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Kowalski J, Dąbkowska M, Aleksandrowicz A, Jarkiewicz M, Larøi F, Gawęda Ł. Associations of Cognitive Expectancies With Auditory Hallucinations and Hallucinatory-Like Experiences in Patients With Schizophrenia. Schizophr Bull 2024:sbae115. [PMID: 38982879 DOI: 10.1093/schbul/sbae115] [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: 07/11/2024]
Abstract
BACKGROUND Various neurocognitive models explore perceptual distortions and hallucinations in schizophrenia and the general population. A variant of predictive coding account suggests that strong priors, like cognitive expectancy, may influence perception. This study examines if stronger cognitive expectancies result in more auditory false percepts in clinical and healthy control groups, investigates group differences, and explores the association between false percepts and hallucinations. STUDY DESIGN Patients diagnosed with schizophrenia with current auditory hallucinations (n = 51) and without hallucinations (n = 66) and healthy controls (n = 51) underwent the False Perception Task under various expectancy conditions. All groups were examined for the presence and severity of hallucinations or hallucinatory-like experiences. STUDY RESULTS We observed a main effect of condition across all groups, ie, the stronger the cognitive expectancy, the greater the ratio of auditory false percepts. However, there was no group effect for the ratio of auditory false percepts. Despite modest pairwise correlations in the hallucinating group, the ratio of auditory false percepts was not predicted by levels of hallucinations and hallucinatory-like experiences in a linear mixed model. CONCLUSIONS The current study demonstrates that strong priors in the form of cognitive expectancies affect perception and play a role in perceptual disturbances. There is also a tentative possibility that overreliance on strong priors may be associated with hallucinations in currently hallucinating subjects. Possible, avoidable confounding factors are discussed in detail.
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Affiliation(s)
- Joachim Kowalski
- Experimental Psychopathology Lab, Institute of Psychology, Polish Academy of Sciences, Warsaw, Poland
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Małgorzata Dąbkowska
- Experimental Psychopathology Lab, Institute of Psychology, Polish Academy of Sciences, Warsaw, Poland
| | - Adrianna Aleksandrowicz
- Experimental Psychopathology Lab, Institute of Psychology, Polish Academy of Sciences, Warsaw, Poland
| | - Michał Jarkiewicz
- Third Department of Psychiatry, Institute of Psychiatry and Neurology, Warsaw, Poland
| | - Frank Larøi
- Department of Psychology, University of Oslo, Oslo, Norway
- Psychology and Neuroscience of Cognition Research Unit, Department of Psychology, University of Liège, Liège, Belgium
| | - Łukasz Gawęda
- Experimental Psychopathology Lab, Institute of Psychology, Polish Academy of Sciences, Warsaw, Poland
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Perret M, Neige C, Brunelin J, Mondino M. Unraveling the brain mechanisms of source monitoring with non-invasive brain stimulation: A systematic review. Int J Clin Health Psychol 2024; 24:100449. [PMID: 38406179 PMCID: PMC10884508 DOI: 10.1016/j.ijchp.2024.100449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Accepted: 02/14/2024] [Indexed: 02/27/2024] Open
Abstract
Background/Objective Source monitoring refers to the ability to determine the source of memories and encompasses three subprocesses: internal source monitoring, reality monitoring, and external source monitoring. Neuroimaging studies provide valuable insights about neural correlates of source monitoring, but the causal relationship between brain and behavior is lacking. This study aimed to identify brain circuits involved in source monitoring by synthesizing the effects of brain stimulation on source monitoring as a function of the targeted brain regions or circuits. Method We conducted a systematic review of interventional studies that have examined the effects of brain stimulation on source monitoring across six databases. The principal outcome was the difference of source monitoring performance between active and control stimulation conditions. Results 23 studies (920 healthy participants and 54 patients with schizophrenia) were included. Our findings revealed the involvement of i) the lateral prefrontal and temporoparietal cortices in internal source monitoring, ii) the medial prefrontal and temporoparietal cortices in reality monitoring, and iii) the precuneus and the left angular gyrus in external source monitoring. Conclusions These findings deepen our understanding of the brain mechanisms of source monitoring and highlight specific stimulation targets to alleviate source monitoring deficits.
