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Jeganathan J, Campbell MEJ, Legrand N, Allen M, Breakspear M. Aberrant Cardiac Interoception in Psychosis. Schizophr Bull 2024:sbae078. [PMID: 38788050 DOI: 10.1093/schbul/sbae078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/26/2024]
Abstract
BACKGROUND AND HYPOTHESIS There is mounting evidence that cardiac interoception, the perception of one's heartbeat, is central to affective experiences. It has been proposed that symptoms of psychosis could arise from interoceptive dysfunction. Here we hypothesized that people with psychotic disorders would have a specific impairment in cardiac interoception, over and above broader perceptual deficits. STUDY DESIGN 43 adults with a history of psychosis (31 schizophrenia, 12 schizoaffective disorder) and 41 matched control participants completed a heart rate discrimination task. Participants responded to whether they perceived a sequence of auditory tones to be faster or slower than their heart rate. By trialing a range of auditory tone rates, we estimated a threshold for each participant, the difference between perceived heart rate and actual heart rate. To test whether differences were specific to interoception, participants completed an exteroceptive control condition, testing their discrimination of the rate of 2 sets of audible sounds instead of heart rate. STUDY RESULTS Participants with a history of psychosis had greater absolute differences between perceived and actual heart rate, indicating over- or under-estimation of heart rate compared to healthy controls. This difference was specific to the interoceptive condition, and not explained by group differences in exteroceptive perception. CONCLUSIONS Psychotic disorders are associated with misestimation of heart rate. Further research may elucidate whether interoceptive abnormalities contribute to specific symptoms such as somatic delusions or affective features, and whether interoception could be a treatment target in psychotic disorders.
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Affiliation(s)
- Jayson Jeganathan
- School of Psychology, College of Engineering, Science and the Environment, University of Newcastle, Newcastle, NSW, Australia
- Hunter Medical Research Institute, Newcastle, NSW, Australia
| | - Megan E J Campbell
- School of Psychology, College of Engineering, Science and the Environment, University of Newcastle, Newcastle, NSW, Australia
- Hunter Medical Research Institute, Newcastle, NSW, Australia
| | - Nicolas Legrand
- School of Culture and Society, Interacting Minds Centre, Aarhus University, Aarhus, Denmark
| | - Micah Allen
- Center of Functionally Integrative Neuroscience, Aarhus University, Aarhus, Denmark
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Michael Breakspear
- School of Psychology, College of Engineering, Science and the Environment, University of Newcastle, Newcastle, NSW, Australia
- Hunter Medical Research Institute, Newcastle, NSW, Australia
- School of Medicine and Public Health, College of Medicine, Health and Wellbeing, University of Newcastle, Newcastle, NSW, Australia
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2
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Percelay S, Lahogue C, Billard JM, Freret T, Boulouard M, Bouet V. The 3-hit animal models of schizophrenia: Improving strategy to decipher and treat the disease? Neurosci Biobehav Rev 2024; 157:105526. [PMID: 38176632 DOI: 10.1016/j.neubiorev.2023.105526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 12/08/2023] [Accepted: 12/23/2023] [Indexed: 01/06/2024]
Abstract
Schizophrenia is a complex disease related to combination and interactions between genetic and environmental factors, with an epigenetic influence. After the development of the first mono-factorial animal models of schizophrenia (1-hit), that reproduced patterns of either positive, negative and/or cognitive symptoms, more complex models combining two factors (2-hit) have been developed to better fit with the multifactorial etiology of the disease. In the two past decades, a new way to design animal models of schizophrenia have emerged by adding a third hit (3-hit). This review aims to discuss the relevance of the risk factors chosen for the tuning of the 3-hit animal models, as well as the validities measurements and their contribution to schizophrenia understanding. We intended to establish a comprehensive overview to help in the choice of factors for the design of multiple-hit animal models of schizophrenia.
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Affiliation(s)
- Solenn Percelay
- Normandie Univ, UNICAEN, INSERM, CYCERON, CHU Caen, COMETE UMR 1075, 14000 Caen, France
| | - Caroline Lahogue
- Normandie Univ, UNICAEN, INSERM, CYCERON, CHU Caen, COMETE UMR 1075, 14000 Caen, France.
| | - Jean-Marie Billard
- Normandie Univ, UNICAEN, INSERM, CYCERON, CHU Caen, COMETE UMR 1075, 14000 Caen, France
| | - Thomas Freret
- Normandie Univ, UNICAEN, INSERM, CYCERON, CHU Caen, COMETE UMR 1075, 14000 Caen, France
| | - Michel Boulouard
- Normandie Univ, UNICAEN, INSERM, CYCERON, CHU Caen, COMETE UMR 1075, 14000 Caen, France
| | - Valentine Bouet
- Normandie Univ, UNICAEN, INSERM, CYCERON, CHU Caen, COMETE UMR 1075, 14000 Caen, France.
