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Honcamp H, Schwartze M, Amorim M, Linden DEJ, Pinheiro AP, Kotz SA. Revisiting alpha resting state dynamics underlying hallucinatory vulnerability: Insights from Hidden semi-Markov Modeling. J Neurosci Methods 2024; 407:110138. [PMID: 38648892 DOI: 10.1016/j.jneumeth.2024.110138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 03/22/2024] [Accepted: 04/12/2024] [Indexed: 04/25/2024]
Abstract
BACKGROUND Resting state (RS) brain activity is inherently non-stationary. Hidden semi-Markov Models (HsMM) can characterize continuous RS data as a sequence of recurring and distinct brain states along with their spatio-temporal dynamics. NEW METHOD Recent explorations suggest that HsMM state dynamics in the alpha frequency band link to auditory hallucination proneness (HP) in non-clinical individuals. The present study aimed to replicate these findings to elucidate robust neural correlates of hallucinatory vulnerability. Specifically, we aimed to investigate the reproducibility of HsMM states across different data sets and within-data set variants as well as the replicability of the association between alpha brain state dynamics and HP. RESULTS We found that most brain states are reproducible in different data sets, confirming that the HsMM characterized robust and generalizable EEG RS dynamics on a sub-second timescale. Brain state topographies and temporal dynamics of different within-data set variants showed substantial similarities and were robust against reduced data length and number of electrodes. However, the association with HP was not directly reproducible across data sets. COMPARISON WITH EXISTING METHODS The HsMM optimally leverages the high temporal resolution of EEG data and overcomes time-domain restrictions of other state allocation methods. CONCLUSION The results indicate that the sensitivity of brain state dynamics to capture individual variability in HP may depend on the data recording characteristics and individual variability in RS cognition, such as mind wandering. Future studies should consider that the order in which eyes-open and eyes-closed RS data are acquired directly influences an individual's attentional state and generation of spontaneous thoughts, and thereby might mediate the link to hallucinatory vulnerability.
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Affiliation(s)
- Hanna Honcamp
- Department of Neuropsychology and Psychopharmacology, Faculty of Psychology and Neuroscience, Maastricht University, the Netherlands.
| | - Michael Schwartze
- Department of Neuropsychology and Psychopharmacology, Faculty of Psychology and Neuroscience, Maastricht University, the Netherlands
| | - Maria Amorim
- Centro de Investigação em Ciência Psicológica, Faculdade de Psicologia, Universidade de Lisboa, Lisboa, Portugal
| | - David E J Linden
- Department of Psychiatry and Neuropsychology, School of Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Ana P Pinheiro
- Centro de Investigação em Ciência Psicológica, Faculdade de Psicologia, Universidade de Lisboa, Lisboa, Portugal
| | - Sonja A Kotz
- Department of Neuropsychology and Psychopharmacology, Faculty of Psychology and Neuroscience, Maastricht University, the Netherlands
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Nazare K, Tomescu MI. Valence-specific EEG microstate modulations during self-generated affective states. Front Psychol 2024; 15:1300416. [PMID: 38855303 PMCID: PMC11160840 DOI: 10.3389/fpsyg.2024.1300416] [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: 09/23/2023] [Accepted: 04/26/2024] [Indexed: 06/11/2024] Open
Abstract
Introduction This study aims to explore the temporal dynamics of brain networks involved in self-generated affective states, specifically focusing on modulating these states in both positive and negative valences. The overarching goal is to contribute to a deeper understanding of the neurodynamic patterns associated with affective regulation, potentially informing the development of biomarkers for therapeutic interventions in mood and anxiety disorders. Methods Utilizing EEG microstate analysis during self-generated affective states, we investigated the temporal dynamics of five distinct microstates across different conditions, including baseline resting state and self-generated states of positive valence (e.g., awe, contentment) and negative valence (e.g., anger, fear). Results The study revealed noteworthy modulations in microstate dynamics during affective states. Additionally, valence-specific mechanisms of spontaneous affective regulation were identified. Negative valence affective states were characterized by the heightened presence of attention-associated microstates and reduced occurrence of salience-related microstates during negative valence states. In contrast, positive valence affective states manifested a prevalence of microstates related to visual/autobiographical memory and a reduced presence of auditory/language-associated microstates compared to both baseline and negative valence states. Discussion This study contributes to the field by employing EEG microstate analysis to discern the temporal dynamics of brain networks involved in self-generated affective states. Insights from this research carry significant implications for understanding neurodynamic patterns in affective regulation. The identification of valence-specific modulations and mechanisms has potential applications in developing biomarkers for mood and anxiety disorders, offering novel avenues for therapeutic interventions.
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Affiliation(s)
- Karina Nazare
- CINETic Center, Department of Research and Development, National University of Theatre and Film “I.L. Caragiale”, Bucharest, Romania
- Faculty of Automatic Control and Computers, POLITEHNICA University of Bucharest, Bucharest, Romania
| | - Miralena I. Tomescu
- CINETic Center, Department of Research and Development, National University of Theatre and Film “I.L. Caragiale”, Bucharest, Romania
- Department of Psychology, Faculty of Educational Sciences, University “Stefan cel Mare” of Suceava, Suceava, Romania
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Chivu A, Pascal SA, Damborská A, Tomescu MI. EEG Microstates in Mood and Anxiety Disorders: A Meta-analysis. Brain Topogr 2024; 37:357-368. [PMID: 37615799 PMCID: PMC11026263 DOI: 10.1007/s10548-023-00999-0] [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: 05/19/2023] [Accepted: 08/06/2023] [Indexed: 08/25/2023]
Abstract
To reduce the psycho-social burden increasing attention has focused on brain abnormalities in the most prevalent and highly co-occurring neuropsychiatric disorders, such as mood and anxiety. However, high inter-study variability in these patients results in inconsistent and contradictory alterations in the fast temporal dynamics of large-scale networks as measured by EEG microstates. Thus, in this meta-analysis, we aim to investigate the consistency of these changes to better understand possible common neuro-dynamical mechanisms of these disorders.In the systematic search, twelve studies investigating EEG microstate changes in participants with mood and anxiety disorders and individuals with subclinical depression were included in this meta-analysis, adding up to 787 participants.The results suggest that EEG microstates consistently discriminate mood and anxiety impairments from the general population in patients and subclinical states. Specifically, we found a small significant effect size for B microstates in patients compared to healthy controls, with larger effect sizes for increased B presence in unmedicated patients with comorbidity. In a subgroup meta-analysis of ten mood disorder studies, microstate D showed a significant effect size for decreased presence. When investigating only the two anxiety disorder studies, we found a significantly small effect size for the increased microstate A and a medium effect size for decreased microstate E (one study). However, more studies are needed to elucidate whether these findings are diagnostic-specific markers.Results are discussed in relation to the functional meaning of microstates and possible contribution to an explanatory mechanism of overlapping symptomatology of mood and anxiety disorders.
