David Benrimoh
- Department of Psychiatry, McGill University, Montreal, Canada
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2
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Schaaf JV, Weidinger L, Molleman L, van den Bos W. Test-retest reliability of reinforcement learning parameters. Behav Res Methods 2024; 56:4582-4599. [PMID: 37684495 PMCID: PMC11289054 DOI: 10.3758/s13428-023-02203-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/18/2023] [Indexed: 09/10/2023]
Abstract
It has recently been suggested that parameter estimates of computational models can be used to understand individual differences at the process level. One area of research in which this approach, called computational phenotyping, has taken hold is computational psychiatry. One requirement for successful computational phenotyping is that behavior and parameters are stable over time. Surprisingly, the test-retest reliability of behavior and model parameters remains unknown for most experimental tasks and models. The present study seeks to close this gap by investigating the test-retest reliability of canonical reinforcement learning models in the context of two often-used learning paradigms: a two-armed bandit and a reversal learning task. We tested independent cohorts for the two tasks (N = 69 and N = 47) via an online testing platform with a between-test interval of five weeks. Whereas reliability was high for personality and cognitive measures (with ICCs ranging from .67 to .93), it was generally poor for the parameter estimates of the reinforcement learning models (with ICCs ranging from .02 to .52 for the bandit task and from .01 to .71 for the reversal learning task). Given that simulations indicated that our procedures could detect high test-retest reliability, this suggests that a significant proportion of the variability must be ascribed to the participants themselves. In support of that hypothesis, we show that mood (stress and happiness) can partly explain within-participant variability. Taken together, these results are critical for current practices in computational phenotyping and suggest that individual variability should be taken into account in the future development of the field.
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Affiliation(s)
- Jessica V Schaaf
- Department of Psychology, University of Amsterdam, Amsterdam, the Netherlands.
- Cognitive Neuroscience Department, Radboud University Medical Centre, Nijmegen, the Netherlands.
- Donders Institute for Brain, Cognition and Behaviour, Nijmegen, the Netherlands.
| | - Laura Weidinger
- DeepMind, London, United Kingdom
- Center for Adaptive Rationality, Max Planck Institute for Human Development, Berlin, Germany
| | - Lucas Molleman
- Department of Psychology, University of Amsterdam, Amsterdam, the Netherlands
- Center for Adaptive Rationality, Max Planck Institute for Human Development, Berlin, Germany
| | - Wouter van den Bos
- Department of Psychology, University of Amsterdam, Amsterdam, the Netherlands
- Center for Adaptive Rationality, Max Planck Institute for Human Development, Berlin, Germany
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3
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Rossi-Goldthorpe R, Silverstein SM, Gold JM, Schiffman J, Waltz JA, Williams TF, Powers AR, Woods SW, Zinbarg RE, Mittal VA, Ellman LM, Strauss GP, Walker EF, Levin JA, Castiello S, Kenney J, Corlett PR. Different learning aberrations relate to delusion-like beliefs with different contents. Brain 2024; 147:2854-2866. [PMID: 38637303 PMCID: PMC11292907 DOI: 10.1093/brain/awae122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 03/21/2024] [Accepted: 03/24/2024] [Indexed: 04/20/2024] Open
Abstract
The prediction error account of delusions has had success. However, its explanation of delusions with different contents has been lacking. Persecutory delusions and paranoia are the common unfounded beliefs that others have harmful intentions towards us. Other delusions include believing that one's thoughts or actions are under external control or that events in the world have specific personal meaning. We compare learning in two different cognitive tasks, probabilistic reversal learning and Kamin blocking, that have relationships to paranoid and non-paranoid delusion-like beliefs, respectively. We find that clinical high-risk status alone does not result in different behavioural results in the probabilistic reversal learning task but that an individual's level of paranoia is associated with excessive switching behaviour. During the Kamin blocking task, paranoid individuals learned inappropriately about the blocked cue. However, they also had decreased learning about the control cue, suggesting more general learning impairments. Non-paranoid delusion-like belief conviction (but not paranoia) was associated with aberrant learning about the blocked cue but intact learning about the control cue, suggesting specific impairments in learning related to cue combination. We fit task-specific computational models separately to behavioural data to explore how latent parameters vary within individuals between tasks and how they can explain symptom-specific effects. We find that paranoia is associated with low learning rates in the probabilistic reversal learning task and the blocking task. Non-paranoid delusion-like belief conviction is instead related to parameters controlling the degree and direction of similarity between cue updating during simultaneous cue presentation. These results suggest that paranoia and other delusion-like beliefs involve dissociable deficits in learning and belief updating, which, given the transdiagnostic status of paranoia, might have differential utility in predicting psychosis.
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Affiliation(s)
- Rosa Rossi-Goldthorpe
- Interdepartmental Neuroscience Program, Wu Tsai Institute, Yale University, New Haven, CT 06511, USA
- Department of Psychiatry, Yale University, New Haven, CT 06511, USA
| | - Steven M Silverstein
- Department of Psychiatry, University of Rochester Medical Center, Rochester, NY 14623, USA
- Department of Neuroscience, University of Rochester Medical Center, Rochester, NY 14623, USA
- Department of Opthalmology, University of Rochester Medical Center, Rochester, NY 14623, USA
| | - James M Gold
- Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD 21228, USA
| | - Jason Schiffman
- Department of Psychological Sciences, University of California Irvine, Irvine, CA 92617, USA
| | - James A Waltz
- Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD 21228, USA
| | - Trevor F Williams
- Department of Psychology, Northwestern University, Evanston, IL 60208-2710, USA
| | - Albert R Powers
- Department of Psychiatry, Yale University, New Haven, CT 06511, USA
| | - Scott W Woods
- Department of Psychiatry, Yale University, New Haven, CT 06511, USA
| | - Richard E Zinbarg
- Department of Psychology, Northwestern University, Evanston, IL 60208-2710, USA
| | - Vijay A Mittal
- Department of Psychology, Northwestern University, Evanston, IL 60208-2710, USA
| | - Lauren M Ellman
- Department of Psychology and Neuroscience, Temple University, Philadelphia, PA 19122, USA
| | - Gregory P Strauss
- Department of Psychology, University of Georgia, Athens, GA 30602, USA
| | - Elaine F Walker
- Department of Psychology, Emory University, Atlanta, GA 30322, USA
| | - Jason A Levin
- Department of Psychology, University of Georgia, Athens, GA 30602, USA
| | - Santiago Castiello
- Department of Psychiatry, Yale University, New Haven, CT 06511, USA
- Wu Tsai Institute, Yale University, New Haven, CT 06511, USA
| | - Joshua Kenney
- Department of Psychiatry, Yale University, New Haven, CT 06511, USA
- Wu Tsai Institute, Yale University, New Haven, CT 06511, USA
| | - Philip R Corlett
- Department of Psychiatry, Yale University, New Haven, CT 06511, USA
- Wu Tsai Institute, Yale University, New Haven, CT 06511, USA
- Department of Psychology, Yale University, New Haven, CT 06511, USA
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4
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Griffin JD, Diederen KMJ, Haarsma J, Jarratt Barnham IC, Cook BRH, Fernandez-Egea E, Williamson S, van Sprang ED, Gaillard R, Vinckier F, Goodyer IM, Murray GK, Fletcher PC. Distinct alterations in probabilistic reversal learning across at-risk mental state, first episode psychosis and persistent schizophrenia. Sci Rep 2024; 14:17614. [PMID: 39080434 PMCID: PMC11289106 DOI: 10.1038/s41598-024-68004-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Accepted: 07/17/2024] [Indexed: 08/02/2024] Open
Abstract
We used a probabilistic reversal learning task to examine prediction error-driven belief updating in three clinical groups with psychosis or psychosis-like symptoms. Study 1 compared people with at-risk mental state and first episode psychosis (FEP) to matched controls. Study 2 compared people diagnosed with treatment-resistant schizophrenia (TRS) to matched controls. The design replicated our previous work showing ketamine-related perturbations in how meta-level confidence maintained behavioural policy. We applied the same computational modelling analysis here, in order to compare the pharmacological model to three groups at different stages of psychosis. Accuracy was reduced in FEP, reflecting increased tendencies to shift strategy following probabilistic errors. The TRS group also showed a greater tendency to shift choice strategies though accuracy levels were not significantly reduced. Applying the previously-used computational modelling approach, we observed that only the TRS group showed altered confidence-based modulation of responding, previously observed under ketamine administration. Overall, our behavioural findings demonstrated resemblance between clinical groups (FEP and TRS) and ketamine in terms of a reduction in stabilisation of responding in a noisy environment. The computational analysis suggested that TRS, but not FEP, replicates ketamine effects but we consider the computational findings preliminary given limitations in performance of the model.
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Affiliation(s)
- J D Griffin
- Department of Psychiatry, University of Cambridge, Addenbrookes Hospital, Cambridge, CB2 0QQ, UK.
| | - K M J Diederen
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, London, UK
| | - J Haarsma
- Wellcome Centre for Human Neuroimaging, Queen Square, UCL, London, UK
| | - I C Jarratt Barnham
- Department of Psychiatry, University of Cambridge, Addenbrookes Hospital, Cambridge, CB2 0QQ, UK
- Cambridgeshire and Peterborough NHS Trust, Cambridge, UK
| | - B R H Cook
- Department of Psychiatry, University of Cambridge, Addenbrookes Hospital, Cambridge, CB2 0QQ, UK
| | - E Fernandez-Egea
- Department of Psychiatry, University of Cambridge, Addenbrookes Hospital, Cambridge, CB2 0QQ, UK
- Cambridgeshire and Peterborough NHS Trust, Cambridge, UK
| | - S Williamson
- Coventry and Warwickshire NHS Partnership Trust, Warwick, UK
| | - E D van Sprang
- Amsterdam University Medical Centres (UMC), Amsterdam, The Netherlands
| | - R Gaillard
- Paris Descartes University, Paris, France
| | - F Vinckier
- Service Hospitalo-Universitaire, GHU Paris Psychiatrie & Neurosciences, F-75014, Paris, France
- Motivation, Brain & Behavior (MBB) lab, Institut du Cerveau et de la Moelle épinière (ICM), F-75013, Paris, France
- Université Paris Cité, F-75006, Paris, France
| | - I M Goodyer
- Department of Psychiatry, University of Cambridge, Addenbrookes Hospital, Cambridge, CB2 0QQ, UK
- Cambridgeshire and Peterborough NHS Trust, Cambridge, UK
| | - G K Murray
- Department of Psychiatry, University of Cambridge, Addenbrookes Hospital, Cambridge, CB2 0QQ, UK
- Cambridgeshire and Peterborough NHS Trust, Cambridge, UK
| | - P C Fletcher
- Department of Psychiatry, University of Cambridge, Addenbrookes Hospital, Cambridge, CB2 0QQ, UK.
- Cambridgeshire and Peterborough NHS Trust, Cambridge, UK.
- Wellcome Trust MRC Institute of Metabolic Science, University of Cambridge, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK.
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5
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Sheffield JM, Brinen AP, Feola B, Heckers S, Corlett PR. Understanding Cognitive Behavioral Therapy for Psychosis Through the Predictive Coding Framework. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2024; 4:100333. [PMID: 38952435 PMCID: PMC11215207 DOI: 10.1016/j.bpsgos.2024.100333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 05/02/2024] [Accepted: 05/04/2024] [Indexed: 07/03/2024] Open
Abstract
Psychological treatments for persecutory delusions, particularly cognitive behavioral therapy for psychosis, are efficacious; however, mechanistic theories explaining why they work rarely bridge to the level of cognitive neuroscience. Predictive coding, a general brain processing theory rooted in cognitive and computational neuroscience, has increasing experimental support for explaining symptoms of psychosis, including the formation and maintenance of delusions. Here, we describe recent advances in cognitive behavioral therapy for psychosis-based psychotherapy for persecutory delusions, which targets specific psychological processes at the computational level of information processing. We outline how Bayesian learning models employed in predictive coding are superior to simple associative learning models for understanding the impact of cognitive behavioral interventions at the algorithmic level. We review hierarchical predictive coding as an account of belief updating rooted in prediction error signaling. We examine how this process is abnormal in psychotic disorders, garnering noisy sensory data that is made sense of through the development of overly strong delusional priors. We argue that effective cognitive behavioral therapy for psychosis systematically targets the way sensory data are selected, experienced, and interpreted, thus allowing for the strengthening of alternative beliefs. Finally, future directions based on these arguments are discussed.
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Affiliation(s)
- Julia M. Sheffield
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Aaron P. Brinen
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Brandee Feola
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Stephan Heckers
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Philip R. Corlett
- Department of Psychiatry, Clinical Neuroscience Research Unit, Yale School of Medicine, New Haven, Connecticut
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6
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Wang HR, Liu ZQ, Nakua H, Hegarty CE, Thies MB, Patel PK, Schleifer CH, Boeck TP, McKinney RA, Currin D, Leathem L, DeRosse P, Bearden CE, Misic B, Karlsgodt KH. Decoding Early Psychoses: Unraveling Stable Microstructural Features Associated With Psychopathology Across Independent Cohorts. Biol Psychiatry 2024:S0006-3223(24)01391-X. [PMID: 38908657 DOI: 10.1016/j.biopsych.2024.06.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 05/14/2024] [Accepted: 06/11/2024] [Indexed: 06/24/2024]
Abstract
BACKGROUND Patients with early psychosis (EP) (within 3 years after psychosis onset) show significant variability, which makes predicting outcomes challenging. Currently, little evidence exists for stable relationships between neural microstructural properties and symptom profiles across EP diagnoses, which limits the development of early interventions. METHODS A data-driven approach, partial least squares correlation, was used across 2 independent datasets to examine multivariate relationships between white matter properties and symptomatology and to identify stable and generalizable signatures in EP. The primary cohort included patients with EP from the Human Connectome Project for Early Psychosis (n = 124). The replication cohort included patients with EP from the Feinstein Institute for Medical Research (n = 78) as part of the MEND (Multimodal Evaluation of Neural Disorders) Project. Both samples included individuals with schizophrenia, schizoaffective disorder, and psychotic mood disorders. RESULTS In both cohorts, a significant latent component corresponded to a symptom profile that combined negative symptoms, primarily diminished expression, with specific somatic symptoms. Both latent components captured comprehensive features of white matter disruption, primarily a combination of subcortical and frontal association fibers. Strikingly, the partial least squares model trained on the primary cohort accurately predicted microstructural features and symptoms in the replication cohort. Findings were not driven by diagnosis, medication, or substance use. CONCLUSIONS This data-driven transdiagnostic approach revealed a stable and replicable neurobiological signature of microstructural white matter alterations in EP across diagnoses and datasets, showing strong covariance of these alterations with a unique profile of negative and somatic symptoms. These findings suggest the clinical utility of applying data-driven approaches to reveal symptom domains that share neurobiological underpinnings.