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3
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Ibanez A, Northoff G. Intrinsic timescales and predictive allostatic interoception in brain health and disease. Neurosci Biobehav Rev 2024; 157:105510. [PMID: 38104789 PMCID: PMC11184903 DOI: 10.1016/j.neubiorev.2023.105510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 11/29/2023] [Accepted: 12/12/2023] [Indexed: 12/19/2023]
Abstract
The cognitive neuroscience of brain diseases faces challenges in understanding the complex relationship between brain structure and function, the heterogeneity of brain phenotypes, and the lack of dimensional and transnosological explanations. This perspective offers a framework combining the predictive coding theory of allostatic interoceptive overload (PAIO) and the intrinsic neural timescales (INT) theory to provide a more dynamic understanding of brain health in psychiatry and neurology. PAIO integrates allostasis and interoception to assess the interaction between internal patterns and environmental stressors, while INT shows that different brain regions operate on different intrinsic timescales. The allostatic overload can be understood as a failure of INT, which involves a breakdown of proper temporal integration and segregation. This can lead to dimensional disbalances between exteroceptive/interoceptive inputs across brain and whole-body levels (cardiometabolic, cardiovascular, inflammatory, immune). This approach offers new insights, presenting novel perspectives on brain spatiotemporal hierarchies and interactions. By integrating these theories, the paper opens innovative paths for studying brain health dynamics, which can inform future research in brain health and disease.
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Affiliation(s)
- Agustin Ibanez
- Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), CA, USA; Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile; Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina; Trinity College Dublin, Dublin, Ireland.
| | - Georg Northoff
- Mental Health Center, Zhejiang University School of Medicine, Hangzhou, Zhejiang, People's Republic of China; Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, People's Republic of China; Mind, Brain Imaging and Neuroethics, Institute of Mental Health Research, University of Ottawa, Ottawa, Canada.
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Idei H, Yamashita Y. Elucidating multifinal and equifinal pathways to developmental disorders by constructing real-world neurorobotic models. Neural Netw 2024; 169:57-74. [PMID: 37857173 DOI: 10.1016/j.neunet.2023.10.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Revised: 10/04/2023] [Accepted: 10/05/2023] [Indexed: 10/21/2023]
Abstract
Vigorous research has been conducted to accumulate biological and theoretical knowledge about neurodevelopmental disorders, including molecular, neural, computational, and behavioral characteristics; however, these findings remain fragmentary and do not elucidate integrated mechanisms. An obstacle is the heterogeneity of developmental pathways causing clinical phenotypes. Additionally, in symptom formations, the primary causes and consequences of developmental learning processes are often indistinguishable. Herein, we review developmental neurorobotic experiments tackling problems related to the dynamic and complex properties of neurodevelopmental disorders. Specifically, we focus on neurorobotic models under predictive processing lens for the study of developmental disorders. By constructing neurorobotic models with predictive processing mechanisms of learning, perception, and action, we can simulate formations of integrated causal relationships among neurodynamical, computational, and behavioral characteristics in the robot agents while considering developmental learning processes. This framework has the potential to bind neurobiological hypotheses (excitation-inhibition imbalance and functional disconnection), computational accounts (unusual encoding of uncertainty), and clinical symptoms. Developmental neurorobotic approaches may serve as a complementary research framework for integrating fragmented knowledge and overcoming the heterogeneity of neurodevelopmental disorders.
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Affiliation(s)
- Hayato Idei
- Department of Information Medicine, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo 187-8502, Japan
| | - Yuichi Yamashita
- Department of Information Medicine, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo 187-8502, Japan.
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Pan Y, Wen Y, Jin J, Chen J. The interpersonal computational psychiatry of social coordination in schizophrenia. Lancet Psychiatry 2023; 10:801-808. [PMID: 37478889 DOI: 10.1016/s2215-0366(23)00146-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 04/13/2023] [Accepted: 04/13/2023] [Indexed: 07/23/2023]
Abstract
Impairments in social coordination form a core dimension of various psychiatric disorders, including schizophrenia. Advances in interpersonal and computational psychiatry support a major change in studying social coordination in schizophrenia. Although these developments provided novel perspectives to study how interpersonal activities shape coordination and to examine computational mechanisms, direct attempts to integrate the two methodologies have been sparse. Here, we propose an interpersonal computational framework that (1) leverages the active inference framework to model aberrant social coordination processes in schizophrenia and (2) incorporates dynamical system models to dissect intrapersonal and interpersonal synchronisation to inform a statistical model based on active inference. We discuss how this interpersonal computational psychiatry framework can elucidate the aberrant processes leading to psychopathology, with schizophrenia as an example, and highlight how it might aid clinical intervention and practice. Finally, we discuss challenges and opportunities for using the framework in studying social coordination impairments.
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Affiliation(s)
- Yafeng Pan
- Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou, China
| | - Yalan Wen
- Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou, China
| | - Jingwen Jin
- Department of Psychology, The University of Hong Kong, Hong Kong Special Administrative Region, China; State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Ji Chen
- Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou, China; Department of Psychiatry, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, Zhejiang, China.