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Affiliation(s)
- Alina Chivu
- CINETic Center, National University of Theatre and Film "I.L. Caragiale" Bucharest, Bucharest, Romania
- Faculty of Psychology and Educational Sciences, Department of Applied Psychology and Psychotherapy, University of Bucharest, Bucharest, Romania
| | - Simona A Pascal
- Faculty of Psychology and Educational Sciences, Department of Applied Psychology and Psychotherapy, University of Bucharest, Bucharest, Romania
| | - Alena Damborská
- Department of Psychiatry, Faculty of Medicine, Masaryk University and University Hospital Brno, Brno, Czech Republic
- Multimodal and Functional Neuroimaging Research Group, CEITEC - Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Miralena I Tomescu
- CINETic Center, National University of Theatre and Film "I.L. Caragiale" Bucharest, Bucharest, Romania.
- Faculty of Educational Sciences, Department of Psychology, University "Stefan cel Mare" of Suceava, Suceava, Romania.
- Faculty of Psychology and Educational Sciences, Department of Cognitive Sciences, University of Bucharest, Bucharest, Romania.
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Chen J, Jin L, Lin N. Utilization of EEG microstates as a prospective biomarker for assessing the impact of ketogenic diet in GLUT1-DS. Neurol Sci 2024:10.1007/s10072-024-07519-3. [PMID: 38589768 DOI: 10.1007/s10072-024-07519-3] [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: 01/30/2024] [Accepted: 04/02/2024] [Indexed: 04/10/2024]
Abstract
OBJECTIVE The aim of the study is to analyze microstate patterns in GLUT1-DS, both before and after the ketogenic diet (KD). METHODS We conducted microstate analysis of a patient with GLUT-1 DS and 27 healthy controls. A systematic literature review and meta-analysis was done. We compared the parameters of the patients with those of healthy controls and the incorporating findings in literature. RESULTS The durations of the patient were notably shorter, and the occurrence rates were longer than those of healthy controls and incorporating findings from the review. After 10 months of KD, the patient's microstate durations exhibited an increase from 53.05 ms, 57.17 ms, 61.80 ms, and 49.49 ms to 60.53 ms, 63.27 ms, 71.11 ms, and 66.55 ms. The occurrence rates changed from 4.0774 Hz, 4.9462 Hz, 4.8006 Hz, and 4.0579 Hz to 3.3354 Hz, 3.7893 Hz, 3.5956 Hz, and 4.1672 Hz. In healthy controls, the durations of microstate class A, B, C, and D were 61.86 ms, 63.58 ms, 70.57 ms, and 72.00 ms, respectively. CONCLUSIONS Our findings suggest EEG microstates may be a promising biomarker for monitoring the effect of KD. Administration of KD may normalize the dysfunctional patterns of temporal parameters.
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Affiliation(s)
- Jianhua Chen
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, 100730, China.
| | - Liri Jin
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, 100730, China.
| | - Nan Lin
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, 100730, China
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Tarailis P, Koenig T, Michel CM, Griškova-Bulanova I. The Functional Aspects of Resting EEG Microstates: A Systematic Review. Brain Topogr 2024; 37:181-217. [PMID: 37162601 DOI: 10.1007/s10548-023-00958-9] [Citation(s) in RCA: 25] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Accepted: 04/11/2023] [Indexed: 05/11/2023]
Abstract
A growing body of clinical and cognitive neuroscience studies have adapted a broadband EEG microstate approach to evaluate the electrical activity of large-scale cortical networks. However, the functional aspects of these microstates have not yet been systematically reviewed. Here, we present an overview of the existing literature and systematize the results to provide hints on the functional role of electrical brain microstates. Studies that evaluated and manipulated the temporal properties of resting-state microstates and utilized questionnaires, task-initiated thoughts, specific tasks before or between EEG session(s), pharmacological interventions, neuromodulation approaches, or localized sources of the extracted microstates were selected. Fifty studies that met the inclusion criteria were included. A new microstate labeling system has been proposed for a comprehensible comparison between the studies, where four classical microstates are referred to as A-D, and the others are labeled by the frequency of their appearance. Microstate A was associated with both auditory and visual processing and links to subjects' arousal/arousability. Microstate B showed associations with visual processing related to self, self-visualization, and autobiographical memory. Microstate C was related to processing personally significant information, self-reflection, and self-referential internal mentation rather than autonomic information processing. In contrast, microstate E was related to processing interoceptive and emotional information and to the salience network. Microstate D was associated with executive functioning. Microstate F is suggested to be a part of the Default Mode Network and plays a role in personally significant information processing, mental simulations, and theory of mind. Microstate G is potentially linked to the somatosensory network.
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Affiliation(s)
- Povilas Tarailis
- Life Sciences Centre, Institute of Biosciences, Vilnius University, Vilnius, Lithuania
| | - Thomas Koenig
- Translational Research Center, University Hospital of Psychiatry, University of Bern, Bern, Switzerland
| | - Christoph M Michel
- Functional Brain Mapping Laboratory, Department of Fundamental Neuroscience, University of Geneva, Geneva, Switzerland
- Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
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Černý F, Piorecká V, Kliková M, Kopřivová J, Bušková J, Piorecký M. All-night spectral and microstate EEG analysis in patients with recurrent isolated sleep paralysis. Front Neurosci 2024; 18:1321001. [PMID: 38389790 PMCID: PMC10882627 DOI: 10.3389/fnins.2024.1321001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Accepted: 01/25/2024] [Indexed: 02/24/2024] Open
Abstract
The pathophysiology of recurrent isolated sleep paralysis (RISP) has yet to be fully clarified. Very little research has been performed on electroencephalographic (EEG) signatures outside RISP episodes. This study aimed to investigate whether sleep is disturbed even without the occurrence of a RISP episode and in a stage different than conventional REM sleep. 17 RISP patients and 17 control subjects underwent two consecutive full-night video-polysomnography recordings. Spectral analysis was performed on all sleep stages in the delta, theta, and alpha band. EEG microstate (MS) analysis was performed on the NREM 3 phase due to the overall high correlation of subject template maps with canonical templates. Spectral analysis showed a significantly higher power of theta band activity in REM and NREM 2 sleep stages in RISP patients. The observed rise was also apparent in other sleep stages. Conversely, alpha power showed a downward trend in RISP patients' deep sleep. MS maps similar to canonical topographies were obtained indicating the preservation of prototypical EEG generators in RISP patients. RISP patients showed significant differences in the temporal dynamics of MS, expressed by different transitions between MS C and D and between MS A and B. Both spectral analysis and MS characteristics showed abnormalities in the sleep of non-episodic RISP subjects. Our findings suggest that in order to understand the neurobiological background of RISP, there is a need to extend the analyzes beyond REM-related processes and highlight the value of EEG microstate dynamics as promising functional biomarkers of RISP.
