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Thibaudeau E, Bowie CR, Montreuil T, Baer L, Lecomte T, Joober R, Abdel-Baki A, Jarvis GE, Margolese HC, De Benedictis L, Schmitz N, Malla AK, Lepage M. Acceptability, engagement, and efficacy of cognitive remediation for cognitive outcomes in young adults with first-episode psychosis and social anxiety: A randomized-controlled trial. Psychiatry Res 2024; 342:116243. [PMID: 39467482 DOI: 10.1016/j.psychres.2024.116243] [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: 06/19/2024] [Revised: 10/17/2024] [Accepted: 10/19/2024] [Indexed: 10/30/2024]
Abstract
Social anxiety disorder (SAD) is a frequent comorbidity in first-episode psychosis (FEP) and may increase cognitive impairments. Cognitive remediation (CR) is an effective treatment for cognition, particularly in a group format. This study aims to assess the efficacy, acceptability and engagement of group CR on cognitive outcomes in FEP+SAD compared to group cognitive-behavioral therapy (CBT). Participants with FEP+SAD were randomized to group CR (n = 45) or CBT-SAD (n = 51). They were assessed for cognition at baseline, post-therapy and 3- and 6-month follow-up. The CR group additionally completed scale to assess perceived competency and enjoyment in CR. Linear mixed models for repeated measures were used for cognitive scores. Descriptive statistics and t-tests were used to summarize acceptability, perceived competency, and enjoyment, for CR completers and non-completers. The CR group performed significantly better than CBT on executive functions and visual memory at post-therapy compared to baseline. Twenty participants completed CR (44 %; mean 5.5 sessions). At week 1, CR non-completers presented higher levels of perceived competency. Completers reported higher enjoyment scores at the last session compared to the first session. Group CR is effective for cognitive outcomes in FEP+SAD, but acceptability and engagement present a challenge. Future studies are necessary to explore approaches promoting engagement.
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Affiliation(s)
- Elisabeth Thibaudeau
- Prevention and Early Intervention Program for Psychoses, Douglas Mental Health University Institute, Montreal, 6875 Bd LaSalle, Verdun, Quebec, H4H 1R3, Canada; Department of Psychiatry, McGill University, Ludmer Research & Training Building, 1033 Pine Avenue West, Montreal, Quebec, H3A 1A1, Canada.
| | - Christopher R Bowie
- Department of Psychology, Department of Psychiatry, Centre for Neuroscience Studies, Queen's University, 62 Arch Street, Kingston, Ontario, K7L 3N6, Canada.
| | - Tina Montreuil
- Department of Psychiatry, McGill University, Ludmer Research & Training Building, 1033 Pine Avenue West, Montreal, Quebec, H3A 1A1, Canada; Departments of Educational & Counselling Psychology and Psychiatry, McGill University, Education Bldg, 3700 McTavish St Suite 614, Montreal, Quebec, H3A 1Y2, Canada; Child Health and Human Development, Research Institute of the McGill University Health Centre, 2155 Guy Street, Suite 500, Montreal, Quebec, H3H 2R9, Canada.
| | - Larry Baer
- Prevention and Early Intervention Program for Psychoses, Douglas Mental Health University Institute, Montreal, 6875 Bd LaSalle, Verdun, Quebec, H4H 1R3, Canada; Department of Psychiatry, McGill University, Ludmer Research & Training Building, 1033 Pine Avenue West, Montreal, Quebec, H3A 1A1, Canada; Department of Psychiatry & Behavioural Neurosciences, McMaster University, 100 West 5th Street, Hamilton, Ontario, L8N 3K7, Canada
| | - Tania Lecomte
- Department of Psychology, University of Montréal, Marie-Victorin Building, PO BOX 6128 Centre-ville STN, Montreal Quebec, H3C 3J7, Canada.
| | - Ridha Joober
- Prevention and Early Intervention Program for Psychoses, Douglas Mental Health University Institute, Montreal, 6875 Bd LaSalle, Verdun, Quebec, H4H 1R3, Canada; Department of Psychiatry, McGill University, Ludmer Research & Training Building, 1033 Pine Avenue West, Montreal, Quebec, H3A 1A1, Canada.
