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Storozheva ZI, Kirenskaya AV, Samylkin DV, Gruden MA, Sewell RDE. Association of GAD1 gene polymorphism rs3749034 with the information processing and cognitive event-related potentials in schizophrenia patients and healthy subjects. Clin Neurophysiol 2024; 166:142-151. [PMID: 39168087 DOI: 10.1016/j.clinph.2024.08.001] [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: 02/24/2024] [Revised: 08/05/2024] [Accepted: 08/05/2024] [Indexed: 08/23/2024]
Abstract
OBJECTIVE Glutamic acid decarboxylase, an enzyme in GABA biosynthesis, is encoded by the GAD1 gene, the transcriptional activity of which is affected by the rs3749034 polymorphism. The aim was to investigate the effects of rs3749034 on cognitive event-related potentials (P300) in healthy subjects and schizophrenic patients. METHODS Determination of rs3749034 polymorphism was performed in 89 healthy volunteers and 109 schizophrenic patients (males). Two-stimulus oddball task performance and P300 auditory evoked potentials were analyzed and patient symptomatology was assessed using the Positive and Negative Syndrome Scale (PANSS). RESULTS An increased frequency of C allele carriers was disclosed in patients. In controls, superior task performance was observed in cytosine-thymine carriers, while a greater P300 amplitude and shorter latency were found in C/C carriers. Analogous effects were found in patients with a disease onset before 25 years of age. Higher N5 and lower P3 and G5 PANSS scales were revealed in C/C homozygotes. CONCLUSIONS The findings substantiate an involvement of GABA-ergic mechanisms in maintaining an optimal excitatory-inhibitory balance and an association of rs3749034 with early-onset disorder and negative symptoms of schizophrenia. SIGNIFICANCE These results are important for understanding underlying mechanisms and the development of evidence-based methods for assessing the risk of schizophrenia.
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Affiliation(s)
| | - Anna V Kirenskaya
- Center of Psychosomatic Medicine and Psychotherapy "Alvian", Moscow, Russia
| | - Denis V Samylkin
- National Medical Research Centre for Psychiatry and Narcology, Moscow, Russia
| | - Marina A Gruden
- P. K. Anokhin Institute of Normal Physiology, Moscow, Russia
| | - Robert D E Sewell
- Cardiff School of Pharmacy and Pharmaceutical Sciences, Cardiff University, Cardiff, UK; Department of Pharmacy, CECOS University, Peshawar 25000, Khyber Pakhtunkhwa, Pakistan.
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Yi C, Li F, Wang J, Li Y, Zhang J, Chen W, Jiang L, Yao D, Xu P, He B, Dong W. Abnormal trial-to-trial variability in P300 time-varying directed eeg network of schizophrenia. Med Biol Eng Comput 2024:10.1007/s11517-024-03133-9. [PMID: 38834855 DOI: 10.1007/s11517-024-03133-9] [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: 06/08/2023] [Accepted: 05/18/2024] [Indexed: 06/06/2024]
Abstract
Cognitive disturbance in identifying, processing, and responding to salient or novel stimuli are typical attributes of schizophrenia (SCH), and P300 has been proven to serve as a reliable psychosis endophenotype. The instability of neural processing across trials, i.e., trial-to-trial variability (TTV), is getting increasing attention in uncovering how the SCH "noisy" brain organizes during cognition processes. Nevertheless, the TTV in the brain network remains unrevealed, notably how it varies in different task stages. In this study, resorting to the time-varying directed electroencephalogram (EEG) network, we investigated the time-resolved TTV of the functional organizations subserving the evoking of P300. Results revealed anomalous TTV in time-varying networks across the delta, theta, alpha, beta1, and beta2 bands of SCH. The TTV of cross-band time-varying network properties can efficiently recognize SCH (accuracy: 83.39%, sensitivity: 89.22%, and specificity: 74.55%) and evaluate the psychiatric symptoms (i.e., Hamilton's depression scale-24, r = 0.430, p = 0.022, RMSE = 4.891; Hamilton's anxiety scale-14, r = 0.377, p = 0.048, RMSE = 4.575). Our study brings new insights into probing the time-resolved functional organization of the brain, and TTV in time-varying networks may provide a powerful tool for mining the substrates accounting for SCH and diagnostic evaluation of SCH.
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Affiliation(s)
- Chanlin Yi
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, 611731, China
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Fali Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, 611731, China
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, Chengdu, 2019RU035, China
- Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau, China
| | - Jiuju Wang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
| | - Yuqin Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, 611731, China
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Jiamin Zhang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, 611731, China
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Wanjun Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, 611731, China
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Lin Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, 611731, China
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, 611731, China
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, Chengdu, 2019RU035, China
- School of Electrical Engineering, Zhengzhou University, Zhengzhou, 450001, China
| | - Peng Xu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, 611731, China.
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, China.
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China.
- Radiation Oncology Key Laboratory of Sichuan Province, Chengdu, 610041, China.
- Rehabilitation Center, Qilu Hospital of Shandong University, Jinan, 250012, China.
| | - Baoming He
- Department of Neurology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China.
- Chinese Academy of Sciences Sichuan Translational Medicine Research Hospital, Chengdu, 610072, China.
| | - Wentian Dong
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China.
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Wang B, Otten LJ, Schulze K, Afrah H, Varney L, Cotic M, Saadullah Khani N, Linden JF, Kuchenbaecker K, McQuillin A, Hall MH, Bramon E. Is auditory processing measured by the N100 an endophenotype for psychosis? A family study and a meta-analysis. Psychol Med 2024; 54:1559-1572. [PMID: 37997703 DOI: 10.1017/s0033291723003409] [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: 11/25/2023]
Abstract
BACKGROUND The N100, an early auditory event-related potential, has been found to be altered in patients with psychosis. However, it is unclear if the N100 is a psychosis endophenotype that is also altered in the relatives of patients. METHODS We conducted a family study using the auditory oddball paradigm to compare the N100 amplitude and latency across 243 patients with psychosis, 86 unaffected relatives, and 194 controls. We then conducted a systematic review and a random-effects meta-analysis pooling our results and 14 previously published family studies. We compared data from a total of 999 patients, 1192 relatives, and 1253 controls in order to investigate the evidence and degree of N100 differences. RESULTS In our family study, patients showed reduced N100 amplitudes and prolonged N100 latencies compared to controls, but no significant differences were found between unaffected relatives and controls. The meta-analysis revealed a significant reduction of the N100 amplitude and delay of the N100 latency in both patients with psychosis (standardized mean difference [s.m.d.] = -0.48 for N100 amplitude and s.m.d. = 0.43 for N100 latency) and their relatives (s.m.d. = - 0.19 for N100 amplitude and s.m.d. = 0.33 for N100 latency). However, only the N100 latency changes in relatives remained significant when excluding studies with affected relatives. CONCLUSIONS N100 changes, especially prolonged N100 latencies, are present in both patients with psychosis and their relatives, making the N100 a promising endophenotype for psychosis. Such changes in the N100 may reflect changes in early auditory processing underlying the etiology of psychosis.
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Affiliation(s)
- Baihan Wang
- Division of Psychiatry, University College London, London, UK
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Leun J Otten
- Institute of Cognitive Neuroscience, University College London, London, UK
| | - Katja Schulze
- South London and Maudsley NHS Foundation Trust, London, UK
| | - Hana Afrah
- Division of Psychiatry, University College London, London, UK
| | - Lauren Varney
- Division of Psychiatry, University College London, London, UK
| | - Marius Cotic
- Division of Psychiatry, University College London, London, UK
- Department of Genetics & Genomic Medicine, UCL Great Ormond Street Institute of Child Health, University College London, London, UK
| | | | - Jennifer F Linden
- Ear Institute, University College London, London, UK
- Department of Neuroscience, Physiology & Pharmacology, University College London, London, UK
| | - Karoline Kuchenbaecker
- Division of Psychiatry, University College London, London, UK
- Division of Biosciences, UCL Genetics Institute, University College London, London, UK
| | | | - Mei-Hua Hall
- Psychosis Neurobiology Laboratory, Harvard Medical School, McLean Hospital, Belmont, MA, USA
| | - Elvira Bramon
- Division of Psychiatry, University College London, London, UK
- Institute of Cognitive Neuroscience, University College London, London, UK
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Hou Y, Xia H, He T, Zhang B, Qiu G, Chen A. N2 Responses in Youths With Psychosis Risk Syndrome and Their Association With Clinical Outcomes: A Cohort Follow-Up Study Based on the Three-Stimulus Visual Oddball Paradigm. Am J Psychiatry 2024; 181:330-341. [PMID: 38419496 DOI: 10.1176/appi.ajp.20221013] [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] [Indexed: 03/02/2024]
Abstract
OBJECTIVE Schizophrenia often occurs during youth, and psychosis risk syndrome occurs before the onset of psychosis. The aim of this study was to determine whether the visual event-related potential responses in youths with psychosis risk syndrome were defective in the presence of interference stimuli and associated with their clinical outcomes. METHODS A total of 223 participants, including 122 patients with psychosis risk syndrome, 50 patients with emotional disorders, and 51 healthy control subjects, were assessed. Baseline EEG was recorded during the three-stimulus visual oddball task. The event-related potentials induced by square pictures with different colors were measured. Almost all patients with psychosis risk syndrome were followed up for 12 months and were reclassified into three subgroups: conversion, symptomatic, and remission. The differences in baseline event-related potential responses were compared among the clinical outcome subgroups. RESULTS The average N2 amplitude of the psychosis risk syndrome group was significantly less negative than that in the healthy control group (d=0.53). The baseline average N2 amplitude in the conversion subgroup was significantly less negative than that in the symptomatic (d=0.58) and remission (d=0.50) subgroups and in the healthy control group (d=0.97). The average N2 amplitude did not differ significantly between the symptomatic and remission subgroups (d=0.02). However, it was significantly less negative in the symptomatic and remission subgroups than in the healthy control group (d=0.46 and d=0.38). No statistically significant results were found in the P3 response. CONCLUSIONS Youths with psychosis risk syndrome had significant N2 amplitude defects in attention processing with interference stimuli. N2 amplitude shows potential as a prognostic biomarker of clinical outcome in the psychosis risk syndrome.
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Affiliation(s)
- Yongqing Hou
- Key Laboratory of Cognition and Personality of the Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China (Hou, Xia, Zhang); Clinical Laboratory of Psychiatry, Mental Health Center of Guangyuan, Sichuan, China (Hou, He); College of Education, Psychology, and Social Work, Flinders University, Adelaide, Australia (Zhang); College of Teacher Education, Ningxia University, Yinchuan, China (Qiu); School of Psychology, Shanghai University of Sport, Shanghai, China (Chen)
| | - Haishuo Xia
- Key Laboratory of Cognition and Personality of the Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China (Hou, Xia, Zhang); Clinical Laboratory of Psychiatry, Mental Health Center of Guangyuan, Sichuan, China (Hou, He); College of Education, Psychology, and Social Work, Flinders University, Adelaide, Australia (Zhang); College of Teacher Education, Ningxia University, Yinchuan, China (Qiu); School of Psychology, Shanghai University of Sport, Shanghai, China (Chen)
| | - Tianbao He
- Key Laboratory of Cognition and Personality of the Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China (Hou, Xia, Zhang); Clinical Laboratory of Psychiatry, Mental Health Center of Guangyuan, Sichuan, China (Hou, He); College of Education, Psychology, and Social Work, Flinders University, Adelaide, Australia (Zhang); College of Teacher Education, Ningxia University, Yinchuan, China (Qiu); School of Psychology, Shanghai University of Sport, Shanghai, China (Chen)
| | - Bohua Zhang
- Key Laboratory of Cognition and Personality of the Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China (Hou, Xia, Zhang); Clinical Laboratory of Psychiatry, Mental Health Center of Guangyuan, Sichuan, China (Hou, He); College of Education, Psychology, and Social Work, Flinders University, Adelaide, Australia (Zhang); College of Teacher Education, Ningxia University, Yinchuan, China (Qiu); School of Psychology, Shanghai University of Sport, Shanghai, China (Chen)
| | - Guiping Qiu
- Key Laboratory of Cognition and Personality of the Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China (Hou, Xia, Zhang); Clinical Laboratory of Psychiatry, Mental Health Center of Guangyuan, Sichuan, China (Hou, He); College of Education, Psychology, and Social Work, Flinders University, Adelaide, Australia (Zhang); College of Teacher Education, Ningxia University, Yinchuan, China (Qiu); School of Psychology, Shanghai University of Sport, Shanghai, China (Chen)
| | - Antao Chen
- Key Laboratory of Cognition and Personality of the Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China (Hou, Xia, Zhang); Clinical Laboratory of Psychiatry, Mental Health Center of Guangyuan, Sichuan, China (Hou, He); College of Education, Psychology, and Social Work, Flinders University, Adelaide, Australia (Zhang); College of Teacher Education, Ningxia University, Yinchuan, China (Qiu); School of Psychology, Shanghai University of Sport, Shanghai, China (Chen)
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Hamilton HK, Mathalon DH, Ford JM. P300 in schizophrenia: Then and now. Biol Psychol 2024; 187:108757. [PMID: 38316196 DOI: 10.1016/j.biopsycho.2024.108757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 01/23/2024] [Accepted: 01/23/2024] [Indexed: 02/07/2024]
Abstract
The 1965 discovery of the P300 component of the electroencephalography (EEG)-based event-related potential (ERP), along with the subsequent identification of its alteration in people with schizophrenia, initiated over 50 years of P300 research in schizophrenia. Here, we review what we now know about P300 in schizophrenia after nearly six decades of research. We describe recent efforts to expand our understanding of P300 beyond its sensitivity to schizophrenia itself to its potential role as a biomarker of risk for psychosis or a heritable endophenotype that bridges genetic risk and psychosis phenomenology. We also highlight efforts to move beyond a syndrome-based approach to understand P300 within the context of the clinical, cognitive, and presumed pathophysiological heterogeneity among people diagnosed with schizophrenia. Finally, we describe several recent approaches that extend beyond measuring the traditional P300 ERP component in people with schizophrenia, including time-frequency analyses and pharmacological challenge studies, that may help to clarify specific cognitive mechanisms that are disrupted in schizophrenia. Moreover, we discuss several promising areas for future research, including studies of animal models that can be used for treatment development.
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Affiliation(s)
- Holly K Hamilton
- University of Minnesota, Department of Psychiatry & Behavioral Sciences, Minneapolis, MN, USA; Minneapolis Veterans Affairs Health Care System, Minneapolis, MN, USA; University of California, San Francisco, Department of Psychiatry & Behavioral Sciences, San Francisco, CA, USA; San Francisco Veterans Affairs Health Care System, San Francisco, CA, USA.
| | - Daniel H Mathalon
- University of California, San Francisco, Department of Psychiatry & Behavioral Sciences, San Francisco, CA, USA; San Francisco Veterans Affairs Health Care System, San Francisco, CA, USA
| | - Judith M Ford
- University of California, San Francisco, Department of Psychiatry & Behavioral Sciences, San Francisco, CA, USA; San Francisco Veterans Affairs Health Care System, San Francisco, CA, USA
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Kirschner H, Nassar MR, Fischer AG, Frodl T, Meyer-Lotz G, Froböse S, Seidenbecher S, Klein TA, Ullsperger M. Transdiagnostic inflexible learning dynamics explain deficits in depression and schizophrenia. Brain 2024; 147:201-214. [PMID: 38058203 PMCID: PMC10766268 DOI: 10.1093/brain/awad362] [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: 07/13/2023] [Revised: 09/25/2023] [Accepted: 10/10/2023] [Indexed: 12/08/2023] Open
Abstract
Deficits in reward learning are core symptoms across many mental disorders. Recent work suggests that such learning impairments arise by a diminished ability to use reward history to guide behaviour, but the neuro-computational mechanisms through which these impairments emerge remain unclear. Moreover, limited work has taken a transdiagnostic approach to investigate whether the psychological and neural mechanisms that give rise to learning deficits are shared across forms of psychopathology. To provide insight into this issue, we explored probabilistic reward learning in patients diagnosed with major depressive disorder (n = 33) or schizophrenia (n = 24) and 33 matched healthy controls by combining computational modelling and single-trial EEG regression. In our task, participants had to integrate the reward history of a stimulus to decide whether it is worthwhile to gamble on it. Adaptive learning in this task is achieved through dynamic learning rates that are maximal on the first encounters with a given stimulus and decay with increasing stimulus repetitions. Hence, over the course of learning, choice preferences would ideally stabilize and be less susceptible to misleading information. We show evidence of reduced learning dynamics, whereby both patient groups demonstrated hypersensitive learning (i.e. less decaying learning rates), rendering their choices more susceptible to misleading feedback. Moreover, there was a schizophrenia-specific approach bias and a depression-specific heightened sensitivity to disconfirmational feedback (factual losses and counterfactual wins). The inflexible learning in both patient groups was accompanied by altered neural processing, including no tracking of expected values in either patient group. Taken together, our results thus provide evidence that reduced trial-by-trial learning dynamics reflect a convergent deficit across depression and schizophrenia. Moreover, we identified disorder distinct learning deficits.