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Botvinik-Nezer R, Petre B, Ceko M, Lindquist MA, Friedman NP, Wager TD. Placebo treatment affects brain systems related to affective and cognitive processes, but not nociceptive pain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.21.558825. [PMID: 37790543 PMCID: PMC10543005 DOI: 10.1101/2023.09.21.558825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
Placebo analgesia is a replicable and well-studied phenomenon, yet it remains unclear to what degree it includes modulation of nociceptive processes. Some studies find effects consistent with nociceptive effects, but meta-analyses show that these effects are often small. We analyzed placebo analgesia in a large fMRI study (N = 392), including placebo effects on brain responses to noxious stimuli. Placebo treatment caused robust analgesia in both conditioned thermal and unconditioned mechanical pain. Placebo did not decrease fMRI activity in nociceptive pain regions, including the Neurologic Pain Signature (NPS) and pre-registered spinothalamic pathway regions, with strong support from Bayes Factor analyses. However, placebo treatment affected activity in pre-registered analyses of a second neuromarker, the Stimulus Intensity Independent Pain Signature (SIIPS), and several associated a priori brain regions related to motivation and value, in both thermal and mechanical pain. Individual differences in behavioral analgesia were correlated with neural changes in both thermal and mechanical pain. Our results indicate that processes related to affective and cognitive aspects of pain primarily drive placebo analgesia.
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Brændholt M, Kluger DS, Varga S, Heck DH, Gross J, Allen MG. Breathing in waves: Understanding respiratory-brain coupling as a gradient of predictive oscillations. Neurosci Biobehav Rev 2023; 152:105262. [PMID: 37271298 DOI: 10.1016/j.neubiorev.2023.105262] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2022] [Revised: 05/03/2023] [Accepted: 05/24/2023] [Indexed: 06/06/2023]
Abstract
Breathing plays a crucial role in shaping perceptual and cognitive processes by regulating the strength and synchronisation of neural oscillations. Numerous studies have demonstrated that respiratory rhythms govern a wide range of behavioural effects across cognitive, affective, and perceptual domains. Additionally, respiratory-modulated brain oscillations have been observed in various mammalian models and across diverse frequency spectra. However, a comprehensive framework to elucidate these disparate phenomena remains elusive. In this review, we synthesise existing findings to propose a neural gradient of respiratory-modulated brain oscillations and examine recent computational models of neural oscillations to map this gradient onto a hierarchical cascade of precision-weighted prediction errors. By deciphering the computational mechanisms underlying respiratory control of these processes, we can potentially uncover new pathways for understanding the link between respiratory-brain coupling and psychiatric disorders.
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Affiliation(s)
- Malthe Brændholt
- Center of Functionally Integrative Neuroscience, Aarhus University, Denmark
| | - Daniel S Kluger
- Institute for Biomagnetism and Biosignal Analysis, University of Münster, Germany.
| | - Somogy Varga
- School of Culture and Society, Aarhus University, Denmark; The Centre for Philosophy of Epidemiology, Medicine and Public Health, University of Johannesburg, South Africa
| | - Detlef H Heck
- Department of Biomedical Sciences, University of Minnesota Medical School, Duluth, MN
| | - Joachim Gross
- Institute for Biomagnetism and Biosignal Analysis, University of Münster, Germany; Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of Münster, Germany
| | - Micah G Allen
- Center of Functionally Integrative Neuroscience, Aarhus University, Denmark; Cambridge Psychiatry, University of Cambridge, UK
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Lin CH, Li TM, Huang YJ, Chen SJ, Lane HY. Differential Impacts of Endogenous Antioxidants on Clinical Symptoms and Cognitive Function in Acute and Chronic Schizophrenia Patients. Int J Neuropsychopharmacol 2023; 26:576-583. [PMID: 37422918 PMCID: PMC10464923 DOI: 10.1093/ijnp/pyad040] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 07/07/2023] [Indexed: 07/11/2023] Open
Abstract
BACKGROUND Impaired antioxidant defense is implicated in the pathophysiology of schizophrenia, and superoxide dismutase (SOD), catalase (CAT), and glutathione (GSH) are 3 first-line endogenous antioxidants. Various cognitive functions decline differently during the schizophrenia course. The characteristic roles of the 3 antioxidants in clinical and cognitive profiles in acute and chronic phases of schizophrenia require study. METHODS We recruited 311 patients with schizophrenia, including 92 acutely exacerbated patients who had been off antipsychotics for at least 2 weeks and 219 chronic patients who had been stable on medication for at least 2 months. Blood SOD, CAT, and GSH levels; clinical symptoms; and 9 cognitive test scores were measured. RESULTS Blood CAT levels were higher in the acute patients than in the chronic patients, whereas SOD and GSH levels were similar to one another. Higher CAT levels were correlated with less positive symptoms, better working memory and problem solving in the acute phase, and less negative symptoms, less general psychopathology, better global assessment of function, and better cognitive function (in speed of processing, attention, problem solving) in the chronic period. Higher SOD levels were correlated with better global assessment of function in the acute phase and better speed of processing, working memory, and verbal learning and memory in the chronic period. GSH influenced neither clinical nor cognitive manifestations. CONCLUSIONS This study showed that blood CAT affected different clinical and cognitive domains between acute and chronic stages of schizophrenia, SOD influenced cognitive functions in chronic state, but GSH affected none. Further studies are needed to explore the underlying mechanisms.