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Affiliation(s)
- Haley R Wang
- Department of Psychology, University of California, Los Angeles, Los Angeles, California; Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, California
| | - Zhen-Qi Liu
- Montréal Neurological Institute, McGill University, Montréal, Québec, Canada
| | - Hajer Nakua
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Institute of Medical Sciences, University of Toronto, Toronto, Ontario, Canada
| | - Catherine E Hegarty
- Department of Psychology, University of California, Los Angeles, Los Angeles, California
| | - Melanie Blair Thies
- Department of Psychiatry & Behavioral Sciences, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Pooja K Patel
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, California; Desert Pacific Mental Illness Research, Education, and Clinical Center Greater Los Angeles VA Healthcare System, Los Angeles, California
| | - Charles H Schleifer
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, California; David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
| | - Thomas P Boeck
- Department of Psychology, University of California, Los Angeles, Los Angeles, California
| | - Rachel A McKinney
- Department of Psychology, University of California, Los Angeles, Los Angeles, California
| | - Danielle Currin
- Department of Psychology, University of California, Los Angeles, Los Angeles, California
| | - Logan Leathem
- Department of Psychology, University of California, Los Angeles, Los Angeles, California
| | - Pamela DeRosse
- Department of Psychology, Stony Brook University, Stony Brook, New York
| | - Carrie E Bearden
- Department of Psychology, University of California, Los Angeles, Los Angeles, California; Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, California
| | - Bratislav Misic
- Montréal Neurological Institute, McGill University, Montréal, Québec, Canada
| | - Katherine H Karlsgodt
- Department of Psychology, University of California, Los Angeles, Los Angeles, California; Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, California.
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7
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Wang HR, Liu ZQ, Nakua H, Hegarty CE, Thies MB, Patel PK, Schleifer CH, Boeck TP, McKinney RA, Currin D, Leathem L, DeRosse P, Bearden CE, Misic B, Karlsgodt KH. Decoding Early Psychoses: Unraveling Stable Microstructural Features Associated with Psychopathology Across Independent Cohorts. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.10.593636. [PMID: 38766080 PMCID: PMC11100779 DOI: 10.1101/2024.05.10.593636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Background Early Psychosis patients (EP, within 3 years after psychosis onset) show significant variability, making outcome predictions challenging. Currently, little evidence exists for stable relationships between neural microstructural properties and symptom profiles across EP diagnoses, limiting the development of early interventions. Methods A data-driven approach, Partial Least Squares (PLS) correlation, was used across two independent datasets to examine multivariate relationships between white matter (WM) properties and symptomatology, to identify stable and generalizable signatures in EP. The primary cohort included EP patients from the Human Connectome Project-Early Psychosis (n=124). The replication cohort included EP patients from the Feinstein Institute for Medical Research (n=78). Both samples included individuals with schizophrenia, schizoaffective disorder, and psychotic mood disorders. Results In both cohorts, a significant latent component (LC) corresponded to a symptom profile combining negative symptoms, primarily diminished expression, with specific somatic symptoms. Both LCs captured comprehensive features of WM disruption, primarily a combination of subcortical and frontal association fibers. Strikingly, the PLS model trained on the primary cohort accurately predicted microstructural features and symptoms in the replication cohort. Findings were not driven by diagnosis, medication, or substance use. Conclusions This data-driven transdiagnostic approach revealed a stable and replicable neurobiological signature of microstructural WM alterations in EP, across diagnoses and datasets, showing a strong covariance of these alterations with a unique profile of negative and somatic symptoms. This finding suggests the clinical utility of applying data-driven approaches to reveal symptom domains that share neurobiological underpinnings.
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8
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Leclercq S, Szaffarczyk S, Leptourgos P, Yger P, Fakhri A, Wathelet M, Bouttier V, Denève S, Jardri R. Conspiracy beliefs and perceptual inference in times of political uncertainty. Sci Rep 2024; 14:9001. [PMID: 38637589 PMCID: PMC11026417 DOI: 10.1038/s41598-024-59434-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 04/10/2024] [Indexed: 04/20/2024] Open
Abstract
Sociopolitical crises causing uncertainty have accumulated in recent years, providing fertile ground for the emergence of conspiracy ideations. Computational models constitute valuable tools for understanding the mechanisms at play in the formation and rigidification of these unshakeable beliefs. Here, the Circular Inference model was used to capture associations between changes in perceptual inference and the dynamics of conspiracy ideations in times of uncertainty. A bistable perception task and conspiracy belief assessment focused on major sociopolitical events were administered to large populations from three polarized countries. We show that when uncertainty peaks, an overweighting of sensory information is associated with conspiracy ideations. Progressively, this exploration strategy gives way to an exploitation strategy in which increased adherence to conspiracy theories is associated with the amplification of prior information. Overall, the Circular Inference model sheds new light on the possible mechanisms underlying the progressive strengthening of conspiracy theories when individuals face highly uncertain situations.
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Affiliation(s)
- Salomé Leclercq
- INSERM U1172, CHU Lille, Lille Neuroscience and Cognition Centre, CURE Platform, Fontan Hospital, Lille University, 59000, Lille, France.
| | - Sébastien Szaffarczyk
- INSERM U1172, CHU Lille, Lille Neuroscience and Cognition Centre, CURE Platform, Fontan Hospital, Lille University, 59000, Lille, France
| | - Pantelis Leptourgos
- INSERM U1172, CHU Lille, Lille Neuroscience and Cognition Centre, CURE Platform, Fontan Hospital, Lille University, 59000, Lille, France
| | - Pierre Yger
- INSERM U1172, CHU Lille, Lille Neuroscience and Cognition Centre, CURE Platform, Fontan Hospital, Lille University, 59000, Lille, France
| | | | - Marielle Wathelet
- INSERM U1172, CHU Lille, Lille Neuroscience and Cognition Centre, CURE Platform, Fontan Hospital, Lille University, 59000, Lille, France
| | - Vincent Bouttier
- INSERM U1172, CHU Lille, Lille Neuroscience and Cognition Centre, CURE Platform, Fontan Hospital, Lille University, 59000, Lille, France
- LNC, INSERM U-960, Institut de Sciences Cognitives, École Normale Supérieure, 75005, Paris, France
| | - Sophie Denève
- LNC, INSERM U-960, Institut de Sciences Cognitives, École Normale Supérieure, 75005, Paris, France
| | - Renaud Jardri
- INSERM U1172, CHU Lille, Lille Neuroscience and Cognition Centre, CURE Platform, Fontan Hospital, Lille University, 59000, Lille, France.
- LNC, INSERM U-960, Institut de Sciences Cognitives, École Normale Supérieure, 75005, Paris, France.
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9
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Powers A, Angelos P, Bond A, Farina E, Fredericks C, Gandhi J, Greenwald M, Hernandez-Busot G, Hosein G, Kelley M, Mourgues C, Palmer W, Rodriguez-Sanchez J, Seabury R, Toribio S, Vin R, Weleff J, Benrimoh D. A computational account of the development and evolution of psychotic symptoms. ARXIV 2024:arXiv:2404.10954v1. [PMID: 38699166 PMCID: PMC11065053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 05/05/2024]
Abstract
The mechanisms of psychotic symptoms like hallucinations and delusions are often investigated in fully-formed illness, well after symptoms emerge. These investigations have yielded key insights, but are not well-positioned to reveal the dynamic forces underlying symptom formation itself. Understanding symptom development over time would allow us to identify steps in the pathophysiological process leading to psychosis, shifting the focus of psychiatric intervention from symptom alleviation to prevention. We propose a model for understanding the emergence of psychotic symptoms within the context of an adaptive, developing neural system. We will make the case for a pathophysiological process that begins with cortical hyperexcitability and bottom-up noise transmission, which engenders inappropriate belief formation via aberrant prediction error signaling. We will argue that this bottom-up noise drives learning about the (im)precision of new incoming sensory information because of diminished signal-to-noise ratio, causing an adaptive relative over-reliance on prior beliefs. This over-reliance on priors predisposes to hallucinations and covaries with hallucination severity. An over-reliance on priors may also lead to increased conviction in the beliefs generated by bottom-up noise and drive movement toward conversion to psychosis. We will identify predictions of our model at each stage, examine evidence to support or refute those predictions, and propose experiments that could falsify or help select between alternative elements of the overall model. Nesting computational abnormalities within longitudinal development allows us to account for hidden dynamics among the mechanisms driving symptom formation and to view established symptomatology as a point of equilibrium among competing biological forces.
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Affiliation(s)
- Albert Powers
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Philip Angelos
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Alexandria Bond
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Emily Farina
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Carolyn Fredericks
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Jay Gandhi
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Maximillian Greenwald
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | | | - Gabriel Hosein
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Megan Kelley
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Catalina Mourgues
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - William Palmer
- Yale University Department of Psychology, New Haven, CT USA
| | | | - Rashina Seabury
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Silmilly Toribio
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Raina Vin
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Jeremy Weleff
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - David Benrimoh
- Department of Psychiatry, McGill University, Montreal, Canada
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10
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Deng W, Tuominen L, Sussman R, Leathem L, Vinke LN, Holt DJ. Changes in responses of the amygdala and hippocampus during fear conditioning are associated with persecutory beliefs. Sci Rep 2024; 14:8173. [PMID: 38589562 PMCID: PMC11001942 DOI: 10.1038/s41598-024-57746-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Accepted: 03/21/2024] [Indexed: 04/10/2024] Open
Abstract
The persecutory delusion is the most common symptom of psychosis, yet its underlying neurobiological mechanisms are poorly understood. Prior studies have suggested that abnormalities in medial temporal lobe-dependent associative learning may contribute to this symptom. In the current study, this hypothesis was tested in a non-clinical sample of young adults without histories of psychiatric treatment (n = 64), who underwent classical Pavlovian fear conditioning while fMRI data were collected. During the fear conditioning procedure, participants viewed images of faces which were paired (the CS+) or not paired (the CS-) with an aversive stimulus (a mild electrical shock). Fear conditioning-related neural responses were measured in two medial temporal lobe regions, the amygdala and hippocampus, and in other closely connected brain regions of the salience and default networks. The participants without persecutory beliefs (n = 43) showed greater responses to the CS- compared to the CS+ in the right amygdala and hippocampus, while the participants with persecutory beliefs (n = 21) failed to exhibit this response. These between-group differences were not accounted for by symptoms of depression, anxiety or a psychosis risk syndrome. However, the severity of subclinical psychotic symptoms overall was correlated with the level of this aberrant response in the amygdala (p = .013) and hippocampus (p = .033). Thus, these findings provide evidence for a disruption of medial temporal lobe-dependent associative learning in young people with subclinical psychotic symptoms, specifically persecutory thinking.
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Affiliation(s)
- Wisteria Deng
- Department of Psychiatry, Massachusetts General Hospital, 149 13th, St. Charlestown, Boston, MA, 02129, USA
- Department of Psychology, Yale University, New Haven, CT, USA
| | - Lauri Tuominen
- Department of Psychiatry, Massachusetts General Hospital, 149 13th, St. Charlestown, Boston, MA, 02129, USA
- Department of Psychiatry, University of Ottawa, Ottawa, ON, Canada
| | - Rachel Sussman
- Department of Psychiatry, Massachusetts General Hospital, 149 13th, St. Charlestown, Boston, MA, 02129, USA
| | - Logan Leathem
- Department of Psychiatry, Massachusetts General Hospital, 149 13th, St. Charlestown, Boston, MA, 02129, USA
| | - Louis N Vinke
- Department of Psychiatry, Massachusetts General Hospital, 149 13th, St. Charlestown, Boston, MA, 02129, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Daphne J Holt
- Department of Psychiatry, Massachusetts General Hospital, 149 13th, St. Charlestown, Boston, MA, 02129, USA.
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA.
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11
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Yang X, Song Y, Zou Y, Li Y, Zeng J. Neural correlates of prediction error in patients with schizophrenia: evidence from an fMRI meta-analysis. Cereb Cortex 2024; 34:bhad471. [PMID: 38061699 DOI: 10.1093/cercor/bhad471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 11/07/2023] [Accepted: 11/09/2023] [Indexed: 01/19/2024] Open
Abstract
Abnormal processes of learning from prediction errors, i.e. the discrepancies between expectations and outcomes, are thought to underlie motivational impairments in schizophrenia. Although dopaminergic abnormalities in the mesocorticolimbic reward circuit have been found in patients with schizophrenia, the pathway through which prediction error signals are processed in schizophrenia has yet to be elucidated. To determine the neural correlates of prediction error processing in schizophrenia, we conducted a meta-analysis of whole-brain neuroimaging studies that investigated prediction error signal processing in schizophrenia patients and healthy controls. A total of 14 studies (324 schizophrenia patients and 348 healthy controls) using the reinforcement learning paradigm were included. Our meta-analysis showed that, relative to healthy controls, schizophrenia patients showed increased activity in the precentral gyrus and middle frontal gyrus and reduced activity in the mesolimbic circuit, including the striatum, thalamus, amygdala, hippocampus, anterior cingulate cortex, insula, superior temporal gyrus, and cerebellum, when processing prediction errors. We also found hyperactivity in frontal areas and hypoactivity in mesolimbic areas when encoding prediction error signals in schizophrenia patients, potentially indicating abnormal dopamine signaling of reward prediction error and suggesting failure to represent the value of alternative responses during prediction error learning and decision making.
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Affiliation(s)
- Xun Yang
- School of Public Policy and Administration, Chongqing University, No. 174, Shazhengjie, Shapingba, Chongqing, China
| | - Yuan Song
- School of Public Policy and Administration, Chongqing University, No. 174, Shazhengjie, Shapingba, Chongqing, China
| | - Yuhan Zou
- School of Economics and Business Administration, Chongqing University, No. 174, Shazhengjie, Shapingba, Chongqing, China
| | - Yilin Li
- Psychology and Neuroscience Department, University of St Andrews, Forbes 1 DRA, Buchanan Garden, St Andrews, Fife, United Kingdom
| | - Jianguang Zeng
- School of Economics and Business Administration, Chongqing University, No. 174, Shazhengjie, Shapingba, Chongqing, China
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12
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Frith U, Frith C. What makes us social and what does it tell us about mental disorders? Cogn Neuropsychiatry 2024; 29:1-9. [PMID: 38281115 DOI: 10.1080/13546805.2024.2307958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Accepted: 01/16/2024] [Indexed: 01/29/2024]
Affiliation(s)
- Uta Frith
- Institute of Cognitive Neuroscience, University College London, London, UK
| | - Chris Frith
- Institute of Philosophy, School of Advanced Study, University of London, London, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
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13
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Okazaki M, Yumoto M, Kaneko Y, Maruo K. Correlation of motor-auditory cross-modal and auditory unimodal N1 and mismatch responses of schizophrenic patients and normal subjects: an MEG study. Front Psychiatry 2023; 14:1217307. [PMID: 37886112 PMCID: PMC10598755 DOI: 10.3389/fpsyt.2023.1217307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 09/25/2023] [Indexed: 10/28/2023] Open
Abstract
Introduction It has been suggested that the positive symptoms of schizophrenic patients (hallucinations, delusions, and passivity experience) are caused by dysfunction of their internal and external sensory prediction errors. This is often discussed as related to dysfunction of the forward model that executes self-monitoring. Several reports have suggested that dysfunction of the forward model in schizophrenia causes misattributions of self-generated thoughts and actions to external sources. There is some evidence that the forward model can be measured using the electroencephalography (EEG) and magnetoencephalography (MEG) components such as N1 (m) and mismatch negativity (MMN) (m). The objective in this MEG study is to investigate differences in the N1m and MMNm-like activity generated in motor-auditory cross-modal tasks in normal control (NC) subjects and schizophrenic (SC) patients, and compared that activity with N1m and MMNm in the auditory unimodal task. Methods The N1m and MMNm/MMNm-like activity were recorded in 15 SC patients and 12 matched NC subjects. The N1m-attenuation effects and peak amplitude of MMNm/MMNm-like activity of the NC and SC groups were compared. Additionally, correlations between MEG measures (N1m suppression rate, MMNm, and MMNm-like activity) and clinical variables (Positive and Negative Syndrome Scale (PANSS) scores and antipsychotic drug (APD) dosages) in SC patients were investigated. Results It was found that (i) there was no significant difference in N1m-attenuation for the NC and SC groups, and that (ii) MMNm in the unimodal task in the SC group was significantly smaller than that in the NC group. Further, the MMNm-like activity in the cross-modal task was smaller than that of the MMNm in the unimodal task in the NC group, but there was no significant difference in the SC group. The PANSS positive symptoms and general psychopathology score were moderately negatively correlated with the amplitudes of the MMNm-like activity, and the APD dosage was moderately negatively correlated with the N1m suppression rate. However, none of these correlations reached statistical significance. Discussion The findings suggest that schizophrenic patients perform altered predictive processes differently from healthy subjects in latencies reflecting MMNm, depending on whether they are under forward model generation or not. This may support the hypothesis that schizophrenic patients tend to misattribute their inner experience to external agents, thus leading to the characteristic schizophrenia symptoms.