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Affiliation(s)
- Filip Černý
- Faculty of Biomedical Engineering, Czech Technical University, Prague, Czechia
- Sleep and Chronobiology Research Center, National Institute of Mental Health, Klecany, Czechia
| | - Václava Piorecká
- Faculty of Biomedical Engineering, Czech Technical University, Prague, Czechia
- Sleep and Chronobiology Research Center, National Institute of Mental Health, Klecany, Czechia
| | - Monika Kliková
- Sleep and Chronobiology Research Center, National Institute of Mental Health, Klecany, Czechia
| | - Jana Kopřivová
- Sleep and Chronobiology Research Center, National Institute of Mental Health, Klecany, Czechia
- Third Faculty of Medicine, Charles University, Prague, Czechia
| | - Jitka Bušková
- Sleep and Chronobiology Research Center, National Institute of Mental Health, Klecany, Czechia
- Third Faculty of Medicine, Charles University, Prague, Czechia
| | - Marek Piorecký
- Faculty of Biomedical Engineering, Czech Technical University, Prague, Czechia
- Sleep and Chronobiology Research Center, National Institute of Mental Health, Klecany, Czechia
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7
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Thirioux B, Langbour N, Bokam P, Wassouf I, Guillard-Bouhet N, Wangermez C, Leblanc PM, Doolub D, Harika-Germaneau G, Jaafari N. EEG microstate co-specificity in schizophrenia and obsessive-compulsive disorder. Eur Arch Psychiatry Clin Neurosci 2024; 274:207-225. [PMID: 37421444 DOI: 10.1007/s00406-023-01642-6] [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: 04/17/2023] [Accepted: 06/19/2023] [Indexed: 07/10/2023]
Abstract
The past 20 years of research on EEG microstates has yielded the hypothesis that the imbalance pattern in the temporal dynamics of microstates C (increased) and D (decreased) is specific to schizophrenia. A similar microstate imbalance has been recently found in obsessive-compulsive disorder (OCD). The aim of the present high-density EEG study was to examine whether this pathological microstate pattern is co-specific to schizophrenia and OCD. We compared microstate temporal dynamics using Bayesian analyses, transition probabilities analyses and the Topographic Electrophysiological State Source-Imaging method for source reconstruction in 24 OCD patients and 28 schizophrenia patients, respectively, free of comorbid psychotic and OCD symptoms, and 27 healthy controls. OCD and schizophrenia patients exhibited the same increased contribution of microstate C, decreased duration and contribution of microstate D and greater D → C transition probabilities, compared with controls. A Bayes factor of 4.424 for the contribution of microstate C, 4.600 and 3.824, respectively, for the duration and contribution of microstate D demonstrated that there was no difference in microstate patterns between the two disorders. Source reconstruction further showed undistinguishable dysregulations between the Salience Network (SN), associated with microstate C, and the Executive Control Network (ECN), associated with microstate D, and between the ECN and cognitive cortico-striato-thalamo-cortical (CSTC) loop in the two disorders. The ECN/CSTC loop dysconnectivity was slightly worsened in schizophrenia. Our findings provide substantial evidence for a common aetiological pathway in schizophrenia and OCD, i.e. microstate co-specificity, and same anomalies in salience and external attention processing, leading to co-expression of symptoms.
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Affiliation(s)
- Bérangère Thirioux
- Unité de Recherche Clinique Pierre Deniker, Centre Hospitalier Henri Laborit, 370 Avenue Jacques Coeur, 86021, Poitiers, France.
- Centre de Recherches sur la Cognition et l'Apprentissage, Université de Poitiers, CNRS 7295, 86021, Poitiers, France.
| | - Nicolas Langbour
- Unité de Recherche Clinique Pierre Deniker, Centre Hospitalier Henri Laborit, 370 Avenue Jacques Coeur, 86021, Poitiers, France
- Centre de Recherches sur la Cognition et l'Apprentissage, Université de Poitiers, CNRS 7295, 86021, Poitiers, France
| | - Prasanth Bokam
- Unité de Recherche Clinique Pierre Deniker, Centre Hospitalier Henri Laborit, 370 Avenue Jacques Coeur, 86021, Poitiers, France
| | - Issa Wassouf
- Unité de Recherche Clinique Pierre Deniker, Centre Hospitalier Henri Laborit, 370 Avenue Jacques Coeur, 86021, Poitiers, France
- Centre Hospitalier Nord Deux-Sèvres, Parthenay, France
| | - Nathalie Guillard-Bouhet
- Centre de Réhabilitation et d'Activités Thérapeutiques Intersectorial de la Vienne, Centre Hospitalier Henri Laborit, 86021, Poitiers, France
- Centre Médico-Psychologique, Centre Hospitalier Henri Laborit, 86021, Poitiers, France
| | - Carole Wangermez
- Unité de Recherche Clinique Pierre Deniker, Centre Hospitalier Henri Laborit, 370 Avenue Jacques Coeur, 86021, Poitiers, France
- Centre de Réhabilitation et d'Activités Thérapeutiques Intersectorial de la Vienne, Centre Hospitalier Henri Laborit, 86021, Poitiers, France
| | - Pierre-Marie Leblanc
- Unité de Recherche Clinique Pierre Deniker, Centre Hospitalier Henri Laborit, 370 Avenue Jacques Coeur, 86021, Poitiers, France
| | - Damien Doolub
- Unité de Recherche Clinique Pierre Deniker, Centre Hospitalier Henri Laborit, 370 Avenue Jacques Coeur, 86021, Poitiers, France
- Centre de Recherches sur la Cognition et l'Apprentissage, Université de Poitiers, CNRS 7295, 86021, Poitiers, France
| | - Ghina Harika-Germaneau
- Unité de Recherche Clinique Pierre Deniker, Centre Hospitalier Henri Laborit, 370 Avenue Jacques Coeur, 86021, Poitiers, France
- Centre de Recherches sur la Cognition et l'Apprentissage, Université de Poitiers, CNRS 7295, 86021, Poitiers, France
- Faculté de Médecine et de Pharmacie, Université de Poitiers, 86021, Poitiers, France
| | - Nematollah Jaafari
- Unité de Recherche Clinique Pierre Deniker, Centre Hospitalier Henri Laborit, 370 Avenue Jacques Coeur, 86021, Poitiers, France
- Centre de Recherches sur la Cognition et l'Apprentissage, Université de Poitiers, CNRS 7295, 86021, Poitiers, France
- Centre Médico-Psychologique, Centre Hospitalier Henri Laborit, 86021, Poitiers, France
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Liebrand M, Katsarakis A, Josi J, Diezig S, Michel C, Schultze-Lutter F, Rochas V, Mancini V, Kaess M, Hubl D, Koenig T, Kindler J. EEG microstate D as psychosis-specific correlate in adolescents and young adults with clinical high risk for psychosis and first-episode psychosis. Schizophr Res 2024; 264:49-57. [PMID: 38096659 DOI: 10.1016/j.schres.2023.11.014] [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: 05/17/2023] [Revised: 10/05/2023] [Accepted: 11/29/2023] [Indexed: 03/01/2024]
Abstract
Resting-state electroencephalography (EEG) microstates are brief periods (60-120 ms) of quasi-stable scalp field potentials, indicating simultaneous activity of large-scale networks. Microstates are assumed to reflect basic neuronal information processing. A common finding in psychosis spectrum disorders is that microstates classes C and D are altered. Whereas evidence in adults with schizophrenia is substantial, little is known about effects in underage patients, particularly in those at clinical high risk for psychosis (CHR) and first-episode psychosis (FEP). The present study used 74-channel EEG to investigate microstate effects in a large sample of patients with CHR (n = 100) and FEP (n = 33), clinical controls (CC, n = 18), as well as age-matched healthy controls (HC, n = 68). Subjects span an age range from 9 to 35 years, thus, covering underage patients as well as the most vulnerable period for the emergence of psychosis and its prodrome. Four EEG microstates classes were analyzed (A-D). In class D, CHR and FEP patients showed a decrease compared to HC, and CHR patients also to CC. An increase in class C was found in CHR and FEP compared to HC but not to CC. Results were independent of age and no differences were found between the psychosis spectrum groups. The findings suggest an age-independent decrease of microstate class D to be specific to the psychosis spectrum, whereas the increase in class C seems to reflect unspecific psychopathology. Overall, present data strengthens the role of microstate D as potential biomarker for psychosis, as early as in adolescence and already in CHR status.