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Affiliation(s)
- Hans Kirschner
- Institute of Psychology, Otto-von-Guericke University, D-39106 Magdeburg, Germany
| | - Matthew R Nassar
- Robert J. and Nancy D. Carney Institute for Brain Science, Brown University, Providence, RI 02912-1821, USA
- Department of Neuroscience, Brown University, Providence, RI 02912-1821, USA
| | - Adrian G Fischer
- Department of Education and Psychology, Freie Universität Berlin, D-14195 Berlin, Germany
| | - Thomas Frodl
- Department of Psychiatry and Psychotherapy, Otto-von-Guericke University, D-39106 Magdeburg, Germany
- Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen 52074, Germany
- German Center for Mental Health (DZPG), D-39106 Magdeburg, Germany
- Center for Intervention and Research on adaptive and maladaptive brain Circuits underlying mental health (C-I-R-C), Jena-Magdeburg-Halle, D-39106 Magdeburg, Germany
| | - Gabriela Meyer-Lotz
- Department of Psychiatry and Psychotherapy, Otto-von-Guericke University, D-39106 Magdeburg, Germany
| | - Sören Froböse
- Department of Psychiatry and Psychotherapy, Otto-von-Guericke University, D-39106 Magdeburg, Germany
| | - Stephanie Seidenbecher
- Department of Psychiatry and Psychotherapy, Otto-von-Guericke University, D-39106 Magdeburg, Germany
| | - Tilmann A Klein
- Institute of Psychology, Otto-von-Guericke University, D-39106 Magdeburg, Germany
- Center for Behavioral Brain Sciences, D-39106 Magdeburg, Germany
| | - Markus Ullsperger
- Institute of Psychology, Otto-von-Guericke University, D-39106 Magdeburg, Germany
- German Center for Mental Health (DZPG), D-39106 Magdeburg, Germany
- Center for Intervention and Research on adaptive and maladaptive brain Circuits underlying mental health (C-I-R-C), Jena-Magdeburg-Halle, D-39106 Magdeburg, Germany
- Center for Behavioral Brain Sciences, D-39106 Magdeburg, Germany
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Hou Y, Qiu G, Xia H, He T, Liu X, Chen A. The specificity of the auditory P300 responses and its association with clinical outcomes in youth with psychosis risk syndrome. Int J Clin Health Psychol 2024; 24:100437. [PMID: 38292829 PMCID: PMC10825643 DOI: 10.1016/j.ijchp.2024.100437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2023] [Accepted: 01/02/2024] [Indexed: 02/01/2024] Open
Abstract
Background Schizophrenia often occurs in youth, and psychosis risk syndrome (PRS) occurs before the onset of psychosis. Assessing the neuropsychological abnormalities of PRS individuals can help in early identification and active intervention of mental illness. Auditory P300 amplitude defect is an important manifestation of attention processing abnormality in PRS, but it is still unclear whether there are abnormalities in the attention processing of rhythmic compound tone stimuli in PRS individuals, and whether the P300 amplitude induced by these stimuli is specific to PRS individuals and related to their clinical outcomes. Methods In total, 226 participants, including 122 patients with PRS, 51 patients with emotional disorders (ED), and 53 healthy controls (HC) were assessed. Baseline electroencephalography was recorded during the compound tone oddball task. The event-related potentials (ERPs) induced by rhythmic compound tone stimuli of two frequencies (20-Hz, 40-Hz) were measured. Almost all patients with PRS were followed up for 12 months and reclassified into four groups: PRS-conversion, PRS-symptomatic, PRS-emotional disorder, and PRS-complete remission. The differences in baseline ERPs were compared among the clinical outcome groups. Results Regardless of the stimulation frequency, the average P300 amplitude were significantly higher in patients with PRS than in those with ED (p = 0.003, d = 0.48) and in HC (p = 0.002, d = 0.44) group. The average P300 amplitude of PRS-conversion group was significantly higher than that of the PRS-complete remission (p = 0.016, d = 0.72) and HC group (p = 0.001, d = 0.76), and the average P300 amplitude of PRS-symptomatic group was significantly higher than that of the HC group (p = 0.006, d = 0.48). Regardless of the groups (PRS, ED, HC) or the PRS clinical outcome groups, the average P300 amplitude induced by 20-Hz tone stimulation was significantly higher than that induced by 40-Hz stimulation (ps < 0.001, Ƞ2 = 0.074-0.082). The average reaction times of PRS was significantly faster than that of ED (p = 0.01, d = 0.38), and the average reaction times of the participants to 20-Hz target stimulation was significantly faster than that to 40-Hz target stimulation (p < 0.001, d = 0.21). Conclusion The auditory P300 amplitude induced by rhythmic compound tone stimuli is a specific electrophysiological manifestation of PRS, and the auditory P300 amplitude induced by compound tone stimuli shows promise as a putative prognostic biomarker for PRS clinical outcomes, including conversion to psychosis and clinical complete remission.
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Affiliation(s)
- Yongqing Hou
- Key Laboratory of Cognition and Personality of Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
- Mental Health Center of Guangyuan, Sichuan, China
| | - Guiping Qiu
- College of Teacher Education, Ningxia University, Yinchuan, China
| | - Haishuo Xia
- Key Laboratory of Cognition and Personality of Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
| | - Tianbao He
- Mental Health Center of Guangyuan, Sichuan, China
| | - Xiaoxian Liu
- Faculty of Education, Henan Normal University, Xinxiang, China
| | - Antao Chen
- School of Psychology, Research Center for Exercise and Brain Science, Shanghai University of Sport, Shanghai, China
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8
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Wang B, Irizar H, Thygesen JH, Zartaloudi E, Austin-Zimmerman I, Bhat A, Harju-Seppänen J, Pain O, Bass N, Gkofa V, Alizadeh BZ, van Amelsvoort T, Arranz MJ, Bender S, Cahn W, Stella Calafato M, Crespo-Facorro B, Di Forti M, Giegling I, de Haan L, Hall J, Hall MH, van Haren N, Iyegbe C, Kahn RS, Kravariti E, Lawrie SM, Lin K, Luykx JJ, Mata I, McDonald C, McIntosh AM, Murray RM, Picchioni M, Powell J, Prata DP, Rujescu D, Rutten BPF, Shaikh M, Simons CJP, Toulopoulou T, Weisbrod M, van Winkel R, Kuchenbaecker K, McQuillin A, Bramon E. Psychosis Endophenotypes: A Gene-Set-Specific Polygenic Risk Score Analysis. Schizophr Bull 2023; 49:1625-1636. [PMID: 37582581 PMCID: PMC10686343 DOI: 10.1093/schbul/sbad088] [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: 08/17/2023]
Abstract
BACKGROUND AND HYPOTHESIS Endophenotypes can help to bridge the gap between psychosis and its genetic predispositions, but their underlying mechanisms remain largely unknown. This study aims to identify biological mechanisms that are relevant to the endophenotypes for psychosis, by partitioning polygenic risk scores into specific gene sets and testing their associations with endophenotypes. STUDY DESIGN We computed polygenic risk scores for schizophrenia and bipolar disorder restricted to brain-related gene sets retrieved from public databases and previous publications. Three hundred and seventy-eight gene-set-specific polygenic risk scores were generated for 4506 participants. Seven endophenotypes were also measured in the sample. Linear mixed-effects models were fitted to test associations between each endophenotype and each gene-set-specific polygenic risk score. STUDY RESULTS After correction for multiple testing, we found that a reduced P300 amplitude was associated with a higher schizophrenia polygenic risk score of the forebrain regionalization gene set (mean difference per SD increase in the polygenic risk score: -1.15 µV; 95% CI: -1.70 to -0.59 µV; P = 6 × 10-5). The schizophrenia polygenic risk score of forebrain regionalization also explained more variance of the P300 amplitude (R2 = 0.032) than other polygenic risk scores, including the genome-wide polygenic risk scores. CONCLUSIONS Our finding on reduced P300 amplitudes suggests that certain genetic variants alter early brain development thereby increasing schizophrenia risk years later. Gene-set-specific polygenic risk scores are a useful tool to elucidate biological mechanisms of psychosis and endophenotypes, offering leads for experimental validation in cellular and animal models.
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Affiliation(s)
- Baihan Wang
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, UK
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Haritz Irizar
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, UK
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Johan H Thygesen
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, UK
- Institute of Health Informatics, University College London, London, UK
| | - Eirini Zartaloudi
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, UK
| | - Isabelle Austin-Zimmerman
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, UK
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Anjali Bhat
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, UK
| | - Jasmine Harju-Seppänen
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, UK
| | - Oliver Pain
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Nick Bass
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, UK
| | - Vasiliki Gkofa
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, UK
| | - Behrooz Z Alizadeh
- University of Groningen, University Medical Center Groningen, University Center for Psychiatry, Rob Giel Research Center, Groningen, The Netherlands
- Department of Epidemiology, University Medical Center Groningen, Groningen, The Netherlands
| | - Therese van Amelsvoort
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Maria J Arranz
- Fundació Docència i Recerca Mutua Terrassa, Terrassa, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Institut de Recerca Biomédica Sant Pau (IIB-Sant Pau), Barcelona, Spain
| | - Stephan Bender
- Department of Child and Adolescent Psychiatry, Psychosomatic Medicine and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Wiepke Cahn
- Department of Psychiatry, Brain Centre Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Altrecht, General Mental Health Care, Utrecht, The Netherlands
| | - Maria Stella Calafato
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, UK
| | - Benedicto Crespo-Facorro
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Sevilla, Spain
- Department of Psychiatry, University Hospital Virgen del Rocio, School of Medicine, University of Sevilla–IBiS, Sevilla, Spain
| | - Marta Di Forti
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | | | - Ina Giegling
- Comprehensive Centers for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Austria
| | - Lieuwe de Haan
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
- Arkin, Institute for Mental Health, Amsterdam, The Netherlands
| | - Jeremy Hall
- Neuroscience and Mental Health Innovation Institute, School of Medicine, Cardiff University, Hadyn Ellis Building, Mandy Road, Cardiff, UK
| | - Mei-Hua Hall
- Psychosis Neurobiology Laboratory, Harvard Medical School, McLean Hospital, Belmont, MA, USA
| | - Neeltje van Haren
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center, Sophia’s Children Hospital, Rotterdam, The Netherlands
| | - Conrad Iyegbe
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - René S Kahn
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Eugenia Kravariti
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Stephen M Lawrie
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Kuang Lin
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Jurjen J Luykx
- Department of Psychiatry, Brain Centre Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Department of Translational Neuroscience, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Ignacio Mata
- Fundacion Argibide, Pamplona, Spain
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain
| | - Colm McDonald
- The Centre for Neuroimaging & Cognitive Genomics (NICOG) and NCBES Galway Neuroscience Centre, University of Galway, Galway, Ireland
| | - Andrew M McIntosh
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Robin M Murray
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | | | - Marco Picchioni
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- St Magnus Hospital, Surrey, UK
| | - John Powell
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Diana P Prata
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciencias da Universidade de Lisboa, Portugal
| | - Dan Rujescu
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
- Division of General Psychiatry, Medical University of Vienna, Austria
| | - Bart P F Rutten
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Madiha Shaikh
- North East London Foundation Trust, London, UK
- Research Department of Clinical, Educational and Health Psychology, University College London, London, UK
| | - Claudia J P Simons
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, The Netherlands
- GGzE Institute for Mental Health Care, Eindhoven, The Netherlands
| | - Timothea Toulopoulou
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- Interdisciplinary Program in Neuroscience, Aysel Sabuncu Brain Research Center, Bilkent University, Ankara, Türkiye
- National Magnetic Resonance Research Center (UMRAM), Bilkent University, Ankara, Türkiye
- Department of Psychology, Bilkent University, Ankara, Türkiye
- School of Medicine, Department of Psychiatry, National and Kapodistrian University of Athens, Athens, Greece
- Department of Psychiatry and Behavioral Health System, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Matthias Weisbrod
- Department of General Psychiatry, Center of Psychosocial Medicine, University of Heidelberg, Germany
- SRH Klinikum, Karlsbad-Langensteinbach, Germany
| | - Ruud van Winkel
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, The Netherlands
- KU Leuven, Department of Neuroscience, Research Group Psychiatry, Leuven, Belgium
| | - Karoline Kuchenbaecker
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, UK
- UCL Genetics Institute, Division of Biosciences, University College London, London, UK
| | - Andrew McQuillin
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, UK
| | - Elvira Bramon
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, UK
- Institute of Cognitive Neuroscience, University College London, London, UK
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9
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Zhang Y, Yang T, He Y, Meng F, Zhang K, Jin X, Cui X, Luo X. Value of P300 amplitude in the diagnosis of untreated first-episode schizophrenia and psychosis risk syndrome in children and adolescents. BMC Psychiatry 2023; 23:743. [PMID: 37828471 PMCID: PMC10571359 DOI: 10.1186/s12888-023-05218-5] [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: 04/01/2023] [Accepted: 09/23/2023] [Indexed: 10/14/2023] Open
Abstract
BACKGROUND Identifying the characteristic neurobiological changes of early psychosis is helpful for early clinical diagnosis. However, previous studies on the brain electrophysiology of children and adolescents with psychosis are rare. METHODS This study compared P300 amplitude at multiple electrodes between children and adolescents with first-episode schizophrenia (FES, n = 48), children and adolescents with psychosis risk syndrome (PRS, n = 24), and healthy controls (HC, n = 30). Receiver operating characteristic (ROC) analysis was used to test the ability of P300 amplitude to distinguish FES, PRS and HC individuals. RESULTS The P300 amplitude in the FES group were significantly lower than those in the HC at the Cz, Pz, and Oz electrodes. The P300 amplitude was also significantly lower in the prodromal group than in the HC at the Pz and Oz electrodes. ROC curve analysis showed that at the Pz electrode, the P300 amplitude evoked by the target and standard stimulus showed high sensitivity, specificity, accuracy, and area under the curve value for distinguishing FES from HC individuals. CONCLUSIONS This study found early visual P300 deficits in children and adolescents with FES and PRS, with the exclusion of possible influence of medication and chronic medical conditions, suggesting the value of P300 amplitude for the identification of early psychosis.
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Affiliation(s)
- Yaru Zhang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, 410011, China
| | - Tingyu Yang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, 410011, China
| | - Yuqiong He
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, 410011, China
| | - Fanchao Meng
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Kun Zhang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, 410011, China
| | - Xingyue Jin
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, 410011, China
| | - Xilong Cui
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, 410011, China.
| | - Xuerong Luo
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, 410011, China.
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10
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Wang J, Dong W, Li Y, Wydell TN, Quan W, Tian J, Song Y, Jiang L, Li F, Yi C, Zhang Y, Yao D, Xu P. Discrimination of auditory verbal hallucination in schizophrenia based on EEG brain networks. Psychiatry Res Neuroimaging 2023; 331:111632. [PMID: 36958075 DOI: 10.1016/j.pscychresns.2023.111632] [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: 12/26/2022] [Revised: 02/23/2023] [Accepted: 03/15/2023] [Indexed: 03/25/2023]
Abstract
Auditory verbal hallucinations (AVH) are a core positive symptom of schizophrenia and are regarded as a consequence of the functional breakdown in the related sensory process. Yet, the potential mechanism of AVH is still lacking. In the present study, we explored the difference between AVHs (n = 23) and non-AVHs (n = 19) in schizophrenia and healthy controls (n = 29) by using multidimensional electroencephalograms data during an auditory oddball task. Compared to healthy controls, both AVH and non-AVH groups showed reduced P300 amplitudes. Additionally, the results from brain networks analysis revealed that AVH patients showed reduced left frontal to posterior parietal/temporal connectivity compared to non-AVH patients. Moreover, using the fused network properties of both delta and theta bands as features for in-depth learning made it possible to identify the AVH from non-AVH patients at an accuracy of 80.95%. The left frontal-parietal/temporal networks seen in the auditory oddball paradigm might be underlying biomarkers of AVH in schizophrenia. This study demonstrated for the first time the functional breakdown of the auditory processing pathway in the AVH patients, leading to a better understanding of the atypical brain network of the AVH patients.