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Affiliation(s)
- Mélanie Perret
- Université Claude Bernard Lyon 1, CNRS, INSERM, Centre de Recherche en Neurosciences de Lyon CRNL U1028 UMR5292, PSYR2, F-69500 Bron, France
- Centre Hospitalier Le Vinatier, 95 Boulevard Pinel, F-69500 Bron, France
| | - Cécilia Neige
- Université Claude Bernard Lyon 1, CNRS, INSERM, Centre de Recherche en Neurosciences de Lyon CRNL U1028 UMR5292, PSYR2, F-69500 Bron, France
- Centre Hospitalier Le Vinatier, 95 Boulevard Pinel, F-69500 Bron, France
| | - Jerome Brunelin
- Université Claude Bernard Lyon 1, CNRS, INSERM, Centre de Recherche en Neurosciences de Lyon CRNL U1028 UMR5292, PSYR2, F-69500 Bron, France
- Centre Hospitalier Le Vinatier, 95 Boulevard Pinel, F-69500 Bron, France
| | - Marine Mondino
- Université Claude Bernard Lyon 1, CNRS, INSERM, Centre de Recherche en Neurosciences de Lyon CRNL U1028 UMR5292, PSYR2, F-69500 Bron, France
- Centre Hospitalier Le Vinatier, 95 Boulevard Pinel, F-69500 Bron, France
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Gawęda Ł, Kowalski J, Aleksandrowicz A, Bagrowska P, Dąbkowska M, Pionke-Ubych R. A systematic review of performance-based assessment studies on cognitive biases in schizophrenia spectrum psychoses and clinical high-risk states: A summary of 40 years of research. Clin Psychol Rev 2024; 108:102391. [PMID: 38301343 DOI: 10.1016/j.cpr.2024.102391] [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: 08/30/2022] [Revised: 01/05/2024] [Accepted: 01/12/2024] [Indexed: 02/03/2024]
Abstract
Cognitive models of psychosis have stimulated empirical studies on cognitive biases involved in schizophrenia spectrum psychoses and their symptoms. This systematic review aimed to summarize the studies on the role of cognitive biases as assessed in different performance-based tasks in schizophrenia spectrum psychoses and clinical high-risk states. We focused on five cognitive biases linked to psychosis, i.e., aberrant salience, attentional biases, source monitoring biases, jumping to conclusions, and bias against disconfirmatory evidence. We identified N = 324 studies published in N = 308 articles fulfilling inclusion criteria. Most studies have been cross-sectional and confirmed that the schizophrenia spectrum psychoses are related to exaggerated cognitive biases compared to healthy controls. On the contrary, less evidence suggests a higher tendency for cognitive biases in the UHR sample. The only exceptions were source monitoring and jumping to conclusions, which were confirmed to be exaggerated in both clinical groups. Hallucinations and delusions were the most frequent symptoms studied in the context of cognitive biases. Based on the findings, we presented a hypothetical model on the role of interactions between cognitive biases or additive effects of biases in shaping the risk of psychosis. Future research is warranted for further development of cognitive models for psychosis.
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Affiliation(s)
- Łukasz Gawęda
- Experimental Psychopathology Lab, Institute of Psychology, Polish Academy of Sciences, Warsaw, Poland.