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Affiliation(s)
- Matthias Liebrand
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Switzerland
| | - Angelos Katsarakis
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Switzerland
| | - Johannes Josi
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Switzerland
| | - Sarah Diezig
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Switzerland
| | - Chantal Michel
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Switzerland
| | - Frauke Schultze-Lutter
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Switzerland; Department of Psychiatry and Psychotherapy, Medical Faculty, Heinrich-Heine-University, Düsseldorf, Germany; Department of Psychology, Faculty of Psychology, Airlangga University, Surabaya, Indonesia
| | - Vincent Rochas
- Department of Basic Neurosciences, University of Geneva, Campus Biotech, Switzerland
| | - Valentina Mancini
- Department of Basic Neurosciences, University of Geneva, Campus Biotech, Switzerland; Developmental Imaging and Psychopathology Laboratory, University of Geneva School of Medicine, Switzerland
| | - Michael Kaess
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Switzerland
| | - Daniela Hubl
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Switzerland
| | - Thomas Koenig
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Switzerland
| | - Jochen Kindler
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Switzerland
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Zhao S, Dai G, Li J, Zhu X, Huang X, Li Y, Tan M, Wang L, Fang P, Chen X, Yan N, Liu H. An interpretable model based on graph learning for diagnosis of Parkinson's disease with voice-related EEG. NPJ Digit Med 2024; 7:3. [PMID: 38182737 PMCID: PMC10770376 DOI: 10.1038/s41746-023-00983-9] [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: 08/23/2023] [Accepted: 11/29/2023] [Indexed: 01/07/2024] Open
Abstract
Parkinson's disease (PD) exhibits significant clinical heterogeneity, presenting challenges in the identification of reliable electroencephalogram (EEG) biomarkers. Machine learning techniques have been integrated with resting-state EEG for PD diagnosis, but their practicality is constrained by the interpretable features and the stochastic nature of resting-state EEG. The present study proposes a novel and interpretable deep learning model, graph signal processing-graph convolutional networks (GSP-GCNs), using event-related EEG data obtained from a specific task involving vocal pitch regulation for PD diagnosis. By incorporating both local and global information from single-hop and multi-hop networks, our proposed GSP-GCNs models achieved an averaged classification accuracy of 90.2%, exhibiting a significant improvement of 9.5% over other deep learning models. Moreover, the interpretability analysis revealed discriminative distributions of large-scale EEG networks and topographic map of microstate MS5 learned by our models, primarily located in the left ventral premotor cortex, superior temporal gyrus, and Broca's area that are implicated in PD-related speech disorders, reflecting our GSP-GCN models' ability to provide interpretable insights identifying distinctive EEG biomarkers from large-scale networks. These findings demonstrate the potential of interpretable deep learning models coupled with voice-related EEG signals for distinguishing PD patients from healthy controls with accuracy and elucidating the underlying neurobiological mechanisms.
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Affiliation(s)
- Shuzhi Zhao
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- School of Biomedical Engineering, Sun Yat-sen University, Shenzhen, China
- CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Guangyan Dai
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Jingting Li
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Xiaoxia Zhu
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Xiyan Huang
- Department of Rehabilitation Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Yongxue Li
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Mingdan Tan
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Lan Wang
- CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
- Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Peng Fang
- CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
- Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Xi Chen
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
| | - Nan Yan
- CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
- Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
| | - Hanjun Liu
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
- Guangdong Provincial Key Laboratory of Brain Function and Disease, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China.
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Zhu M, Gong Q. EEG spectral and microstate analysis originating residual inhibition of tinnitus induced by tailor-made notched music training. Front Neurosci 2023; 17:1254423. [PMID: 38148944 PMCID: PMC10750374 DOI: 10.3389/fnins.2023.1254423] [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: 07/07/2023] [Accepted: 11/21/2023] [Indexed: 12/28/2023] Open
Abstract
Tailor-made notched music training (TMNMT) is a promising therapy for tinnitus. Residual inhibition (RI) is one of the few interventions that can temporarily inhibit tinnitus, which is a useful technique that can be applied to tinnitus research and explore tinnitus mechanisms. In this study, RI effect of TMNMT in tinnitus was investigated mainly using behavioral tests, EEG spectral and microstate analysis. To our knowledge, this study is the first to investigate RI effect of TMNMT. A total of 44 participants with tinnitus were divided into TMNMT group (22 participants; ECnm, NMnm, RInm represent that EEG recordings with eyes closed stimuli-pre, stimuli-ing, stimuli-post by TMNMT music, respectively) and Placebo control group (22 participants; ECpb, PBpb, RIpb represent that EEG recordings with eyes closed stimuli-pre, stimuli-ing, stimuli-post by Placebo music, respectively) in a single-blind manner. Behavioral tests, EEG spectral analysis (covering delta, theta, alpha, beta, gamma frequency bands) and microstate analysis (involving four microstate classes, A to D) were employed to evaluate RI effect of TMNMT. The results of the study showed that TMNMT had a stronger inhibition ability and longer inhibition time according to the behavioral tests compared to Placebo. Spectral analysis showed that RI effect of TMNMT increased significantly the power spectral density (PSD) of delta, theta bands and decreased significantly the PSD of alpha2 band, and microstate analysis showed that RI effect of TMNMT had shorter duration (microstate B, microstate C), higher Occurrence (microstate A, microstate C, microstate D), Coverage (microstate A) and transition probabilities (microstate A to microstate B, microstate A to microstate D and microstate D to microstate A). Meanwhile, RI effect of Placebo decreased significantly the PSD of alpha2 band, and microstate analysis showed that RI effect of Placebo had shorter duration (microstate C, microstate D), higher occurrence (microstate B, microstate C), lower coverage (microstate C, microstate D), higher transition probabilities (microstate A to microstate B, microstate B to microstate A). It was also found that the intensity of tinnitus symptoms was significant positively correlated with the duration of microstate B in five subgroups (ECnm, NMnm, RInm, ECpb, PBpb). Our study provided valuable experimental evidence and practical applications for the effectiveness of TMNMT as a novel music therapy for tinnitus. The observed stronger residual inhibition (RI) ability of TMNMT supported its potential applications in tinnitus treatment. Furthermore, the temporal dynamics of EEG microstates serve as novel functional and trait markers of synchronous brain activity that contribute to a deep understanding of the neural mechanism underlying TMNMT treatment for tinnitus.