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Affiliation(s)
- Jiuju Wang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Wentian Dong
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Yuqin Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu, Sichuan 611731, China; School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Taeko N Wydell
- Centre for Cognitive Neuroscience, Brunel University London, Uxbridge, UK
| | - Wenxiang Quan
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Ju Tian
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Yanping Song
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Lin Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu, Sichuan 611731, China; School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Fali Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu, Sichuan 611731, China; School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, China; Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, Chengdu 2019RU035, China.
| | - Chanlin Yi
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu, Sichuan 611731, China; School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Yangsong Zhang
- School of Computer Science and Technology, Southwest University of Science and Technology, Mianyang 621010, China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu, Sichuan 611731, China; School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, China; Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, Chengdu 2019RU035, China; School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, China
| | - Peng Xu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu, Sichuan 611731, China; School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, China; Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, Chengdu 2019RU035, China.
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11
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Teixeira FL, Costa MRE, Abreu JP, Cabral M, Soares SP, Teixeira JP. A Narrative Review of Speech and EEG Features for Schizophrenia Detection: Progress and Challenges. Bioengineering (Basel) 2023; 10:bioengineering10040493. [PMID: 37106680 PMCID: PMC10135748 DOI: 10.3390/bioengineering10040493] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 04/06/2023] [Accepted: 04/14/2023] [Indexed: 04/29/2023] Open
Abstract
Schizophrenia is a mental illness that affects an estimated 21 million people worldwide. The literature establishes that electroencephalography (EEG) is a well-implemented means of studying and diagnosing mental disorders. However, it is known that speech and language provide unique and essential information about human thought. Semantic and emotional content, semantic coherence, syntactic structure, and complexity can thus be combined in a machine learning process to detect schizophrenia. Several studies show that early identification is crucial to prevent the onset of illness or mitigate possible complications. Therefore, it is necessary to identify disease-specific biomarkers for an early diagnosis support system. This work contributes to improving our knowledge about schizophrenia and the features that can identify this mental illness via speech and EEG. The emotional state is a specific characteristic of schizophrenia that can be identified with speech emotion analysis. The most used features of speech found in the literature review are fundamental frequency (F0), intensity/loudness (I), frequency formants (F1, F2, and F3), Mel-frequency cepstral coefficients (MFCC's), the duration of pauses and sentences (SD), and the duration of silence between words. Combining at least two feature categories achieved high accuracy in the schizophrenia classification. Prosodic and spectral or temporal features achieved the highest accuracy. The work with higher accuracy used the prosodic and spectral features QEVA, SDVV, and SSDL, which were derived from the F0 and spectrogram. The emotional state can be identified with most of the features previously mentioned (F0, I, F1, F2, F3, MFCCs, and SD), linear prediction cepstral coefficients (LPCC), linear spectral features (LSF), and the pause rate. Using the event-related potentials (ERP), the most promissory features found in the literature are mismatch negativity (MMN), P2, P3, P50, N1, and N2. The EEG features with higher accuracy in schizophrenia classification subjects are the nonlinear features, such as Cx, HFD, and Lya.
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Affiliation(s)
- Felipe Lage Teixeira
- Research Centre in Digitalization and Intelligent Robotics (CEDRI), Instituto Politécnico de Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal
- Engineering Department, School of Sciences and Technology, University of Trás-os-Montes and Alto Douro (UTAD), Quinta de Prados, 5000-801 Vila Real, Portugal
| | - Miguel Rocha E Costa
- Research Centre in Digitalization and Intelligent Robotics (CEDRI), Instituto Politécnico de Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal
| | - José Pio Abreu
- Faculty of Medicine of the University of Coimbra, 3000-548 Coimbra, Portugal
- Hospital da Universidade de Coimbra, 3004-561 Coimbra, Portugal
| | - Manuel Cabral
- Engineering Department, School of Sciences and Technology, University of Trás-os-Montes and Alto Douro (UTAD), Quinta de Prados, 5000-801 Vila Real, Portugal
- Institute of Electronics and Informatics Engineering of Aveiro (IEETA), University of Aveiro, 3810-193 Aveiro, Portugal
| | - Salviano Pinto Soares
- Engineering Department, School of Sciences and Technology, University of Trás-os-Montes and Alto Douro (UTAD), Quinta de Prados, 5000-801 Vila Real, Portugal
- Institute of Electronics and Informatics Engineering of Aveiro (IEETA), University of Aveiro, 3810-193 Aveiro, Portugal
- Intelligent Systems Associate Laboratory (LASI), University of Aveiro, 3810-193 Aveiro, Portugal
| | - João Paulo Teixeira
- Research Centre in Digitalization and Intelligent Robotics (CEDRI), Instituto Politécnico de Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal
- Laboratório para a Sustentabilidade e Tecnologia em Regiões de Montanha (SusTEC), Instituto Politécnico de Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal
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12
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Shah SJH, Albishri A, Kang SS, Lee Y, Sponheim SR, Shim M. ETSNet: A deep neural network for EEG-based temporal-spatial pattern recognition in psychiatric disorder and emotional distress classification. Comput Biol Med 2023; 158:106857. [PMID: 37044046 DOI: 10.1016/j.compbiomed.2023.106857] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 03/06/2023] [Accepted: 03/30/2023] [Indexed: 04/03/2023]
Abstract
The use of EEG for evaluating and diagnosing neurological abnormalities related to psychiatric diseases and identifying human emotions has been improved by deep learning advancements. This research aims to categorize individuals with schizophrenia (SZ), their biological relatives (REL), and healthy controls (HC) using resting EEG brain source signal data defined by regions of interest (ROIs). The proposed solution is a deep neural network for the cortical source signals of the ROIs, incorporating a Squeeze-and-Excitation Block and multiple CNNs designed for eyes-open and closed resting states. The model, called EEG Temporal Spatial Network (ETSNet), has two variants: ETSNets and ETSNetf. Two evaluations were conducted to show the effectiveness of the proposed model. The average accuracy for the classification of SZ, REL, and HC using EEG resting data was 99.57% (ETSNetf), and the average accuracy for the classification of eyes-open (EO) and eyes-closed (EC) resting states was 93.15% (ETSNets). An ablation study was also conducted using two public datasets for intellectual and developmental disorders and emotional states, showing improved classification accuracy compared to advanced EEG classification algorithms when using ETSNets.
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13
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Baklushev ME, Nazarova MA, Novikov PA, Nikulin VV. [Methods for assessing aberrant and adaptive salience]. Zh Nevrol Psikhiatr Im S S Korsakova 2023; 123:30-35. [PMID: 37655407 DOI: 10.17116/jnevro202312308130] [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] [Indexed: 09/02/2023]
Abstract
The term «salience» is most often used to describe «aberrant salience», which means assigning false significance to insignificant facts and details, that is inherent to patients with schizophrenia. Most often it is used in combination with «aberrant salience», which is understood as the assignment of false significance to insignificant facts and details. The term «adaptive salience» is less commonly used and means the «correct» assignment of the significance to important biological information. It is believed that in schizophrenia there is a decrease of adaptive salience in combination with an increase of aberrant salience. The concepts of aberrant and adaptive salience are a kind of link between the dopamine imbalance underlying the pathogenesis of schizophrenia and the diverse clinic of the disease. This article provides a review of the literature on methods for assessing, including quantitatively assessment, salience in schizophrenia. The comparison of these methods and their possible clinical and scientific application are provided.
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14
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van der Merwe J, Biagio-de Jager L, Mahomed-Asmail F, Hall JW. Documentation of Peripheral Auditory Function in Studies of the Auditory P300 Response. J PSYCHOPHYSIOL 2022. [DOI: 10.1027/0269-8803/a000312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Abstract. A critical review was conducted to examine whether the peripheral hearing status of participants with neurological and psychological disorders was documented in published clinical studies of the auditory P300 response. Literature searches were conducted with three databases: PubMed, PsycINFO, and Scopus. Studies of participants with seven neurological or psychological disorders were included in the study. Each disorder was coupled with the main search phrase in separate searches on each database. Of the total 102 papers which met the inclusion criteria, the majority (64%) did not describe the peripheral hearing sensitivity of participants. In this review with studies that included participants at risk for hearing impairment, particularly age-related hearing loss, only a single publication adequately described formal hearing evaluation. Peripheral hearing status is rarely defined in studies of the P300 response. The inclusion of participants with a hearing loss likely affects the validity of findings for these studies. We recommend formal hearing assessment prior to inclusion of participants in studies of the auditory P300 response. The findings of this study may increase the awareness among researchers outside the field of audiology of the effects of peripheral hearing loss on the auditory P300.
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Affiliation(s)
- Janushca van der Merwe
- Department of Speech Language Pathology and Audiology, University of Pretoria, South Africa
| | - Leigh Biagio-de Jager
- Department of Speech Language Pathology and Audiology, University of Pretoria, South Africa
| | - Faheema Mahomed-Asmail
- Department of Speech Language Pathology and Audiology, University of Pretoria, South Africa
- Virtual Hearing Lab, Collaborative Initiative between University of Colorado and the University of Pretoria, Aurora, CO, USA
| | - James W. Hall
- Department of Speech Language Pathology and Audiology, University of Pretoria, South Africa
- George Osborne College of Audiology, Salus University, Elkins Park, PA, USA
- Department of Communication Science and Disorders, University of Hawaii, Honolulu, HI, USA
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15
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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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16
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Kool L, Oranje B, Meijs H, De Wilde B, Van Hecke J, Niemegeers P, Luykx JJ. Event-related potentials and use of psychotropic medication in major psychiatric disorders. Psychiatry Res 2022; 314:114637. [PMID: 35649338 DOI: 10.1016/j.psychres.2022.114637] [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: 10/20/2021] [Revised: 05/09/2022] [Accepted: 05/13/2022] [Indexed: 11/16/2022]
Abstract
BACKGROUND Attention deficits measured using event-related potentials (ERPs) have been frequently reported in several major psychiatric disorders, e.g. mood disorder (MD), psychotic disorder (PD) and substance use disorder (SUD). However, comparisons between these specific categories are lacking. Here we investigated if electrophysiological parameters of basic information processing are associated with the above-mentioned categories of psychiatric disorders, or instead were associated with general psychopathology. METHODS 579 subjects with MD, PD or SUD and healthy controls (HC) were included. Participants were tested in a passive auditory and an active visual oddball paradigm to assess mismatch negativity (MMN), P3A and P3B amplitudes. Additionally, we examined associations between these measures and psychoactive medication treatments. RESULTS All patients had significantly lower P3B amplitudes compared to healthy controls, while only SUD patients had lower P3A amplitudes than MD, PD and HC. PD patients also produced significantly less MMN than both MD and SUD patients. Additionally, we found significantly higher P3B amplitude in HC compared to patients without psychopharmacological treatment and patients treated with two or more psychoactive compounds (polypharmacy), but no significant associations with medication on P3A and MMN amplitudes. CONCLUSIONS Our results add to the theory that P3B deficits are associated with general psychopathology, whereas P3A and MMN deficits appear to be associated with substance abuse and psychotic disorders respectively.
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Affiliation(s)
- Lindy Kool
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Huispostnummer Str. 4.205, Universiteitsweg 100, Utrecht 3584 CG, The Netherlands; Department of Translational Neuroscience, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
| | - Bob Oranje
- Center for Neuropsychiatric Schizophrenia Research (CNSR) and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research (CINS), Academic Hospital Glostrup, Glostrup, Denmark
| | - Hannah Meijs
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Huispostnummer Str. 4.205, Universiteitsweg 100, Utrecht 3584 CG, The Netherlands; Research Institute Brainclinics, Brainclinics Foundation, Nijmegen, The Netherlands
| | - Bieke De Wilde
- Department of Psychiatry, Ziekenhuis Netwerk Antwerpen (ZNA), Antwerp, Belgium
| | - Jan Van Hecke
- Department of Psychiatry, Ziekenhuis Netwerk Antwerpen (ZNA), Antwerp, Belgium
| | - Peter Niemegeers
- Department of Psychiatry, Ziekenhuis Netwerk Antwerpen (ZNA), Antwerp, Belgium
| | - Jurjen J Luykx
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Huispostnummer Str. 4.205, Universiteitsweg 100, Utrecht 3584 CG, The Netherlands; Department of Translational Neuroscience, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands; Outpatient second opinion clinic, GGNet Mental Health, Apeldoorn, The Netherlands
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17
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Jiang L, Wang J, Dai J, Li F, Chen B, He R, Liao Y, Yao D, Dong W, Xu P. Altered temporal variability in brain functional connectivity identified by fuzzy entropy underlines schizophrenia deficits. J Psychiatr Res 2022; 148:315-324. [PMID: 35193035 DOI: 10.1016/j.jpsychires.2022.02.011] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2021] [Revised: 01/13/2022] [Accepted: 02/14/2022] [Indexed: 11/18/2022]
Abstract
Investigation of the temporal variability of resting-state brain networks informs our understanding of how neural connectivity aggregates and disassociates over time, further shedding light on the aberrant neural interactions that underlie symptomatology and psychosis development. In the current work, an electroencephalogram-based sliding window analysis was utilized for the first time to measure the nonlinear complexity of dynamic resting-state brain networks of schizophrenia (SZ) patients by applying fuzzy entropy. The results of this study demonstrated the attenuated temporal variability among multiple electrodes that were distributed in the frontal and right parietal lobes for SZ patients when compared with healthy controls (HCs). Meanwhile, a concomitant strengthening of the posterior and peripheral flexible connections that may be attributed to the excessive alertness or sensitivity of SZ patients to the external environment was also revealed. These temporal fluctuation distortions combined reflect an abnormality in the coordination of functional network switching in SZ, which is further the source of worse task performance (i.e., P300 amplitude) and the negative relationship between individual complexity metrics and P300 amplitude. Notably, when using the network metrics as features, multiple linear regressions of P300 amplitudes were also exactly achieved for both the SZ and HC groups. These findings shed light on the pathophysiological mechanisms of SZ from a temporal variability perspective and provide potential biomarkers for quantifying SZ's progressive neurophysiological deterioration.
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Affiliation(s)
- Lin Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, 610054, China; School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Jiuju Wang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
| | - Jing Dai
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, 610054, China; Chengdu Mental Health Center, Chengdu, 610036, China
| | - Fali Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, 610054, China; School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu, 611731, China; Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, China.
| | - Baodan Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, 610054, China; School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Runyang He
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, 610054, China; School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Yuanyuan Liao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, 610054, China; School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, 610054, China; School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu, 611731, China; Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, China; School of Electrical Engineering, Zhengzhou University, Zhengzhou, 450001, China
| | - Wentian Dong
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China.
| | - Peng Xu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, 610054, China; School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu, 611731, China; Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, China.
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18
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Wang B, Zartaloudi E, Linden JF, Bramon E. Neurophysiology in psychosis: The quest for disease biomarkers. Transl Psychiatry 2022; 12:100. [PMID: 35277479 PMCID: PMC8917164 DOI: 10.1038/s41398-022-01860-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 02/14/2022] [Accepted: 02/18/2022] [Indexed: 01/11/2023] Open
Abstract
Psychotic disorders affect 3% of the population at some stage in life, are a leading cause of disability, and impose a great economic burden on society. Major breakthroughs in the genetics of psychosis have not yet been matched by an understanding of its neurobiology. Biomarkers of perception and cognition obtained through non-invasive neurophysiological tools, especially EEG, offer a unique opportunity to gain mechanistic insights. Techniques for measuring neurophysiological markers are inexpensive and ubiquitous, thus having the potential as an accessible tool for patient stratification towards early treatments leading to better outcomes. In this paper, we review the literature on neurophysiological markers for psychosis and their relevant disease mechanisms, mainly covering event-related potentials including P50/N100 sensory gating, mismatch negativity, and the N100 and P300 waveforms. While several neurophysiological deficits are well established in patients with psychosis, more research is needed to study neurophysiological markers in their unaffected relatives and individuals at clinical high risk. We need to harness EEG to investigate markers of disease risk as key steps to elucidate the aetiology of psychosis and facilitate earlier detection and treatment.