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Affiliation(s)
- Mitsutoshi Okazaki
- Department of Psychiatry, National Center Hospital of Neurology and Psychiatry, Kodaira, Japan
- Department of Psychiatry, Ome Municipal General Hospital, Ome, Japan
| | - Masato Yumoto
- Department of Clinical Engineering, Faculty of Medical Science and Technology, Gunma Paz University, Takasaki, Japan
| | - Yuu Kaneko
- Department of Neurosurgery, National Center Hospital of Neurology and Psychiatry, Kodaira, Japan
| | - Kazushi Maruo
- Department of Biostatistics, Faculty of Medicine, University of Tsukuba, Tsukuba, Japan
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14
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Hird EJ, Diederen K, Leucht S, Jensen KB, McGuire P. The Placebo Effect in Psychosis: Why It Matters and How to Measure It. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2023; 3:605-613. [PMID: 37881581 PMCID: PMC10593894 DOI: 10.1016/j.bpsgos.2023.02.008] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 12/04/2022] [Accepted: 02/20/2023] [Indexed: 03/07/2023] Open
Abstract
Psychosis is characterized by unusual percepts and beliefs in the form of hallucinations and delusions. Antipsychotic medication, the primary treatment for psychosis, is often ineffective and accompanied by severe side effects, but research has not identified an effective alternative in several decades. One reason that clinical trials fail is that patients with psychosis tend to show a significant therapeutic response to inert control treatments, known as the placebo effect, which makes it difficult to distinguish drug effects from placebo effects. Conversely, in clinical practice, a strong placebo effect may be useful because it could enhance the overall treatment response. Identifying factors that predict large placebo effects could improve the future outlook of psychosis treatment. Biomarkers of the placebo effect have already been suggested in pain and depression, but not in psychosis. Quantifying markers of the placebo effect would have the potential to predict placebo effects in psychosis clinical trials. Furthermore, the placebo effect and psychosis may represent a shared neurocognitive mechanism in which prior beliefs are weighted against new sensory information to make inferences about reality. Examining this overlap could reveal new insights into the mechanisms underlying psychosis and indicate novel treatment targets. We provide a narrative review of the importance of the placebo effect in psychosis and propose a novel method to assess it.
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Affiliation(s)
- Emily J. Hird
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, England
| | - Kelly Diederen
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, England
| | - Stefan Leucht
- Department of Psychiatry and Psychotherapy, Technical University of Munich, Munich, Germany
| | - Karin B. Jensen
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden
| | - Philip McGuire
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, England
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15
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Hanewald B, Lockhofen DEL, Sammer G, Stingl M, Gallhofer B, Mulert C, Iffland JR. Functional connectivity in a monetary and social incentive delay task in medicated patients with schizophrenia. Front Psychiatry 2023; 14:1200860. [PMID: 37711426 PMCID: PMC10498543 DOI: 10.3389/fpsyt.2023.1200860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 08/02/2023] [Indexed: 09/16/2023] Open
Abstract
Introduction Numerous studies indicate impaired reward-related learning in individuals with schizophrenia, with various factors such as illness duration, medication, disease severity, and level of analysis (behavioral or neurophysiological data) potentially confounding the results. Patients with schizophrenia who are treated with second-generation antipsychotics have been found to have a less affected reward system. However, this finding does not explain the neural dysfunctions observed in previous studies. This study aimed to address the open question of whether the less impaired reward-related behavior is associated with unimpaired task-related functional connectivity or altered task-related functional connectivity. Methods The study included 23 participants diagnosed within the schizophrenia spectrum and 23 control participants matched in terms of age, sex, and education. Participants underwent an MRI while performing a monetary incentive delay task and a social incentive delay task. The collected data were analyzed in terms of behavior and functional connectivity. Results Both groups exhibited a main effect of reward type on behavioral performance, indicating faster reaction times in the social incentive delay task, but no main effect of reward level. Altered functional connectivity was observed in predictable brain regions within the patient group, depending on the chosen paradigm, but not when compared to healthy individuals. Discussion In addition to expected slower response times, patients with schizophrenia demonstrated similar response patterns to control participants at the behavioral level. The similarities in behavioral data may underlie different connectivity patterns. Our findings suggest that perturbations in reward processing do not necessarily imply disturbances in underlying connectivities. Consequently, we were able to demonstrate that patients with schizophrenia are indeed capable of exhibiting goal-directed, reward-responsive behavior, although there are differences depending on the type of reward.
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Affiliation(s)
- Bernd Hanewald
- Center for Psychiatry, Justus Liebig University Giessen, Giessen, Germany
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16
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Foley JA, Chen C, Paget A, Cipolotti L. A Bayesian predictive processing account of Othello syndrome in Parkinson's disease. Cogn Neuropsychiatry 2023; 28:269-284. [PMID: 37366042 DOI: 10.1080/13546805.2023.2229080] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 03/24/2023] [Indexed: 06/28/2023]
Abstract
Introduction: Although delusions in Parkinson's disease (PD) are rare, when they occur they frequently take the form of "Othello syndrome": the irrational belief that a spouse or partner is being unfaithful. Hitherto dismissed as either a by-product of dopamine therapy or cognitive impairment, there are still no convincing theoretical accounts to explain why only some patients fall prey to this delusion, or why it persists despite clear disconfirmatory evidence.Methods: We discuss the limitations of existing explanations of this delusion, namely hyperdopaminergia-induced anomalous perceptual experiences and cognitive impairment, before describing how Bayesian predictive processing accounts can provide a more comprehensive explanation by foregrounding the importance of prior experience and its impact upon computation of probability. We illustrate this new conceptualisation with three case vignettes.Results: We suggest that in those with prior experience of romantic betrayal, hyperdominergic-induced aberrant prediction errors enable anomalous perceptual experiences to accrue greater prominence, which is then maintained through Bayes-optimal inferencing to confirm cognitive distortions, eliciting and shaping this dangerous delusion.Conclusions: We propose the first comprehensive mechanistic account of Othello syndrome in PD and discuss implications for clinical interventions.
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Affiliation(s)
- Jennifer A Foley
- Department of Neuropsychology, National Hospital for Neurology and Neurosurgery, London, UK
- UCL Queen Square Institute of Neurology, London, UK
| | - Cliff Chen
- Department of Clinical Neuropsychology, Salford Royal NHS Foundation Trust, Salford, UK
| | - Andrew Paget
- Department of Neuropsychology, National Hospital for Neurology and Neurosurgery, London, UK
| | - Lisa Cipolotti
- Department of Neuropsychology, National Hospital for Neurology and Neurosurgery, London, UK
- UCL Queen Square Institute of Neurology, London, UK
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17
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Tangmose K, Rostrup E, Bojesen KB, Sigvard A, Glenthøj BY, Nielsen MØ. Clinical response to treatment with a partial dopamine agonist is related to changes in reward processing. Psychiatry Res 2023; 326:115308. [PMID: 37399765 DOI: 10.1016/j.psychres.2023.115308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Revised: 06/08/2023] [Accepted: 06/13/2023] [Indexed: 07/05/2023]
Abstract
Aberrant neuronal coding of reward processing has been linked to psychosis. It remains unresolved how treatment with a partial dopamine agonist affects reward processing, and whether treatment affects reward processing differently in patients responding and not responding to treatment. Here, 33 antipsychotic-naïve psychosis patients and 33 matched healthy controls underwent functional magnetic resonance imaging before and after patients received aripiprazole monotherapy for six weeks. Processing of motivational salient events and negative outcome evaluation (NOE) was examined using a monetary incentive delay task. Psychopathology was assessed with the Positive and Negative Syndrome Scale, and responders were identified by having ≥30% reduction in positive symptoms (N=21). At baseline, patients displayed an increased NOE signal in the caudate and dorsolateral prefrontal cortex compared to healthy controls. In the caudate, the NOE signal was normalized at follow-up, and normalization was driven by responders. In responders only, there was a significant improvement in the motivational salience signal in the caudate at follow-up. Motivational salience and NOE signals in the caudate may be associated with a dopaminergic mechanism in patients characterized as responders which may not be the case in non-responders. Likewise, non-dopaminergic mechanism may underly abnormal NOE processing in dorsolateral prefrontal cortex.
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Affiliation(s)
- Karen Tangmose
- Center for Neuropsychiatric Schizophrenia Research (CNSR) and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research (CINS), Mental Health Center Glostrup, Glostrup, Denmark
| | - Egill Rostrup
- Center for Neuropsychiatric Schizophrenia Research (CNSR) and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research (CINS), Mental Health Center Glostrup, Glostrup, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; Functional Imaging Unit, Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet Glostrup, University of Copenhagen, Rigshospitalet, Glostrup, Denmark
| | - Kirsten Borup Bojesen
- Center for Neuropsychiatric Schizophrenia Research (CNSR) and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research (CINS), Mental Health Center Glostrup, Glostrup, Denmark
| | - Anne Sigvard
- Center for Neuropsychiatric Schizophrenia Research (CNSR) and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research (CINS), Mental Health Center Glostrup, Glostrup, Denmark
| | - Birte Y Glenthøj
- Center for Neuropsychiatric Schizophrenia Research (CNSR) and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research (CINS), Mental Health Center Glostrup, Glostrup, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Mette Ødegaard Nielsen
- Center for Neuropsychiatric Schizophrenia Research (CNSR) and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research (CINS), Mental Health Center Glostrup, Glostrup, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
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18
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Purcell JR, Brown JW, Tullar RL, Bloomer BF, Kim DJ, Moussa-Tooks AB, Dolan-Bennett K, Bangert BM, Wisner KM, Lundin NB, O'Donnell BF, Hetrick WP. Insular and Striatal Correlates of Uncertain Risky Reward Pursuit in Schizophrenia. Schizophr Bull 2023; 49:726-737. [PMID: 36869757 PMCID: PMC10154703 DOI: 10.1093/schbul/sbac206] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/05/2023]
Abstract
BACKGROUND AND HYPOTHESIS Risk-taking in specific contexts can be beneficial, leading to rewarding outcomes. Schizophrenia is associated with disadvantageous decision-making, as subjects pursue uncertain risky rewards less than controls. However, it is unclear whether this behavior is associated with more risk sensitivity or less reward incentivization. Matching on demographics and intelligence quotient (IQ), we determined whether risk-taking was more associated with brain activation in regions affiliated with risk evaluation or reward processing. STUDY DESIGN Subjects (30 schizophrenia/schizoaffective disorder, 30 controls) completed a modified, fMRI Balloon Analogue Risk Task. Brain activation was modeled during decisions to pursue risky rewards and parametrically modeled according to risk level. STUDY RESULTS The schizophrenia group exhibited less risky-reward pursuit despite previous adverse outcomes (Average Explosions; F(1,59) = 4.06, P = .048) but the comparable point at which risk-taking was volitionally discontinued (Adjusted Pumps; F(1,59) = 2.65, P = .11). Less activation was found in schizophrenia via whole brain and region of interest (ROI) analyses in the right (F(1,59) = 14.91, P < 0.001) and left (F(1,59) = 16.34, P < 0.001) nucleus accumbens (NAcc) during decisions to pursue rewards relative to riskiness. Risk-taking correlated with IQ in schizophrenia, but not controls. Path analyses of average ROI activation revealed less statistically determined influence of anterior insula upon dorsal anterior cingulate bilaterally (left: χ2 = 12.73, P < .001; right: χ2 = 9.54, P = .002) during risky reward pursuit in schizophrenia. CONCLUSIONS NAcc activation in schizophrenia varied less according to the relative riskiness of uncertain rewards compared to controls, suggesting aberrations in reward processing. The lack of activation differences in other regions suggests similar risk evaluation. Less insular influence on the anterior cingulate may relate to attenuated salience attribution or inability for risk-related brain region collaboration to sufficiently perceive situational risk.