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Affiliation(s)
- Chieh-Hsin Lin
- Department of Psychiatry, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan
- School of Medicine, Chang Gung University, Taoyuan, Taiwan
- Graduate Institute of Biomedical Sciences, China Medical University, Taichung, Taiwan
| | - Tin-May Li
- Department of Psychiatry and Center for Addiction and Mental Health, China Medical University Hospital, Taichung, Taiwan
| | - Yu-Jhen Huang
- Department of Psychiatry and Center for Addiction and Mental Health, China Medical University Hospital, Taichung, Taiwan
| | - Shaw-Ji Chen
- Department of Psychiatry, Mackay Memorial Hospital Taitung Branch, Taitung, Taiwan
- Department of Medicine, Mackay Medical College, New Taipei, Taiwan
| | - Hsien-Yuan Lane
- Graduate Institute of Biomedical Sciences, China Medical University, Taichung, Taiwan
- Department of Psychiatry and Center for Addiction and Mental Health, China Medical University Hospital, Taichung, Taiwan
- Neuroscience and Brain Disease Center, China Medical University, Taichung, Taiwan
- Department of Psychology, College of Medical and Health Sciences, Asia University, Taichung, Taiwan
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Limongi R, Silva AM, Mackinley M, Ford SD, Palaniyappan L. Active Inference, Epistemic Value, and Uncertainty in Conceptual Disorganization in First-Episode Schizophrenia. Schizophr Bull 2023; 49:S115-S124. [PMID: 36946528 PMCID: PMC10031740 DOI: 10.1093/schbul/sbac125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/23/2023]
Abstract
BACKGROUND AND HYPOTHESIS Active inference has become an influential concept in psychopathology. We apply active inference to investigate conceptual disorganization in first-episode schizophrenia. We conceptualize speech production as a decision-making process affected by the latent "conceptual organization"-as a special case of uncertainty about the causes of sensory information. Uncertainty is both minimized via speech production-in which function words index conceptual organization in terms of analytic thinking-and tracked by a domain-general salience network. We hypothesize that analytic thinking depends on conceptual organization. Therefore, conceptual disorganization in schizophrenia would be both indexed by low conceptual organization and reflected in the effective connectivity within the salience network. STUDY DESIGN With 1-minute speech samples from a picture description task and resting state fMRI from 30 patients and 30 healthy subjects, we employed dynamic causal and probabilistic graphical models to investigate if the effective connectivity of the salience network underwrites conceptual organization. STUDY RESULTS Low analytic thinking scores index low conceptual organization which affects diagnostic status. The influence of the anterior insula on the anterior cingulate cortex and the self-inhibition within the anterior cingulate cortex are elevated given low conceptual organization (ie, conceptual disorganization). CONCLUSIONS Conceptual organization, a construct that explains formal thought disorder, can be modeled in an active inference framework and studied in relation to putative neural substrates of disrupted language in schizophrenia. This provides a critical advance to move away from rating-scale scores to deeper constructs in the pursuit of the pathophysiology of formal thought disorder.
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Affiliation(s)
- Roberto Limongi
- Department of Psychology, University of Western Ontario, London, ON, Canada
- Robarts Research Institute, London, ON, Canada
| | | | - Michael Mackinley
- Robarts Research Institute, London, ON, Canada
- Department of Psychiatry, University of Western Ontario, London, ON, Canada
- Lawson Health Research Institute, London, ON, Canada
| | | | - Lena Palaniyappan
- Robarts Research Institute, London, ON, Canada
- Department of Psychiatry, University of Western Ontario, London, ON, Canada
- Lawson Health Research Institute, London, ON, Canada
- Department of Medical Biophysics, University of Western Ontario, London, ON, Canada
- The Brain and Mind Institute, University of Western Ontario, London, ON, Canada
- Department of Psychiatry, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada
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From fear of falling to choking under pressure: A predictive processing perspective of disrupted motor control under anxiety. Neurosci Biobehav Rev 2023; 148:105115. [PMID: 36906243 DOI: 10.1016/j.neubiorev.2023.105115] [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: 10/03/2022] [Revised: 02/27/2023] [Accepted: 02/28/2023] [Indexed: 03/11/2023]
Abstract
Under the Predictive Processing Framework, perception is guided by internal models that map the probabilistic relationship between sensory states and their causes. Predictive processing has contributed to a new understanding of both emotional states and motor control but is yet to be fully applied to their interaction during the breakdown of motor movements under heightened anxiety or threat. We bring together literature on anxiety and motor control to propose that predictive processing provides a unifying principle for understanding motor breakdowns as a disruption to the neuromodulatory control mechanisms that regulate the interactions of top-down predictions and bottom-up sensory signals. We illustrate this account using examples from disrupted balance and gait in populations who are anxious/fearful of falling, as well as 'choking' in elite sport. This approach can explain both rigid and inflexible movement strategies, as well as highly variable and imprecise action and conscious movement processing, and may also unite the apparently opposing self-focus and distraction approaches to choking. We generate predictions to guide future work and propose practical recommendations.