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Affiliation(s)
- Baihan Wang
- Division of Psychiatry, University College London, London, UK.
| | - Eirini Zartaloudi
- Division of Psychiatry, University College London, London, UK.
- Institute of Clinical Trials and Methodology, University College London, London, UK.
| | - Jennifer F Linden
- Ear Institute, University College London, London, UK
- Department of Neuroscience, Physiology & Pharmacology, University College London, London, UK
| | - Elvira Bramon
- Division of Psychiatry, University College London, London, UK
- Institute of Cognitive Neuroscience, University College London, London, UK
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19
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Pokorny VJ, Sponheim SR. Neural Indicator of Altered Mismatch Detection Predicts Atypical Cognitive-Perceptual Experiences in Psychotic Psychopathology. Schizophr Bull 2022; 48:371-381. [PMID: 34665861 PMCID: PMC8886594 DOI: 10.1093/schbul/sbab127] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
BACKGROUND Atypical auditory processing (AAP) in psychotic psychopathology is evident in early (N1), mid-latency (P2/N2/mismatch negativity), and late (P3) neural responses. The influence of attention on AAP, and how temporal stages of AAP are associated with phenomenology of psychotic psychopathology are not well understood. METHODS We used a directed attention oddball task to characterize stages of AAP in psychosis and to examine the influence of selective attention. Ninety patients with schizophrenia (SCZ), 53 patients with bipolar disorder (BP), 90 healthy controls and 72 first-degree relatives of SCZ (SREL) were studied. We used principal components analysis to decompose average-reference 64-channel subject-level ERPs. RESULTS Altered attentional modulation was evident in SCZ at early (N1 factor) and late (P3 factor) stages of AAP, but not at mid-latency P2 factor. Irrespective of condition, N1 and P3 were reduced in SCZ, which predicted greater psychopathology and schizotypal personality traits. Diminished mid-latency mismatch detection (P2 factor) was evident in SCZ, BP, and SREL and was associated with greater positive symptoms of psychosis as well as self-reported atypical cognitive-perceptual experiences. CONCLUSIONS Attentional modulation of early N1, and later P3 neural responses was atypical in patients, but the degree of attentional modulation did not relate to symptom severity or schizotypal traits. Our findings suggest the link between mid-latency mismatch detection and atypical cognitive/perceptual experiences is not driven by attentional deficits alone and point to the promise of mid-latency mismatch detection as a candidate endophenotype and intervention target.
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Affiliation(s)
- Victor J Pokorny
- Minneapolis Veterans Affairs Health Care System.,Department of Psychology, University of Minnesota
| | - Scott R Sponheim
- Minneapolis Veterans Affairs Health Care System.,Department of Psychology, University of Minnesota.,Department of Psychiatry and Behavioral Science, University of Minnesota, Minneapolis, MN, USA
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20
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Westhoff MLS, Ladwig J, Heck J, Schülke R, Groh A, Deest M, Bleich S, Frieling H, Jahn K. Early Detection and Prevention of Schizophrenic Psychosis-A Review. Brain Sci 2021; 12:11. [PMID: 35053755 PMCID: PMC8774083 DOI: 10.3390/brainsci12010011] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 12/16/2021] [Accepted: 12/20/2021] [Indexed: 01/04/2023] Open
Abstract
Psychotic disorders often run a chronic course and are associated with a considerable emotional and social impact for patients and their relatives. Therefore, early recognition, combined with the possibility of preventive intervention, is urgently warranted since the duration of untreated psychosis (DUP) significantly determines the further course of the disease. In addition to established diagnostic tools, neurobiological factors in the development of schizophrenic psychoses are increasingly being investigated. It is shown that numerous molecular alterations already exist before the clinical onset of the disease. As schizophrenic psychoses are not elicited by a single mutation in the deoxyribonucleic acid (DNA) sequence, epigenetics likely constitute the missing link between environmental influences and disease development and could potentially serve as a biomarker. The results from transcriptomic and proteomic studies point to a dysregulated immune system, likely evoked by epigenetic alterations. Despite the increasing knowledge of the neurobiological mechanisms involved in the development of psychotic disorders, further research efforts with large population-based study designs are needed to identify suitable biomarkers. In conclusion, a combination of blood examinations, functional imaging techniques, electroencephalography (EEG) investigations and polygenic risk scores should be considered as the basis for predicting how subjects will transition into manifest psychosis.
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Affiliation(s)
- Martin Lennart Schulze Westhoff
- Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, D-30625 Hannover, Germany; (J.L.); (R.S.); (A.G.); (M.D.); (S.B.); (H.F.); (K.J.)
| | - Johannes Ladwig
- Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, D-30625 Hannover, Germany; (J.L.); (R.S.); (A.G.); (M.D.); (S.B.); (H.F.); (K.J.)
| | - Johannes Heck
- Institute for Clinical Pharmacology, Hannover Medical School, D-30625 Hannover, Germany;
| | - Rasmus Schülke
- Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, D-30625 Hannover, Germany; (J.L.); (R.S.); (A.G.); (M.D.); (S.B.); (H.F.); (K.J.)
| | - Adrian Groh
- Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, D-30625 Hannover, Germany; (J.L.); (R.S.); (A.G.); (M.D.); (S.B.); (H.F.); (K.J.)
| | - Maximilian Deest
- Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, D-30625 Hannover, Germany; (J.L.); (R.S.); (A.G.); (M.D.); (S.B.); (H.F.); (K.J.)
| | - Stefan Bleich
- Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, D-30625 Hannover, Germany; (J.L.); (R.S.); (A.G.); (M.D.); (S.B.); (H.F.); (K.J.)
| | - Helge Frieling
- Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, D-30625 Hannover, Germany; (J.L.); (R.S.); (A.G.); (M.D.); (S.B.); (H.F.); (K.J.)
| | - Kirsten Jahn
- Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, D-30625 Hannover, Germany; (J.L.); (R.S.); (A.G.); (M.D.); (S.B.); (H.F.); (K.J.)
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21
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Gao L, Gu L, Shu H, Chen J, Zhu J, Wang B, Shi Y, Song R, Li K, Li X, Zhang H, Zhang H, Zhang Z. The reduced left hippocampal volume related to the delayed P300 latency in amnestic mild cognitive impairment. Psychol Med 2021; 51:2054-2062. [PMID: 32308167 DOI: 10.1017/s0033291720000811] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
BACKGROUND Amnestic mild cognitive impairment (aMCI) is characterized by delayed P300 latency and reduced grey matter (GM) volume, respectively. The relationship between the features in aMCI is unclear. This study was to investigate the relationship between the altered P300 latency and the GM volume in aMCI. METHODS Thirty-four aMCI and 34 well-matched normal controls (NC) were studied using electroencephalogram during a visual oddball task and scanned with MRI. Both tests were finished in the same day. RESULTS As compared with the NC group, the aMCI group exhibited delayed P300 latency in parietal cortex and reduced GM volumes in bilateral temporal pole and left hippocampus/parahippocampal gyrus. A remarkable negative correlation was found between delayed P300 latency and reduced left hippocampal volume only in the aMCI group. Interestingly, the mediating analysis found P300 latency significantly mediated the association between right supramarginal gyrus volume and information processing speed indicated by Stroop Color and Word Test A scores. CONCLUSIONS The association between delayed P300 latency and reduced left hippocampal volume in aMCI subjects suggests that reduced left hippocampal volume may be the potential structural basis of delayed P300 latency.
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Affiliation(s)
- Lijuan Gao
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Institution of Neuropsychiatry, Southeast University, Nanjing, Jiangsu210009, China
| | - Lihua Gu
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Institution of Neuropsychiatry, Southeast University, Nanjing, Jiangsu210009, China
| | - Hao Shu
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Institution of Neuropsychiatry, Southeast University, Nanjing, Jiangsu210009, China
| | - Jiu Chen
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Institution of Neuropsychiatry, Southeast University, Nanjing, Jiangsu210009, China
| | - Jianli Zhu
- Department of Psychology, Xinxiang Medical University, Xinxiang, Henan453003, China
| | - Bi Wang
- Department of Radiology, Henan Mental Hospital, the Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan453002, China
| | - Yachen Shi
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Institution of Neuropsychiatry, Southeast University, Nanjing, Jiangsu210009, China
| | - Ruize Song
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Institution of Neuropsychiatry, Southeast University, Nanjing, Jiangsu210009, China
| | - Kun Li
- Department of Psychology, Xinxiang Medical University, Xinxiang, Henan453003, China
| | - Xianrui Li
- Department of Psychology, Xinxiang Medical University, Xinxiang, Henan453003, China
| | - Haisan Zhang
- Department of Radiology, Henan Mental Hospital, the Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan453002, China
| | - Hongxing Zhang
- Department of Psychology, Xinxiang Medical University, Xinxiang, Henan453003, China
| | - Zhijun Zhang
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Institution of Neuropsychiatry, Southeast University, Nanjing, Jiangsu210009, China
- Department of Psychology, Xinxiang Medical University, Xinxiang, Henan453003, China
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22
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Türközer HB, Ivleva EI, Palka J, Clementz BA, Shafee R, Pearlson GD, Sweeney JA, Keshavan MS, Gershon ES, Tamminga CA. Biomarker Profiles in Psychosis Risk Groups Within Unaffected Relatives Based on Familiality and Age. Schizophr Bull 2021; 47:1058-1067. [PMID: 33693883 PMCID: PMC8266584 DOI: 10.1093/schbul/sbab013] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Investigating biomarkers in unaffected relatives (UR) of individuals with psychotic disorders has already proven productive in research on psychosis neurobiology. However, there is considerable heterogeneity among UR based on features linked to psychosis vulnerability. Here, using the Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) dataset, we examined cognitive and neurophysiologic biomarkers in first-degree UR of psychosis probands, stratified by 2 widely used risk factors: familiality status of the respective proband (the presence or absence of a first- or second-degree relative with a history of psychotic disorder) and age (within or older than the common age range for developing psychosis). We investigated biomarkers that best differentiate the above specific risk subgroups. Additionally, we examined the relationship of biomarkers with Polygenic Risk Scores for Schizophrenia (PRSSCZ) in a subsample of Caucasian probands and healthy controls (HC). Our results demonstrate that the Brief Assessment of Cognition in Schizophrenia (BACS) score, antisaccade error (ASE) factor, and stop-signal task (SST) factor best differentiate UR (n = 169) from HC (n = 137) (P = .013). Biomarker profiles of UR of familial (n = 82) and non-familial (n = 83) probands were not significantly different. Furthermore, ASE and SST factors best differentiated younger UR (age ≤ 30) (n = 59) from older UR (n = 110) and HC from both age groups (age ≤ 30 years, n=49; age > 30 years, n = 88) (P < .001). In addition, BACS (r = -0.175, P = .006) and ASE factor (r = 0.188, P = .006) showed associations with PRSSCZ. Taken together, our findings indicate that cognitive biomarkers-"top-down inhibition" impairments in particular-may be of critical importance as indicators of psychosis vulnerability.
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Affiliation(s)
- Halide Bilge Türközer
- Department of Psychiatry, the University of Texas Southwestern Medical Center, Dallas, TX
| | - Elena I Ivleva
- Department of Psychiatry, the University of Texas Southwestern Medical Center, Dallas, TX
| | - Jayme Palka
- Department of Psychiatry, the University of Texas Southwestern Medical Center, Dallas, TX
| | - Brett A Clementz
- Department of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, GA
| | - Rebecca Shafee
- Department of Genetics, Harvard Medical School, Boston, MA
| | - Godfrey D Pearlson
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, CT
- Departments of Psychiatry and Neuroscience, Yale University, New Haven, CT
| | - John A Sweeney
- Department of Psychiatry, the University of Texas Southwestern Medical Center, Dallas, TX
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH
| | - Matcheri S Keshavan
- Department of Psychiatry and Cognitive Neurology, Beth Israel Deaconess Medical Center, Boston, MA
- Harvard Medical School, Boston, MA
| | - Elliot S Gershon
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL
| | - Carol A Tamminga
- Department of Psychiatry, the University of Texas Southwestern Medical Center, Dallas, TX
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23
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Northoff G, Gomez-Pilar J. Overcoming Rest-Task Divide-Abnormal Temporospatial Dynamics and Its Cognition in Schizophrenia. Schizophr Bull 2021; 47:751-765. [PMID: 33305324 PMCID: PMC8661394 DOI: 10.1093/schbul/sbaa178] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Schizophrenia is a complex psychiatric disorder exhibiting alterations in spontaneous and task-related cerebral activity whose relation (termed "state dependence") remains unclear. For unraveling their relationship, we review recent electroencephalographic (and a few functional magnetic resonance imaging) studies in schizophrenia that assess and compare both rest/prestimulus and task states, ie, rest/prestimulus-task modulation. Results report reduced neural differentiation of task-related activity from rest/prestimulus activity across different regions, neural measures, cognitive domains, and imaging modalities. Together, the findings show reduced rest/prestimulus-task modulation, which is mediated by abnormal temporospatial dynamics of the spontaneous activity. Abnormal temporospatial dynamics, in turn, may lead to abnormal prediction, ie, predictive coding, which mediates cognitive changes and psychopathological symptoms, including confusion of internally and externally oriented cognition. In conclusion, reduced rest/prestimulus-task modulation in schizophrenia provides novel insight into the neuronal mechanisms that connect task-related changes to cognitive abnormalities and psychopathological symptoms.
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Affiliation(s)
- Georg Northoff
- Mental Health Center/7th Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Mind, Brain Imaging and Neuroethics, Institute of Mental Health Research, Royal Ottawa Healthcare Group, University of Ottawa, Ottawa ON, Canada
| | - Javier Gomez-Pilar
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, Valladolid, Spain
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24
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Prolonged P300 Latency in Antipsychotic-Free Subjects with At-Risk Mental States Who Later Developed Schizophrenia. J Pers Med 2021; 11:jpm11050327. [PMID: 33919276 PMCID: PMC8143351 DOI: 10.3390/jpm11050327] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Revised: 04/16/2021] [Accepted: 04/18/2021] [Indexed: 12/17/2022] Open
Abstract
We measured P300, an event-related potential, in subjects with at-risk mental states (ARMS) and aimed to determine whether P300 parameter can predict progression to overt schizophrenia. Thirty-three subjects with ARMS, 39 with schizophrenia, and 28 healthy controls participated in the study. All subjects were antipsychotic-free. Subjects with ARMS were followed-up for more than two years. Cognitive function was measured by the Brief assessment of Cognition in Schizophrenia (BACS) and Schizophrenia Cognition Rating Scale (SCoRS), while the modified Global Assessment of Functioning (mGAF) was used to assess global function. Patients with schizophrenia showed smaller P300 amplitudes and prolonged latency at Pz compared to those of healthy controls and subjects with ARMS. During the follow-up period, eight out of 33 subjects with ARMS developed overt psychosis (ARMS-P) while 25 did not (ARMS-NP). P300 latency of ARMS-P was significantly longer than that of ARMS-NP. At baseline, ARMS-P elicited worse cognitive functions, as measured by the BACS and SCoRS compared to ARMS-NP. We also detected a significant relationship between P300 amplitudes and mGAF scores in ARMS subjects. Our results suggest the usefulness of prolonged P300 latency and cognitive impairment as a predictive marker of later development of schizophrenia in vulnerable individuals.