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Affiliation(s)
- John R Purcell
- Department of Psychological & Brain Sciences, Indiana University, Bloomington, IN, USA
- Program in Neuroscience, Indiana University, Bloomington, IN, USA
- Department of Psychiatry, Brain Health Institute, Rutgers University, Piscataway, NJ, USA
| | - Joshua W Brown
- Department of Psychological & Brain Sciences, Indiana University, Bloomington, IN, USA
- Program in Neuroscience, Indiana University, Bloomington, IN, USA
| | - Rachel L Tullar
- Department of Psychological & Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Bess F Bloomer
- Department of Psychological & Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Dae-Jin Kim
- Department of Psychological & Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Alexandra B Moussa-Tooks
- Department of Psychological & Brain Sciences, Indiana University, Bloomington, IN, USA
- Program in Neuroscience, Indiana University, Bloomington, IN, USA
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Katherine Dolan-Bennett
- Department of Psychological & Brain Sciences, Indiana University, Bloomington, IN, USA
- Department of Psychological and Brain Science, Washington University, St. Louise, MO, USA
| | - Brianna M Bangert
- Program in Neuroscience, Indiana University, Bloomington, IN, USA
- College of Medicine, University of Cincinnati, Cincinnati, OH, USA
| | - Krista M Wisner
- Department of Psychological & Brain Sciences, Indiana University, Bloomington, IN, USA
- Program in Neuroscience, Indiana University, Bloomington, IN, USA
| | - Nancy B Lundin
- Department of Psychological & Brain Sciences, Indiana University, Bloomington, IN, USA
- Program in Neuroscience, Indiana University, Bloomington, IN, USA
- Department of Psychiatry and Behavioral Health, The Ohio State University, Columbus, OH, USA
| | - Brian F O'Donnell
- Department of Psychological & Brain Sciences, Indiana University, Bloomington, IN, USA
- Program in Neuroscience, Indiana University, Bloomington, IN, USA
| | - William P Hetrick
- Department of Psychological & Brain Sciences, Indiana University, Bloomington, IN, USA
- Program in Neuroscience, Indiana University, Bloomington, IN, USA
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19
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D'Mello AM, Frosch IR, Meisler SL, Grotzinger H, Perrachione TK, Gabrieli JDE. Diminished Repetition Suppression Reveals Selective and Systems-Level Face Processing Differences in ASD. J Neurosci 2023; 43:1952-1962. [PMID: 36759192 PMCID: PMC10027049 DOI: 10.1523/jneurosci.0608-22.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 01/24/2023] [Accepted: 01/28/2023] [Indexed: 02/11/2023] Open
Abstract
Repeated exposure to a stimulus results in reduced neural response, or repetition suppression, in brain regions responsible for processing that stimulus. This rapid accommodation to repetition is thought to underlie learning, stimulus selectivity, and strengthening of perceptual expectations. Importantly, reduced sensitivity to repetition has been identified in several neurodevelopmental, learning, and psychiatric disorders, including autism spectrum disorder (ASD), a neurodevelopmental disorder characterized by challenges in social communication and repetitive behaviors and restricted interests. Reduced ability to exploit or learn from repetition in ASD is hypothesized to contribute to sensory hypersensitivities, and parallels several theoretical frameworks claiming that ASD individuals show difficulty using regularities in the environment to facilitate behavior. Using fMRI in autistic and neurotypical human adults (females and males), we assessed the status of repetition suppression across two modalities (vision, audition) and with four stimulus categories (faces, objects, printed words, and spoken words). ASD individuals showed domain-specific reductions in repetition suppression for face stimuli only, but not for objects, printed words, or spoken words. Reduced repetition suppression for faces was associated with greater challenges in social communication in ASD. We also found altered functional connectivity between atypically adapting cortical regions and higher-order face recognition regions, and microstructural differences in related white matter tracts in ASD. These results suggest that fundamental neural mechanisms and system-wide circuits are selectively altered for face processing in ASD and enhance our understanding of how disruptions in the formation of stable face representations may relate to higher-order social communication processes.SIGNIFICANCE STATEMENT A common finding in neuroscience is that repetition results in plasticity in stimulus-specific processing regions, reflecting selectivity and adaptation (repetition suppression [RS]). RS is reduced in several neurodevelopmental and psychiatric conditions including autism spectrum disorder (ASD). Theoretical frameworks of ASD posit that reduced adaptation may contribute to associated challenges in social communication and sensory processing. However, the scope of RS differences in ASD is unknown. We examined RS for multiple categories across visual and auditory domains (faces, objects, printed words, spoken words) in autistic and neurotypical individuals. We found reduced RS in ASD for face stimuli only and altered functional connectivity and white matter microstructure between cortical face-recognition areas. RS magnitude correlated with social communication challenges among autistic individuals.
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Affiliation(s)
- Anila M D'Mello
- McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, 02139
| | - Isabelle R Frosch
- McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, 02139
| | - Steven L Meisler
- Program in Speech and Hearing Bioscience and Technology, Harvard University, Cambridge, Massachusetts, 02115
| | - Hannah Grotzinger
- McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, 02139
| | - Tyler K Perrachione
- Department of Speech, Language, and Hearing Sciences, Boston University, Boston, Massachusetts 02215
| | - John D E Gabrieli
- McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, 02139
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20
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Tulver K, Kaup KK, Laukkonen R, Aru J. Restructuring insight: An integrative review of insight in problem-solving, meditation, psychotherapy, delusions and psychedelics. Conscious Cogn 2023; 110:103494. [PMID: 36913839 DOI: 10.1016/j.concog.2023.103494] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 02/03/2023] [Accepted: 02/26/2023] [Indexed: 03/13/2023]
Abstract
Occasionally, a solution or idea arrives as a sudden understanding - an insight. Insight has been considered an "extra" ingredient of creative thinking and problem-solving. Here we propose that insight is central in seemingly distinct areas of research. Drawing on literature from a variety of fields, we show that besides being commonly studied in problem-solving literature, insight is also a core component in psychotherapy and meditation, a key process underlying the emergence of delusions in schizophrenia, and a factor in the therapeutic effects of psychedelics. In each case, we discuss the event of insight and its prerequisites and consequences. We review evidence for the commonalities and differences between the fields and discuss their relevance for capturing the essence of the insight phenomenon. The goal of this integrative review is to bridge the gap between the different views and inspire interdisciplinary research efforts for understanding this central process of human cognition.
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Affiliation(s)
- Kadi Tulver
- Institute of Computer Science, University of Tartu, Estonia.
| | | | | | - Jaan Aru
- Institute of Computer Science, University of Tartu, Estonia.
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21
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Tandon R. Computational psychiatry and the psychopathology of psychosis: Promising leads and blind alleys. Schizophr Res 2023; 254:143-145. [PMID: 36889180 DOI: 10.1016/j.schres.2023.02.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 02/03/2023] [Accepted: 02/04/2023] [Indexed: 03/10/2023]
Affiliation(s)
- Rajiv Tandon
- Department of Psychiatry, WMU Homer Stryker School of Medicine, Kalamazoo, MI, United States of America.
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22
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Koller WN, Cannon TD. Aberrant memory and delusional ideation: A pernicious partnership? Clin Psychol Rev 2023; 99:102231. [PMID: 36469975 DOI: 10.1016/j.cpr.2022.102231] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Revised: 06/02/2022] [Accepted: 11/23/2022] [Indexed: 11/29/2022]
Abstract
Delusions can be conceptualized as beliefs that are both at odds with consensus reality and espoused with high conviction. While delusions represent a cardinal symptom of schizophrenia, delusion-like beliefs can be found in the general population. Do similar cognitive mechanisms support delusionality across this spectrum? If so, what are they? Here, we examine evidence for a mechanistic role of the (associative) memory system in the formation and maintenance of delusions and delusion-like beliefs. While general neurocognitive metrics do not tend to associate with delusionality, our scoping review of the clinical and subclinical literature reveals several subdomains of memory function that do. These include a propensity to commit errors of commission (i.e., false alarms and intrusions), source memory biases, and metamemory impairment. We discuss how several of these effects may stem from aberrant associative memory function and offer recommendations for future research. Further, we propose a state/trait interaction model in which underlying traits (i.e., impaired associative and metamemory function) may become coupled with delusionality during states of acute psychosis, when memory function is particularly challenged by aberrant salience attribution and noisy perceptual input. According to this model, delusions may arise as explanations to high-salience (but low-source) mnemonic content that is endorsed with high confidence.
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Affiliation(s)
- William N Koller
- Department of Psychology, Yale University, Hillhouse Avenue, New Haven, CT 06520-8205, United States of America.
| | - Tyrone D Cannon
- Department of Psychology, Yale University, Hillhouse Avenue, New Haven, CT 06520-8205, United States of America
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23
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Kandilarova S, Stoyanov D, Aryutova K, Paunova R, Mantarkov M, Mitrev I, Todeva-Radneva A, Specht K. Effective Connectivity Between the Orbitofrontal Cortex and the Precuneus Differentiates Major Psychiatric Disorders: Results from a Transdiagnostic Spectral DCM Study. CNS & NEUROLOGICAL DISORDERS DRUG TARGETS 2023; 22:180-190. [PMID: 34533450 DOI: 10.2174/1871527320666210917142815] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 08/09/2021] [Accepted: 08/12/2021] [Indexed: 12/16/2022]
Abstract
BACKGROUND & OBJECTIVE We have previously identified aberrant connectivity of the left precuneus, ventrolateral prefrontal cortex, anterior cingulate cortex, and anterior insula in patients with either a paranoid (schizophrenia), or a depressive syndrome (both unipolar and bipolar). In the current study, we attempted to replicate and expand these findings by including a healthy control sample and separating the patients in a depressive episode into two groups: unipolar and bipolar depression. We hypothesized that the connections between those major nodes of the resting state networks would demonstrate different patterns in the three patient groups compared to the healthy subjects. METHODS Resting-state functional MRI was performed on a sample of 101 participants, of which 26 patients with schizophrenia (current psychotic episodes), 24 subjects with Bipolar Disorder (BD), 33 with Major Depressive Disorder (MDD) (both BD and MDD patients were in a current depressive episode), and 21 healthy controls. Spectral Dynamic Causal Modeling was used to calculate the coupling values between eight regions of interest, including the anterior precuneus (PRC), anterior hippocampus, anterior insula, angular gyrus, lateral Orbitofrontal Cortex (OFC), middle frontal gyrus, planum temporale, and anterior thalamus. RESULTS & CONCLUSION We identified disturbed effective connectivity from the left lateral orbitofrontal cortex to the left anterior precuneus that differed significantly between unipolar depression, where the influence was inhibitory, and bipolar depression, where the effect was excitatory. A logistic regression analysis correctly classified 75% of patients with unipolar and bipolar depression based solely on the coupling values of this connection. In addition, patients with schizophrenia demonstrated negative effective connectivity from the anterior PRC to the lateral OFC, which distinguished them from healthy controls and patients with major depression. Future studies with unmedicated patients will be needed to establish the replicability of our findings.
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Affiliation(s)
- Sevdalina Kandilarova
- Department of Psychiatry and Medical Psychology, Medical University-Plovdiv, Plovdiv, Bulgaria
- Division of Translational Neuroscience, Research Institute at Medical University-Plovdiv, Plovdiv, Bulgaria
| | - Drozdstoy Stoyanov
- Department of Psychiatry and Medical Psychology, Medical University-Plovdiv, Plovdiv, Bulgaria
- Division of Translational Neuroscience, Research Institute at Medical University-Plovdiv, Plovdiv, Bulgaria
| | - Katrin Aryutova
- Department of Psychiatry and Medical Psychology, Medical University-Plovdiv, Plovdiv, Bulgaria
- Division of Translational Neuroscience, Research Institute at Medical University-Plovdiv, Plovdiv, Bulgaria
| | - Rossitsa Paunova
- Department of Psychiatry and Medical Psychology, Medical University-Plovdiv, Plovdiv, Bulgaria
- Division of Translational Neuroscience, Research Institute at Medical University-Plovdiv, Plovdiv, Bulgaria
| | - Mladen Mantarkov
- Department of Psychiatry and Medical Psychology, Medical University-Plovdiv, Plovdiv, Bulgaria
| | - Ivo Mitrev
- Department of Psychiatry and Medical Psychology, Medical University-Plovdiv, Plovdiv, Bulgaria
| | - Anna Todeva-Radneva
- Department of Psychiatry and Medical Psychology, Medical University-Plovdiv, Plovdiv, Bulgaria
- Division of Translational Neuroscience, Research Institute at Medical University-Plovdiv, Plovdiv, Bulgaria
| | - Karsten Specht
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway
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24
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Fromm S, Katthagen T, Deserno L, Heinz A, Kaminski J, Schlagenhauf F. Belief Updating in Subclinical and Clinical Delusions. SCHIZOPHRENIA BULLETIN OPEN 2023; 4:sgac074. [PMID: 39145350 PMCID: PMC11207849 DOI: 10.1093/schizbullopen/sgac074] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 08/16/2024]
Abstract
Background and Hypothesis Current frameworks propose that delusions result from aberrant belief updating due to altered prediction error (PE) signaling and misestimation of environmental volatility. We aimed to investigate whether behavioral and neural signatures of belief updating are specifically related to the presence of delusions or generally associated with manifest schizophrenia. Methods Our cross-sectional design includes human participants (n[female/male] = 66[25/41]), stratified into four groups: healthy participants with minimal (n = 22) or strong delusional-like ideation (n = 18), and participants with diagnosed schizophrenia with minimal (n = 13) or strong delusions (n = 13), resulting in a 2 × 2 design, which allows to test for the effects of delusion and diagnosis. Participants performed a reversal learning task with stable and volatile task contingencies during fMRI scanning. We formalized learning with a hierarchical Gaussian filter model and conducted model-based fMRI analysis regarding beliefs of outcome uncertainty and volatility, precision-weighted PEs of the outcome- and the volatility-belief. Results Patients with schizophrenia as compared to healthy controls showed lower accuracy and heightened choice switching, while delusional ideation did not affect these measures. Participants with delusions showed increased precision-weighted PE-related neural activation in fronto-striatal regions. People with diagnosed schizophrenia overestimated environmental volatility and showed an attenuated neural representation of volatility in the anterior insula, medial frontal and angular gyrus. Conclusions Delusional beliefs are associated with altered striatal PE-signals. Juxtaposing, the potentially unsettling belief that the environment is constantly changing and weaker neural encoding of this subjective volatility seems to be associated with manifest schizophrenia, but not with the presence of delusional ideation.
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Affiliation(s)
- Sophie Fromm
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health CCM, Department of Psychiatry and Neuroscience | CCM, NeuroCure Clinical Research Center, Berlin, Germany
- Charité – Universitätsmedizin Berlin, Einstein Center for Neurosciences Berlin, Berlin, Germany
- Bernstein Center for Computational Neuroscience, Berlin, Germany
- Department of Psychology, Humboldt-Universität zu Berlin, Germany
| | - Teresa Katthagen
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health CCM, Department of Psychiatry and Neuroscience | CCM, NeuroCure Clinical Research Center, Berlin, Germany
| | - Lorenz Deserno
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Würzburg, Würzburg, Germany
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Department of Psychiatry and Psychotherapy, Technische Universität, Dresden, Germany
| | - Andreas Heinz
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health CCM, Department of Psychiatry and Neuroscience | CCM, NeuroCure Clinical Research Center, Berlin, Germany
- Charité – Universitätsmedizin Berlin, Einstein Center for Neurosciences Berlin, Berlin, Germany
- Bernstein Center for Computational Neuroscience, Berlin, Germany
| | - Jakob Kaminski
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health CCM, Department of Psychiatry and Neuroscience | CCM, NeuroCure Clinical Research Center, Berlin, Germany
| | - Florian Schlagenhauf
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health CCM, Department of Psychiatry and Neuroscience | CCM, NeuroCure Clinical Research Center, Berlin, Germany
- Charité – Universitätsmedizin Berlin, Einstein Center for Neurosciences Berlin, Berlin, Germany
- Bernstein Center for Computational Neuroscience, Berlin, Germany
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25
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Atypical prediction error learning is associated with prodromal symptoms in individuals at clinical high risk for psychosis. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2022; 8:105. [PMID: 36433979 PMCID: PMC9700713 DOI: 10.1038/s41537-022-00302-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 10/20/2022] [Indexed: 11/27/2022]
Abstract
Reductions in the auditory mismatch negativity (MMN) have been well-demonstrated in schizophrenia rendering it a promising biomarker for understanding the emergence of psychosis. According to the predictive coding theory of psychosis, MMN impairments may reflect disturbances in hierarchical information processing driven by maladaptive precision-weighted prediction errors (pwPEs) and enhanced belief updating. We applied a hierarchical Bayesian model of learning to single-trial EEG data from an auditory oddball paradigm in 31 help-seeking antipsychotic-naive high-risk individuals and 23 healthy controls to understand the computational mechanisms underlying the auditory MMN. We found that low-level sensory and high-level volatility pwPE expression correlated with EEG amplitudes, coinciding with the timing of the MMN. Furthermore, we found that prodromal positive symptom severity was associated with increased expression of sensory pwPEs and higher-level belief uncertainty. Our findings provide support for the role of pwPEs in auditory MMN generation, and suggest that increased sensory pwPEs driven by changes in belief uncertainty may render the environment seemingly unpredictable. This may predispose high-risk individuals to delusion-like ideation to explain this experience. These results highlight the value of computational models for understanding the pathophysiological mechanisms of psychosis.