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Sabaroedin K, Tiego J, Fornito A. Circuit-Based Approaches to Understanding Corticostriatothalamic Dysfunction Across the Psychosis Continuum. Biol Psychiatry 2023; 93:113-124. [PMID: 36253195 DOI: 10.1016/j.biopsych.2022.07.017] [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: 10/05/2021] [Revised: 06/14/2022] [Accepted: 07/17/2022] [Indexed: 11/28/2022]
Abstract
Dopamine is known to play a role in the pathogenesis of psychotic symptoms, but the mechanisms driving dopaminergic dysfunction in psychosis remain unclear. Considerable attention has focused on the role of corticostriatothalamic (CST) circuits, given that they regulate and are modulated by the activity of dopaminergic cells in the midbrain. Preclinical studies have proposed multiple models of CST dysfunction in psychosis, each prioritizing different brain regions and pathophysiological mechanisms. A particular challenge is that CST circuits have undergone considerable evolutionary modification across mammals, complicating comparisons across species. Here, we consider preclinical models of CST dysfunction in psychosis and evaluate the degree to which they are supported by evidence from human resting-state functional magnetic resonance imaging studies conducted across the psychosis continuum, ranging from subclinical schizotypy to established schizophrenia. In partial support of some preclinical models, human studies indicate that dorsal CST and hippocampal-striatal functional dysconnectivity are apparent across the psychosis spectrum and may represent a vulnerability marker for psychosis. In contrast, midbrain dysfunction may emerge when symptoms warrant clinical assistance and may thus be a trigger for illness onset. The major difference between clinical and preclinical findings is the strong involvement of the dorsal CST in the former, consistent with an increasing prominence of this circuitry in the primate brain. We close by underscoring the need for high-resolution characterization of phenotypic heterogeneity in psychosis to develop a refined understanding of how the dysfunction of specific circuit elements gives rise to distinct symptom profiles.
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Affiliation(s)
- Kristina Sabaroedin
- Departments of Radiology and Paediatrics, Hotchkiss Brain Institute and Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada.
| | - Jeggan Tiego
- Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
| | - Alex Fornito
- Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
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Chen MY, Zhang Q, Liu YF, Zheng WY, Si TL, Su Z, Cheung T, Jackson T, Li XH, Xiang YT. Schizophrenia and oxidative stress from the perspective of bibliometric analysis. Front Psychiatry 2023; 14:1145409. [PMID: 36923522 PMCID: PMC10008861 DOI: 10.3389/fpsyt.2023.1145409] [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: 01/16/2023] [Accepted: 02/06/2023] [Indexed: 03/01/2023] Open
Abstract
BACKGROUND A growing number of studies has implicated oxidative stress in the pathophysiology of psychiatric disorders including schizophrenia. The aim of this study was to explore the field of schizophrenia and oxidative stress-related research from a bibliometric perspective. METHODS All relevant publications on schizophrenia and oxidative stress were obtained from Web of Science Core Collection (WOSCC) database from its inception date to November 8, 2022. VOSviewer software was used to examine co-authorships and co-occurring keywords. R software was used to present the main characteristics of publications and cooperation frequency among countries. CiteSpace was used to investigate keywords with the strongest citation bursts. RESULTS A total of 3,510 publications on schizophrenia and oxidative stress were included. The United States had the largest number of publications (26.1%), and international collaborations. University of Melbourne was the most productive institution, while Schizophrenia Research was the most productive journal in this field. Apart from "schizophrenia" and "oxidative stress", the terms "prefrontal cortex", "brain" and "nitric oxide" were among the most frequently used keywords. CONCLUSIONS In conclusion, research on the association between oxidative stress and schizophrenia has received growing attention in the academic literature that is expected to continue its upward trajectory during the next two decades. Existing research suggests there has been a transition from research focused on pathways to animal models, and subsequently to clinical applications. Intervention studies on oxidative stress and schizophrenia are likely to be an important focus of related work in the near future.