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25
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Pokorny VJ, Lano TJ, Schallmo MP, Olman CA, Sponheim SR. Reduced influence of perceptual context in schizophrenia: behavioral and neurophysiological evidence. Psychol Med 2021; 51:786-794. [PMID: 31858929 PMCID: PMC7444089 DOI: 10.1017/s0033291719003751] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND Accurate perception of visual contours is essential for seeing and differentiating objects in the environment. Both the ability to detect visual contours and the influence of perceptual context created by surrounding stimuli are diminished in people with schizophrenia (SCZ). The central aim of the present study was to better understand the biological underpinnings of impaired contour integration and weakened effects of perceptual context. Additionally, we sought to determine whether visual perceptual abnormalities reflect genetic factors in SCZ and are present in other severe mental disorders. METHODS We examined behavioral data and event-related potentials (ERPs) collected during the perception of simple linear contours embedded in similar background stimuli in 27 patients with SCZ, 23 patients with bipolar disorder (BP), 23 first-degree relatives of SCZ, and 37 controls. RESULTS SCZ exhibited impaired visual contour detection while BP exhibited intermediate performance. The orientation of neighboring stimuli (i.e. flankers) relative to the contour modulated perception across all groups, but SCZ exhibited weakened suppression by the perceptual context created by flankers. Late visual (occipital P2) and cognitive (centroparietal P3) neural responses showed group differences and flanker orientation effects, unlike earlier ERPs (occipital P1 and N1). Moreover, behavioral effects of flanker context on contour perception were correlated with modulation in P2 & P3 amplitudes. CONCLUSION In addition to replicating and extending findings of abnormal contour integration and visual context modulation in SCZ, we provide novel evidence that the abnormal use of perceptual context is associated with higher-order sensory and cognitive processes.
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Affiliation(s)
- Victor J. Pokorny
- Minneapolis Veterans Affairs Health Care System, Minneapolis, MN 55417, USA
| | - Timothy J. Lano
- Minneapolis Veterans Affairs Health Care System, Minneapolis, MN 55417, USA
- Department of Psychiatry and Behavioral Science, University of Minnesota, Minneapolis, MN, USA
| | - Michael-Paul Schallmo
- Department of Psychiatry and Behavioral Science, University of Minnesota, Minneapolis, MN, USA
| | - Cheryl A. Olman
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Scott R. Sponheim
- Minneapolis Veterans Affairs Health Care System, Minneapolis, MN 55417, USA
- Department of Psychiatry and Behavioral Science, University of Minnesota, Minneapolis, MN, USA
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26
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Bhat A, Irizar H, Thygesen JH, Kuchenbaecker K, Pain O, Adams RA, Zartaloudi E, Harju-Seppänen J, Austin-Zimmerman I, Wang B, Muir R, Summerfelt A, Du XM, Bruce H, O'Donnell P, Srivastava DP, Friston K, Hong LE, Hall MH, Bramon E. Transcriptome-wide association study reveals two genes that influence mismatch negativity. Cell Rep 2021; 34:108868. [PMID: 33730571 PMCID: PMC7972991 DOI: 10.1016/j.celrep.2021.108868] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2020] [Revised: 12/09/2020] [Accepted: 02/24/2021] [Indexed: 01/22/2023] Open
Abstract
Mismatch negativity (MMN) is a differential electrophysiological response measuring cortical adaptability to unpredictable stimuli. MMN is consistently attenuated in patients with psychosis. However, the genetics of MMN are uncharted, limiting the validation of MMN as a psychosis endophenotype. Here, we perform a transcriptome-wide association study of 728 individuals, which reveals 2 genes (FAM89A and ENGASE) whose expression in cortical tissues is associated with MMN. Enrichment analyses of neurodevelopmental expression signatures show that genes associated with MMN tend to be overexpressed in the frontal cortex during prenatal development but are significantly downregulated in adulthood. Endophenotype ranking value calculations comparing MMN and three other candidate psychosis endophenotypes (lateral ventricular volume and two auditory-verbal learning measures) find MMN to be considerably superior. These results yield promising insights into sensory processing in the cortex and endorse the notion of MMN as a psychosis endophenotype.
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Affiliation(s)
- Anjali Bhat
- Division of Psychiatry, University College London, London, UK; Wellcome Centre for Human Neuroimaging, University College London, London, UK; Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK; Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK; MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK.
| | - Haritz Irizar
- Division of Psychiatry, University College London, London, UK
| | | | - Karoline Kuchenbaecker
- Division of Psychiatry, University College London, London, UK; UCL Genetics Institute, University College London, London, UK
| | - Oliver Pain
- Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Rick A Adams
- Division of Psychiatry, University College London, London, UK; Institute of Cognitive Neuroscience, University College London, London, UK
| | | | - Jasmine Harju-Seppänen
- Division of Psychiatry, University College London, London, UK; Department of Clinical, Educational and Health Psychology, University College London, London, UK
| | | | - Baihan Wang
- Division of Psychiatry, University College London, London, UK
| | - Rebecca Muir
- Division of Psychiatry, University College London, London, UK
| | - Ann Summerfelt
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland, Baltimore, MD, USA
| | - Xiaoming Michael Du
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland, Baltimore, MD, USA
| | - Heather Bruce
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland, Baltimore, MD, USA
| | - Patricio O'Donnell
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland, Baltimore, MD, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA; Takeda Pharmaceuticals, Cambridge, MA, USA
| | - Deepak P Srivastava
- Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK; Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK; MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK
| | - Karl Friston
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - L Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland, Baltimore, MD, USA
| | - Mei-Hua Hall
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA; Psychosis Neurobiology Laboratory, McLean Hospital, Belmont, MA, USA
| | - Elvira Bramon
- Division of Psychiatry, University College London, London, UK; Institute of Cognitive Neuroscience, University College London, London, UK; Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK; Camden and Islington NHS Foundation Trust, London, UK.
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27
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Barros C, Silva CA, Pinheiro AP. Advanced EEG-based learning approaches to predict schizophrenia: Promises and pitfalls. Artif Intell Med 2021; 114:102039. [PMID: 33875158 DOI: 10.1016/j.artmed.2021.102039] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Revised: 12/11/2020] [Accepted: 02/16/2021] [Indexed: 01/10/2023]
Abstract
The complexity and heterogeneity of schizophrenia symptoms challenge an objective diagnosis, which is typically based on behavioral and clinical manifestations. Moreover, the boundaries of schizophrenia are not precisely demarcated from other nosologic categories, such as bipolar disorder. The early detection of schizophrenia can lead to a more effective treatment, improving patients' quality of life. Over the last decades, hundreds of studies aimed at specifying the neurobiological mechanisms that underpin clinical manifestations of schizophrenia, using techniques such as electroencephalography (EEG). Changes in event-related potentials of the EEG have been associated with sensory and cognitive deficits and proposed as biomarkers of schizophrenia. Besides contributing to a more effective diagnosis, biomarkers can be crucial to schizophrenia onset prediction and prognosis. However, any proposed biomarker requires substantial clinical research to prove its validity and cost-effectiveness. Fueled by developments in computational neuroscience, automatic classification of schizophrenia at different stages (prodromal, first episode, chronic) has been attempted, using brain imaging pattern recognition methods to capture differences in functional brain activity. Advanced learning techniques have been studied for this purpose, with promising results. This review provides an overview of recent machine learning-based methods for schizophrenia classification using EEG data, discussing their potentialities and limitations. This review is intended to serve as a starting point for future developments of effective EEG-based models that might predict the onset of schizophrenia, identify subjects at high-risk of psychosis conversion or differentiate schizophrenia from other disorders, promoting more effective early interventions.
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Affiliation(s)
- Carla Barros
- Center for Research in Psychology (CIPsi), School of Psychology, University of Minho, Braga, Portugal
| | - Carlos A Silva
- Center for Microelectromechanical Systems (CMEMS), School of Engineering, University of Minho, Guimarães, Portugal
| | - Ana P Pinheiro
- Center for Research in Psychology (CIPsi), School of Psychology, University of Minho, Braga, Portugal; CICPSI, Faculdade de Psicologia, Universidade de Lisboa, Lisboa, Portugal.
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28
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Effects of Transcranial Direct Current Stimulation (tDCS) in the Normalization of Brain Activation in Patients with Neuropsychiatric Disorders: A Systematic Review of Neurophysiological and Neuroimaging Studies. Neural Plast 2020; 2020:8854412. [PMID: 33424961 PMCID: PMC7773462 DOI: 10.1155/2020/8854412] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Revised: 11/23/2020] [Accepted: 12/03/2020] [Indexed: 11/17/2022] Open
Abstract
Background People with neuropsychiatric disorders have been found to have abnormal brain activity, which is associated with the persistent functional impairment found in these patients. Recently, transcranial direct current stimulation (tDCS) has been shown to normalize this pathological brain activity, although the results are inconsistent. Objective We explored whether tDCS alters and normalizes brain activity among patients with neuropsychiatric disorders. Moreover, we examined whether these changes in brain activity are clinically relevant, as evidenced by brain-behavior correlations. Methods A systematic review was conducted according to PRISMA guidelines. Randomized controlled trials that studied the effects of tDCS on brain activity by comparing experimental and sham control groups using either electrophysiological or neuroimaging methods were included. Results With convergent evidence from 16 neurophysiological/neuroimaging studies, active tDCS was shown to be able to induce changes in brain activation patterns in people with neuropsychiatric disorders. Importantly, anodal tDCS appeared to normalize aberrant brain activation in patients with schizophrenia and substance abuse, and the effect was selectively correlated with reaction times, task-specific accuracy performance, and some symptom severity measures. Limitations and Conclusions. Due to the inherent heterogeneity in brain activity measurements for tDCS studies among people with neuropsychiatric disorders, no meta-analysis was conducted. We recommend that future studies investigate the effect of repeated cathodal tDCS on brain activity. We suggest to clinicians that the prescription of 1-2 mA anodal stimulation for patients with schizophrenia may be a promising treatment to alleviate positive symptoms. This systematic review is registered with registration number CRD42020183608.
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29
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Delfin C, Ruzich E, Wallinius M, Björnsdotter M, Andiné P. Trait Disinhibition and NoGo Event-Related Potentials in Violent Mentally Disordered Offenders and Healthy Controls. Front Psychiatry 2020; 11:577491. [PMID: 33362599 PMCID: PMC7759527 DOI: 10.3389/fpsyt.2020.577491] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Accepted: 11/17/2020] [Indexed: 12/21/2022] Open
Abstract
Trait disinhibition may function as a dispositional liability toward maladaptive behaviors relevant in the treatment of mentally disordered offenders (MDOs). Reduced amplitude and prolonged latency of the NoGo N2 and P3 event-related potentials have emerged as promising candidates for transdiagnostic, biobehavioral markers of trait disinhibition, yet no study has specifically investigated these two components in violent, inpatient MDOs. Here, we examined self-reported trait disinhibition, experimentally assessed response inhibition, and NoGo N2 and P3 amplitude and latency in male, violent MDOs (N = 27) and healthy controls (N = 20). MDOs had a higher degree of trait disinhibition, reduced NoGo P3 amplitude, and delayed NoGo P3 latency compared to controls. The reduced NoGo P3 amplitude and delayed NoGo P3 latency in MDOs may stem from deficits during monitoring or evaluation of behavior. NoGo P3 latency was associated with increased trait disinhibition in the whole sample, suggesting that trait disinhibition may be associated with reduced neural efficiency during later stages of outcome monitoring or evaluation. Findings for NoGo N2 amplitude and latency were small and non-robust. With several limitations in mind, this is the first study to demonstrate attenuated NoGo P3 amplitude and delayed NoGo P3 latency in violent, inpatient MDOs compared to healthy controls.
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Affiliation(s)
- Carl Delfin
- Centre for Ethics, Law and Mental Health, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Research Department, Regional Forensic Psychiatric Clinic, Växjö, Sweden
| | - Emily Ruzich
- MedTech West, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Märta Wallinius
- Centre for Ethics, Law and Mental Health, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Research Department, Regional Forensic Psychiatric Clinic, Växjö, Sweden
- Lund Clinical Research on Externalizing and Developmental Psychopathology, Child and Adolescent Psychiatry, Department of Clinical Sciences Lund, Lund University, Lund, Sweden
| | - Malin Björnsdotter
- Centre for Ethics, Law and Mental Health, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Affective Psychiatry, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Peter Andiné
- Centre for Ethics, Law and Mental Health, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Forensic Psychiatric Clinic, Sahlgrenska University Hospital, Gothenburg, Sweden
- Department of Forensic Psychiatry, National Board of Forensic Medicine, Gothenburg, Sweden
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30
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Donati FL, D’Agostino A, Ferrarelli F. Neurocognitive and neurophysiological endophenotypes in schizophrenia: An overview. Biomark Neuropsychiatry 2020. [DOI: 10.1016/j.bionps.2020.100017] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
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31
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Flasbeck V, Juckel G, Brüne M. Evidence for Altered Neural Processing in Patients With Borderline Personality Disorder. J PSYCHOPHYSIOL 2020. [DOI: 10.1027/0269-8803/a000271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Abstract. Borderline personality disorder (BPD) is characterized by difficulties in emotion regulation, self-identity disturbances, self-injurious behavior, and reduced inhibitory control. Event-related potential (ERP) studies have sought to reveal the neural correlates of cognitive distortions and behavioral alterations in BPD. The article presents an overview of the existing ERP literature pertaining to BPD and discusses whether any one of the electrophysiological findings could serve as a reliable and specific marker for BPD. In short, ERP studies investigating P300 tentatively suggest impaired inhibitory control. Moreover, reduced error- and feedback-related processing and impaired response inhibition seem to be associated with impulsivity and risk-taking behavior in BPD patients. However, these findings are not specific for BPD. Regarding emotional and self-referential information processing, individuals with BPD display heightened vigilance toward social threat impacting their cognitive performance in various social-cognitive tasks demonstrating alterations of early negative and late positive potentials. These multifaceted electrophysiological alterations may be attributed to dysfunctional activity and connectivity of frontal brain regions and the limbic system.
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Affiliation(s)
- Vera Flasbeck
- LWL University Hospital, Department of Psychiatry, Psychotherapy and Preventive Medicine, Division of Social Neuropsychiatry and Evolutionary Medicine, Ruhr University Bochum, Germany
| | - Georg Juckel
- LWL University Hospital, Department of Psychiatry, Psychotherapy and Preventive Medicine, Ruhr University Bochum, Germany
| | - Martin Brüne
- LWL University Hospital, Department of Psychiatry, Psychotherapy and Preventive Medicine, Division of Social Neuropsychiatry and Evolutionary Medicine, Ruhr University Bochum, Germany
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32
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Kim M, Lee TH, Hwang WJ, Lee TY, Kwon JS. Auditory P300 as a Neurophysiological Correlate of Symptomatic Improvement by Transcranial Direct Current Stimulation in Patients With Schizophrenia: A Pilot Study. Clin EEG Neurosci 2020; 51:252-258. [PMID: 30474393 DOI: 10.1177/1550059418815228] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background. The reduced amplitude, prolonged latency, and increased intertrial variability of auditory P300 have been consistently reported in relation to the symptomatic severity of schizophrenia. This study investigated whether auditory P300 event-related potentials can be used as an objective indicator of symptomatic improvement by transcranial direct current stimulation (tDCS) in patients with schizophrenia. Methods. Ten patients with schizophrenia received 20 minutes of 2-mA tDCS twice a day for 5 consecutive weekdays. The anode was placed over the left dorsolateral prefrontal cortex, and the cathode was placed over the left temporo-parietal cortex. The Positive and Negative Syndrome Scale (PANSS) and the auditory P300 were measured for each participant at baseline and after the completion of the tDCS applications. Results. The participants showed significant improvement in the positive and negative symptoms as indexed by change in the PANSS scores by the tDCS. The P300 amplitude, latency, and intertrial variability did not statistically significantly differ after the tDCS application. However, a significant association was observed between the reduced P300 intertrial variability and improvement in the positive symptoms by tDCS. In addition, the changes in both the P300 latency and intertrial variability were significantly correlated with reduced negative symptoms after the tDCS application. Conclusions. Although this pilot study is limited by the small sample size and lack of a sham control, the results suggest that auditory P300 may be a putative marker reflecting the effect of tDCS on the positive and negative symptoms of schizophrenia.