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26
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Al-Musawi AF, Al-Hakeim HK, Al-Khfaji ZA, Al-Haboby IH, Almulla AF, Stoyanov DS, Maes M. In Schizophrenia, the Effects of the IL-6/IL-23/Th17 Axis on Health-Related Quality of Life and Disabilities Are Partly Mediated by Generalized Cognitive Decline and the Symptomatome. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:15281. [PMID: 36429996 PMCID: PMC9690590 DOI: 10.3390/ijerph192215281] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 10/31/2022] [Accepted: 11/15/2022] [Indexed: 05/08/2023]
Abstract
Schizophrenia patients show increased disabilities and lower quality of life (DisQoL). Nevertheless, there are no data on whether the activation of the interleukin (IL)-6, IL-23, T helper (Th)-17 axis, and lower magnesium and calcium levels impact DisQoL scores. This study recruited 90 patients with schizophrenia (including 40 with deficit schizophrenia) and 40 healthy controls and assessed the World Health Association QoL instrument-Abbreviated version and Sheehan Disability scale, Brief Assessment of Cognition in Schizophrenia (BACS), IL-6, IL-23, IL-17, IL-21, IL-22, tumor necrosis factor (TNF)-α, magnesium and calcium. Regression analyses showed that a large part of the first factor extracted from the physical, psychological, social and environmental HR-QoL and interference with school/work, social life, and home responsibilities was predicted by a generalized cognitive deterioration (G-CoDe) index (a latent vector extracted from BACs scores), and the first vector extracted from various symptom domains ("symptomatome"), whereas the biomarkers had no effects. Partial Least Squares analysis showed that the IL6IL23Th17 axis and magnesium/calcium had highly significant total (indirect + direct) effects on HR-QoL/disabilities, which were mediated by G-CoDe and the symptomatome (a first factor extracted from negative and positive symptoms). The IL6IL23Th17 axis explained 63.1% of the variance in the behavioral-cognitive-psycho-social (BCPS) worsening index a single latent trait extracted from G-CoDe, symptomatome, HR-QoL and disability data. In summary, the BCPS worsening index is partly caused by the neuroimmunotoxic effects of the IL6IL23Th17 axis in subjects with lowered antioxidant defenses (magnesium and calcium), thereby probably damaging the neuronal circuits that may underpin deficit schizophrenia.
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Affiliation(s)
- Ali Fattah Al-Musawi
- Department of Clinical Pharmacy and Laboratory Sciences, College of Pharmacy, University of Al-Kafeel, Kufa 54001, Iraq
| | | | - Zahraa Abdulrazaq Al-Khfaji
- Department of Pharmacology, Toxicology and Clinical Pharmacy, Al-Zahraa University for Women, Karbala 56001, Iraq
| | | | - Abbas F. Almulla
- Medical Laboratory Technology Department, College of Medical Technology, The Islamic University, Najaf 54001, Iraq
- Department of Psychiatry, Faculty of Medicine, Chulalongkorn University, PathumWan, Bangkok 10330, Thailand
| | - Drozdstoj St. Stoyanov
- Department of Psychiatry, Medical University of Plovdiv, 4000 Plovdiv, Bulgaria
- Research Institute, Medical University of Plovdiv, 4000 Plovdiv, Bulgaria
| | - Michael Maes
- Department of Psychiatry, Faculty of Medicine, Chulalongkorn University, PathumWan, Bangkok 10330, Thailand
- Department of Psychiatry, Medical University of Plovdiv, 4000 Plovdiv, Bulgaria
- Research Institute, Medical University of Plovdiv, 4000 Plovdiv, Bulgaria
- IMPACT, School of Medicine, Barwon Health, The Institute for Mental and Physical Health and Clinical Translation, Deakin University, Geelong 3217, Australia
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27
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Zeng J, Yan J, Cao H, Su Y, Song Y, Luo Y, Yang X. Neural substrates of reward anticipation and outcome in schizophrenia: a meta-analysis of fMRI findings in the monetary incentive delay task. Transl Psychiatry 2022; 12:448. [PMID: 36244990 PMCID: PMC9573872 DOI: 10.1038/s41398-022-02201-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Revised: 09/21/2022] [Accepted: 09/22/2022] [Indexed: 01/10/2023] Open
Abstract
Dysfunction of the mesocorticolimbic dopaminergic reward system is a core feature of schizophrenia (SZ), yet its precise contributions to different stages of reward processing and their relevance to disease symptomology are not fully understood. We performed a coordinate-based meta-analysis, using the monetary incentive delay task, to identify which brain regions are implicated in different reward phases in functional magnetic resonance imaging in SZ. A total of 17 studies (368 SZ and 428 controls) were included in the reward anticipation, and 10 studies (229 SZ and 281 controls) were included in the reward outcome. Our meta-analysis revealed that during anticipation, patients showed hypoactivation in the striatum, anterior cingulate cortex, median cingulate cortex (MCC), amygdala, precentral gyrus, and superior temporal gyrus compared with controls. Striatum hypoactivation was negatively associated with negative symptoms and positively associated with the proportion of second-generation antipsychotic users (percentage of SGA users). During outcome, patients displayed hyperactivation in the striatum, insula, amygdala, hippocampus, parahippocampal gyrus, cerebellum, postcentral gyrus, and MCC, and hypoactivation in the dorsolateral prefrontal cortex (DLPFC) and medial prefrontal cortex (mPFC). Hypoactivity of mPFC during outcome was negatively associated with positive symptoms. Moderator analysis showed that the percentage of SGA users was a significant moderator of the association between symptom severity and brain activity in both the anticipation and outcome stages. Our findings identified the neural substrates for different reward phases in SZ and may help explain the neuropathological mechanisms underlying reward processing deficits in the disorder.
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Affiliation(s)
- Jianguang Zeng
- grid.190737.b0000 0001 0154 0904School of Economics and Business Administration, Chongqing University, Chongqing, 400044 China
| | - Jiangnan Yan
- grid.190737.b0000 0001 0154 0904School of Economics and Business Administration, Chongqing University, Chongqing, 400044 China
| | - Hengyi Cao
- grid.250903.d0000 0000 9566 0634Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Hempstead, NY USA ,grid.440243.50000 0004 0453 5950Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY USA
| | - Yueyue Su
- grid.190737.b0000 0001 0154 0904School of Public Affairs, Chongqing University, Chongqing, 400044 China
| | - Yuan Song
- grid.190737.b0000 0001 0154 0904School of Public Affairs, Chongqing University, Chongqing, 400044 China
| | - Ya Luo
- grid.412901.f0000 0004 1770 1022Department of Psychiatry, State Key Lab of Biotherapy, West China Hospital of Sichuan University, Chengdu, 610041 China
| | - Xun Yang
- School of Public Affairs, Chongqing University, Chongqing, 400044, China.
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28
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Menon V, Palaniyappan L, Supekar K. Integrative Brain Network and Salience Models of Psychopathology and Cognitive Dysfunction in Schizophrenia. Biol Psychiatry 2022:S0006-3223(22)01637-7. [PMID: 36702660 DOI: 10.1016/j.biopsych.2022.09.029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 08/09/2022] [Accepted: 09/06/2022] [Indexed: 01/28/2023]
Abstract
Brain network models of cognitive control are central to advancing our understanding of psychopathology and cognitive dysfunction in schizophrenia. This review examines the role of large-scale brain organization in schizophrenia, with a particular focus on a triple-network model of cognitive control and its role in aberrant salience processing. First, we provide an overview of the triple network involving the salience, frontoparietal, and default mode networks and highlight the central role of the insula-anchored salience network in the aberrant mapping of salient external and internal events in schizophrenia. We summarize the extensive evidence that has emerged from structural, neurochemical, and functional brain imaging studies for aberrancies in these networks and their dynamic temporal interactions in schizophrenia. Next, we consider the hypothesis that atypical striatal dopamine release results in misattribution of salience to irrelevant external stimuli and self-referential mental events. We propose an integrated triple-network salience-based model incorporating striatal dysfunction and sensitivity to perceptual and cognitive prediction errors in the insula node of the salience network and postulate that dysregulated dopamine modulation of salience network-centered processes contributes to the core clinical phenotype of schizophrenia. Thus, a powerful paradigm to characterize the neurobiology of schizophrenia emerges when we combine conceptual models of salience with large-scale cognitive control networks in a unified manner. We conclude by discussing potential therapeutic leads on restoring brain network dysfunction in schizophrenia.
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Affiliation(s)
- Vinod Menon
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California; Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California; Wu Tsai Neurosciences Institute, Stanford University School of Medicine, Stanford, California.
| | - Lena Palaniyappan
- Department of Psychiatry and Robarts Research Institute, University of Western Ontario, London, Ontario, Canada; Lawson Health Research Institute, London, Ontario, Canada; Douglas Mental Health University Institute, Montreal, Quebec, Canada; Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Kaustubh Supekar
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California; Wu Tsai Neurosciences Institute, Stanford University School of Medicine, Stanford, California
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29
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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: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [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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30
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The sense of agency for brain disorders: A comprehensive review and proposed framework. Neurosci Biobehav Rev 2022; 139:104759. [PMID: 35780975 DOI: 10.1016/j.neubiorev.2022.104759] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Revised: 06/24/2022] [Accepted: 06/26/2022] [Indexed: 11/21/2022]
Abstract
Sense of Agency (SoA) refers to the feeling of control over voluntary actions and the outcomes of those actions. Several brain disorders are characterized by an abnormal SoA. To date, there is no robust treatment for aberrant agency across disorders; this is, in large part, due to gaps in our understanding of the cognitive mechanisms and neural correlates of the SoA. This apparent gap stems from a lack of synthesis in established findings. As such, the current review reconciles previously established findings into a novel neurocognitive framework for future investigations of the SoA in brain disorders, which we term the Agency in Brain Disorders Framework (ABDF). In doing so, we highlight key top-down and bottom-up cues that contribute to agency prospectively (i.e., prior to action execution) and retrospectively (i.e., after action execution). We then examine brain disorders, including schizophrenia, autism spectrum disorders (ASD), obsessive-compulsive disorders (OCD), and cortico-basal syndrome (CBS), within the ABDF, to demonstrate its potential utility in investigating neurocognitive mechanisms underlying phenotypically variable presentations of the SoA in brain disorders.
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31
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Leighton E, Garrett M, Beltrani A, Min JY, Schilder V. Capgras Syndrome and Other Delusions of Misidentification: a Summary of the Psychological, Psychiatric, and Neurophysiological Literature on DMI. Curr Behav Neurosci Rep 2022. [DOI: 10.1007/s40473-022-00248-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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32
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Fouladirad S, Chen LV, Roes M, Chinchani A, Percival C, Khangura J, Zahid H, Moscovitz A, Arreaza L, Wun C, Sanford N, Balzan R, Moritz S, Menon M, Woodward TS. Functional brain networks underlying probabilistic reasoning and delusions in schizophrenia. Psychiatry Res Neuroimaging 2022; 323:111472. [PMID: 35405574 DOI: 10.1016/j.pscychresns.2022.111472] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 02/20/2022] [Accepted: 03/28/2022] [Indexed: 10/18/2022]
Abstract
Delusions in schizophrenia are false beliefs that are assigned certainty and not afforded the scrutiny that normally gives rise to doubt, even under conditions of weak evidence. The goal of the current functional magnetic resonance imaging (fMRI) study is to identify the brain network(s) involved in gathering information under conditions of weak evidence, in people with schizophrenia experiencing delusions. fMRI activity during probabilistic reasoning in people with schizophrenia experiencing delusions (n = 29) compared to people with schizophrenia not experiencing delusions (n = 41) and healthy controls (n = 41) was observed when participants made judgments based on evidence that weakly or strongly matched (or mismatched) with the focal hypothesis. A brain network involved in visual attention was strongly elicited for conditions of weak evidence for healthy controls and patients not experiencing delusions, but this increase was absent for patients experiencing delusions. This suggests that the state associated with delusions manifests in fMRI as reduced activity in an early visual attentional process whereby weak evidence is incorrectly stamped as conclusive, manifestating as a feeling of fluency and misplaced certainty, short-circuiting the search for evidence, and providing a candidate neural process for 'seeding' delusions.
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Affiliation(s)
- Saman Fouladirad
- BC Mental Health and Substance Use Services, Vancouver, BC, Canada; Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Linda V Chen
- BC Mental Health and Substance Use Services, Vancouver, BC, Canada; Faculty of Science, University of British Columbia, Vancouver, BC, Canada
| | - Meighen Roes
- BC Mental Health and Substance Use Services, Vancouver, BC, Canada; Department of Psychology, University of British Columbia, Vancouver, BC, Canada
| | - Abhijit Chinchani
- BC Mental Health and Substance Use Services, Vancouver, BC, Canada; Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Chantal Percival
- BC Mental Health and Substance Use Services, Vancouver, BC, Canada; Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Jessica Khangura
- BC Mental Health and Substance Use Services, Vancouver, BC, Canada; Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Hafsa Zahid
- Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada
| | - Aly Moscovitz
- BC Mental Health and Substance Use Services, Vancouver, BC, Canada; Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Leonardo Arreaza
- BC Mental Health and Substance Use Services, Vancouver, BC, Canada; Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Charlotte Wun
- BC Mental Health and Substance Use Services, Vancouver, BC, Canada; Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Nicole Sanford
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Ryan Balzan
- College of Education, Psychology & Social Work, Flinders University, Adelaide, SA, Australia
| | - Steffen Moritz
- Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Mahesh Menon
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Todd S Woodward
- BC Mental Health and Substance Use Services, Vancouver, BC, Canada; Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada.