| | - Joachim Kowalski
- Experimental Psychopathology Lab, Institute of Psychology, Polish Academy of Sciences, Warsaw, Poland
| | - Adrianna Aleksandrowicz
- Experimental Psychopathology Lab, Institute of Psychology, Polish Academy of Sciences, Warsaw, Poland
| | - Paulina Bagrowska
- Experimental Psychopathology Lab, Institute of Psychology, Polish Academy of Sciences, Warsaw, Poland
| | - Małgorzata Dąbkowska
- Experimental Psychopathology Lab, Institute of Psychology, Polish Academy of Sciences, Warsaw, Poland
| | - Renata Pionke-Ubych
- Experimental Psychopathology Lab, Institute of Psychology, Polish Academy of Sciences, Warsaw, Poland
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Chen J, Wei Y, Xue K, Han S, Li W, Zhou B, Cheng J. Abnormal effective connectivity of reward network in first-episode schizophrenia with auditory verbal hallucinations. J Psychiatr Res 2024; 171:207-214. [PMID: 38309210 DOI: 10.1016/j.jpsychires.2024.01.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 12/02/2023] [Accepted: 01/15/2024] [Indexed: 02/05/2024]
Abstract
OBJECTIVE Auditory verbal hallucinations (AVHs) in schizophrenia is proved to be associated with dysfunction of mesolimbic-cortical circuits, especially during abnormal salient and internal verbal resource monitoring processing procedures. However, the information flow among areas involved in coordinated interaction implicated the pathophysiology of AVHs remains unclear. METHODS We used spectral dynamic causal modeling (DCM) to quantify connections among eight critical hubs of reward network in 86 first-episode drug-naïve schizophrenia patients with AVHs (AVH), 93 patients without AVHs (NAVH), and 88 matched normal controls (NC) using resting-state functional magnetic resonance imaging. Group-level connection coefficients, between-group differences and correlation analysis between image measures and symptoms were performed. RESULT DCM revealed weaker effective connectivity (EC) from right ventral striatum (RVS) to ventral tegmental area (VTA) in AVH compared to NAVH. AVH showed stronger EC from left anterior insula (AI) to RVS, stronger EC from RVS to anterior cingulate cortex (ACC), and stronger EC from VTA to posterior cingulate cortex (PCC) compared to NC. The correlation analysis results were mostly visible in the negative correlation between EC from right AI to ACC and positive sub-score, P1 sub-score, and P3 sub-score of PNASS in group-level. CONCLUSION These findings suggest that neural causal interactions between the reward network associated with AVHs are disrupted, expanding the evidence for potential neurobiological mechanisms of AVHs. Particularly, dopamine-dependent salience attribution and top-down monitoring impairments and compensatory effects of enhanced excitatory afferents to ACC, which may provide evidence for a therapeutic target based on direct in vivo of AVHs in schizophrenia.
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Affiliation(s)
- Jingli Chen
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China; Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, 450052, China
| | - Yarui Wei
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China; Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, 450052, China
| | - Kangkang Xue
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China; Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, 450052, China
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China; Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, 450052, China
| | - Wenbin Li
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China; Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, 450052, China
| | - Bingqian Zhou
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China; Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, 450052, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China; Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, 450052, China.
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Ghieh R, Krężołek M, Gawęda Ł. Self-monitoring deficits in schizophrenia: A cross-sectional study of the underlying cognitive mechanisms. Schizophr Res 2024; 264:378-385. [PMID: 38237359 DOI: 10.1016/j.schres.2024.01.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Revised: 11/09/2023] [Accepted: 01/03/2024] [Indexed: 03/01/2024]
Abstract
BACKGROUND People diagnosed with schizophrenia share underlying cognitive deficits in self-monitoring (i.e., identifying the source of self-generated behaviours). This study aimed to investigate whether self-monitoring deficits in schizophrenia are due to a cognitive response bias towards external perceptions or a reduced discriminability of imagined and performed actions. We hypothesised that self-monitoring deficits in individuals with schizophrenia are primarily driven by bottom-up processes, leading to a compromised ability to discriminate between internally generated behaviours as opposed to a cognitive response bias towards performed actions. METHODS We recruited 333 participants, including 192 with schizophrenia and 141 healthy controls. As part of the Action-Memory Task, participants were instructed to either imagine or physically perform 36 different actions, half of which were presented as pictograms and half as text. In the test phase, participants indicated whether they had performed or imagined each action, whether it appeared in text or pictogram, or whether it was a new action. Using Signal Detection Theory, the study primarily analysed group differences in discriminability and response-bias. RESULTS Participants with schizophrenia made significantly more self-monitoring errors than healthy controls. This was primarily due to significantly lower sensitivity, but not a response bias. Whereas recognition memory errors were driven by both lower sensitivity and a response bias. CONCLUSIONS The findings suggest that self-monitoring in schizophrenia was specifically impaired by a compromised discriminability of imagined and performed events and an inability to appropriately compensate by adjusting decision-thresholds. Implications on the role of bottom-up and top-down cognitive mechanisms are discussed.
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Affiliation(s)
- Rachid Ghieh
- Orygen, Parkville, Victoria, Australia; Centre for Youth Mental Health, The University of Melbourne, Parkville, Australia
| | - Martyna Krężołek
- II Department of Psychiatry, Medical University of Warsaw, Poland
| | - Łukasz Gawęda
- Experimental Psychopathology Lab, Institute of Psychology, Polish Academy of Sciences, Warsaw, Poland.