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Affiliation(s)
- Minah Kim
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea.,Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Tak Hyung Lee
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Science, Seoul, Republic of Korea
| | - Wu Jeong Hwang
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Science, Seoul, Republic of Korea
| | - Tae Young Lee
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jun Soo Kwon
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea.,Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea.,Department of Brain and Cognitive Sciences, Seoul National University College of Natural Science, Seoul, Republic of Korea.,Institute of Human Behavioral Medicine, SNU-MRC, Seoul, Republic of Korea
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33
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Bramon E, Dempster E, Frangou S, McDonald C, Schoenberg P, MacCabe JH, Walshe M, Sham P, Collier D, Murray RM. Is there an association between the COMT gene and P300 endophenotypes? Eur Psychiatry 2020; 21:70-3. [PMID: 16414251 DOI: 10.1016/j.eurpsy.2005.11.001] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
Abstract
AbstractP300 wave anomalies correlate with genetic risk for schizophrenia and constitute a plausible endophenotype for the disease. The COMT gene is thought to influence cognitive performance and to be a susceptibility gene for schizophrenia. Unlike two previous studies, we found no significant influence of the COMT gene on P300 amplitude or latency in 189 individuals examined. The well-supported role of the COMT gene both in dopamine catabolism as well as in prefrontal cognition makes a strong theoretical case for the influence of COMT Val158Met polymorphism on P300 endophenotypes. However, the available neurophysiologic evidence suggests that any such association, if present, must be very subtle.
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Affiliation(s)
- E Bramon
- Institute of Psychiatry, King's College London, De Crespigny Park, London SE5 8AF, UK.
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Delusional ideation, manic symptomatology and working memory in a cohort at clinical high-risk for psychosis: A longitudinal study. Eur Psychiatry 2020; 27:258-63. [DOI: 10.1016/j.eurpsy.2010.07.008] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2010] [Revised: 05/24/2010] [Accepted: 07/01/2010] [Indexed: 11/22/2022] Open
Abstract
AbstractWe followed up a cohort (n = 35) of clients with an “At Risk Mental State” (ARMS) for almost 2 years (mean 21.3 months). At baseline, these clients had taken part in research looking at the relationship between reasoning biases, memory, personality styles and delusional ideation. During the follow-up period, clients underwent a package of intervention from a specialist early detection team. Eighty percent (n = 28) of these clients were successfully re-interviewed. There was improvement across the cohort as a whole, however five participants (17.9%) had made the transition to psychosis at follow-up. Those who had become psychotic had lower levels of manic symptomatology at baseline than those who did not enter the first episode. Further, across the cohort, impaired working memory and delusional ideation at baseline combined to predict 45% of the delusional ideation at follow-up. These preliminary findings suggest that working memory impairments may be linked to the persistence of delusional ideation and that manic symptoms in someone with an ARMS may suggest that such an individual is less likely to develop a frank psychotic episode.
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35
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Lavoie S, Polari AR, Goldstone S, Nelson B, McGorry PD. Staging model in psychiatry: Review of the evolution of electroencephalography abnormalities in major psychiatric disorders. Early Interv Psychiatry 2019; 13:1319-1328. [PMID: 30688016 DOI: 10.1111/eip.12792] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/06/2018] [Revised: 10/03/2018] [Accepted: 12/29/2018] [Indexed: 12/29/2022]
Abstract
AIM Clinical staging in psychiatry aims to classify patients according to the severity of their symptoms, from stage 0 (increased risk, asymptomatic) to stage 4 (severe illness), enabling adapted treatment at each stage of the illness. The staging model would gain specificity if one or more quantifiable biological markers could be identified. Several biomarkers reflecting possible causal mechanisms and/or consequences of the pathophysiology are candidates for integration into the clinical staging model of psychiatric illnesses. METHODS This review covers the evolution (from stage 0 to stage 4) of the most important brain functioning impairments as measured with electroencephalography (EEG), in psychosis spectrum and in severe mood disorders. RESULTS The present review of the literature demonstrates that it is currently not possible to draw any conclusion with regard to the state or trait character of any of the EEG impairments in both major depressive disorder and bipolar disorder. As for schizophrenia, the most promising markers of the stage of the illness are the pitch mismatch negativity as well as the p300 event-related potentials, as these components seem to deteriorate with increasing severity of the illness. CONCLUSIONS Given the complexity of major psychiatric disorders, and that not a single impairment can be observed in all patients, future research should most likely consider combinations of markers in the quest for a better identification of the stages of the psychiatric illnesses.
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Affiliation(s)
- Suzie Lavoie
- Orygen, The National Centre of Excellence in Youth Mental Health, Melbourne, Victoria, Australia.,Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Andrea R Polari
- Orygen, The National Centre of Excellence in Youth Mental Health, Melbourne, Victoria, Australia.,Orygen Youth Health, Melbourne Health, Melbourne, Victoria, Australia
| | - Sherilyn Goldstone
- Orygen, The National Centre of Excellence in Youth Mental Health, Melbourne, Victoria, Australia.,Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Barnaby Nelson
- Orygen, The National Centre of Excellence in Youth Mental Health, Melbourne, Victoria, Australia.,Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Patrick D McGorry
- Orygen, The National Centre of Excellence in Youth Mental Health, Melbourne, Victoria, Australia.,Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
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Hamilton HK, Roach BJ, Bachman PM, Belger A, Carrion RE, Duncan E, Johannesen JK, Light GA, Niznikiewicz MA, Addington J, Bearden CE, Cadenhead KS, Cornblatt BA, McGlashan TH, Perkins DO, Seidman LJ, Tsuang MT, Walker EF, Woods SW, Cannon TD, Mathalon DH. Association Between P300 Responses to Auditory Oddball Stimuli and Clinical Outcomes in the Psychosis Risk Syndrome. JAMA Psychiatry 2019; 76:1187-1197. [PMID: 31389974 PMCID: PMC6686970 DOI: 10.1001/jamapsychiatry.2019.2135] [Citation(s) in RCA: 52] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
IMPORTANCE In most patients, a prodromal period precedes the onset of schizophrenia. Although clinical criteria for identifying the psychosis risk syndrome (PRS) show promising predictive validity, assessment of neurophysiologic abnormalities in at-risk individuals may improve clinical prediction and clarify the pathogenesis of schizophrenia. OBJECTIVE To determine whether P300 event-related potential amplitude, which is deficient in schizophrenia, is reduced in the PRS and associated with clinical outcomes. DESIGN, SETTING, AND PARTICIPANTS Auditory P300 data were collected as part of the multisite, case-control North American Prodrome Longitudinal Study (NAPLS-2) at 8 university-based outpatient programs. Participants included 552 individuals meeting PRS criteria and 236 healthy controls with P300 data. Auditory P300 data of participants at risk who converted to psychosis (n = 73) were compared with those of nonconverters who were followed up for 24 months and continued to be symptomatic (n = 135) or remitted from the PRS (n = 90). Data were collected from May 27, 2009, to September 17, 2014, and were analyzed from December 3, 2015, to May 1, 2019. MAIN OUTCOMES AND MEASURES Baseline electroencephalography was recorded during an auditory oddball task. Two P300 subcomponents were measured: P3b, elicited by infrequent target stimuli, and P3a, elicited by infrequent nontarget novel stimuli. RESULTS This study included 788 participants. The PRS group (n = 552) included 236 females (42.8%) (mean [SD] age, 19.21 [4.38] years), and the healthy control group (n = 236) included 111 females (47.0%) (mean [SD] age, 20.44 [4.73] years). Target P3b and novelty P3a amplitudes were reduced in at-risk individuals vs healthy controls (d = 0.37). Target P3b, but not novelty P3a, was significantly reduced in psychosis converters vs nonconverters (d = 0.26), and smaller target P3b amplitude was associated with a shorter time to psychosis onset in at-risk individuals (hazard ratio, 1.45; 95% CI, 1.04-2.00; P = .03). Participants with the PRS who remitted had baseline target P3b amplitudes that were similar to those of healthy controls and greater than those of converters (d = 0.51) and at-risk individuals who remained symptomatic (d = 0.41). CONCLUSIONS AND RELEVANCE In this study, deficits in P300 amplitude appeared to precede psychosis onset. Target P3b amplitudes, in particular, may be sensitive to clinical outcomes in the PRS, including both conversion to psychosis and clinical remission. Auditory target P3b amplitude shows promise as a putative prognostic biomarker of clinical outcome in the PRS.
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Affiliation(s)
- Holly K. Hamilton
- Department of Psychiatry, University of California, San Francisco,San Francisco Veterans Affairs Health Care System, San Francisco, California
| | - Brian J. Roach
- San Francisco Veterans Affairs Health Care System, San Francisco, California
| | - Peter M. Bachman
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Aysenil Belger
- Department of Psychiatry, University of North Carolina at Chapel Hill
| | - Ricardo E. Carrion
- Division of Psychiatry Research, The Zucker Hillside Hospital, North Shore-Long Island Jewish Health System, Glen Oaks, New York,Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, North Shore-Long Island Jewish Health System, Manhasset, New York,Department of Psychiatry, Hofstra Northwell School of Medicine, Hempstead, New York
| | - Erica Duncan
- Atlanta Veterans Affairs Medical Center, Decatur, Georgia,Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia
| | - Jason K. Johannesen
- Department of Psychiatry, School of Medicine, Yale University, New Haven, Connecticut,Veterans Affairs Connecticut Health Care System, West Haven, Connecticut
| | - Gregory A. Light
- Department of Psychiatry, University of California, San Diego, La Jolla,Veterans Affairs San Diego Healthcare System, La Jolla, California
| | - Margaret A. Niznikiewicz
- Department of Psychiatry, Harvard Medical School at Beth Israel Deaconess Medical Center, Massachusetts General Hospital, Boston, Massachusetts,Veterans Affairs Boston Healthcare System, Brockton, Massachusetts
| | - Jean Addington
- Hotchkiss Brain Institute Department of Psychiatry, University of Calgary, Calgary, Alberta, Canada
| | - Carrie E. Bearden
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles,Department of Psychology, University of California, Los Angeles
| | | | - Barbara A. Cornblatt
- Division of Psychiatry Research, The Zucker Hillside Hospital, North Shore-Long Island Jewish Health System, Glen Oaks, New York,Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, North Shore-Long Island Jewish Health System, Manhasset, New York,Department of Psychiatry, Hofstra Northwell School of Medicine, Hempstead, New York,Department of Molecular Medicine, Hofstra North Shore-Long Island Jewish School of Medicine, Hempstead, New York
| | - Thomas H. McGlashan
- Department of Psychiatry, School of Medicine, Yale University, New Haven, Connecticut
| | - Diana O. Perkins
- Department of Psychiatry, University of North Carolina at Chapel Hill
| | - Larry J. Seidman
- Department of Psychiatry, Harvard Medical School at Beth Israel Deaconess Medical Center, Massachusetts General Hospital, Boston, Massachusetts
| | - Ming T. Tsuang
- Department of Psychiatry, University of California, San Diego, La Jolla
| | - Elaine F. Walker
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia,Department of Psychology, Emory University, Atlanta, Georgia
| | - Scott W. Woods
- Department of Psychiatry, School of Medicine, Yale University, New Haven, Connecticut
| | - Tyrone D. Cannon
- Department of Psychiatry, School of Medicine, Yale University, New Haven, Connecticut,Department of Psychology, School of Medicine, Yale University, New Haven, Connecticut
| | - Daniel H. Mathalon
- Department of Psychiatry, University of California, San Francisco,San Francisco Veterans Affairs Health Care System, San Francisco, California
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37
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Monaghan CK, Brickman S, Huynh P, Öngür D, Hall MH. A longitudinal study of event related potentials and correlations with psychosocial functioning and clinical features in first episode psychosis patients. Int J Psychophysiol 2019; 145:48-56. [PMID: 31108121 DOI: 10.1016/j.ijpsycho.2019.05.007] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2018] [Revised: 05/10/2019] [Accepted: 05/13/2019] [Indexed: 10/26/2022]
Abstract
BACKGROUND Deficits in auditory event-related potentials (ERPs), brain responses to stimuli indexing different cognitive processes, have been demonstrated widely in chronic schizophrenia (SZ) patients though much less is known about these responses across the early course of psychosis. The present study examined multiple ERP components in first episode psychosis (FEP) patients longitudinally and investigated the relationships between ERPs, psychosocial functioning, and clinical features over time. METHODS N1, P2, P3a, and P3b ERPs were elicited using a three-stimulus (novelty) auditory oddball paradigm. FEP patients included SZ-spectrum and psychotic bipolar disorder (BD) diagnoses. Data were collected from 41 patients at baseline, 20 patients at 12-month follow-up, 14 at 24-month follow-up, and 29 healthy control subjects. RESULTS N1 and P2 ERPs were intact across the early stages of psychosis. Baseline P2 was significantly larger in BD than SZ patients. Reduced P3a and P3b ERPs were found in patients followed longitudinally and are stable over time. ERPs tracked distinct aspects of symptomology and medication, though specific associations were inconsistent across time. Baseline P3a amplitude predicted later psychosocial functioning. The pattern of correlations between ERP components in patients differed from controls. DISCUSSION Baseline P3a ERP, and PANSS general score were significant and independent predictors of later MCAS functioning at 12-month. Overall, individuals with worse functioning and greater symptomology produced smaller amplitudes. Our results highlight the heterogeneity within the FEP population. Correlation patterns among ERPs are similar between patients and controls. P3a and P3b amplitudes appear to link with higher-order cognitive and psychosocial functioning.
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Affiliation(s)
- Caitlin K Monaghan
- Schizophrenia and Bipolar Disorders Program, McLean Hospital, Harvard Medical School, Belmont, MA, USA; Psychosis Neurobiology Laboratory, McLean Hospital, Harvard Medical School, Belmont, MA, USA
| | - Sophie Brickman
- Schizophrenia and Bipolar Disorders Program, McLean Hospital, Harvard Medical School, Belmont, MA, USA; Psychosis Neurobiology Laboratory, McLean Hospital, Harvard Medical School, Belmont, MA, USA
| | - Polly Huynh
- Schizophrenia and Bipolar Disorders Program, McLean Hospital, Harvard Medical School, Belmont, MA, USA
| | - Dost Öngür
- Schizophrenia and Bipolar Disorders Program, McLean Hospital, Harvard Medical School, Belmont, MA, USA
| | - Mei-Hua Hall
- Schizophrenia and Bipolar Disorders Program, McLean Hospital, Harvard Medical School, Belmont, MA, USA; Psychosis Neurobiology Laboratory, McLean Hospital, Harvard Medical School, Belmont, MA, USA.
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Li F, Wang J, Liao Y, Yi C, Jiang Y, Si Y, Peng W, Yao D, Zhang Y, Dong W, Xu P. Differentiation of Schizophrenia by Combining the Spatial EEG Brain Network Patterns of Rest and Task P300. IEEE Trans Neural Syst Rehabil Eng 2019; 27:594-602. [DOI: 10.1109/tnsre.2019.2900725] [Citation(s) in RCA: 49] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Blakey R, Ranlund S, Zartaloudi E, Cahn W, Calafato S, Colizzi M, Crespo-Facorro B, Daniel C, Díez-Revuelta Á, Di Forti M, Iyegbe C, Jablensky A, Jones R, Hall MH, Kahn R, Kalaydjieva L, Kravariti E, Lin K, McDonald C, McIntosh AM, Picchioni M, Powell J, Presman A, Rujescu D, Schulze K, Shaikh M, Thygesen JH, Toulopoulou T, Van Haren N, Van Os J, Walshe M, Murray RM, Bramon E. Associations between psychosis endophenotypes across brain functional, structural, and cognitive domains. Psychol Med 2018; 48:1325-1340. [PMID: 29094675 PMCID: PMC6516747 DOI: 10.1017/s0033291717002860] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
BACKGROUND A range of endophenotypes characterise psychosis, however there has been limited work understanding if and how they are inter-related. METHODS This multi-centre study includes 8754 participants: 2212 people with a psychotic disorder, 1487 unaffected relatives of probands, and 5055 healthy controls. We investigated cognition [digit span (N = 3127), block design (N = 5491), and the Rey Auditory Verbal Learning Test (N = 3543)], electrophysiology [P300 amplitude and latency (N = 1102)], and neuroanatomy [lateral ventricular volume (N = 1721)]. We used linear regression to assess the interrelationships between endophenotypes. RESULTS The P300 amplitude and latency were not associated (regression coef. -0.06, 95% CI -0.12 to 0.01, p = 0.060), and P300 amplitude was positively associated with block design (coef. 0.19, 95% CI 0.10-0.28, p 0.38). All the cognitive endophenotypes were associated with each other in the expected directions (all p < 0.001). Lastly, the relationships between pairs of endophenotypes were consistent in all three participant groups, differing for some of the cognitive pairings only in the strengths of the relationships. CONCLUSIONS The P300 amplitude and latency are independent endophenotypes; the former indexing spatial visualisation and working memory, and the latter is hypothesised to index basic processing speed. Individuals with psychotic illnesses, their unaffected relatives, and healthy controls all show similar patterns of associations between endophenotypes, endorsing the theory of a continuum of psychosis liability across the population.