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Rethinking delusions: A selective review of delusion research through a computational lens. Schizophr Res 2022; 245:23-41. [PMID: 33676820 PMCID: PMC8413395 DOI: 10.1016/j.schres.2021.01.023] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2020] [Revised: 01/27/2021] [Accepted: 01/29/2021] [Indexed: 02/06/2023]
Abstract
Delusions are rigid beliefs held with high certainty despite contradictory evidence. Notwithstanding decades of research, we still have a limited understanding of the computational and neurobiological alterations giving rise to delusions. In this review, we highlight a selection of recent work in computational psychiatry aimed at developing quantitative models of inference and its alterations, with the goal of providing an explanatory account for the form of delusional beliefs in psychosis. First, we assess and evaluate the experimental paradigms most often used to study inferential alterations in delusions. Based on our review of the literature and theoretical considerations, we contend that classic draws-to-decision paradigms are not well-suited to isolate inferential processes, further arguing that the commonly cited 'jumping-to-conclusion' bias may reflect neither delusion-specific nor inferential alterations. Second, we discuss several enhancements to standard paradigms that show promise in more effectively isolating inferential processes and delusion-related alterations therein. We further draw on our recent work to build an argument for a specific failure mode for delusions consisting of prior overweighting in high-level causal inferences about partially observable hidden states. Finally, we assess plausible neurobiological implementations for this candidate failure mode of delusional beliefs and outline promising future directions in this area.
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Haarsma J, Kok P, Browning M. The promise of layer-specific neuroimaging for testing predictive coding theories of psychosis. Schizophr Res 2022; 245:68-76. [PMID: 33199171 PMCID: PMC9241988 DOI: 10.1016/j.schres.2020.10.009] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Revised: 10/03/2020] [Accepted: 10/28/2020] [Indexed: 12/24/2022]
Abstract
Predictive coding potentially provides an explanatory model for understanding the neurocognitive mechanisms of psychosis. It proposes that cognitive processes, such as perception and inference, are implemented by a hierarchical system, with the influence of each level being a function of the estimated precision of beliefs at that level. However, predictive coding models of psychosis are insufficiently constrained-any phenomenon can be explained in multiple ways by postulating different changes to precision at different levels of processing. One reason for the lack of constraint in these models is that the core processes are thought to be implemented by the function of specific cortical layers, and the technology to measure layer specific neural activity in humans has until recently been lacking. As a result, our ability to constrain the models with empirical data has been limited. In this review we provide a brief overview of predictive processing models of psychosis and then describe the potential for newly developed, layer specific neuroimaging techniques to test and thus constrain these models. We conclude by discussing the most promising avenues for this research as well as the technical and conceptual challenges which may limit its application.
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Affiliation(s)
- J. Haarsma
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom,Department of Psychiatry, University of Oxford, Oxford, United Kingdom,Corresponding author at: Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom.
| | - P. Kok
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom
| | - M. Browning
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom,Oxford Health NHS Trust, Oxford, United Kingdom
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Seitz BM, Hoang IB, DiFazio LE, Blaisdell AP, Sharpe MJ. Dopamine errors drive excitatory and inhibitory components of backward conditioning in an outcome-specific manner. Curr Biol 2022; 32:3210-3218.e3. [PMID: 35752165 DOI: 10.1016/j.cub.2022.06.035] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Revised: 04/29/2022] [Accepted: 06/13/2022] [Indexed: 01/06/2023]
Abstract
For over two decades, phasic activity in midbrain dopamine neurons was considered synonymous with the prediction error in temporal-difference reinforcement learning.1-4 Central to this proposal is the notion that reward-predictive stimuli become endowed with the scalar value of predicted rewards. When these cues are subsequently encountered, their predictive value is compared to the value of the actual reward received, allowing for the calculation of prediction errors.5,6 Phasic firing of dopamine neurons was proposed to reflect this computation,1,2 facilitating the backpropagation of value from the predicted reward to the reward-predictive stimulus, thus reducing future prediction errors. There are two critical assumptions of this proposal: (1) that dopamine errors can only facilitate learning about scalar value and not more complex features of predicted rewards, and (2) that the dopamine signal can only be involved in anticipatory cue-reward learning in which cues or actions precede rewards. Recent work7-15 has challenged the first assumption, demonstrating that phasic dopamine signals across species are involved in learning about more complex features of the predicted outcomes, in a manner that transcends this value computation. Here, we tested the validity of the second assumption. Specifically, we examined whether phasic midbrain dopamine activity would be necessary for backward conditioning-when a neutral cue reliably follows a rewarding outcome.16-20 Using a specific Pavlovian-to-instrumental transfer (PIT) procedure,21-23 we show rats learn both excitatory and inhibitory components of a backward association, and that this association entails knowledge of the specific identity of the reward and cue. We demonstrate that brief optogenetic inhibition of VTADA neurons timed to the transition between the reward and cue reduces both of these components of backward conditioning. These findings suggest VTADA neurons are capable of facilitating associations between contiguously occurring events, regardless of the content of those events. We conclude that these data may be in line with suggestions that the VTADA error acts as a universal teaching signal. This may provide insight into why dopamine function has been implicated in myriad psychological disorders that are characterized by very distinct reinforcement-learning deficits.
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Affiliation(s)
- Benjamin M Seitz
- Department of Psychology, University of California, Los Angeles, Portola Plaza, Los Angeles, CA 91602, USA
| | - Ivy B Hoang
- Department of Psychology, University of California, Los Angeles, Portola Plaza, Los Angeles, CA 91602, USA
| | - Lauren E DiFazio
- Department of Psychology, University of California, Los Angeles, Portola Plaza, Los Angeles, CA 91602, USA
| | - Aaron P Blaisdell
- Department of Psychology, University of California, Los Angeles, Portola Plaza, Los Angeles, CA 91602, USA
| | - Melissa J Sharpe
- Department of Psychology, University of California, Los Angeles, Portola Plaza, Los Angeles, CA 91602, USA.
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Adam Yaple Z, Tolomeo S, Yu R. Spatial and chronic differences in neural activity in medicated and unmedicated schizophrenia patients. Neuroimage Clin 2022; 35:103029. [PMID: 35569228 PMCID: PMC9112098 DOI: 10.1016/j.nicl.2022.103029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 04/10/2022] [Accepted: 04/28/2022] [Indexed: 11/07/2022]
Abstract
The medicated schizophrenia group yielded concordant activity among three right lateralized frontal clusters and a left lateralized parietal cluster. The unmedicated schizophrenia group yielded concordant activity among right lateralized frontal-parietal regions. A neural compensatory mechanism in schizophrenia.
A major caveat with investigations on schizophrenic patients is the difficulty to control for medication usage across samples as disease-related neural differences may be confounded by medication usage. Following a thorough literature search (632 records identified), we included 37 studies with a total of 740 medicated schizophrenia patients and 367 unmedicated schizophrenia patients. Here, we perform several meta-analyses to assess the neurofunctional differences between medicated and unmedicated schizophrenic patients across fMRI studies to determine systematic regions associated with medication usage. Several clusters identified by the meta-analysis on the medicated group include three right lateralized frontal clusters and a left lateralized parietal cluster, whereas the unmedicated group yielded concordant activity among right lateralized frontal-parietal regions. We further explored the prevalence of activity within these regions across illness duration and task type. These findings suggest a neural compensatory mechanism across these regions both spatially and chronically, offering new insight into the spatial and temporal dynamic neural differences among medicated and unmedicated schizophrenia patients.
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Affiliation(s)
| | - Serenella Tolomeo
- Social and Cognitive Computing Department, Institute of High Performance Computing, Agency for Science, Technology and Research, Singapore, Singapore
| | - Rongjun Yu
- Department of Management, Hong Kong Baptist University, Hong Kong, China; Department of Sport, Physical Education and Health, Hong Kong Baptist University, Hong Kong, China; Department of Physics, Hong Kong Baptist University, Hong Kong, China.
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Louzolo A, Almeida R, Guitart-Masip M, Björnsdotter M, Lebedev A, Ingvar M, Olsson A, Petrovic P. Enhanced Instructed Fear Learning in Delusion-Proneness. Front Psychol 2022; 13:786778. [PMID: 35496229 PMCID: PMC9043131 DOI: 10.3389/fpsyg.2022.786778] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 01/04/2022] [Indexed: 11/20/2022] Open
Abstract
Psychosis is associated with distorted perceptions and deficient bottom-up learning such as classical fear conditioning. This has been interpreted as reflecting imprecise priors in low-level predictive coding systems. Paradoxically, overly strong beliefs, such as overvalued beliefs and delusions, are also present in psychosis-associated states. In line with this, research has suggested that patients with psychosis and associated phenotypes rely more on high-order priors to interpret perceptual input. In this behavioural and fMRI study we studied two types of fear learning, i.e., instructed fear learning mediated by verbal suggestions about fear contingencies and classical fear conditioning mediated by low level associative learning, in delusion proneness-a trait in healthy individuals linked to psychotic disorders. Subjects were shown four faces out of which two were coupled with an aversive stimulation (CS+) while two were not (CS-) in a fear conditioning procedure. Before the conditioning, subjects were informed about the contingencies for two of the faces of each type, while no information was given for the two other faces. We could thereby study the effect of both classical fear conditioning and instructed fear learning. Our main outcome variable was evaluative rating of the faces. Simultaneously, fMRI-measurements were performed to study underlying mechanisms. We postulated that instructed fear learning, measured with evaluative ratings, is stronger in psychosis-related phenotypes, in contrast to classical fear conditioning that has repeatedly been shown to be weaker in these groups. In line with our hypothesis, we observed significantly larger instructed fear learning on a behavioural level in delusion-prone individuals (n = 20) compared to non-delusion-prone subjects (n = 23; n = 20 in fMRI study). Instructed fear learning was associated with a bilateral activation of lateral orbitofrontal cortex that did not differ significantly between groups. However, delusion-prone subjects showed a stronger functional connectivity between right lateral orbitofrontal cortex and regions processing fear and pain. Our results suggest that psychosis-related states are associated with a strong instructed fear learning in addition to previously reported weak classical fear conditioning. Given the similarity between nocebo paradigms and instructed fear learning, our results also have an impact on understanding why nocebo effects differ between individuals.
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Affiliation(s)
- Anaïs Louzolo
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Rita Almeida
- Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Marc Guitart-Masip
- Department of Neurobiology, Care Science and Society, Karolinska Institutet, Stockholm, Sweden
| | - Malin Björnsdotter
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Alexander Lebedev
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Martin Ingvar
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Andreas Olsson
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Predrag Petrovic
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
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Duerler P, Vollenweider FX, Preller KH. A neurobiological perspective on social influence: Serotonin and social adaptation. J Neurochem 2022; 162:60-79. [PMID: 35274296 PMCID: PMC9322456 DOI: 10.1111/jnc.15607] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Revised: 02/26/2022] [Accepted: 03/02/2022] [Indexed: 01/09/2023]
Abstract
Humans are inherently social beings. Being suggestible to each other's expectations enables pro-social skills that are crucial for social learning and adaptation. Despite its high relevance for psychiatry, the neurobiological mechanisms underlying social adaptation are still not well understood. This review therefore provides a conceptual framework covering various distinct mechanisms underlying social adaptation and explores the neuropharmacology - in particular the role of the serotonin (5-HT) system - modulating these mechanisms. This article therefore reviews empirical results on social influence processing and reconciles them with recent findings from psychedelic research on social processing to elucidate neurobiological and neuropharmacological underpinnings of social adaptation. Various computational, neurobiological, and neurochemical processes are involved in distinct mechanisms underlying social adaptation such as the multisensory process of social information integration that is crucial for the forming of self-representation and representations of social norms. This is again associated with self- and other-perception during social interactions as well as value-based decision making that guides our behaviour in daily interactions. We highlight the critical role of 5-HT in these processes and suggest that 5-HT can facilitate social learning and may represent an important target for treating psychiatric disorders characterized by impairments in social functioning. This framework also has important implications for psychedelic-assisted therapy as well as for the development of novel treatment approaches and future research directions.
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Affiliation(s)
- Patricia Duerler
- Neuropsychopharmacology and Brain Imaging, Department of Psychiatry, Psychotherapy and Psychosomatics, University Hospital for Psychiatry Zurich, Lenggstr. 31, Zurich, Switzerland
| | - Franz X Vollenweider
- Neuropsychopharmacology and Brain Imaging, Department of Psychiatry, Psychotherapy and Psychosomatics, University Hospital for Psychiatry Zurich, Lenggstr. 31, Zurich, Switzerland
| | - Katrin H Preller
- Neuropsychopharmacology and Brain Imaging, Department of Psychiatry, Psychotherapy and Psychosomatics, University Hospital for Psychiatry Zurich, Lenggstr. 31, Zurich, Switzerland
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Khaleghi A, Mohammadi MR, Shahi K, Nasrabadi AM. Computational Neuroscience Approach to Psychiatry: A Review on Theory-driven Approaches. CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE 2022; 20:26-36. [PMID: 35078946 PMCID: PMC8813324 DOI: 10.9758/cpn.2022.20.1.26] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Revised: 06/09/2021] [Accepted: 06/14/2021] [Indexed: 11/21/2022]
Abstract
Translating progress in neuroscience into clinical benefits for patients with psychiatric disorders is challenging because it involves the brain as the most complex organ and its interaction with a complex environment and condition. Dealing with such complexity requires powerful techniques. Computational neuroscience approach to psychiatry integrates multiple levels and types of simulation, analysis and computation according to the different types of computational models to enhance comprehending, prediction and treatment of psychiatric disorder. This approach comprises two approaches: theory-driven and data-driven. In this review, we focus on recent advances in theory-driven approaches that mathematically and mechanistically examine the relationships between disorder-related changes and behavior at different level of brain organization. We discuss recent progresses in computational neuroscience models that relate to psychiatry and show how principles of neural computational modeling can be employed to explain psychopathology.
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Affiliation(s)
- Ali Khaleghi
- Psychiatry and Psychology Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad Reza Mohammadi
- Psychiatry and Psychology Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Kian Shahi
- Psychiatry and Psychology Research Center, Tehran University of Medical Sciences, Tehran, Iran
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Millard SJ, Bearden CE, Karlsgodt KH, Sharpe MJ. The prediction-error hypothesis of schizophrenia: new data point to circuit-specific changes in dopamine activity. Neuropsychopharmacology 2022; 47:628-640. [PMID: 34588607 PMCID: PMC8782867 DOI: 10.1038/s41386-021-01188-y] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 08/23/2021] [Accepted: 09/07/2021] [Indexed: 02/07/2023]
Abstract
Schizophrenia is a severe psychiatric disorder affecting 21 million people worldwide. People with schizophrenia suffer from symptoms including psychosis and delusions, apathy, anhedonia, and cognitive deficits. Strikingly, schizophrenia is characterised by a learning paradox involving difficulties learning from rewarding events, whilst simultaneously 'overlearning' about irrelevant or neutral information. While dysfunction in dopaminergic signalling has long been linked to the pathophysiology of schizophrenia, a cohesive framework that accounts for this learning paradox remains elusive. Recently, there has been an explosion of new research investigating how dopamine contributes to reinforcement learning, which illustrates that midbrain dopamine contributes in complex ways to reinforcement learning, not previously envisioned. This new data brings new possibilities for how dopamine signalling contributes to the symptomatology of schizophrenia. Building on recent work, we present a new neural framework for how we might envision specific dopamine circuits contributing to this learning paradox in schizophrenia in the context of models of reinforcement learning. Further, we discuss avenues of preclinical research with the use of cutting-edge neuroscience techniques where aspects of this model may be tested. Ultimately, it is hoped that this review will spur to action more research utilising specific reinforcement learning paradigms in preclinical models of schizophrenia, to reconcile seemingly disparate symptomatology and develop more efficient therapeutics.