| | - Amal Abdel-Baki
- Clinique JAP-Centre hospitalier de l'Université de Montréal (CHUM), 1051 Rue Sanguinet, Montreal, Quebec, H2X3E4, Canada; Centre de recherche du Centre hospitalier de l'Université de Montréal CRCHUM, 900 R. Saint-Denis, Montreal, Quebec, H2X0A9, Canada; Département de psychiatrie et d'addictologie, Université de Montréal, Pavillon Roger-Gaudry, 2900, boul. Édouard-Montpetit, bureau S-750, Montreal, Quebec, H3T 1J4, Canada
| | - G Eric Jarvis
- First Episode Psychosis Program, Jewish General Hospital, Department of Psychiatry, McGill University, 4333 Côte St-Catherine Road, Montreal, Quebec, H3T 1E4, Canada.
| | - Howard C Margolese
- Department of Psychiatry, McGill University, Ludmer Research & Training Building, 1033 Pine Avenue West, Montreal, Quebec, H3A 1A1, Canada; Prevention and Early Intervention Program for Psychoses, McGill University Health Centre, 1025, avenue Pine Ouest, Montréal Quebec, H3A 1A1, Canada.
| | - Luigi De Benedictis
- Département de psychiatrie et d'addictologie, Université de Montréal, Pavillon Roger-Gaudry, 2900, boul. Édouard-Montpetit, bureau S-750, Montreal, Quebec, H3T 1J4, Canada; Connec-T Clinic (First Psychotic Episode and Early Intervention Program), Institut universitaire en santé mentale de Montréal, Pavillon Lahaise, 3e étage, aile 303, 7401, rue Hochelaga, Montréal, Quebec, H1N 3M5, Canada.
| | - Norbert Schmitz
- Department of Population-Based Medicine, Institute of Health Sciences, University Hospital Tuebingen, Postfach 2669, 72016, Tuebingen, Germany.
| | - Ashok K Malla
- Prevention and Early Intervention Program for Psychoses, Douglas Mental Health University Institute, Montreal, 6875 Bd LaSalle, Verdun, Quebec, H4H 1R3, Canada; Department of Psychiatry, McGill University, Ludmer Research & Training Building, 1033 Pine Avenue West, Montreal, Quebec, H3A 1A1, Canada.
| | - Martin Lepage
- Prevention and Early Intervention Program for Psychoses, Douglas Mental Health University Institute, Montreal, 6875 Bd LaSalle, Verdun, Quebec, H4H 1R3, Canada; Department of Psychiatry, McGill University, Ludmer Research & Training Building, 1033 Pine Avenue West, Montreal, Quebec, H3A 1A1, Canada.
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Yao R, Song M, Shi L, Pei Y, Li H, Tan S, Wang B. Microstate D as a Biomarker in Schizophrenia: Insights from Brain State Transitions. Brain Sci 2024; 14:985. [PMID: 39451999 PMCID: PMC11505886 DOI: 10.3390/brainsci14100985] [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: 09/05/2024] [Revised: 09/23/2024] [Accepted: 09/26/2024] [Indexed: 10/26/2024] Open
Abstract
Objectives. There is a significant correlation between EEG microstate and the neurophysiological basis of mental illness, brain state, and cognitive function. Given that the unclear relationship between network dynamics and different microstates, this paper utilized microstate, brain network, and control theories to understand the microstate characteristics of short-term memory task, aiming to mechanistically explain the most influential microstates and brain regions driving the abnormal changes in brain state transitions in patients with schizophrenia. Methods. We identified each microstate and analyzed the microstate abnormalities in schizophrenia patients during short-term memory tasks. Subsequently, the network dynamics underlying the primary microstates were studied to reveal the relationships between network dynamics and microstates. Finally, using control theory, we confirmed that the abnormal changes in brain state transitions in schizophrenia patients are driven by specific microstates and brain regions. Results. The frontal-occipital lobes activity of microstate D decreased significantly, but the left frontal lobe of microstate B increased significantly in schizophrenia, when the brain was moving toward the easy-to-reach states. However, the frontal-occipital lobes activity of microstate D decreased significantly in schizophrenia, when the brain was moving toward the hard-to-reach states. Microstate D showed that the right-frontal activity had a higher priority than the left-frontal, but microstate B showed that the left-frontal priority decreased significantly in schizophrenia, when changes occur in the synchronization state of the brain. Conclusions. In conclusion, microstate D may be a biomarker candidate of brain abnormal activity during the states transitions in schizophrenia, and microstate B may represent a compensatory mechanism that maintains brain function and exchanges information with other brain regions. Microstate and brain network provide complementary perspectives on the neurodynamics, offering potential insights into brain function in health and disease.