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Krcmar M, Wannan CMJ, Lavoie S, Allott K, Davey CG, Yuen HP, Whitford T, Formica M, Youn S, Shetty J, Beedham R, Rayner V, Murray G, Polari A, Gawęda Ł, Koren D, Sass L, Parnas J, Rasmussen AR, McGorry P, Hartmann JA, Nelson B. The self, neuroscience and psychosis study: Testing a neurophenomenological model of the onset of psychosis. Early Interv Psychiatry 2024; 18:153-164. [PMID: 37394278 DOI: 10.1111/eip.13448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 04/17/2023] [Accepted: 06/07/2023] [Indexed: 07/04/2023]
Abstract
AIM Basic self disturbance is a putative core vulnerability marker of schizophrenia spectrum disorders. The primary aims of the Self, Neuroscience and Psychosis (SNAP) study are to: (1) empirically test a previously described neurophenomenological self-disturbance model of psychosis by examining the relationship between specific clinical, neurocognitive, and neurophysiological variables in UHR patients, and (2) develop a prediction model using these neurophenomenological disturbances for persistence or deterioration of UHR symptoms at 12-month follow-up. METHODS SNAP is a longitudinal observational study. Participants include 400 UHR individuals, 100 clinical controls with no attenuated psychotic symptoms, and 50 healthy controls. All participants complete baseline clinical and neurocognitive assessments and electroencephalography. The UHR sample are followed up for a total of 24 months, with clinical assessment completed every 6 months. RESULTS This paper presents the protocol of the SNAP study, including background rationale, aims and hypotheses, design, and assessment procedures. CONCLUSIONS The SNAP study will test whether neurophenomenological disturbances associated with basic self-disturbance predict persistence or intensification of UHR symptomatology over a 2-year follow up period, and how specific these disturbances are to a clinical population with attenuated psychotic symptoms. This may ultimately inform clinical care and pathoaetiological models of psychosis.
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Affiliation(s)
- Marija Krcmar
- Orygen, Parkville, Parkville, Victoria, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Cassandra M J Wannan
- Orygen, Parkville, Parkville, Victoria, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Suzie Lavoie
- Orygen, Parkville, Parkville, Victoria, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Kelly Allott
- Orygen, Parkville, Parkville, Victoria, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Christopher G Davey
- Orygen, Parkville, Parkville, Victoria, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
- Department of Psychiatry, University of Melbourne, Melbourne, Victoria, Australia
| | - Hok Pan Yuen
- Orygen, Parkville, Parkville, Victoria, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Thomas Whitford
- School of Psychology, University of New South Wales (UNSW), Kensington, New South Wales, Australia
| | - Melanie Formica
- Orygen, Parkville, Parkville, Victoria, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Sarah Youn
- Orygen, Parkville, Parkville, Victoria, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Jashmina Shetty
- Orygen, Parkville, Parkville, Victoria, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Rebecca Beedham
- Orygen, Parkville, Parkville, Victoria, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Victoria Rayner
- Orygen, Parkville, Parkville, Victoria, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Graham Murray
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - Andrea Polari
- Orygen, Parkville, Parkville, Victoria, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Łukasz Gawęda
- Experimental Psychopathology Lab, Institute of Psychology, Polish Academy of Sciences, Warsaw, Poland
| | - Dan Koren
- Psychology Department, University of Haifa, Haifa, Israel
| | - Louis Sass
- Department of Clinical Psychology, GSAPP-Rutgers University, Piscataway, New Jersey, USA
| | - Josef Parnas
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Center for Subjectivity Research, University of Copenhagen, Copenhagen, Denmark
| | - Andreas R Rasmussen
- Orygen, Parkville, Parkville, Victoria, Australia
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Patrick McGorry
- Orygen, Parkville, Parkville, Victoria, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Jessica A Hartmann
- Department of Public Mental Health, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Barnaby Nelson
- Orygen, Parkville, Parkville, Victoria, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