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Affiliation(s)
- Min Zhu
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Qin Gong
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
- School of Medicine, Shanghai University, Shanghai, China
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11
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Ni G, Xu Z, Bai Y, Zheng Q, Zhao R, Wu Y, Ming D. EEG-based assessment of temporal fine structure and envelope effect in mandarin syllable and tone perception. Cereb Cortex 2023; 33:11287-11299. [PMID: 37804238 DOI: 10.1093/cercor/bhad366] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2023] [Revised: 09/13/2023] [Accepted: 09/15/2023] [Indexed: 10/09/2023] Open
Abstract
In recent years, speech perception research has benefited from low-frequency rhythm entrainment tracking of the speech envelope. However, speech perception is still controversial regarding the role of speech envelope and temporal fine structure, especially in Mandarin. This study aimed to discuss the dependence of Mandarin syllables and tones perception on the speech envelope and the temporal fine structure. We recorded the electroencephalogram (EEG) of the subjects under three acoustic conditions using the sound chimerism analysis, including (i) the original speech, (ii) the speech envelope and the sinusoidal modulation, and (iii) the fine structure of time and the modulation of the non-speech (white noise) sound envelope. We found that syllable perception mainly depended on the speech envelope, while tone perception depended on the temporal fine structure. The delta bands were prominent, and the parietal and prefrontal lobes were the main activated brain areas, regardless of whether syllable or tone perception was involved. Finally, we decoded the spatiotemporal features of Mandarin perception from the microstate sequence. The spatiotemporal feature sequence of the EEG caused by speech material was found to be specific, suggesting a new perspective for the subsequent auditory brain-computer interface. These results provided a new scheme for the coding strategy of new hearing aids for native Mandarin speakers. HIGHLIGHTS
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Affiliation(s)
- Guangjian Ni
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072 China
- Tianjin Key Laboratory of Brain Science and Neuroengineering, Tianjin 300072 China
- Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration, Tianjin 300392 China
| | - Zihao Xu
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072 China
- Tianjin Key Laboratory of Brain Science and Neuroengineering, Tianjin 300072 China
| | - Yanru Bai
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072 China
- Tianjin Key Laboratory of Brain Science and Neuroengineering, Tianjin 300072 China
| | - Qi Zheng
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072 China
| | - Ran Zhao
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072 China
- Tianjin Key Laboratory of Brain Science and Neuroengineering, Tianjin 300072 China
| | - Yubo Wu
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072 China
| | - Dong Ming
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072 China
- Tianjin Key Laboratory of Brain Science and Neuroengineering, Tianjin 300072 China
- Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration, Tianjin 300392 China
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12
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Thirioux B, Langbour N, Bokam P, Renaudin L, Wassouf I, Harika-Germaneau G, Jaafari N. Microstates imbalance is associated with a functional dysregulation of the resting-state networks in obsessive-compulsive disorder: a high-density electrical neuroimaging study using the TESS method. Cereb Cortex 2023; 33:2593-2611. [PMID: 35739579 DOI: 10.1093/cercor/bhac229] [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: 04/08/2022] [Revised: 05/13/2022] [Accepted: 05/14/2022] [Indexed: 11/14/2022] Open
Abstract
The dysfunctional patterns of microstates dynamics in obsessive-compulsive disorder (OCD) remain uncertain. Using high-density electrical neuroimaging (EEG) at rest, we explored microstates deterioration in OCD and whether abnormal microstates patterns are associated with a dysregulation of the resting-state networks interplay. We used EEG microstates analyses, TESS method for sources reconstruction, and General Linear Models to test for the effect of disease severity on neural responses. OCD patients exhibited an increased contribution and decreased duration of microstates C and D, respectively. Activity was decreased in the Salience Network (SN), associated with microstate C, but increased in the Default Mode Network (DMN) and Executive Control Network (ECN), respectively, associated with microstates E and D. The hyperactivity of the right angular gyrus in the ECN correlated with the symptoms severity. The imbalance between microstates C and D invalidates the hypothesis that this electrophysiological pattern is specific to psychosis. Demonstrating that the SN-ECN dysregulation manifests as abnormalities in microstates C and D, we confirm that the SN deterioration in OCD is accompanied by a failure of the DMN to deactivate and aberrant compensatory activation mechanisms in the ECN. These abnormalities explain typical OCD clinical features but also detachment from reality, shared with psychosis.