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Affiliation(s)
- Rong Yao
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan 030024, China; (R.Y.); (M.S.); (L.S.); (Y.P.); (H.L.)
| | - Meirong Song
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan 030024, China; (R.Y.); (M.S.); (L.S.); (Y.P.); (H.L.)
| | - Langhua Shi
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan 030024, China; (R.Y.); (M.S.); (L.S.); (Y.P.); (H.L.)
| | - Yan Pei
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan 030024, China; (R.Y.); (M.S.); (L.S.); (Y.P.); (H.L.)
| | - Haifang Li
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan 030024, China; (R.Y.); (M.S.); (L.S.); (Y.P.); (H.L.)
| | - Shuping Tan
- Psychiatry Research Center, Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing 100096, China;
| | - Bin Wang
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan 030024, China; (R.Y.); (M.S.); (L.S.); (Y.P.); (H.L.)
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Wang L, Wang L, Chen J, Qiu C, Liu T, Wu Y, Li Y, Zou P, Guo S, Lu J. Five-week music therapy improves overall symptoms in schizophrenia by modulating theta and gamma oscillations. Front Psychiatry 2024; 15:1358726. [PMID: 38505791 PMCID: PMC10948521 DOI: 10.3389/fpsyt.2024.1358726] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Accepted: 02/22/2024] [Indexed: 03/21/2024] Open
Abstract
Introduction Some clinical studies have shown that music therapy as an adjunctive therapy can improve overall symptoms in patients with schizophrenia. However, the neural mechanisms of this improvement remain unclear due to insufficient neuroimaging evidence. Methods In this work, 17 patients with schizophrenia accepted a five-week music therapy (music group) that integrated listening, singing, and composing, and required patients to cooperate in a group to complete music therapy tasks. Meanwhile, 15 patients with schizophrenia received a five-week visual art intervention as the control group including handicraft and painting activities. We collected the Manchester Scale (MS) and Positive and Negative Symptom Scale (PANSS) scores and electroencephalography (EEG) data before and after intervention in two groups. Results Behavioral results showed that both interventions mentioned above can effectively help patients with schizophrenia relieve their overall symptoms, while a trend-level effect was observed in favor of music therapy. The EEG results indicated that music therapy can improve abnormal neural oscillations in schizophrenia which is reflected by a decrease in theta oscillation in the parietal lobe and an increase in gamma oscillation in the prefrontal lobe. In addition, correlation analysis showed that in the music group, both reductions in theta oscillations in the parietal lobe and increases in gamma oscillations in the prefrontal lobe were positively correlated with the improvement of overall symptoms. Discussion These findings help us to better understand the neural mechanisms by which music therapy improves overall symptoms in schizophrenia and provide more evidence for the application of music therapy in other psychiatric disorders.