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Damiani S, Cavicchioli M, Guiot C, Donadeo A, Scalabrini A, Grecuzzo V, Bergamaschini I, Provenzani U, Politi P, Fusar-Poli P. The noise in our brain: A systematic review and meta-analysis of neuroimaging and signal-detection studies on source monitoring in psychosis. J Psychiatr Res 2024; 169:142-151. [PMID: 38039688 DOI: 10.1016/j.jpsychires.2023.11.036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 10/09/2023] [Accepted: 11/20/2023] [Indexed: 12/03/2023]
Abstract
OBJECTIVES Noisy thoughts or perceptions are characteristics of psychosis (PSY) and, they are deeply related to source monitoring (SM) - the ability to discriminate the origin of internal/external experiences. METHODS This MOOSE, PRISMA-compliant meta-analysis compared SM performances in PSY compared to healthy controls (HC) focusing on signal-to-noise discrimination in order to: i) test whether neuroimaging procedures (fMRI/EEG) might be a group-specific source of noise for SM; ii) compare error- and accuracy-based indexes; iii) to meta-analyze signal-detection measures (i.e., discrimination index and response bias); iv) to determine the best index capturing SM deficits in psychosis. We conducted a 3-level meta-analysis for each aim to estimate pooled effect-sizes (Cohen's d). SM type, source discrimination and stimulus modality were used as meta-regressors. Heterogeneity (I2), publication bias (Egger's test) and multiple comparisons (Bonferroni correction) were considered. RESULTS Sixteen neuroimaging, 44 error/accuracy-based behavioral and 7 signal-detection trials were included (2297 PSY, age range = 18.78-52.6; 1745 HC, age range = 21.1-53.3). The noise generated by neuroimaging procedures slightly influenced error, but not accuracy. Accuracy-based (d = -0.83), but not error-based, indexes showed significant and large SM impairments in PSY compared to HC. Overall SM performance differences between PSY and HC were larger in discrimination index (d = -0.65) and accuracy (d = -0.61), followed by response bias (d = -0.59, ns) and error-based (d = 0.35) indexes. CONCLUSION Although both accuracy and discrimination indexes differentiate patients with PSY from HC, discrimination index is more reliable and may better capture the bi-directional nature of the internal/external source confusion.
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Affiliation(s)
- Stefano Damiani
- University of Pavia, Department of Brain and Behavioral Sciences, Italy.
| | - Marco Cavicchioli
- University Vita-Salute San Raffaele, Department of Psychology, Italy
| | - Cecilia Guiot
- University of Pavia, Department of Brain and Behavioral Sciences, Italy
| | - Alberto Donadeo
- University of Pavia, Department of Brain and Behavioral Sciences, Italy
| | - Andrea Scalabrini
- University of Bergamo, Department of Human and Social Science, Italy
| | | | | | | | - Pierluigi Politi
- University of Pavia, Department of Brain and Behavioral Sciences, Italy
| | - Paolo Fusar-Poli
- University of Pavia, Department of Brain and Behavioral Sciences, Italy; Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, UK; OASIS Service, South London and Maudsley NHS Foundation Trust, London, UK
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McClatchy DB, Powell SB, Yates JR. In vivo mapping of protein-protein interactions of schizophrenia risk factors generates an interconnected disease network. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.12.571320. [PMID: 38168169 PMCID: PMC10759996 DOI: 10.1101/2023.12.12.571320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Genetic analyses of Schizophrenia (SCZ) patients have identified thousands of risk factors. In silico protein-protein interaction (PPI) network analysis has provided strong evidence that disrupted PPI networks underlie SCZ pathogenesis. In this study, we performed in vivo PPI analysis of several SCZ risk factors in the rodent brain. Using endogenous antibody immunoprecipitations coupled to mass spectrometry (MS) analysis, we constructed a SCZ network comprising 1612 unique PPI with a 5% FDR. Over 90% of the PPI were novel, reflecting the lack of previous PPI MS studies in brain tissue. Our SCZ PPI network was enriched with known SCZ risk factors, which supports the hypothesis that an accumulation of disturbances in selected PPI networks underlies SCZ. We used Stable Isotope Labeling in Mammals (SILAM) to quantitate phencyclidine (PCP) perturbations in the SCZ network and found that PCP weakened most PPI but also led to some enhanced or new PPI. These findings demonstrate that quantitating PPI in perturbed biological states can reveal alterations to network biology.