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Affiliation(s)
- R. Blakey
- Division of Psychiatry, University College London, London, UK
| | - S. Ranlund
- Division of Psychiatry, University College London, London, UK
- Institute of Psychiatry Psychology and Neuroscience at King’s College London and South London and Maudsley NHS Foundation Trust, London, UK
| | - E. Zartaloudi
- Division of Psychiatry, University College London, London, UK
| | - W. Cahn
- Department of Psychiatry, Brain Centre Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - S. Calafato
- Division of Psychiatry, University College London, London, UK
| | - M. Colizzi
- Institute of Psychiatry Psychology and Neuroscience at King’s College London and South London and Maudsley NHS Foundation Trust, London, UK
| | - B. Crespo-Facorro
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain
- Department of Psychiatry, University Hospital Marqués de Valdecilla, School of Medicine, University of Cantabria–IDIVAL, Santander, Spain
| | - C. Daniel
- Division of Psychiatry, University College London, London, UK
| | - Á. Díez-Revuelta
- Division of Psychiatry, University College London, London, UK
- Laboratory of Cognitive and Computational Neuroscience – Centre for Biomedical Technology (CTB), Complutense University and Technical University of Madrid, Madrid, Spain
| | - M. Di Forti
- Institute of Psychiatry Psychology and Neuroscience at King’s College London and South London and Maudsley NHS Foundation Trust, London, UK
| | | | - C. Iyegbe
- Institute of Psychiatry Psychology and Neuroscience at King’s College London and South London and Maudsley NHS Foundation Trust, London, UK
| | - A. Jablensky
- Centre for Clinical Research in Neuropsychiatry, The University of Western Australia, Perth, Western Australia, Australia
| | - R. Jones
- Division of Psychiatry, University College London, London, UK
| | - M.-H. Hall
- Psychology Research Laboratory, Harvard Medical School, McLean Hospital, Belmont, MA, USA
| | - R. Kahn
- Department of Psychiatry, Brain Centre Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - L. Kalaydjieva
- Harry Perkins Institute of Medical Research and Centre for Medical Research, The University of Western Australia, Perth, Australia
| | - E. Kravariti
- Institute of Psychiatry Psychology and Neuroscience at King’s College London and South London and Maudsley NHS Foundation Trust, London, UK
| | - K. Lin
- Institute of Psychiatry Psychology and Neuroscience at King’s College London and South London and Maudsley NHS Foundation Trust, London, UK
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - C. McDonald
- Department of Psychiatry, Clinical Science Institute, National University of Ireland Galway, Ireland
| | - A. M. McIntosh
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, UK
| | | | - M. Picchioni
- Institute of Psychiatry Psychology and Neuroscience at King’s College London and South London and Maudsley NHS Foundation Trust, London, UK
| | - J. Powell
- Institute of Psychiatry Psychology and Neuroscience at King’s College London and South London and Maudsley NHS Foundation Trust, London, UK
| | - A. Presman
- Division of Psychiatry, University College London, London, UK
| | - D. Rujescu
- Department of Psychiatry, Ludwig-Maximilians University of Munich, Munich, Germany
- Department of Psychiatry, Psychotherapy and Psychosomatics, University of Halle Wittenberg, Halle, Germany
| | - K. Schulze
- Institute of Psychiatry Psychology and Neuroscience at King’s College London and South London and Maudsley NHS Foundation Trust, London, UK
| | - M. Shaikh
- Institute of Psychiatry Psychology and Neuroscience at King’s College London and South London and Maudsley NHS Foundation Trust, London, UK
- North East London Foundation Trust, London, UK
| | - J. H. Thygesen
- Division of Psychiatry, University College London, London, UK
| | - T. Toulopoulou
- Institute of Psychiatry Psychology and Neuroscience at King’s College London and South London and Maudsley NHS Foundation Trust, London, UK
- Department of Psychology, Bilkent University, Main Campus, Bilkent, Ankara, Turkey
- Department of Psychology, the University of Hong Kong, Pokfulam Rd, Hong Kong SAR, China
- The State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, The Hong Kong Jockey Club Building for Interdisciplinary Research, Hong Kong SAR, China
| | - N. Van Haren
- Department of Psychiatry, Brain Centre Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - J. Van Os
- Institute of Psychiatry Psychology and Neuroscience at King’s College London and South London and Maudsley NHS Foundation Trust, London, UK
- Department of Psychiatry and Psychology, Maastricht University Medical Centre, EURON, Maastricht, The Netherlands
| | - M. Walshe
- Division of Psychiatry, University College London, London, UK
- Institute of Psychiatry Psychology and Neuroscience at King’s College London and South London and Maudsley NHS Foundation Trust, London, UK
| | | | - R. M. Murray
- Institute of Psychiatry Psychology and Neuroscience at King’s College London and South London and Maudsley NHS Foundation Trust, London, UK
| | - E. Bramon
- Division of Psychiatry, University College London, London, UK
- Institute of Psychiatry Psychology and Neuroscience at King’s College London and South London and Maudsley NHS Foundation Trust, London, UK
- Institute of Cognitive Neuroscience, University College London, London, UK
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Li F, Wang J, Jiang Y, Si Y, Peng W, Song L, Jiang Y, Zhang Y, Dong W, Yao D, Xu P. Top-Down Disconnectivity in Schizophrenia During P300 Tasks. Front Comput Neurosci 2018; 12:33. [PMID: 29875646 PMCID: PMC5974256 DOI: 10.3389/fncom.2018.00033] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2018] [Accepted: 05/03/2018] [Indexed: 12/03/2022] Open
Abstract
Cognitive deficits in schizophrenia are correlated with the dysfunctions of distinct brain regions including anterior cingulate cortex (ACC) and prefrontal cortex (PFC). Apart from the dysfunctions of the intrinsic connectivity of related areas, how the coupled neural populations work is also crucial in related processes. Twenty-four patients with schizophrenia (SZs) and 24 matched healthy controls (HCs) were recruited in our study. Based on the electroencephalogram (EEG) datasets recorded, the Dynamic Causal Modeling (DCM) was then adopted to estimate how the brain architecture adapts among related areas in SZs and to investigate the mechanism that accounts for their cognitive deficits. The distinct winning models in SZs and HCs consistently emphasized the importance of ACC in regulating the elicitations of P300s. Specifically, comparing to that in HCs, the winning model in SZs uncovered a compensatory pathway from dorsolateral PFC to intraparietal sulcus that promised the SZs' accomplishing P300 tasks. The findings demonstrated that the “disconnectivity hypothesis” is helpful and useful in explaining the cognitive deficits in SZs, while the brain architecture adapted with related compensatory pathway promises the limited brain cognitions in SZs. This study provides a new viewpoint that deepens our understanding of the cognitive deficits in schizophrenia.
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Affiliation(s)
- Fali Li
- MOE Key Lab for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Jiuju Wang
- Institute of Mental Health, Peking University Sixth Hospital, National Clinical Research Center for Mental Disorders & Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, China
| | - Yuanling Jiang
- MOE Key Lab for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Yajing Si
- MOE Key Lab for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Wenjing Peng
- MOE Key Lab for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Limeng Song
- MOE Key Lab for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Yi Jiang
- MOE Key Lab for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Yangsong Zhang
- MOE Key Lab for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China.,School of Computer Science and Technology, Southwest University of Science and Technology, Mianyang, China
| | - Wentian Dong
- Institute of Mental Health, Peking University Sixth Hospital, National Clinical Research Center for Mental Disorders & Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, China
| | - Dezhong Yao
- MOE Key Lab for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China.,Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Peng Xu
- MOE Key Lab for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China.,Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
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Kim M, Kwak YB, Lee TY, Kwon JS. Modulation of Electrophysiology by Transcranial Direct Current Stimulation in Psychiatric Disorders: A Systematic Review. Psychiatry Investig 2018; 15:434-444. [PMID: 29695150 PMCID: PMC5976006 DOI: 10.30773/pi.2018.01.10] [Citation(s) in RCA: 9] [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: 08/16/2017] [Revised: 11/15/2017] [Accepted: 01/10/2018] [Indexed: 01/03/2023] Open
Abstract
OBJECTIVE Transcranial direct current stimulation (tDCS) is a non-invasive neuromodulation technique increasingly used to relieve symptoms of psychiatric disorders. Electrophysiologic markers, such as electroencephalography (EEG) and event-related potentials (ERP), have high temporal resolution sensitive to detect plastic changes of the brain associated with symptomatic improvement following tDCS application. METHODS We performed systematic review to identify electrophysiological markers that reflect tDCS effects on plastic brain changes in psychiatric disorders. A total of 638 studies were identified by searching PubMed, Embase, psychINFPO. Of these, 21 full-text articles were assessed eligible and included in the review. RESULTS Although the reviewed studies were heterogeneous in their choices of tDCS protocols, targeted electrophysiological markers, and disease entities, their results strongly support EEG/ERPs to sensitively reflect plastic brain changes and the associated symptomatic improvement following tDCS. CONCLUSION EEG/ERPs may serve a potent tool in revealing the mechanisms underlying psychiatric symptoms, as well as in localizing the brain area targeted for stimulation. Future studies in each disease entities employing consistent tDCS protocols and electrophysiological markers would be necessary in order to substantiate and further elaborate the findings of studies included in the present systematic review.
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Affiliation(s)
- Minah Kim
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Yoo Bin Kwak
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Science, Seoul, Republic of Korea
| | - Tae Young Lee
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
| | - Jun Soo Kwon
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Science, Seoul, Republic of Korea
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
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Brislin SJ, Patrick CJ, Flor H, Nees F, Heinrich A, Drislane LE, Yancey JR, Banaschewski T, Bokde ALW, Bromberg U, Büchel C, Quinlan EB, Desrivières S, Frouin V, Garavan H, Gowland P, Heinz A, Ittermann B, Martinot JL, Martinot MLP, Papadopoulos Orfanos D, Poustka L, Fröhner JH, Smolka MN, Walter H, Whelan R, Conrod P, Stringaris A, Struve M, van Noort B, Grimmer Y, Fadai T, Schumann G, Foell J. Extending the Construct Network of Trait Disinhibition to the Neuroimaging Domain: Validation of a Bridging Scale for Use in the European IMAGEN Project. Assessment 2018; 26:567-581. [PMID: 29557190 DOI: 10.1177/1073191118759748] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Trait disinhibition, a clinical-liability construct, has well-established correlates in the diagnostic, self-rating, task-behavioral, and brain potential response domains. Recently, studies have begun to test for neuroimaging correlates of this liability factor, but more work of this type using larger data sets is needed to clarify its brain bases. The current study details the development and validation of a scale measure of trait disinhibition composed of questionnaire items available in the IMAGEN project, a large-scale longitudinal study of factors contributing to substance abuse that includes clinical interview, self-report personality, task-behavioral, neuroimaging, and genomic measures. Using a construct-rating and psychometric refinement approach, a scale was developed that evidenced: (a) positive relations with interview-assessed psychopathology in the IMAGEN sample, both concurrently and prospectively and (b) positive associations with scale measures of disinhibition and reported psychopathology, and a robust negative correlation with P3 brain response, in a separate adult sample ( Mage = 19.5). These findings demonstrate that a common scale measure can index this construct from adolescence through to early adulthood, and set the stage for systematic work directed at identifying neural and genetic biomarkers of this key liability construct using existing and future data from the IMAGEN project.
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Affiliation(s)
| | | | - Herta Flor
- 2 Heidelberg University, Mannheim, Germany.,3 University of Mannheim, Mannheim, Germany
| | | | | | | | | | | | | | - Uli Bromberg
- 6 University Medical Centre Hamburg-Eppendorf, Hamburg, Germany
| | | | | | | | | | | | - Penny Gowland
- 10 University of Nottingham, University Park, Nottingham, UK
| | - Andreas Heinz
- 11 Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Bernd Ittermann
- 12 Physikalisch-Technische Bundesanstalt, Braunschweig, Germany
| | - Jean-Luc Martinot
- 13 University Paris Sud, Orsay, France.,14 University Paris Descartes, Paris, France.,15 Université Paris-Sorbonne, Paris, France.,16 Maison de Solenn, Cochin Hospital, Paris, France
| | | | | | - Luise Poustka
- 2 Heidelberg University, Mannheim, Germany.,17 Medical University of Vienna, Vienna, Austria
| | | | | | - Henrik Walter
- 11 Charité-Universitätsmedizin Berlin, Berlin, Germany
| | | | | | | | | | | | | | - Tahmine Fadai
- 6 University Medical Centre Hamburg-Eppendorf, Hamburg, Germany
| | | | - Jens Foell
- 1 Florida State University, Tallahassee, FL, USA
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Decomposing P300 into correlates of genetic risk and current symptoms in schizophrenia: An inter-trial variability analysis. Schizophr Res 2018; 192:232-239. [PMID: 28400070 DOI: 10.1016/j.schres.2017.04.001] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2016] [Revised: 03/15/2017] [Accepted: 04/01/2017] [Indexed: 12/28/2022]
Abstract
BACKGROUND The P300 event-related potential (ERP) component, which reflects cognitive processing, is a candidate biomarker for schizophrenia. However, the role of P300 in the pathophysiology of schizophrenia remains unclear because averaged P300 amplitudes reflect both genetic predisposition and current clinical status. Thus, we sought to identify which aspects of P300 are associated with genetic risk versus symptomatic status via an inter-trial variability analysis. METHODS Auditory P300, clinical symptoms, and neurocognitive function assessments were obtained from forty-five patients with schizophrenia, thirty-two subjects at genetic high risk (GHR), thirty-two subjects at clinical high risk (CHR), and fifty-two healthy control (HC) participants. Both conventional averaging and inter-trial variability analyses were conducted for P300, and results were compared across groups using analysis of variance (ANOVA). Pearson's correlation was utilized to determine associations among inter-trial variability for P300, current symptoms and neurocognitive status. RESULTS Average P300 amplitude was reduced in the GHR, CHR, and schizophrenia groups compared with that in the HC group. P300 inter-trial variability was elevated in the CHR and schizophrenia groups but relatively normal in the GHR and HC groups. Furthermore, P300 inter-trial variability was significantly related to negative symptom severity and neurocognitive performance results in schizophrenia patients. CONCLUSIONS These results suggest that P300 amplitude is an endophenotype for schizophrenia and that greater inter-trial variability of P300 is associated with more severe negative and cognitive symptoms in schizophrenia patients.
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Harrewijn A, van der Molen MJW, van Vliet IM, Houwing-Duistermaat JJ, Westenberg PM. Delta-beta correlation as a candidate endophenotype of social anxiety: A two-generation family study. J Affect Disord 2018; 227:398-405. [PMID: 29154156 DOI: 10.1016/j.jad.2017.11.019] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/03/2017] [Revised: 10/01/2017] [Accepted: 11/07/2017] [Indexed: 02/02/2023]
Abstract
BACKGROUND Social anxiety disorder (SAD) is characterized by an extreme and intense fear and avoidance of social situations. In this two-generation family study we examined delta-beta correlation during a social performance task as candidate endophenotype of SAD. METHODS Nine families with a target participant (diagnosed with SAD), their spouse and children, as well as target's siblings with spouse and children performed a social performance task in which they gave a speech in front of a camera. EEG was measured during resting state, anticipation, and recovery. Our analyses focused on two criteria for endophenotypes: co-segregation within families and heritability. RESULTS Co-segregation analyses revealed increased negative delta-low beta correlation during anticipation in participants with (sub)clinical SAD compared to participants without (sub)clinical SAD. Heritability analyses revealed that delta-low beta and delta-high beta correlation during anticipation were heritable. Delta-beta correlation did not differ between participants with and without (sub)clinical SAD during resting state or recovery, nor between participants with and without SAD during all phases of the task. LIMITATIONS It should be noted that participants were seen only once, they all performed the EEG tasks in the same order, and some participants were too anxious to give a speech. CONCLUSIONS Delta-low beta correlation during anticipation of giving a speech might be a candidate endophenotype of SAD, possibly reflecting increased crosstalk between cortical and subcortical regions. If validated as endophenotype, delta-beta correlation during anticipation could be useful in studying the genetic basis, as well as improving treatment and early detection of persons at risk for developing SAD.