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Affiliation(s)
- Meng-Yi Chen
- Unit of Psychiatry, Department of Public Health and Medicinal Administration, and Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macau, Macao SAR, China.,Centre for Cognitive and Brain Sciences, University of Macau, Macau, Macao SAR, China
| | - Qinge Zhang
- The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital & the Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Yu-Fei Liu
- Unit of Psychiatry, Department of Public Health and Medicinal Administration, and Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macau, Macao SAR, China
| | - Wan-Ying Zheng
- Unit of Psychiatry, Department of Public Health and Medicinal Administration, and Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macau, Macao SAR, China
| | - Tong Leong Si
- Unit of Psychiatry, Department of Public Health and Medicinal Administration, and Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macau, Macao SAR, China
| | - Zhaohui Su
- School of Public Health, Southeast University, Nanjing, China
| | - Teris Cheung
- School of Nursing, Hong Kong Polytechnic University, Hong Kong, Hong Kong SAR, China
| | - Todd Jackson
- Department of Psychology, University of Macau, Macau, Macao SAR, China
| | - Xiao-Hong Li
- Peking University Huilongguan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Yu-Tao Xiang
- Unit of Psychiatry, Department of Public Health and Medicinal Administration, and Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macau, Macao SAR, China.,Centre for Cognitive and Brain Sciences, University of Macau, Macau, Macao SAR, China
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13
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The relative contributions of insight and neurocognition to intrinsic motivation in schizophrenia. SCHIZOPHRENIA 2022; 8:18. [PMID: 35260585 PMCID: PMC8904546 DOI: 10.1038/s41537-022-00217-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 08/29/2021] [Accepted: 02/08/2022] [Indexed: 11/24/2022]
Abstract
Intrinsic motivation was described as the mental process of pursuing a task or an action because it is enjoyable or interesting in itself and was found to play a central role in the determination of the functional outcome of schizophrenia. Neurocognition is one of the most studied determinants of intrinsic motivation in clinically stable schizophrenia while little is known about the role of insight. Following this need we decided to focus on the contribution of different aspects of insight and of neurocognition to intrinsic motivation in a large sample (n = 176) of patients with stable schizophrenia. We performed three hierarchical linear regressions from which resulted that, among different insight aspects, the ability to correctly attribute signs and symptoms to the mental disorder made the strongest contribution to intrinsic motivation. Neurocognition, also, was significantly related to intrinsic motivation when analyzed simultaneously with insight. Moreover, even after accounting for sociodemographic and clinical variables significantly correlated with intrinsic motivation, the relationship between insight and neurocognition and intrinsic motivation remained statistically significant. These findings put the emphasis on the complex interplay between insight, neurocognition, and intrinsic motivation suggesting that interventions targeting both insight and neurocognition might possibly improve this motivational deficit in stable schizophrenia should.
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Allen M, Levy A, Parr T, Friston KJ. In the Body’s Eye: The computational anatomy of interoceptive inference. PLoS Comput Biol 2022; 18:e1010490. [PMID: 36099315 PMCID: PMC9506608 DOI: 10.1371/journal.pcbi.1010490] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 09/23/2022] [Accepted: 08/13/2022] [Indexed: 11/24/2022] Open
Abstract
A growing body of evidence highlights the intricate linkage of exteroceptive perception to the rhythmic activity of the visceral body. In parallel, interoceptive inference theories of affective perception and self-consciousness are on the rise in cognitive science. However, thus far no formal theory has emerged to integrate these twin domains; instead, most extant work is conceptual in nature. Here, we introduce a formal model of cardiac active inference, which explains how ascending cardiac signals entrain exteroceptive sensory perception and uncertainty. Through simulated psychophysics, we reproduce the defensive startle reflex and commonly reported effects linking the cardiac cycle to affective behaviour. We further show that simulated ‘interoceptive lesions’ blunt affective expectations, induce psychosomatic hallucinations, and exacerbate biases in perceptual uncertainty. Through synthetic heart-rate variability analyses, we illustrate how the balance of arousal-priors and visceral prediction errors produces idiosyncratic patterns of physiological reactivity. Our model thus offers a roadmap for computationally phenotyping disordered brain-body interaction. Understanding interactions between the brain and the body has become a topic of increased interest in computational neuroscience and psychiatry. A particular question here concerns how visceral, homeostatic rhythms such as the heart beat influence sensory, affective, and cognitive processing. To better understand these and other oscillatory brain-body interactions, we here introduce a novel computational model of interoceptive inference in which a synthetic agent’s perceptual beliefs are coupled to the rhythm of the heart. Our model both helps to explain emerging empirical data indicating that perceptual inference depends upon beat-to-beat heart rhythms, and can be used to better quantify intra- and inter-individual differences in heart-brain coupling. Using proof-of-principle simulations, we demonstrate how future empirical works could utilize our model to better understand and stratify disorders of interoception and brain-body interaction.
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Affiliation(s)
- Micah Allen
- Centre of Functionally Integrative Neuroscience, Aarhus University Hospital, Denmark
- Cambridge Psychiatry, Cambridge University, Cambridge, United Kingdom
- * E-mail:
| | - Andrew Levy
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom
| | - Thomas Parr
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom
| | - Karl J. Friston
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom
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15
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Xu L, Cui H, Wei Y, Qian Z, Tang X, Hu Y, Wang Y, Hu H, Guo Q, Tang Y, Zhang T, Wang J. Relationships between self-reflectiveness and clinical symptoms in individuals during pre-morbid and early clinical stages of psychosis. Gen Psychiatr 2022; 35:e100696. [PMID: 35721834 PMCID: PMC9161056 DOI: 10.1136/gpsych-2021-100696] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Accepted: 04/29/2022] [Indexed: 11/24/2022] Open
Abstract
Background Self-reflectiveness, one dimension of cognitive insight, plays a protective role in an individual's mental state. Both high and low levels of self-reflectiveness have been reported in patients with schizophrenia and individuals at clinical high risk for the illness. Aims This study aimed to explore the relationship patterns between self-reflectiveness and clinical symptoms in individuals during the pre-morbid and early clinical stages of psychosis. Methods A total of 181 subjects, including individuals with attenuated positive symptoms (APS, n=122) and patients with first-episode psychosis (FEP, n=59), completed the Beck Cognitive Insight Scale and were evaluated using the Schedule of Assessment of Insight and Positive and Negative Syndrome Scale. All subjects were classified into three groups according to their level of self-reflectiveness: low level (LSR, n=59), medium level (MSR, n=67) and high level (HSR, n=55). Both linear and non-linear relationships between self-reflectiveness and clinical symptoms were explored. Results More individuals with APS were classified into the MSR group, while more patients with FEP were classified into the LSR group. The LSR group demonstrated less awareness of illness than the MSR and HSR groups, more stereotyped thinking and poorer impulse control but less anxiety than the MSR group, and lower levels of blunted affect and guilt feelings than the HSR group. The MSR group demonstrated lower stereotyped thinking than the HSR group. Compared to the LSR group, the MSR group had increased self-reflectiveness, improved awareness of illness, decreased stereotyped thinking, and better impulse control, but increased feelings of guilt. The HSR group showed increased stereotyped thinking when compared to the MSR group, but the other variables did not change significantly between these two groups. Overall, self-reflectiveness demonstrated an approximately inverse S-shaped relationship with the awareness of illness, a U-shaped relationship with stereotyped thinking and poor impulse control, and an almost linear relationship with anxiety and guilt feelings. Conclusions Self-reflectiveness demonstrates complex relationships with clinical symptoms and fails to exert significant positive effects when reaching a certain high level.