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Hari V, Bose A, Thimmashetty VH, Parlikar R, Sreeraj VS, Venkatasubramanian G. Effect of left temporoparietal transcranial direct current stimulation on self-bias effect and retrospective intentional binding paradigm: A randomised, double-blind, controlled study. Neuropsychologia 2023; 190:108683. [PMID: 37730086 DOI: 10.1016/j.neuropsychologia.2023.108683] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 07/27/2023] [Accepted: 09/14/2023] [Indexed: 09/22/2023]
Abstract
BACKGROUND Self-bias effect is expressed as a preferential selection and accelerated perception of self-related sensory information. Intentional binding (IB) is a related phenomenon where the sensory outcome from a voluntary action and the voluntary action itself are perceived to be closer to each other in time in both predictive (voluntary action predicting sensory consequence) and retrospective (sensory consequence features triggering self-related inference) contexts. Recent evidence indicates that self-related visual stimuli can affect retrospective intentional binding (rIB). We aimed to 1) replicate rIB in the auditory context, and 2) investigate the potential role of left temporoparietal junction (l-TPJ), a crucial node for the self-monitoring process, in self-bias effect and intentional binding effect by manipulating l-TPJ activity with neuromodulation [using High-Definition Transcranial Direct Current Stimulation (HD-tDCS)]. We anticipated self-bias and rIB effects to increase with anodal stimulation of l-TPJ in comparison to cathodal-stimulation of l-TPJ. METHODS Fourteen, right-handed, healthy participants performed sound-label matching (matching tones to self-and-other labels) and rIB (estimating time interval between a button press and a self/other labelled tone) tasks. Each participant underwent both anodal and cathodal stimulation of l-TPJ in separate sessions (at least 72 h apart). Assignment of HD-tDCS type was random and counter-balanced across participants. Behavioural data was collected at three time points: once at baseline (no-stimulation), and twice after stimulation with HD-tDCS. RESULTS Strong self-bias effect was observed across all experimental conditions. Neuromodulation of l-TPJ affected processing of other-labelled tone in the sound-label matching task. rIB was noted in baseline and anodal-HD-tDCS conditions where participants exhibited stronger binding for self-associated stimuli compared to other-associated stimuli. CONCLUSION l-TPJ may potentially play a critical role in self-other distinction. This may have possible implications for disorders of self-disturbances like psychosis.
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Affiliation(s)
- Vinaya Hari
- Department of Psychiatry, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru, India
| | - Anushree Bose
- Department of Psychiatry, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru, India.
| | - Vani Holebasavanahalli Thimmashetty
- Department of Psychiatry, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru, India; Department of Integrative Medicine, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru, India
| | - Rujuta Parlikar
- Department of Psychiatry, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru, India
| | - Vanteemar S Sreeraj
- Department of Psychiatry, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru, India
| | - Ganesan Venkatasubramanian
- Department of Psychiatry, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru, India
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Stephan-Otto C, Núñez C, Lombardini F, Cambra-Martí MR, Ochoa S, Senior C, Brébion G. Neurocognitive bases of self-monitoring of inner speech in hallucination prone individuals. Sci Rep 2023; 13:6251. [PMID: 37069194 PMCID: PMC10110610 DOI: 10.1038/s41598-023-32042-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 03/20/2023] [Indexed: 04/19/2023] Open
Abstract
Verbal hallucinations in schizophrenia patients might be seen as internal verbal productions mistaken for perceptions as a result of over-salient inner speech and/or defective self-monitoring processes. Similar cognitive mechanisms might underpin verbal hallucination proneness in the general population. We investigated, in a non-clinical sample, the cerebral activity associated with verbal hallucinatory predisposition during false recognition of familiar words -assumed to stem from poor monitoring of inner speech-vs. uncommon words. Thirty-seven healthy participants underwent a verbal recognition task. High- and low-frequency words were presented outside the scanner. In the scanner, the participants were then required to recognize the target words among equivalent distractors. Results showed that verbal hallucination proneness was associated with higher rates of false recognition of high-frequency words. It was further associated with activation of language and decisional brain areas during false recognitions of low-, but not high-, frequency words, and with activation of a recollective brain area during correct recognitions of low-, but not high-, frequency words. The increased tendency to report familiar words as targets, along with a lack of activation of the language, recollective, and decisional brain areas necessary for their judgement, suggests failure in the self-monitoring of inner speech in verbal hallucination-prone individuals.
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Affiliation(s)
- Christian Stephan-Otto
- Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Spain
- Parc Sanitari Sant Joan de Déu, Sant Boi de Llobregat, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
| | - Christian Núñez
- Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Spain
- Parc Sanitari Sant Joan de Déu, Sant Boi de Llobregat, Spain
| | | | | | - Susana Ochoa
- Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Spain
- Parc Sanitari Sant Joan de Déu, Sant Boi de Llobregat, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
| | - Carl Senior
- School of Life & Health Sciences, Aston University, Birmingham, UK.