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Affiliation(s)
- Bérangère Thirioux
- Unité de Recherche Clinique Pierre Deniker, Centre Hospitalier Henri Laborit, 86021 Poitiers, France
- CNRS 7295, Centre de Recherches sur la Cognition et l'Apprentissage, Université de Poitiers, 86021 Poitiers, France
| | - Nicolas Langbour
- Unité de Recherche Clinique Pierre Deniker, Centre Hospitalier Henri Laborit, 86021 Poitiers, France
- CNRS 7295, Centre de Recherches sur la Cognition et l'Apprentissage, Université de Poitiers, 86021 Poitiers, France
| | - Prasanth Bokam
- Unité de Recherche Clinique Pierre Deniker, Centre Hospitalier Henri Laborit, 86021 Poitiers, France
| | - Léa Renaudin
- Unité de Recherche Clinique Pierre Deniker, Centre Hospitalier Henri Laborit, 86021 Poitiers, France
| | - Issa Wassouf
- Unité de Recherche Clinique Pierre Deniker, Centre Hospitalier Henri Laborit, 86021 Poitiers, France
- CNRS 7295, Centre de Recherches sur la Cognition et l'Apprentissage, Université de Poitiers, 86021 Poitiers, France
| | - Ghina Harika-Germaneau
- Unité de Recherche Clinique Pierre Deniker, Centre Hospitalier Henri Laborit, 86021 Poitiers, France
- CNRS 7295, Centre de Recherches sur la Cognition et l'Apprentissage, Université de Poitiers, 86021 Poitiers, France
- Faculté de Médecine et de Pharmacie, Université de Poitiers, 86021 Poitiers, France
| | - Nematollah Jaafari
- Unité de Recherche Clinique Pierre Deniker, Centre Hospitalier Henri Laborit, 86021 Poitiers, France
- CNRS 7295, Centre de Recherches sur la Cognition et l'Apprentissage, Université de Poitiers, 86021 Poitiers, France
- Faculté de Médecine et de Pharmacie, Université de Poitiers, 86021 Poitiers, France
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Boyce R, Dard RF, Cossart R. Cortical neuronal assemblies coordinate with EEG microstate dynamics during resting wakefulness. Cell Rep 2023; 42:112053. [PMID: 36716148 PMCID: PMC9989822 DOI: 10.1016/j.celrep.2023.112053] [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: 06/13/2022] [Revised: 09/26/2022] [Accepted: 01/17/2023] [Indexed: 01/30/2023] Open
Abstract
The disruption of cortical assembly activity has been associated with anesthesia-induced loss of consciousness. However, the relationship between cortical assembly activity and the variations in consciousness associated with natural vigilance states remains unclear. Here, we address this by performing vigilance state-specific clustering analysis on 2-photon calcium imaging data from the sensorimotor cortex in combination with global electroencephalogram (EEG) microstate analysis derived from multi-EEG signals obtained over widespread cortical locations. We report no difference in the structure of assembly activity during quiet wakefulness (QW), non-rapid eye movement sleep (NREMs), or REMs, despite the latter two vigilance states being associated with significantly reduced levels of consciousness relative to QW. However, we describe a significant coordination between global EEG microstate dynamics and general local cortical assembly activity during periods of QW, but not sleep. These results suggest that the coordination of cortical assembly activity with global brain dynamics could be a key factor of sustained conscious experience.
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Affiliation(s)
- Richard Boyce
- INMED, INSERM, Aix Marseille University, 13273 Marseille, France.
| | - Robin F Dard
- INMED, INSERM, Aix Marseille University, 13273 Marseille, France
| | - Rosa Cossart
- INMED, INSERM, Aix Marseille University, 13273 Marseille, France
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14
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Costa TDDC, Machado CBDS, Lemos Segundo RP, Silva JPDS, Silva ACT, Andrade RDS, Rosa MRD, Smaili SM, Morya E, Costa-Ribeiro A, Lindquist ARR, Andrade SM, Machado DGDS. Are the EEG microstates correlated with motor and non-motor parameters in patients with Parkinson's disease? Neurophysiol Clin 2023; 53:102839. [PMID: 36716585 DOI: 10.1016/j.neucli.2022.102839] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 11/05/2022] [Accepted: 12/17/2022] [Indexed: 01/30/2023] Open
Abstract
OBJECTIVES This study compared electroencephalography microstates (EEG-MS) of patients with Parkinson's disease (PD) to healthy controls and correlated EEG-MS with motor and non-motor aspects of PD. METHODS This cross-sectional exploratory study was conducted with patients with PD (n = 10) and healthy controls (n = 10) matched by sex and age. We recorded EEG-MS using 32 channels during eyes-closed and eyes-open conditions and analyzed the four classic EEG-MS maps (A, B, C, D). Clinical information (e.g., disease duration, medications, levodopa equivalent daily dose), motor (Movement Disorder Society - Unified Parkinson Disease Rating Scale II and III, Timed Up and Go simple and dual-task, and Mini-Balance Evaluation Systems Test) and non-motor aspects (Mini-Mental State Exam [MMSE], verbal fluency, Hospital Anxiety and Depression Scale, and Parkinson's Disease Questionnaire-39 [PDQ-39]) were assessed in the PD group. Mann-Whitney U test was used to compare groups, and Spearman's correlation coefficient to analyze the correlations between coverage of EEG-MS and clinical aspects of PD. RESULTS The PD group showed a shorter duration of EEG-MS C in the eyes-closed condition than the control group. We observed correlations (rho = 0.64 to 0.82) between EEG-MS B, C, and D and non-motor aspects of PD (MMSE, verbal fluency, PDQ-39, and levodopa equivalent daily dose). CONCLUSION Alterations in EEG-MS and correlations between topographies and cognitive aspects, quality of life, and medication dose indicate that EEG could be used as a PD biomarker. Future studies should investigate these associations using a longitudinal design.
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Affiliation(s)
- Thaísa Dias de Carvalho Costa
- Aging and Neuroscience Laboratory, Federal University of Paraíba, João Pessoa, Brazil; Graduate Program in Cognitive and Behavioural Neuroscience, Federal University of Paraíba, João Pessoa, Brazil
| | | | | | | | | | - Rafael de Souza Andrade
- Division of Neurology, Lauro Wanderley University Hospital, Federal University of Paraíba, João Pessoa, Brazil
| | - Marine Raquel Diniz Rosa
- Graduate Program in Cognitive and Behavioural Neuroscience, Federal University of Paraíba, João Pessoa, Brazil
| | | | - Edgard Morya
- Edmond and Lily Safra International Institute of Neurosciences, Santos Dumont Institute, Natal, Brazil
| | - Adriana Costa-Ribeiro
- NeuroMove Laboratory, Department of Physiotherapy, Federal University of Paraíba, Joao Pessoa, Brazil
| | - Ana Raquel Rodrigues Lindquist
- Laboratory of Intervention and Analysis of Movement, Department of Physiotherapy, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Suellen Marinho Andrade
- Aging and Neuroscience Laboratory, Federal University of Paraíba, João Pessoa, Brazil; Graduate Program in Cognitive and Behavioural Neuroscience, Federal University of Paraíba, João Pessoa, Brazil
| | - Daniel Gomes da Silva Machado
- Research Group in Neuroscience of Human Movement (NeuroMove), Department of Physical Education, Federal University of Rio Grande do Norte, Natal, RN, Brazil.