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Affiliation(s)
- Samuel J. Millard
- grid.19006.3e0000 0000 9632 6718Department of Psychology, University of California, Los Angeles, CA 90095 USA
| | - Carrie E. Bearden
- grid.19006.3e0000 0000 9632 6718Department of Psychology, University of California, Los Angeles, CA 90095 USA ,grid.19006.3e0000 0000 9632 6718Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA 90095 USA
| | - Katherine H. Karlsgodt
- grid.19006.3e0000 0000 9632 6718Department of Psychology, University of California, Los Angeles, CA 90095 USA ,grid.19006.3e0000 0000 9632 6718Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA 90095 USA
| | - Melissa J. Sharpe
- grid.19006.3e0000 0000 9632 6718Department of Psychology, University of California, Los Angeles, CA 90095 USA
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Nielsen MØ, Rostrup E, Hilker R, Legind C, Anhøj S, Robbins TW, Sahakian BJ, Fagerlund B, Glenthøj B. Reward Processing as an Indicator of Vulnerability or Compensatory Resilience in Psychoses? Results From a Twin Study. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2022; 3:47-55. [PMID: 36712565 PMCID: PMC9874133 DOI: 10.1016/j.bpsgos.2022.01.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Revised: 01/04/2022] [Accepted: 01/06/2022] [Indexed: 02/01/2023] Open
Abstract
Background Findings of reward disturbances in unaffected relatives of patients with schizophrenia suggest reward disturbances as an endophenotype for schizophrenia. Twin studies, where 1 twin has been diagnosed with a schizophrenia spectrum disorder, can further explore this. Methods We used Danish registries to identify twin pairs with at least 1 twin having a schizophrenia spectrum disorder diagnosis and control twin pairs matched on age, sex, and zygosity. The analyses included data from 34 unaffected co-twins (16 females), 42 probands with schizophrenia spectrum disorder (17 females), and 83 control twins (42 females). Participants performed a modified incentive delay task during functional magnetic resonance imaging. Whole-brain group differences were analyzed by performing comparisons between co-twins and control twins. Correlations with cognitive flexibility were tested. Results Compared with control twins, co-twins showed no differences in striatal regions, but increased signal in the dorsolateral prefrontal cortex (DLPFC) during missed target contrast was observed. In co-twins, increased DLPFC signal was associated with lower intra-extra dimensional set-shifting scores indicative of higher cognitive flexibility. Conclusions Unaffected co-twins did not have decreased striatal activity during anticipation as previously reported for patients with schizophrenia. Instead, they showed increased activity in the DLPFC during evaluation of missed target contrast, which correlated with their level of cognitive flexibility. Unaffected co-twins had no diagnosis at a mean age of 40 years. This could indicate that greater cognitive flexibility and increased activity in the right DLPFC during processing of unexpected negative outcome represents a compensatory resilience mechanism in predisposed twins.
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Affiliation(s)
- Mette Ødegaard Nielsen
- Center for Neuropsychiatric Schizophrenia Research and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, Copenhagen, Denmark,Department of Clinical Medicine, Faculty of Health and Medical Science, University of Copenhagen, Copenhagen, Denmark,Address correspondence to Mette Ødegaard Nielsen, M.D., Ph.D.
| | - Egill Rostrup
- Center for Neuropsychiatric Schizophrenia Research and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, Copenhagen, Denmark,Functional Imaging Unit, Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, Glostrup, Denmark
| | - Rikke Hilker
- Center for Neuropsychiatric Schizophrenia Research and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, Copenhagen, Denmark,Department of Clinical Medicine, Faculty of Health and Medical Science, University of Copenhagen, Copenhagen, Denmark
| | - Christian Legind
- Center for Neuropsychiatric Schizophrenia Research and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, Copenhagen, Denmark,Department of Clinical Medicine, Faculty of Health and Medical Science, University of Copenhagen, Copenhagen, Denmark
| | - Simon Anhøj
- Center for Neuropsychiatric Schizophrenia Research and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, Copenhagen, Denmark
| | - Trevor William Robbins
- Department of Psychology, Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, United Kingdom
| | - Barbara J. Sahakian
- Department of Psychiatry, Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, United Kingdom
| | - Birgitte Fagerlund
- Center for Neuropsychiatric Schizophrenia Research and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, Copenhagen, Denmark,Department of Psychology, University of Copenhagen, Copenhagen, Denmark
| | - Birte Glenthøj
- Center for Neuropsychiatric Schizophrenia Research and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, Copenhagen, Denmark,Department of Clinical Medicine, Faculty of Health and Medical Science, University of Copenhagen, Copenhagen, Denmark
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Frydecka D, Misiak B, Piotrowski P, Bielawski T, Pawlak E, Kłosińska E, Krefft M, Al Noaimy K, Rymaszewska J, Moustafa AA, Drapała J. The Role of Dopaminergic Genes in Probabilistic Reinforcement Learning in Schizophrenia Spectrum Disorders. Brain Sci 2021; 12:brainsci12010007. [PMID: 35053751 PMCID: PMC8774082 DOI: 10.3390/brainsci12010007] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 11/30/2021] [Accepted: 12/19/2021] [Indexed: 12/27/2022] Open
Abstract
Schizophrenia spectrum disorders (SZ) are characterized by impairments in probabilistic reinforcement learning (RL), which is associated with dopaminergic circuitry encompassing the prefrontal cortex and basal ganglia. However, there are no studies examining dopaminergic genes with respect to probabilistic RL in SZ. Thus, the aim of our study was to examine the impact of dopaminergic genes on performance assessed by the Probabilistic Selection Task (PST) in patients with SZ in comparison to healthy control (HC) subjects. In our study, we included 138 SZ patients and 188 HC participants. Genetic analysis was performed with respect to the following genetic polymorphisms: rs4680 in COMT, rs907094 in DARP-32, rs2734839, rs936461, rs1800497, and rs6277 in DRD2, rs747302 and rs1800955 in DRD4 and rs28363170 and rs2975226 in DAT1 genes. The probabilistic RL task was completed by 59 SZ patients and 95 HC subjects. SZ patients performed significantly worse in acquiring reinforcement contingencies during the task in comparison to HCs. We found no significant association between genetic polymorphisms and RL among SZ patients; however, among HC participants with respect to the DAT1 rs28363170 polymorphism, individuals with 10-allele repeat genotypes performed better in comparison to 9-allele repeat carriers. The present study indicates the relevance of the DAT1 rs28363170 polymorphism in RL in HC participants.
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Affiliation(s)
- Dorota Frydecka
- Department of Psychiatry, Wroclaw Medical University, Pasteur Street 10, 50-367 Wroclaw, Poland; (T.B.); (M.K.); (K.A.N.); (J.R.)
- Correspondence:
| | - Błażej Misiak
- Department of Psychiatry, Division of Consultation Psychiatry and Neuroscience, Wroclaw Medical University, Pasteur Street 10, 50-367 Wroclaw, Poland; (B.M.); (P.P.)
| | - Patryk Piotrowski
- Department of Psychiatry, Division of Consultation Psychiatry and Neuroscience, Wroclaw Medical University, Pasteur Street 10, 50-367 Wroclaw, Poland; (B.M.); (P.P.)
| | - Tomasz Bielawski
- Department of Psychiatry, Wroclaw Medical University, Pasteur Street 10, 50-367 Wroclaw, Poland; (T.B.); (M.K.); (K.A.N.); (J.R.)
| | - Edyta Pawlak
- Department of Experimental Therapy, Institute of Immunology and Experimental Therapy, Polish Academy of Sciences, Weigel Street 12, 53-114 Wroclaw, Poland;
| | - Ewa Kłosińska
- Day-Care Psychiatric Unit, University Clinical Hospital, Pasteur Street 10, 50-367 Wroclaw, Poland;
| | - Maja Krefft
- Department of Psychiatry, Wroclaw Medical University, Pasteur Street 10, 50-367 Wroclaw, Poland; (T.B.); (M.K.); (K.A.N.); (J.R.)
| | - Kamila Al Noaimy
- Department of Psychiatry, Wroclaw Medical University, Pasteur Street 10, 50-367 Wroclaw, Poland; (T.B.); (M.K.); (K.A.N.); (J.R.)
| | - Joanna Rymaszewska
- Department of Psychiatry, Wroclaw Medical University, Pasteur Street 10, 50-367 Wroclaw, Poland; (T.B.); (M.K.); (K.A.N.); (J.R.)
| | - Ahmed A. Moustafa
- School of Psychology, Marcs Institute for Brain and Behaviour, Western Sydney University, Locked Bag 1797, Penrith, NSW 2751, Australia;
- Department of Human Anatomy and Physiology, The Faculty of Health Sciences, University of Johannesburg, Johannesburg 2006, South Africa
| | - Jarosław Drapała
- Department of Computer Science and Systems Engineering, Faculty of Information and Communication Technology, Wroclaw University of Science and Technology, Wybrzeze Wyspianskiego Street 27, 50-370 Wrocław, Poland;
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Kesby JP, Murray GK, Knolle F. Neural Circuitry of Salience and Reward Processing in Psychosis. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2021; 3:33-46. [PMID: 36712572 PMCID: PMC9874126 DOI: 10.1016/j.bpsgos.2021.12.003] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 11/25/2021] [Accepted: 12/01/2021] [Indexed: 02/01/2023] Open
Abstract
The processing of salient and rewarding stimuli is integral to engaging our attention, stimulating anticipation for future events, and driving goal-directed behaviors. Widespread impairments in these processes are observed in psychosis, which may be associated with worse functional outcomes or mechanistically linked to the development of symptoms. Here, we summarize the current knowledge of behavioral and functional neuroimaging in salience, prediction error, and reward. Although each is a specific process, they are situated in multiple feedback and feedforward systems integral to decision making and cognition more generally. We argue that the origin of salience and reward processing dysfunctions may be centered in the subcortex during the earliest stages of psychosis, with cortical abnormalities being initially more spared but becoming more prominent in established psychotic illness/schizophrenia. The neural circuits underpinning salience and reward processing may provide targets for delaying or preventing progressive behavioral and neurobiological decline.
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Affiliation(s)
- James P. Kesby
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia,QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia,Address correspondence to James Kesby, Ph.D.
| | - Graham K. Murray
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia,Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom,Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, United Kingdom
| | - Franziska Knolle
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom,Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany,Franziska Knolle, Ph.D.
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Culbreth AJ, Kasanova Z, Ross TJ, Salmeron BJ, Gold JM, Stein EA, Waltz JA. Schizophrenia Patients Show Largely Similar Salience Signaling Compared to Healthy Controls in an Observational Task Environment. Brain Sci 2021; 11:brainsci11121610. [PMID: 34942913 PMCID: PMC8699423 DOI: 10.3390/brainsci11121610] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Accepted: 11/30/2021] [Indexed: 11/30/2022] Open
Abstract
Recent evidence suggests that the aberrant signaling of salience is associated with psychotic illness. Salience, however, can take many forms in task environments. For example, salience may refer to any of the following: (1) the valence of an outcome, (2) outcomes that are unexpected, called reward prediction errors (PEs), or (3) cues associated with uncertain outcomes. Here, we measure brain responses to different forms of salience in the context of a passive PE-signaling task, testing whether patients with schizophrenia (SZ) showed aberrant signaling of particular types of salience. We acquired event-related MRI data from 29 SZ patients and 23 controls during the performance of a passive outcome prediction task. Across groups, we found that the anterior insula and posterior parietal cortices were activated to multiple different types of salience, including PE magnitude and heightened levels of uncertainty. However, BOLD activation to salient events was not significantly different between patients and controls in many regions, including the insula, posterior parietal cortices, and default mode network nodes. Such results suggest that deficiencies in salience processing in SZ may not result from an impaired ability to signal salience per se, but instead the ability to use such signals to guide future actions. Notably, no between-group differences were observed in BOLD signal changes associated with PE-signaling in the striatum. However, positive symptom severity was found to significantly correlate with the magnitudes of salience contrasts in default mode network nodes. Our results suggest that, in an observational environment, SZ patients may show an intact ability to activate striatal and cortical regions to rewarding and non-rewarding salient events. Furthermore, reduced deactivation of a hypothesized default mode network node for SZ participants with high levels of positive symptoms, following salient events, point to abnormalities in interactions of the salience network with other brain networks, and their potential importance to positive symptoms.
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Affiliation(s)
- Adam J. Culbreth
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD 21228, USA; (J.M.G.); (J.A.W.)
- Correspondence:
| | - Zuzana Kasanova
- Leuven Research & Development Spin-off & Innovation Unit, KU Leuven, Waaistraat 6-Box 5105, 3000 Leuven, Belgium;
| | - Thomas J. Ross
- Neuroimaging Research Branch, National Institute on Drug Abuse-Intramural Research Program, Baltimore, MD 21224, USA; (T.J.R.); (B.J.S.); (E.A.S.)
| | - Betty J. Salmeron
- Neuroimaging Research Branch, National Institute on Drug Abuse-Intramural Research Program, Baltimore, MD 21224, USA; (T.J.R.); (B.J.S.); (E.A.S.)
| | - James M. Gold
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD 21228, USA; (J.M.G.); (J.A.W.)
| | - Elliot A. Stein
- Neuroimaging Research Branch, National Institute on Drug Abuse-Intramural Research Program, Baltimore, MD 21224, USA; (T.J.R.); (B.J.S.); (E.A.S.)
| | - James A. Waltz
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD 21228, USA; (J.M.G.); (J.A.W.)
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45
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Shao X, Liao Y, Gu L, Chen W, Tang J. The Etiology of Auditory Hallucinations in Schizophrenia: From Multidimensional Levels. Front Neurosci 2021; 15:755870. [PMID: 34858129 PMCID: PMC8632545 DOI: 10.3389/fnins.2021.755870] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Accepted: 10/14/2021] [Indexed: 11/25/2022] Open
Abstract
Enormous efforts have been made to unveil the etiology of auditory hallucinations (AHs), and multiple genetic and neural factors have already been shown to have their own roles. Previous studies have shown that AHs in schizophrenia vary from those in other disorders, suggesting that they have unique features and possibly distinguishable mechanisms worthy of further investigation. In this review, we intend to offer a comprehensive summary of current findings related to AHs in schizophrenia from aspects of genetics and transcriptome, neurophysiology (neurometabolic and electroencephalogram studies), and neuroimaging (structural and functional magnetic resonance imaging studies and transcriptome–neuroimaging association study). Main findings include gene polymorphisms, glutamate level change, electroencephalographic alterations, and abnormalities of white matter fasciculi, cortical structure, and cerebral activities, especially in multiple regions, including auditory and language networks. More solid and comparable research is needed to replicate and integrate ongoing findings from multidimensional levels.