- University of Gibraltar, Gibraltar, UK.
| | - Gildas Brébion
- Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Spain.
- Parc Sanitari Sant Joan de Déu, Sant Boi de Llobregat, Spain.
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain.
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11
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Keihani A, Sajadi SS, Hasani M, Ferrarelli F. Bayesian Optimization of Machine Learning Classification of Resting-State EEG Microstates in Schizophrenia: A Proof-of-Concept Preliminary Study Based on Secondary Analysis. Brain Sci 2022; 12:1497. [PMID: 36358423 PMCID: PMC9688063 DOI: 10.3390/brainsci12111497] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 10/22/2022] [Accepted: 11/02/2022] [Indexed: 01/19/2024] Open
Abstract
Resting-state electroencephalography (EEG) microstates reflect sub-second, quasi-stable states of brain activity. Several studies have reported alterations of microstate features in patients with schizophrenia (SZ). Based on these findings, it has been suggested that microstates may represent neurophysiological biomarkers for the classification of SZ. To explore this possibility, machine learning approaches can be employed. Bayesian optimization is a machine learning approach that selects the best-fitted machine learning model with tuned hyperparameters from existing models to improve the classification. In this proof-of-concept preliminary study based on secondary analysis, 20 microstate features were extracted from 14 SZ patients and 14 healthy controls' EEG signals. These parameters were then ranked as predictors based on their importance, and an optimized machine learning approach was applied to evaluate the performance of the classification. SZ patients had altered microstate features compared to healthy controls. Furthermore, Bayesian optimization outperformed conventional multivariate analyses and showed the highest accuracy (90.93%), AUC (0.90), sensitivity (91.37%), and specificity (90.48%), with reliable results using just six microstate predictors. Altogether, in this proof-of-concept study, we showed that machine learning with Bayesian optimization can be utilized to characterize EEG microstate alterations and contribute to the classification of SZ patients.
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Affiliation(s)
- Ahmadreza Keihani
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Seyed Saman Sajadi
- Department of Medical Physics & Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran 1416634793, Iran
| | - Mahsa Hasani
- Institute of Medical Science and Technology, Shahid Beheshti University, Tehran 1985717443, Iran
| | - Fabio Ferrarelli
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15213, USA
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12
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Perrottelli A, Giordano GM, Brando F, Giuliani L, Pezzella P, Mucci A, Galderisi S. Unveiling the Associations between EEG Indices and Cognitive Deficits in Schizophrenia-Spectrum Disorders: A Systematic Review. Diagnostics (Basel) 2022; 12:diagnostics12092193. [PMID: 36140594 PMCID: PMC9498272 DOI: 10.3390/diagnostics12092193] [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: 07/20/2022] [Revised: 09/05/2022] [Accepted: 09/06/2022] [Indexed: 11/16/2022] Open
Abstract
Cognitive dysfunctions represent a core feature of schizophrenia-spectrum disorders due to their presence throughout different illness stages and their impact on functioning. Abnormalities in electrophysiology (EEG) measures are highly related to these impairments, but the use of EEG indices in clinical practice is still limited. A systematic review of articles using Pubmed, Scopus and PsychINFO was undertaken in November 2021 to provide an overview of the relationships between EEG indices and cognitive impairment in schizophrenia-spectrum disorders. Out of 2433 screened records, 135 studies were included in a qualitative review. Although the results were heterogeneous, some significant correlations were identified. In particular, abnormalities in alpha, theta and gamma activity, as well as in MMN and P300, were associated with impairments in cognitive domains such as attention, working memory, visual and verbal learning and executive functioning during at-risk mental states, early and chronic stages of schizophrenia-spectrum disorders. The review suggests that machine learning approaches together with a careful selection of validated EEG and cognitive indices and characterization of clinical phenotypes might contribute to increase the use of EEG-based measures in clinical settings.