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15
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Rochas V, Gschwind M, Nedeltchev K, Seeck M. Spike-microstates correlate with interictal epileptogenic discharges: a marker for hidden epileptic activity. Brain Commun 2023; 5:fcad124. [PMID: 37151228 PMCID: PMC10154908 DOI: 10.1093/braincomms/fcad124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 02/20/2023] [Accepted: 04/14/2023] [Indexed: 05/09/2023] Open
Abstract
Objectively estimating disease severity and treatment success is a main problem in outpatient managing of epilepsy. Self-reported seizures diaries are well-known to underestimate the actual seizure count, and repeated EEGs might not show interictal epileptiform discharges (IEDs), although patients suffer from seizures. In this prospective study, we investigate the potential of microstate analysis to monitor epilepsy patients independently of their IED count. From our databank of candidates for epilepsy surgery, we included 18 patients who underwent controlled resting EEG sessions (with eyes closed, 30 min), at around the same time of the day, during at least four days (range: 4-8 days; mean: 5). Nine patients with temporal foci, six with extratemporal foci, and three with generalized epilepsy were included. Each patient's IEDs were marked and the topographic voltage maps of the IED peaks were averaged, and an individual average spike topography (AST) was created. The AST was then backfitted to each timepoint of the whole EEG resulting in the Spike-Microstate (SMS). The presence of the SMS in the residual EEG outside of the short IEDs epochs was determined for each recording session in each patient and correlated with the occurrence of the IEDs across all recording session, as well as with the drug charge of each day. Overall, SMS was much more represented in the routine EEG than the IEDs: they were identified 262 times more often than IEDs. The SMS time coverage correlated significantly with the IED occurrence rate (rho = 0.56; P < 0.001). If only patients with focal epilepsy were considered, this correlation was even higher rho = 0.69 (P < 0.001). Drug charge per day did not correlate with SMS. In this proof-of-concept study, the time coverage of SMS correlated strongly with the occurrence rate of the IEDs, they can be retrieved in the scalp EEG at a much higher occurrence rate. We conclude that SMS, once obtained for a given patient, are a more abundant marker of hidden epileptic activity than IEDs, in particular in focal epilepsy, and can be used also in absence of IEDs. Future larger studies are needed to verify its potential as monitoring tool and to determine cut-off values when drug protection becomes imperfect.
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Affiliation(s)
- Vincent Rochas
- Correspondence to: Vincent Rochas Fundamental Neuroscience Department University of Geneva, Chemin des Mines 9 1202 Genève, Switzerland E-mail:
| | | | | | - Margitta Seeck
- EEG and Epilepsy Unit, Department of Neurology University Hospital Geneva and University of Geneva, 1201 Geneva, Switzerland
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Supakar R, Satvaya P, Chakrabarti P. A deep learning based model using RNN-LSTM for the Detection of Schizophrenia from EEG data. Comput Biol Med 2022; 151:106225. [PMID: 36306576 DOI: 10.1016/j.compbiomed.2022.106225] [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: 01/08/2022] [Revised: 09/19/2022] [Accepted: 10/15/2022] [Indexed: 12/27/2022]
Abstract
Normal life can be ensured for schizophrenic patients if diagnosed early. Electroencephalogram (EEG) carries information about the brain network connectivity which can be used to detect brain anomalies that are indicative of schizophrenia. Since deep learning is capable of automatically extracting the significant features and make classifications, the authors proposed a deep learning based model using RNN-LSTM to analyze the EEG signal data to diagnose schizophrenia. The proposed model used three dense layers on top of a 100 dimensional LSTM. EEG signal data of 45 schizophrenic patients and 39 healthy subjects were used in the study. Dimensionality reduction algorithm was used to obtain an optimal feature set and the classifier was run with both sets of data. An accuracy of 98% and 93.67% were obtained with the complete feature set and the reduced feature set respectively. The robustness of the model was evaluated using model performance measure and combined performance measure. Outcomes were compared with the outcome obtained with traditional machine learning classifiers such as Random Forest, SVM, FURIA, and AdaBoost, and the proposed model was found to perform better with the complete dataset. When compared with the result of the researchers who worked with the same set of data using either CNN or RNN, the proposed model's accuracy was either better or comparable to theirs.
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Affiliation(s)
- Rinku Supakar
- Lincoln University College, Malaysia; Dr. Sudhir Chandra Sur Institute of Technology and Sports Complex, Dumdum, West Bengal, India.
| | | | - Prasun Chakrabarti
- Provost and Institute Endowed Distinguished Senior Chair Professor, Techno India NJR Institute of Technology, Udaipur, Rajasthan, ThuDau Mot University Vietnam, India.
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17
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Event-related microstate dynamics represents working memory performance. Neuroimage 2022; 263:119669. [PMID: 36206941 DOI: 10.1016/j.neuroimage.2022.119669] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 09/30/2022] [Accepted: 10/03/2022] [Indexed: 11/21/2022] Open
Abstract
In recent years, EEG microstate analysis has attracted much attention as a tool for characterizing the spatial and temporal dynamics of large-scale electrophysiological activities in the human brain. Canonical 4 states (classes A, B, C, and D) have been widely reported, and they have been pointed out for their relationships with cognitive functions and several psychiatric disorders such as schizophrenia, in particular, through their static parameters such as average duration, occurrence, coverage, and transition probability. However, the relationships between event-related microstate changes and their related cognitive functions, as is often analyzed in event-related potentials under time-locked frameworks, is still not well understood. Furthermore, not enough attention has been paid to the relationship between microstate dynamics and static characteristics. To clarify the relationships between the static microstate parameters and dynamic microstate changes, and between the dynamics and working memory (WM) function, we first examined the temporal profiles of the microstates during the N-back task. We found significant event-related microstate dynamics that differed predominantly with WM loads, which were not clearly observed in the static parameters. Furthermore, in the 2-back condition, patterns of state transitions from class A to C in the high- and low-performance groups showed prominent differences at 50-300 ms after stimulus onset. We also confirmed that the transition patterns of the specific time periods were able to predict the performance level (low or high) in the 2-back condition at a significant level, where a specific transition between microstates, namely from class A to C with specific polarity, contributed to the prediction robustly. Taken together, our findings indicate that event-related microstate dynamics at 50-300 ms after onset may be essential for WM function. This suggests that event-related microstate dynamics can reflect more highly-refined brain functions.
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Férat V, Arns M, Deiber MP, Hasler R, Perroud N, Michel CM, Ros T. Electroencephalographic Microstates as Novel Functional Biomarkers for Adult Attention-Deficit/Hyperactivity Disorder. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2022; 7:814-823. [PMID: 34823049 DOI: 10.1016/j.bpsc.2021.11.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 11/05/2021] [Accepted: 11/06/2021] [Indexed: 05/25/2023]
Abstract
BACKGROUND Research on the electroencephalographic (EEG) signatures of attention-deficit/hyperactivity disorder (ADHD) has historically concentrated on its frequency spectrum or event-related evoked potentials. In this work, we investigate EEG microstates (MSs), an alternative framework defined by the clustering of recurring topographical patterns, as a novel approach for examining large-scale cortical dynamics in ADHD. METHODS Using k-means clustering, we studied the spatiotemporal dynamics of ADHD during the rest condition by comparing the MS segmentations between adult patients with ADHD and neurotypical control subjects across two independent datasets: the first dataset consisted of 66 patients with ADHD and 66 control subjects, and the second dataset comprised 22 patients with ADHD and 22 control subjects and was used for out-of-sample validation. RESULTS Spatially, patients with ADHD and control subjects displayed equivalent MS topographies (canonical maps), indicating the preservation of prototypical EEG generators in patients with ADHD. However, this concordance was accompanied by significant differences in temporal dynamics. At the group level, and across both datasets, ADHD diagnosis was associated with longer mean durations of a frontocentral topography (MS D), indicating that its electrocortical generator(s) could be acting as pronounced attractors of global cortical dynamics. In addition, its spatiotemporal metrics were correlated with sleep disturbance, the latter being known to have a strong relationship with ADHD. Finally, in the first (larger) dataset, we also found evidence of decreased time coverage and mean duration of a left-right diagonal topography (MS A), which inversely correlated with ADHD scores. CONCLUSIONS Overall, our study underlines the value of EEG MSs as promising functional biomarkers for ADHD, offering an additional lens through which to examine its neurophysiological mechanisms.