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Affiliation(s)
- Lihua Xu
- Shanghai Intelligent Psychological Evaluation and Intervention Engineering Technology Research Center, Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Huiru Cui
- Shanghai Intelligent Psychological Evaluation and Intervention Engineering Technology Research Center, Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yanyan Wei
- Shanghai Intelligent Psychological Evaluation and Intervention Engineering Technology Research Center, Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhenying Qian
- Shanghai Intelligent Psychological Evaluation and Intervention Engineering Technology Research Center, Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiaochen Tang
- Shanghai Intelligent Psychological Evaluation and Intervention Engineering Technology Research Center, Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yegang Hu
- Shanghai Intelligent Psychological Evaluation and Intervention Engineering Technology Research Center, Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yingchan Wang
- Department of Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hao Hu
- Department of Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qian Guo
- Department of Early Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yingying Tang
- Shanghai Intelligent Psychological Evaluation and Intervention Engineering Technology Research Center, Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tianhong Zhang
- Shanghai Intelligent Psychological Evaluation and Intervention Engineering Technology Research Center, Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jijun Wang
- Shanghai Intelligent Psychological Evaluation and Intervention Engineering Technology Research Center, Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), Chinese Academy of Science, Shanghai, China
- Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai, China
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16
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Osaka K, Matsumoto K, Akiyama T, Tanioka R, Betriana F, Zhao Y, Kai Y, Miyagawa M, Tanioka T, Locsin RC. Investigation of Methods to Create Future Multimodal Emotional Data for Robot Interactions in Patients with Schizophrenia: A Case Study. Healthcare (Basel) 2022; 10:healthcare10050848. [PMID: 35627984 PMCID: PMC9140390 DOI: 10.3390/healthcare10050848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Revised: 04/28/2022] [Accepted: 05/01/2022] [Indexed: 11/16/2022] Open
Abstract
Rapid progress in humanoid robot investigations offers possibilities for improving the competencies of people with social disorders, although this improvement of humanoid robots remains unexplored for schizophrenic people. Methods for creating future multimodal emotional data for robot interactions were studied in this case study of a 40-year-old male patient with disorganized schizophrenia without comorbidities. The qualitative data included heart rate variability (HRV), video-audio recordings, and field notes. HRV, Haar cascade classifier (HCC), and Empath API© were evaluated during conversations between the patient and robot. Two expert nurses and one psychiatrist evaluated facial expressions. The research hypothesis questioned whether HRV, HCC, and Empath API© are useful for creating future multimodal emotional data about robot–patient interactions. The HRV analysis showed persistent sympathetic dominance, matching the human–robot conversational situation. The result of HCC was in agreement with that of human observation, in the case of rough consensus. In the case of observed results disagreed upon by experts, the HCC result was also different. However, emotional assessments by experts using Empath API© were also found to be inconsistent. We believe that with further investigation, a clearer identification of methods for multimodal emotional data for robot interactions can be achieved for patients with schizophrenia.
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Affiliation(s)
- Kyoko Osaka
- Department of Psychiatric Nursing, Nursing Course of Kochi Medical School, Kochi University, Kochi 783-8505, Japan
- Correspondence:
| | - Kazuyuki Matsumoto
- Graduate School of Engineering, Tokushima University, Tokushima 770-8506, Japan;
| | - Toshiya Akiyama
- Graduate School of Health Sciences, Tokushima University, Tokushima 770-8509, Japan; (T.A.); (R.T.); (F.B.)
| | - Ryuichi Tanioka
- Graduate School of Health Sciences, Tokushima University, Tokushima 770-8509, Japan; (T.A.); (R.T.); (F.B.)
| | - Feni Betriana
- Graduate School of Health Sciences, Tokushima University, Tokushima 770-8509, Japan; (T.A.); (R.T.); (F.B.)
| | - Yueren Zhao
- Department of Psychiatry, School of Medicine, Fujita Health University, Toyoake 470-1192, Japan;
| | - Yoshihiro Kai
- Department of Mechanical Engineering, Tokai University, Tokyo 259-1292, Japan;
| | - Misao Miyagawa
- Department of Nursing, Faculty of Health and Welfare, Tokushima Bunri University, Tokushima 770-8514, Japan;
| | - Tetsuya Tanioka
- Institute of Biomedical Sciences, Tokushima University, Tokushima 770-8509, Japan; (T.T.); or (R.C.L.)
| | - Rozzano C. Locsin
- Institute of Biomedical Sciences, Tokushima University, Tokushima 770-8509, Japan; (T.T.); or (R.C.L.)