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13
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Kowalski J, Styła R. Visual worry in patients with schizophrenia. J Psychiatr Res 2022; 153:116-124. [PMID: 35810601 DOI: 10.1016/j.jpsychires.2022.07.007] [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: 10/15/2021] [Revised: 06/22/2022] [Accepted: 07/01/2022] [Indexed: 10/17/2022]
Abstract
OBJECTIVE Worrying is a pervasive transdiagnostic symptom in schizophrenia. It is most often associated in the literature with verbal modality due to many studies of its presence in generalised anxiety disorder. The current study aimed to elucidate worry in different sensory modalities, visual and verbal, in individuals with schizophrenia. METHOD We tested persons with schizophrenia (n = 92) and healthy controls (n = 138) in a cross-sectional design. We used questionnaires of visual and verbal worry (original Worry Modality Questionnaire), trait worry (Penn State Worry Questionnaire) and general psychopathology symptoms (General Functioning Questionnaire-58 and Brief Psychiatric Rating Scale). RESULTS Both visual and verbal worry were associated with psychotic, anxiety and general symptoms of psychopathology in both groups with medium to large effect sizes. Regression analyses indicated that visual worry was a single significant predictor of positive psychotic symptoms in a model with verbal and trait worry, both in clinical and control groups (β's of 0.49 and 0.38, respectively). Visual worry was also a superior predictor of anxiety and general psychopathology severity (β's of 0.34 and 0.37, respectively) than verbal worry (β's of 0.03 and -0.02, respectively), under control of trait worry, in the schizophrenia group. We also proposed two indices of worry modality dominance and analysed profiles of dominating worry modality in both groups. CONCLUSIONS Our study is the first to demonstrate that visual worry might be of specific importance for understanding psychotic and general psychopathology symptoms in persons with schizophrenia.
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Affiliation(s)
- Joachim Kowalski
- Experimental Psychopathology Laboratory, Institute of Psychology, Polish Academy of Sciences, Warsaw, Poland.
| | - Rafał Styła
- Faculty of Psychology, University of Warsaw, Warsaw, Poland
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14
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Johnson JF, Belyk M, Schwartze M, Pinheiro AP, Kotz SA. Hypersensitivity to passive voice hearing in hallucination proneness. Front Hum Neurosci 2022; 16:859731. [PMID: 35966990 PMCID: PMC9366353 DOI: 10.3389/fnhum.2022.859731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Accepted: 06/29/2022] [Indexed: 11/21/2022] Open
Abstract
Voices are a complex and rich acoustic signal processed in an extensive cortical brain network. Specialized regions within this network support voice perception and production and may be differentially affected in pathological voice processing. For example, the experience of hallucinating voices has been linked to hyperactivity in temporal and extra-temporal voice areas, possibly extending into regions associated with vocalization. Predominant self-monitoring hypotheses ascribe a primary role of voice production regions to auditory verbal hallucinations (AVH). Alternative postulations view a generalized perceptual salience bias as causal to AVH. These theories are not mutually exclusive as both ascribe the emergence and phenomenology of AVH to unbalanced top-down and bottom-up signal processing. The focus of the current study was to investigate the neurocognitive mechanisms underlying predisposition brain states for emergent hallucinations, detached from the effects of inner speech. Using the temporal voice area (TVA) localizer task, we explored putative hypersalient responses to passively presented sounds in relation to hallucination proneness (HP). Furthermore, to avoid confounds commonly found in in clinical samples, we employed the Launay-Slade Hallucination Scale (LSHS) for the quantification of HP levels in healthy people across an experiential continuum spanning the general population. We report increased activation in the right posterior superior temporal gyrus (pSTG) during the perception of voice features that positively correlates with increased HP scores. In line with prior results, we propose that this right-lateralized pSTG activation might indicate early hypersensitivity to acoustic features coding speaker identity that extends beyond own voice production to perception in healthy participants prone to experience AVH.
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Affiliation(s)
- Joseph F. Johnson
- Department of Neuropsychology and Psychopharmacology, University of Maastricht, Maastricht, Netherlands
| | - Michel Belyk
- Department of Psychology, Edge Hill University, Ormskirk, United Kingdom
| | - Michael Schwartze
- Department of Neuropsychology and Psychopharmacology, University of Maastricht, Maastricht, Netherlands
| | - Ana P. Pinheiro
- Faculdade de Psicologia, Universidade de Lisboa, Lisbon, Portugal
| | - Sonja A. Kotz
- Department of Neuropsychology and Psychopharmacology, University of Maastricht, Maastricht, Netherlands
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- *Correspondence: Sonja A. Kotz,
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