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Affiliation(s)
- Lujie Wang
- Music and Digital Intelligence, Key Laboratory of Sichuan Province, Sichuan Conservatory of Music, Chengdu, China
- Department of Musicology, Sichuan Conservatory of Music, Chengdu, China
- Southwest Music Research Center, Key Research Base of Social Sciences in Sichuan Province, Sichuan Conservatory of Music, Chengdu, China
| | - Liju Wang
- Ministry of Education (MOE) Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Jiaxian Chen
- Ministry of Education (MOE) Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Chenxi Qiu
- Ministry of Education (MOE) Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Ting Liu
- Department of Rehabilitation, Chengdu Dekang Hospital, Chengdu, China
| | - Yulin Wu
- Yueling Music Therapy Service Center, Chengdu, China
| | - Yan Li
- Ministry of Education (MOE) Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Pengyu Zou
- Ministry of Education (MOE) Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Sijia Guo
- Ministry of Education (MOE) Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Jing Lu
- Ministry of Education (MOE) Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
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Gallucci J, Tan T, Schifani C, Dickie EW, Voineskos AN, Hawco C. Greater individual variability in functional brain activity during working memory performance in Schizophrenia Spectrum Disorders (SSD). Schizophr Res 2022; 248:21-31. [PMID: 35908378 DOI: 10.1016/j.schres.2022.07.012] [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] [Received: 10/21/2021] [Revised: 06/14/2022] [Accepted: 07/17/2022] [Indexed: 10/16/2022]
Abstract
Heterogeneity has been a persistent challenge in understanding Schizophrenia Spectrum Disorders (SSD). Traditional case-control comparisons often show variable results, and may not map well onto individuals. To better understand heterogeneity and group differences in SSD compared to typically developing controls (TDC), we examined variability in functional brain activity during a working memory (WM) task with known deficits in SSD. Neuroimaging and behavioural data were extracted from two datasets collectively providing 34 TDC and 56 individuals with SSD (n = 90). Functional activity in response to an N-Back WM task (3-Back vs 1-Back) was examined between and within groups. Individual variability was calculated via the correlational distance of fMRI activity maps between participants; mean correlational distance from one participant to all others was defined as a 'variability score'. Greater individual variability in functional activity was found in SSD compared to TDC (p = 0.00090). At the group level, a case-control comparison suggested SSD had reduced activity in task positive and task negative networks. However, when SSD were divided into high and low variability subgroups, the low variability groups showed no differences relative to TDC while the high variability group showed little activity at the group level. Our results imply prior case-control differences may be driven by a subgroup of SSD who do not show specific impairments but instead show more 'idiosyncratic' activity patterns. In SSD but not TDC, variability was also related to cognitive performance and age. This novel approach focusing on individual variability has important implications for understanding the neurobiology of SSD.
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Affiliation(s)
- Julia Gallucci
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Thomas Tan
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Christin Schifani
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Erin W Dickie
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Aristotle N Voineskos
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Colin Hawco
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada.
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Abstract
Working memory (WM) refers to the ability to maintain a small number of representations in an activated, easily accessible state for a short period of time in the service of ongoing cognitive processing and behavior. Because WM is a resource critical for multiple forms of complex cognition and executive control of behavior, it is of central interest in the study of disorders such as schizophrenia that involve a broad compromise of cognitive function and in the regulation of goal-directed behavior. There is now robust evidence that WM impairment is characteristic of people with schizophrenia. The impairment includes both elementary storage capacity as well as more complex forms of WM that involve the manipulation and updating of WM representations. These impairments appear to underlie a substantial portion of the generalized cognitive deficit in schizophrenia. Neuroimaging studies have implicated widespread abnormalities in the broad neural system that subserves WM performance, consistent with the evidence of broad cognitive impairment seen in PSZ.
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Affiliation(s)
- James M Gold
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA.
| | - Steven J Luck
- Center for Mind & Brain and Department of Psychology, University of California, Davis, CA, USA
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Bai D, Yao W, Wang S, Wang J. Multiscale Weighted Permutation Entropy Analysis of Schizophrenia Magnetoencephalograms. ENTROPY 2022; 24:e24030314. [PMID: 35327825 PMCID: PMC8946927 DOI: 10.3390/e24030314] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 02/19/2022] [Accepted: 02/20/2022] [Indexed: 12/27/2022]
Abstract
Schizophrenia is a neuropsychiatric disease that affects the nonlinear dynamics of brain activity. The primary objective of this study was to explore the complexity of magnetoencephalograms (MEG) in patients with schizophrenia. We combined a multiscale method and weighted permutation entropy to characterize MEG signals from 19 schizophrenia patients and 16 healthy controls. When the scale was larger than 42, the MEG signals of schizophrenia patients were significantly more complex than those of healthy controls (p<0.004). The difference in complexity between patients with schizophrenia and the controls was strongest in the frontal and occipital areas (p<0.001), and there was almost no difference in the central area. In addition, the results showed that the dynamic range of MEG complexity is wider in healthy individuals than in people with schizophrenia. Overall, the multiscale weighted permutation entropy method reliably quantified the complexity of MEG from schizophrenia patients, contributing to the development of potential magnetoencephalographic biomarkers for schizophrenia.