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Affiliation(s)
- Xu Shao
- Department of Psychiatry, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yanhui Liao
- Department of Psychiatry, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Lin Gu
- RIKEN AIP, Tokyo, Japan.,Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan
| | - Wei Chen
- Department of Psychiatry, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jinsong Tang
- Department of Psychiatry, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
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46
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Paranoia and belief updating during the COVID-19 crisis. Nat Hum Behav 2021; 5:1190-1202. [PMID: 34316049 PMCID: PMC8458246 DOI: 10.1038/s41562-021-01176-8] [Citation(s) in RCA: 51] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Accepted: 07/06/2021] [Indexed: 01/31/2023]
Abstract
The COVID-19 pandemic has made the world seem less predictable. Such crises can lead people to feel that others are a threat. Here, we show that the initial phase of the pandemic in 2020 increased individuals' paranoia and made their belief updating more erratic. A proactive lockdown made people's belief updating less capricious. However, state-mandated mask-wearing increased paranoia and induced more erratic behaviour. This was most evident in states where adherence to mask-wearing rules was poor but where rule following is typically more common. Computational analyses of participant behaviour suggested that people with higher paranoia expected the task to be more unstable. People who were more paranoid endorsed conspiracies about mask-wearing and potential vaccines and the QAnon conspiracy theories. These beliefs were associated with erratic task behaviour and changed priors. Taken together, we found that real-world uncertainty increases paranoia and influences laboratory task behaviour.
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47
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Walter H, Daniels A, Wellan SA. [Positive cognitive neuroscience : Positive valence systems of the Research Domain Criteria initiative]. DER NERVENARZT 2021; 92:878-891. [PMID: 34374803 PMCID: PMC8353935 DOI: 10.1007/s00115-021-01167-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Accepted: 06/28/2021] [Indexed: 12/04/2022]
Abstract
In diesem Artikel werden die Domäne „positive Valenzsysteme“ (PVS) der Research-Domain-Criteria(RDoC)-Matrix sowie ihre Subkonstrukte dargestellt und erläutert. Unter PVS fallen im Wesentlichen verschiedene Formen und Prozesse der Belohnungsverarbeitung. Diese werden in der Psychiatrie schon seit Jahrzehnten im Bereich von Sucht, Schizophrenie und Depression untersucht und letztere sind daher nicht Gegenstand dieses Artikels. Hier soll vielmehr die heuristische Fruchtbarkeit der RDoC-Systematik für das Verständnis anderer Erkrankungen und Konstrukte dargestellt werden und zwar für das transdiagnostische Konstrukt der Anhedonie sowie für die Autismusspektrumstörung und die Gruppe der Essstörungen. Weiterhin wird gezeigt, wie die PVS-Domäne auch klinisch den Blick über die traditionelle Psychopathologie erweitert und wie sie die Entwicklung neuer behavioraler Messinstrumente angeregt hat. Abschließend wird auf Limitationen und mögliche zukünftige Erweiterungen des Ansatzes eingegangen.
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Affiliation(s)
- Henrik Walter
- Klinik für Psychiatrie und Psychotherapie CCM, Forschungsbereich Mind and Brain, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Charitéplatz 1, 10117, Berlin, Deutschland. .,Fakultät für Philosophie, Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Deutschland.
| | - Anna Daniels
- Klinik für Psychiatrie und Psychotherapie CCM, Forschungsbereich Mind and Brain, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Charitéplatz 1, 10117, Berlin, Deutschland.,Fakultät für Philosophie, Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Deutschland
| | - Sarah A Wellan
- Klinik für Psychiatrie und Psychotherapie CCM, Forschungsbereich Mind and Brain, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Charitéplatz 1, 10117, Berlin, Deutschland.,Fakultät für Philosophie, Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Deutschland
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48
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Bernasconi F, Blondiaux E, Potheegadoo J, Stripeikyte G, Pagonabarraga J, Bejr-Kasem H, Bassolino M, Akselrod M, Martinez-Horta S, Sampedro F, Hara M, Horvath J, Franza M, Konik S, Bereau M, Ghika JA, Burkhard PR, Van De Ville D, Faivre N, Rognini G, Krack P, Kulisevsky J, Blanke O. Robot-induced hallucinations in Parkinson's disease depend on altered sensorimotor processing in fronto-temporal network. Sci Transl Med 2021; 13:13/591/eabc8362. [PMID: 33910980 DOI: 10.1126/scitranslmed.abc8362] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2020] [Revised: 08/18/2020] [Accepted: 01/23/2021] [Indexed: 01/23/2023]
Abstract
Hallucinations in Parkinson's disease (PD) are disturbing and frequent non-motor symptoms and constitute a major risk factor for psychosis and dementia. We report a robotics-based approach applying conflicting sensorimotor stimulation, enabling the induction of presence hallucinations (PHs) and the characterization of a subgroup of patients with PD with enhanced sensitivity for conflicting sensorimotor stimulation and robot-induced PH. We next identify the fronto-temporal network of PH by combining MR-compatible robotics (and sensorimotor stimulation in healthy participants) and lesion network mapping (neurological patients without PD). This PH-network was selectively disrupted in an additional and independent cohort of patients with PD, predicted the presence of symptomatic PH, and associated with cognitive decline. These robotics-neuroimaging findings extend existing sensorimotor hallucination models to PD and reveal the pathological cortical sensorimotor processes of PH in PD, potentially indicating a more severe form of PD that has been associated with psychosis and cognitive decline.
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Affiliation(s)
- Fosco Bernasconi
- Laboratory of Cognitive Neuroscience, Center for Neuroprosthetics & Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1202 Geneva, Switzerland
| | - Eva Blondiaux
- Laboratory of Cognitive Neuroscience, Center for Neuroprosthetics & Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1202 Geneva, Switzerland
| | - Jevita Potheegadoo
- Laboratory of Cognitive Neuroscience, Center for Neuroprosthetics & Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1202 Geneva, Switzerland
| | - Giedre Stripeikyte
- Laboratory of Cognitive Neuroscience, Center for Neuroprosthetics & Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1202 Geneva, Switzerland
| | - Javier Pagonabarraga
- Movement Disorders Unit, Neurology Department, Sant Pau Hospital, 08041 Barcelona, Spain.,Universitat Autònoma de Barcelona (UAB), 08193 Barcelona, Spain.,Centro de Investigación en Red-Enfermedades Neurodegenerativas (CIBERNED), 28031 Madrid, Spain.,Biomedical Research Institute (IIB-Sant Pau), 08041 Barcelona, Spain
| | - Helena Bejr-Kasem
- Movement Disorders Unit, Neurology Department, Sant Pau Hospital, 08041 Barcelona, Spain.,Universitat Autònoma de Barcelona (UAB), 08193 Barcelona, Spain.,Centro de Investigación en Red-Enfermedades Neurodegenerativas (CIBERNED), 28031 Madrid, Spain.,Biomedical Research Institute (IIB-Sant Pau), 08041 Barcelona, Spain
| | - Michela Bassolino
- Laboratory of Cognitive Neuroscience, Center for Neuroprosthetics & Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1202 Geneva, Switzerland
| | - Michel Akselrod
- Laboratory of Cognitive Neuroscience, Center for Neuroprosthetics & Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1202 Geneva, Switzerland.,MySpace Lab, Lausanne University UNIL and University Hospital of Lausanne, CHUV, 1011 Lausanne, Switzerland
| | - Saul Martinez-Horta
- Movement Disorders Unit, Neurology Department, Sant Pau Hospital, 08041 Barcelona, Spain.,Universitat Autònoma de Barcelona (UAB), 08193 Barcelona, Spain.,Centro de Investigación en Red-Enfermedades Neurodegenerativas (CIBERNED), 28031 Madrid, Spain.,Biomedical Research Institute (IIB-Sant Pau), 08041 Barcelona, Spain
| | - Frederic Sampedro
- Movement Disorders Unit, Neurology Department, Sant Pau Hospital, 08041 Barcelona, Spain.,Universitat Autònoma de Barcelona (UAB), 08193 Barcelona, Spain.,Centro de Investigación en Red-Enfermedades Neurodegenerativas (CIBERNED), 28031 Madrid, Spain.,Biomedical Research Institute (IIB-Sant Pau), 08041 Barcelona, Spain
| | - Masayuki Hara
- Graduate School of Science and Engineering, Saitama University, 338-8570 Saitama, Japan
| | - Judit Horvath
- Department of Neurology, Geneva University Hospitals, 1205 Geneva, Switzerland
| | - Matteo Franza
- Laboratory of Cognitive Neuroscience, Center for Neuroprosthetics & Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1202 Geneva, Switzerland
| | - Stéphanie Konik
- Laboratory of Cognitive Neuroscience, Center for Neuroprosthetics & Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1202 Geneva, Switzerland.,MySpace Lab, Lausanne University UNIL and University Hospital of Lausanne, CHUV, 1011 Lausanne, Switzerland
| | - Matthieu Bereau
- Department of Neurology, Geneva University Hospitals, 1205 Geneva, Switzerland.,Department of Neurology, Besançon University Hospital, 25056 Besançon, France
| | | | - Pierre R Burkhard
- Department of Neurology, Geneva University Hospitals, 1205 Geneva, Switzerland
| | - Dimitri Van De Ville
- Medical Image Processing Laboratory, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1202 Geneva, Switzerland.,Department of Radiology and Medical Informatics, University of Geneva, 1206 Geneva, Switzerland
| | - Nathan Faivre
- Laboratory of Cognitive Neuroscience, Center for Neuroprosthetics & Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1202 Geneva, Switzerland.,Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, LPNC, 38000 Grenoble, France
| | - Giulio Rognini
- Laboratory of Cognitive Neuroscience, Center for Neuroprosthetics & Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1202 Geneva, Switzerland
| | - Paul Krack
- Department of Neurology, Inselspital, University Hospital and University of Bern, 3010 Bern, Switzerland
| | - Jaime Kulisevsky
- Movement Disorders Unit, Neurology Department, Sant Pau Hospital, 08041 Barcelona, Spain. .,Universitat Autònoma de Barcelona (UAB), 08193 Barcelona, Spain.,Centro de Investigación en Red-Enfermedades Neurodegenerativas (CIBERNED), 28031 Madrid, Spain.,Biomedical Research Institute (IIB-Sant Pau), 08041 Barcelona, Spain
| | - Olaf Blanke
- Laboratory of Cognitive Neuroscience, Center for Neuroprosthetics & Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1202 Geneva, Switzerland. .,Department of Neurology, Geneva University Hospitals, 1205 Geneva, Switzerland
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49
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Yaple ZA, Tolomeo S, Yu R. Mapping working memory-specific dysfunction using a transdiagnostic approach. NEUROIMAGE-CLINICAL 2021; 31:102747. [PMID: 34256292 PMCID: PMC8278205 DOI: 10.1016/j.nicl.2021.102747] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Accepted: 06/26/2021] [Indexed: 01/17/2023]
Abstract
Background Working memory (WM) is an executive ability that allows one to hold and manipulate information for a short period of time. Schizophrenia and mood disorders are severe psychiatric conditions with overlapping genetic and clinical symptoms. Whilst WM has been suggested as meeting the criteria for being an endophenotype for schizophrenia and mood disorders, it still unclear whether they share overlapping neural circuitry. Objective The n-back task has been widely used to measure WM capacity, such as maintenance, flexible updating, and interference control. Here we compiled studies that included psychiatric populations, i.e., schizophrenia, bipolar disorder and major depressive disorder. Methods We performed a coordinate-based meta-analysis that combined 34 BOLD-fMRI studies comparing activity associated with n-back working memory between psychiatric patients and healthy controls. We specifically focused our search using the n-back task to diminish study heterogeneity. Results All patient groups showed blunted activity in the striatum, anterior insula and frontal lobe. The same brain networks related to WM were compromised in schizophrenia, major depressive disorder and bipolar disorder. Conclusion Our findings support the suggestion of commonal functional abnormalities across schizophrenia and mood disorders related to WM.
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Affiliation(s)
| | - Serenella Tolomeo
- Department of Psychology, National University of Singapore, Singapore
| | - Rongjun Yu
- Department of Management, Hong Kong Baptist University, Hong Kong, China; Department of Sport, Physical Education and Health, Hong Kong Baptist University, Hong Kong, China; Department of Physics, Hong Kong Baptist University, Hong Kong, China.
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50
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Yang F, Zhu H, Yu L, Lu W, Zhang C, Tian X. Deficits in multi-scale top-down processes distorting auditory perception in schizophrenia. Behav Brain Res 2021; 412:113411. [PMID: 34119507 DOI: 10.1016/j.bbr.2021.113411] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Revised: 05/12/2021] [Accepted: 06/07/2021] [Indexed: 11/28/2022]
Abstract
Cognitive models postulate that impaired source monitoring incorrectly weights the top-down prediction and bottom-up sensory processes and causes hallucinations. However, the underlying mechanisms of the interaction, such as whether the incorrectly weighting is ubiquitously on all levels of sensory features and whether different top-down processes have distinct effects in subgroups of schizophrenia are still unclear. This study investigates how multi-scale predictions influence perception of basic tonal features in schizophrenia. Sixty-three schizophrenia patients with and without symptoms of auditory verbal hallucinations (AVHs), and thirty healthy controls identified target tones in noise at the end of tone sequences. Predictions of different timescales were manipulated by either an alternating pattern in the preceding tone sequences (long-term regularity) or a repetition between the target tone and the tone immediately before (short-term repetition). The sensitivity index, d prime (d'), was obtained to assess the modulation of predictions on tone identification. Patients with AVHs showed higher d' when the target tones conformed to the long-term regularity of alternating pattern in the preceding tone sequence than when the target tones were inconsistent with the pattern. Whereas, the short-term repetition modulated the tone identification in patients without AVHs. Predictions did not influence tone identification in healthy controls. Our results suggest that impaired source monitoring in schizophrenia patients with AVHs heavily weights top-down predictions over bottom-up perceptual processes to form incorrect perception. The weighting function in source monitoring can extend to the processes of basic tonal features, and predictions at multiple timescales could differentially modulate perception in different clinical populations. The impaired interaction between top-down and bottom-up processes might underlie the development of hallucination symptoms in schizophrenia.
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Affiliation(s)
- Fuyin Yang
- Shanghai Key Laboratory of Brain Functional Genomics (Ministry of Education), School of Psychology and Cognitive Science, East China Normal University, Shanghai, 200062, China; NYU-ECNU Institute of Brain and Cognitive Science at NYU Shanghai, 3663 Zhongshan Road North, Shanghai, 200062, China
| | - Hao Zhu
- NYU-ECNU Institute of Brain and Cognitive Science at NYU Shanghai, 3663 Zhongshan Road North, Shanghai, 200062, China; Division of Arts and Sciences, New York University Shanghai, 1555 Century Avenue, Shanghai, 200122, China
| | - Lingfang Yu
- Schizophrenia Program, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Weihong Lu
- Schizophrenia Program, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Chen Zhang
- Schizophrenia Program, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China.
| | - Xing Tian
- NYU-ECNU Institute of Brain and Cognitive Science at NYU Shanghai, 3663 Zhongshan Road North, Shanghai, 200062, China; Division of Arts and Sciences, New York University Shanghai, 1555 Century Avenue, Shanghai, 200122, China.
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