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Affiliation(s)
- Anita Harrewijn
- Developmental and Educational Psychology, Leiden University, The Netherlands; Leiden Institute for Brain and Cognition, Leiden University, The Netherlands.
| | - Melle J W van der Molen
- Developmental and Educational Psychology, Leiden University, The Netherlands; Leiden Institute for Brain and Cognition, Leiden University, The Netherlands
| | - Irene M van Vliet
- Department of Psychiatry, Leiden University Medical Center, The Netherlands
| | - Jeanine J Houwing-Duistermaat
- Department of Medical Statistics and BioInformatics, Leiden University Medical Center, The Netherlands; Department of Statistics, University of Leeds, United Kingdom
| | - P Michiel Westenberg
- Developmental and Educational Psychology, Leiden University, The Netherlands; Leiden Institute for Brain and Cognition, Leiden University, The Netherlands
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Ranlund S, Calafato S, Thygesen JH, Lin K, Cahn W, Crespo‐Facorro B, de Zwarte SM, Díez Á, Di Forti M, Iyegbe C, Jablensky A, Jones R, Hall M, Kahn R, Kalaydjieva L, Kravariti E, McDonald C, McIntosh AM, McQuillin A, Picchioni M, Prata DP, Rujescu D, Schulze K, Shaikh M, Toulopoulou T, van Haren N, van Os J, Vassos E, Walshe M, Lewis C, Murray RM, Powell J, Bramon E. A polygenic risk score analysis of psychosis endophenotypes across brain functional, structural, and cognitive domains. Am J Med Genet B Neuropsychiatr Genet 2018; 177:21-34. [PMID: 28851104 PMCID: PMC5763362 DOI: 10.1002/ajmg.b.32581] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2017] [Accepted: 07/24/2017] [Indexed: 12/26/2022]
Abstract
This large multi-center study investigates the relationships between genetic risk for schizophrenia and bipolar disorder, and multi-modal endophenotypes for psychosis. The sample included 4,242 individuals; 1,087 patients with psychosis, 822 unaffected first-degree relatives of patients, and 2,333 controls. Endophenotypes included the P300 event-related potential (N = 515), lateral ventricular volume (N = 798), and the cognitive measures block design (N = 3,089), digit span (N = 1,437), and the Ray Auditory Verbal Learning Task (N = 2,406). Data were collected across 11 sites in Europe and Australia; all genotyping and genetic analyses were done at the same laboratory in the United Kingdom. We calculated polygenic risk scores for schizophrenia and bipolar disorder separately, and used linear regression to test whether polygenic scores influenced the endophenotypes. Results showed that higher polygenic scores for schizophrenia were associated with poorer performance on the block design task and explained 0.2% (p = 0.009) of the variance. Associations in the same direction were found for bipolar disorder scores, but this was not statistically significant at the 1% level (p = 0.02). The schizophrenia score explained 0.4% of variance in lateral ventricular volumes, the largest across all phenotypes examined, although this was not significant (p = 0.063). None of the remaining associations reached significance after correction for multiple testing (with alpha at 1%). These results indicate that common genetic variants associated with schizophrenia predict performance in spatial visualization, providing additional evidence that this measure is an endophenotype for the disorder with shared genetic risk variants. The use of endophenotypes such as this will help to characterize the effects of common genetic variation in psychosis.
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Affiliation(s)
- Siri Ranlund
- Division of PsychiatryUniversity College LondonLondonUK
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | | | | | - Kuang Lin
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
- Nuffield Department of Population HealthUniversity of OxfordOxfordUK
| | - Wiepke Cahn
- Department of Psychiatry, Brain Centre Rudolf MagnusUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Benedicto Crespo‐Facorro
- CIBERSAMCentro Investigación Biomédica en Red Salud MentalMadridSpain
- Department of Psychiatry, University Hospital Marqués de Valdecilla, School of MedicineUniversity of Cantabria–IDIVALSantanderSpain
| | - Sonja M.C. de Zwarte
- Department of Psychiatry, Brain Centre Rudolf MagnusUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Álvaro Díez
- Division of PsychiatryUniversity College LondonLondonUK
- Laboratory of Cognitive and Computational Neuroscience—Centre for Biomedical Technology (CTB)Complutense University and Technical University of MadridMadridSpain
| | - Marta Di Forti
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | | | - Conrad Iyegbe
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | - Assen Jablensky
- Centre for Clinical Research in NeuropsychiatryThe University of Western AustraliaPerth, Western AustraliaAustralia
| | - Rebecca Jones
- Division of PsychiatryUniversity College LondonLondonUK
| | - Mei‐Hua Hall
- Psychosis Neurobiology Laboratory, Harvard Medical SchoolMcLean HospitalBelmontMassachusetts
| | - Rene Kahn
- Department of Psychiatry, Brain Centre Rudolf MagnusUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Luba Kalaydjieva
- Harry Perkins Institute of Medical Research and Centre for Medical ResearchThe University of Western AustraliaPerthAustralia
| | - Eugenia Kravariti
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | - Colm McDonald
- The Centre for Neuroimaging & Cognitive Genomics (NICOG) and NCBES Galway Neuroscience CentreNational University of Ireland GalwayGalwayIreland
| | - Andrew M. McIntosh
- Division of Psychiatry, University of EdinburghRoyal Edinburgh HospitalEdinburghUK
- Centre for Cognitive Ageing and Cognitive EpidemiologyUniversity of EdinburghEdinburghUK
| | | | | | - Marco Picchioni
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | - Diana P. Prata
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
- Faculdade de Medicina, Instituto de Medicina MolecularUniversidade de LisboaPortugal
| | - Dan Rujescu
- Department of PsychiatryLudwig‐Maximilians University of MunichMunichGermany
- Department of Psychiatry, Psychotherapy and PsychosomaticsUniversity of Halle WittenbergHalleGermany
| | - Katja Schulze
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | - Madiha Shaikh
- North East London Foundation TrustLondonUK
- Research Department of Clinical, Educational and Health PsychologyUniversity College LondonLondonUK
| | - Timothea Toulopoulou
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
- Department of Psychology, Bilkent UniversityMain CampusBilkent, AnkaraTurkey
- Department of PsychologyThe University of Hong Kong, Pokfulam RdHong Kong SARChina
- The State Key Laboratory of Brain and Cognitive Sciences, The University of Hong KongThe Hong Kong Jockey Club Building for Interdisciplinary ResearchHong Kong SARChina
| | - Neeltje van Haren
- Department of Psychiatry, Brain Centre Rudolf MagnusUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Jim van Os
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
- Department of Psychiatry and Psychology, Maastricht University Medical CentreEURONMaastrichtThe Netherlands
| | - Evangelos Vassos
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | - Muriel Walshe
- Division of PsychiatryUniversity College LondonLondonUK
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | | | - Cathryn Lewis
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | - Robin M. Murray
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | - John Powell
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | - Elvira Bramon
- Division of PsychiatryUniversity College LondonLondonUK
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
- Institute of Cognitive NeuroscienceUniversity College LondonLondonUK
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47
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Electrocortical measures of information processing biases in social anxiety disorder: A review. Biol Psychol 2017; 129:324-348. [DOI: 10.1016/j.biopsycho.2017.09.013] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2017] [Revised: 09/18/2017] [Accepted: 09/23/2017] [Indexed: 01/06/2023]
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48
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Oranje B, Aggernaes B, Rasmussen H, Ebdrup BH, Glenthøj BY. Selective attention and mismatch negativity in antipsychotic-naïve, first-episode schizophrenia patients before and after 6 months of antipsychotic monotherapy. Psychol Med 2017; 47:2155-2165. [PMID: 28443529 DOI: 10.1017/s0033291717000599] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND Attention deficits have been frequently reported in schizophrenia. It has been suggested that treatment with second-generation antipsychotics can ameliorate these deficits. In this study, the influence of 6 months treatment with quetiapine, a compound with less affinity for dopamine D2 receptors than for serotonergic 5-HT2A receptors, on electrophysiological parameters of attention was investigated in a group of antipsychotic-naïve, first-episode schizophrenia patients compared with a group of age- and gender-matched healthy controls. METHOD A total of 34 first-episode, antipsychotic-naïve patients with schizophrenia and an equal number of healthy controls were tested in a selective attention and a typical mismatch negativity (MMN) paradigm at baseline and after 6 months. The patients were treated with quetiapine according to their clinical needs during the period between baseline and follow-up, whereas controls received no treatment. RESULTS Patients showed lower MMN and P200 amplitude than healthy controls in the selective attention paradigm at baseline, while this was not the case for MMN of the typical MMN paradigm. Interestingly, after 6 months treatment, this MMN deficit was only ameliorated in patients treated with above median dosages of quetiapine. Patients had lower P3B amplitude, yet showed similar levels of processing negativity and N100 amplitude compared with healthy controls, both at baseline and follow-up. CONCLUSIONS The results indicate that deficits in MMN, P200 and P3B amplitude are present at early stages of schizophrenia, although depending on the paradigm used. Furthermore, the results indicate that 6 months quetiapine treatment ameliorates MMN but not P3B deficits, and only in those subjects on higher dosages.
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Affiliation(s)
- B Oranje
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research (CINS) and Center for Neuropsychiatric Schizophrenia Research (CNSR), Mental Health Services Glostrup,Capital Region Denmark, Glostrup,Denmark
| | - B Aggernaes
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research (CINS) and Center for Neuropsychiatric Schizophrenia Research (CNSR), Mental Health Services Glostrup,Capital Region Denmark, Glostrup,Denmark
| | - H Rasmussen
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research (CINS) and Center for Neuropsychiatric Schizophrenia Research (CNSR), Mental Health Services Glostrup,Capital Region Denmark, Glostrup,Denmark
| | - B H Ebdrup
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research (CINS) and Center for Neuropsychiatric Schizophrenia Research (CNSR), Mental Health Services Glostrup,Capital Region Denmark, Glostrup,Denmark
| | - B Y Glenthøj
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research (CINS) and Center for Neuropsychiatric Schizophrenia Research (CNSR), Mental Health Services Glostrup,Capital Region Denmark, Glostrup,Denmark
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49
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Sabeti M, Boostani R. Separation of P300 event-related potential using time varying time-lag blind source separation algorithm. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2017; 145:95-102. [PMID: 28552130 DOI: 10.1016/j.cmpb.2017.04.014] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/25/2016] [Revised: 03/10/2017] [Accepted: 04/18/2017] [Indexed: 06/07/2023]
Abstract
Synchronous averaging over time locked single-trial of event-related potential (ERP) is known as the simplest scheme to extract P300 component. This method assumes the P300 features are invariant through the time while they are affected by factors like brain fatigue and habitation. In this study, a new scheme is proposed termed as time-varying time-lag blind source separation (TT-BSS) which is upon the second order statistics of signal to separate P300 waveform from the background electroencephalogram (EEG) while it captures the time variation of P300 component. The time-lag parameter for all channels is determined by maximizing the correlation (similarity) between two successive trials. As the time-lag parameter is varying by time (trial to trial), an average is taken over the time-lag covariance matrices of all two consecutive trials. TT-BSS finally estimates a transform (separating matrix) by joint diagnolization of the covariance matrix of trials and the averaged covariance matrix of the time varying time-lag. To assess the proposed scheme, synthetic and real EEGs containing P300 are used. The EEG signals were collected from twenty schizophrenic and twenty age-matched normal subjects via 20 channels through the resting state and in presence of the oddball audio stimulus. Empirical achievements over the simulated and real EEGs imply on the superiority of TT-BSS in dynamic estimation of P300 characteristics compared to state-of-the-art counterparts such as constant time-lag BSS, constrained BSS and synchronous averaging.
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Affiliation(s)
- Malihe Sabeti
- Department of Computer Engineering, College of Engineering, Shiraz branch, Islamic Azad University, Shiraz, Iran.
| | - Reza Boostani
- Department of CSE & IT, Electrical and Computer College of Engineering, Shiraz University, Shiraz, Iran
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50
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Díez Á, Ranlund S, Pinotsis D, Calafato S, Shaikh M, Hall MH, Walshe M, Nevado Á, Friston KJ, Adams RA, Bramon E. Abnormal frontoparietal synaptic gain mediating the P300 in patients with psychotic disorder and their unaffected relatives. Hum Brain Mapp 2017; 38:3262-3276. [PMID: 28345275 DOI: 10.1002/hbm.23588] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2016] [Revised: 03/14/2017] [Accepted: 03/15/2017] [Indexed: 01/29/2023] Open
Abstract
The "dysconnection hypothesis" of psychosis suggests that a disruption of functional integration underlies cognitive deficits and clinical symptoms. Impairments in the P300 potential are well documented in psychosis. Intrinsic (self-)connectivity in a frontoparietal cortical hierarchy during a P300 experiment was investigated. Dynamic Causal Modeling was used to estimate how evoked activity results from the dynamics of coupled neural populations and how neural coupling changes with the experimental factors. Twenty-four patients with psychotic disorder, twenty-four unaffected relatives, and twenty-five controls underwent EEG recordings during an auditory oddball paradigm. Sixteen frontoparietal network models (including primary auditory, superior parietal, and superior frontal sources) were analyzed and an optimal model of neural coupling, explaining diagnosis and genetic risk effects, as well as their interactions with task condition were identified. The winning model included changes in connectivity at all three hierarchical levels. Patients showed decreased self-inhibition-that is, increased cortical excitability-in left superior frontal gyrus across task conditions, compared with unaffected participants. Relatives had similar increases in excitability in left superior frontal and right superior parietal sources, and a reversal of the normal synaptic gain changes in response to targets relative to standard tones. It was confirmed that both subjects with psychotic disorder and their relatives show a context-independent loss of synaptic gain control at the highest hierarchy levels. The relatives also showed abnormal gain modulation responses to task-relevant stimuli. These may be caused by NMDA-receptor and/or GABAergic pathologies that change the excitability of superficial pyramidal cells and may be a potential biological marker for psychosis. Hum Brain Mapp 38:3262-3276, 2017. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Álvaro Díez
- Division of Psychiatry, University College London, London, United Kingdom.,Department of Basic Psychology II - Cognitive processes, Faculty of Psychology, Complutense University of Madrid, Madrid, Spain.,Laboratory of Cognitive and Computational Neuroscience - Centre for Biomedical Technology (CTB), Complutense University and Technical University of Madrid, Madrid, Spain
| | - Siri Ranlund
- Division of Psychiatry, University College London, London, United Kingdom.,Psychology & Neuroscience - King's College London, Institute of Psychiatry, London, United Kingdom
| | - Dimitris Pinotsis
- The Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, United Kingdom.,The Picower Institute for Learning & Memory and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Stella Calafato
- Division of Psychiatry, University College London, London, United Kingdom
| | - Madiha Shaikh
- North East London NHS Foundation Trust, London, United Kingdom.,Psychology & Neuroscience - King's College London, Institute of Psychiatry, London, United Kingdom
| | - Mei-Hua Hall
- Psychosis Neurobiology Laboratory, McLean Hospital, Harvard Medical School, Belmont, Massachusetts
| | - Muriel Walshe
- Division of Psychiatry, University College London, London, United Kingdom.,Psychology & Neuroscience - King's College London, Institute of Psychiatry, London, United Kingdom
| | - Ángel Nevado
- Department of Basic Psychology II - Cognitive processes, Faculty of Psychology, Complutense University of Madrid, Madrid, Spain.,Laboratory of Cognitive and Computational Neuroscience - Centre for Biomedical Technology (CTB), Complutense University and Technical University of Madrid, Madrid, Spain
| | - Karl J Friston
- The Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, United Kingdom
| | - Rick A Adams
- Division of Psychiatry, University College London, London, United Kingdom.,Institute of Cognitive Neuroscience, University College London, London, United Kingdom
| | - Elvira Bramon
- Division of Psychiatry, University College London, London, United Kingdom.,Psychology & Neuroscience - King's College London, Institute of Psychiatry, London, United Kingdom.,Institute of Cognitive Neuroscience, University College London, London, United Kingdom
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