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Affiliation(s)
- Dengxuan Bai
- School of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China;
| | - Wenpo Yao
- Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province, School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
- Correspondence: (W.Y.); (J.W.)
| | - Shuwang Wang
- School of Electronic Information, Nanjing Vocational College of Information Technolog, Nanjing 210023, China;
| | - Jun Wang
- Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province, School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
- Correspondence: (W.Y.); (J.W.)
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Lack of neural load modulation explains attention and working memory deficits in first-episode schizophrenia. Clin Neurophysiol 2022; 136:206-218. [DOI: 10.1016/j.clinph.2022.02.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Revised: 01/29/2022] [Accepted: 02/02/2022] [Indexed: 11/23/2022]
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Sklar AL, Coffman BA, Salisbury DF. Fronto-parietal network function during cued visual search in the first-episode schizophrenia spectrum. J Psychiatr Res 2021; 141:339-345. [PMID: 34304038 PMCID: PMC8364882 DOI: 10.1016/j.jpsychires.2021.07.014] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 06/15/2021] [Accepted: 07/12/2021] [Indexed: 11/18/2022]
Abstract
Cognitive impairments account for significant morbidity in schizophrenia and are present at disease onset. Controlled processes are particularly susceptible and may contribute to pervasive selective attention deficits. The present study assessed fronto-parietal attention network (FPAN) functioning during cue presentation on a visual search task in first-episode schizophrenia spectrum patients (FE) and its relation to symptom burden and community functioning. Brain activity was recorded with magnetoencephalography from 38 FE and 38 healthy controls (HC) during blocks of pop-out and serial search target detection. Activity during cue presentation was compared between groups across bilateral FPAN regions (frontal eye fields (FEF), inferior frontal gyrus (IFG), midcingulate cortex (MCC), and intraparietal sulcus (IPS)). FE exhibited greater right hemisphere IFG activity despite worse performance relative to HC. Performance and FPAN activity were not correlated in HC. Among FE, however, stronger activity within right hemisphere FEF and IFG was associated with faster responses. Stronger right IPS and left IFG activity in patients was also associated with reduced negative symptoms and improved community functioning, respectively. Increased reliance on the FPAN for task completion suggests an inefficient cognitive control network and might reflect a compensation for impaired attentional deployment during target detection, a strategy employed by those with less severe illness. These findings represent a critical step towards identifying the neural substrates of negative symptoms and impaired neurocognition at disease onset.
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Affiliation(s)
- Alfredo L Sklar
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Western Psychiatric Hospital, Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Brian A Coffman
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Western Psychiatric Hospital, Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Dean F Salisbury
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Western Psychiatric Hospital, Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
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Dynamic Changes of Brain Networks during Working Memory Tasks in Schizophrenia. Neuroscience 2020; 453:187-205. [PMID: 33249224 DOI: 10.1016/j.neuroscience.2020.11.007] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Revised: 11/03/2020] [Accepted: 11/04/2020] [Indexed: 12/20/2022]
Abstract
Electroencephalograph (EEG) signals and graph theory measures have been widely used to characterize the brain functional networks of healthy individuals and patients by calculating the correlations between different electrodes over an entire time series. Although EEG signals have a high temporal resolution and can provide relatively stable results, the process of constructing and analyzing brain functional networks is inevitably complicated by high time complexity. Our goal in this research was to distinguish the brain function networks of schizophrenia patients from those of healthy participants during working memory tasks. Consequently, we utilized a method involving microstates, which are each characterized by a unique topography of electric potentials over an entire channel array, to reduce the dimension of the EEG signals during working memory tasks and then compared and analyzed the brain functional networks using the microstates time series (MTS) and original time series (OTS) of the schizophrenia patients and healthy individuals. We found that the right frontal and parietal-occipital regions neurons of the schizophrenia patients were less active than those of the healthy participants during working memory tasks. Notably, compared with OTS, the time needed to construct the brain functional networks was significantly reduced by using MTS. In conclusion, our results show that, like OTS, MTS can well distinguish the brain functional network of schizophrenia patients from those of healthy individuals during working memory tasks while greatly decreasing time complexity. MTS can thus provide a method for characterizing the original time series for the construction and analysis of EEG brain functional networks.
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