- Christine E Lynn College of Nursing, Florida Atlantic University, Boca Raton, FL 33431, USA
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Palaniyappan L, Venkatasubramanian G. The Bayesian brain and cooperative communication in schizophrenia. J Psychiatry Neurosci 2022; 47:E48-E54. [PMID: 35135834 PMCID: PMC8834248 DOI: 10.1503/jpn.210231] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Affiliation(s)
- Lena Palaniyappan
- From the Department of Psychiatry, Schulich School of Medicine & Dentistry, Western University, London, Ont., Canada (Palaniyappan); the Robart Research Institute & Lawson Health Research Institute, London, Ont., Canada (Palaniyappan); and the InSTAR Program, Schizophrenia Clinic, Department of Psychiatry, National Institute of Mental Health and Neuro Sciences, Bangalore, India (Venkatasubramanian)
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18
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Interoception abnormalities in schizophrenia: A review of preliminary evidence and an integration with Bayesian accounts of psychosis. Neurosci Biobehav Rev 2021; 132:757-773. [PMID: 34823914 DOI: 10.1016/j.neubiorev.2021.11.016] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2021] [Revised: 10/31/2021] [Accepted: 11/13/2021] [Indexed: 01/07/2023]
Abstract
Schizophrenia research has traditionally focused almost exclusively on how the brain interprets the outside world. However, our internal bodily milieu is also central to how we interpret the world and construct our reality: signals from within the body are critical for not only basic survival, but also a wide range of brain functions from basic perception, emotion, and motivation, to sense of self. In this article, we propose that interoception-the processing of bodily signals-may have implications for a wide range of clinical symptoms in schizophrenia and may thus provide key insights into illness mechanisms. We start with an overview of interoception pathways. Then we provide a review of direct and indirect findings in various interoceptive systems in schizophrenia and interpret these findings in the context of computational frameworks that model interoception as hierarchical Bayesian inference. Finally, we propose a conceptual model of how altered interoceptive inference may contribute to specific schizophrenia symptoms-negative symptoms in particular-and suggest directions for future research, including potential new avenues of treatment.
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19
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Saleh Y, Jarratt-Barnham I, Fernandez-Egea E, Husain M. Mechanisms Underlying Motivational Dysfunction in Schizophrenia. Front Behav Neurosci 2021; 15:709753. [PMID: 34566594 PMCID: PMC8460905 DOI: 10.3389/fnbeh.2021.709753] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Accepted: 08/20/2021] [Indexed: 12/24/2022] Open
Abstract
Negative symptoms are a debilitating feature of schizophrenia which are often resistant to pharmacological intervention. The mechanisms underlying them remain poorly understood, and diagnostic methods rely on phenotyping through validated questionnaires. Deeper endo-phenotyping is likely to be necessary in order to improve current understanding. In the last decade, valuable behavioural insights have been gained through the use of effort-based decision making (EBDM) tasks. These have highlighted impairments in reward-related processing in schizophrenia, particularly associated with negative symptom severity. Neuroimaging investigations have related these changes to dysfunction within specific brain networks including the ventral striatum (VS) and frontal brain regions. Here, we review the behavioural and neural evidence associated with negative symptoms, shedding light on potential underlying mechanisms and future therapeutic possibilities. Findings in the literature suggest that schizophrenia is characterised by impaired reward based learning and action selection, despite preserved hedonic responses. Associations between amotivation and reward-processing deficits have not always been clear, and may be mediated by factors including cognitive dysfunction or dysfunctional or self-defeatist beliefs. Successful endo-phenotyping of negative symptoms as a function of objective behavioural and neural measurements is crucial in advancing our understanding of this complex syndrome. Additionally, transdiagnostic research–leveraging findings from other brain disorders, including neurological ones–can shed valuable light on the possible common origins of motivation disorders across diseases and has important implications for future treatment development.
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Affiliation(s)
- Youssuf Saleh
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Isaac Jarratt-Barnham
- Department of Psychiatry, Herchel Smith Building for Brain & Mind Sciences, University of Cambridge, Cambridge, United Kingdom.,Cambridge Psychosis Centre, Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, United Kingdom
| | - Emilio Fernandez-Egea
- Department of Psychiatry, Herchel Smith Building for Brain & Mind Sciences, University of Cambridge, Cambridge, United Kingdom.,Cambridge Psychosis Centre, Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, United Kingdom
| | - Masud Husain
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
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