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Affiliation(s)
- Victor Férat
- Functional Brain Mapping Laboratory, Department of Basic Neurosciences, Campus Biotech, University of Geneva, Geneva, Switzerland.
| | - Martijn Arns
- Research Institute Brainclinics, Brainclinics Foundation, Nijmegen, The Netherlands; Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Location AMC, Amsterdam Neuroscience, Amsterdam, The Netherlands; Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Marie-Pierre Deiber
- Department of Psychiatry, Faculty of Medicine, University of Geneva, Geneva, Switzerland; Division of Psychiatric Specialties, Department of Psychiatry, University Hospitals of Geneva, Geneva, Switzerland
| | - Roland Hasler
- Division of Psychiatric Specialties, Department of Psychiatry, University Hospitals of Geneva, Geneva, Switzerland; Department of Psychiatry, Dalhousie University, Nova Scotia, Halifax, Nova Scotia, Canada
| | - Nader Perroud
- Department of Psychiatry, Faculty of Medicine, University of Geneva, Geneva, Switzerland; Division of Psychiatric Specialties, Department of Psychiatry, University Hospitals of Geneva, Geneva, Switzerland
| | - Christoph M Michel
- Functional Brain Mapping Laboratory, Department of Basic Neurosciences, Campus Biotech, University of Geneva, Geneva, Switzerland; Center for Biomedical Imaging, Lausanne, Geneva, Switzerland
| | - Tomas Ros
- Functional Brain Mapping Laboratory, Department of Basic Neurosciences, Campus Biotech, University of Geneva, Geneva, Switzerland; Division of Psychiatric Specialties, Department of Psychiatry, University Hospitals of Geneva, Geneva, Switzerland; Center for Biomedical Imaging, Lausanne, Geneva, Switzerland
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N Bissonnette J, Anderson TJ, McKearney KJ, Tibbo PG, Fisher DJ. EEG Microstates in Early Phase Psychosis: The Effects of Acute Caffeine Consumption. Clin EEG Neurosci 2022; 53:335-343. [PMID: 35257622 PMCID: PMC9174612 DOI: 10.1177/15500594221084994] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Individuals with schizophrenia use on average twice as much caffeine than the healthy population, but the underlying cortical effects of caffeine in this population are still not well understood. Using resting electroencephalography (EEG) data, we can determine recurrent configurations of the electric field potential over the cortex. These configurations, referred to as microstates, are reported to be altered in schizophrenia and can give us insight into the functional dynamics of large-scale brain networks. In the current study, we use a placebo-controlled, randomized, double-blind, repeated-measures design to examine the effects of a moderate dose of caffeine (200mg) on microstate classes A, B, C, and D in a sample of individuals within the first five years of psychosis onset compared to healthy controls. The results support the reduction of microstate class C and D, as well as the increase of microstate class A and B in schizophrenia. Further, acute caffeine administration appears to exacerbate these group differences by reducing class D, and increasing occurrences of class A and B states in the patient group only. The current results support the hypothesis of a microstate class D reduction as an endophenotypic marker for psychosis and provide the first descriptive account of how caffeine is affecting these microstate classes in an early phase psychosis sample.
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Affiliation(s)
| | - T-Jay Anderson
- 3684Mount Saint Vincent University, Halifax, Nova Scotia, Canada.,3688Dalhousie University, Halifax, Nova Scotia, Canada
| | - Katelyn J McKearney
- 3688Dalhousie University, Halifax, Nova Scotia, Canada.,3690Saint Mary's University, Halifax, Nova Scotia, Canada
| | | | - Derek J Fisher
- 3688Dalhousie University, Halifax, Nova Scotia, Canada.,3684Mount Saint Vincent University, Halifax, Nova Scotia, Canada.,3688Dalhousie University, Halifax, Nova Scotia, Canada.,3690Saint Mary's University, Halifax, Nova Scotia, Canada
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20
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Li YN, Lu W, Li J, Li MX, Fang J, Xu T, Yuan TF, Qian D, Shi HB, Yin SK. Electroencephalography Microstate Alterations in Otogenic Vertigo: A Potential Disease Marker. Front Aging Neurosci 2022; 14:914920. [PMID: 35721015 PMCID: PMC9204792 DOI: 10.3389/fnagi.2022.914920] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Accepted: 05/05/2022] [Indexed: 11/23/2022] Open
Abstract
Objectives A huge population, especially the elderly, suffers from otogenic vertigo. However, the multi-modal vestibular network changes, secondary to periphery vestibular dysfunction, have not been fully elucidated. We aim to identify potential microstate electroencephalography (EEG) signatures for otogenic vertigo in this study. Materials and Methods Patients with recurrent otogenic vertigo and age-matched healthy adults were recruited. We performed 256-channel EEG recording of all participants at resting state. Neuropsychological questionnaires and vestibular function tests were taken as a measurement of patients’ symptoms and severity. We clustered microstates into four classes (A, B, C, and D) and identified their dynamic and syntax alterations of them. These features were further fed into a support vector machine (SVM) classifier to identify microstate signatures for vertigo. Results We compared 40 patients to 45 healthy adults, finding an increase in the duration of Microstate A, and both the occurrence and time coverage of Microstate D. The coverage and occurrence of Microstate C decreased significantly, and the probabilities of non-random transitions between Microstate A and D, as well as Microstate B and C, also changed. To distinguish the patients, the SVM classifier, which is built based on these features, got a balanced accuracy of 0.79 with a sensitivity of 0.78 and a specificity of 0.8. Conclusion There are several temporal dynamic alterations of EEG microstates in patients with otogenic vertigo, especially in Microstate D, reflecting the underlying process of visual-vestibular reorganization and attention redistribution. This neurophysiological signature of microstates could be used to identify patients with vertigo in the future.
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Affiliation(s)
- Yi-Ni Li
- Department of Otorhinolaryngology Head and Neck Surgery, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University, Shanghai, China
| | - Wen Lu
- Department of Otorhinolaryngology Head and Neck Surgery, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University, Shanghai, China
| | - Jie Li
- Department of Otorhinolaryngology Head and Neck Surgery, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University, Shanghai, China
| | - Ming-Xian Li
- Department of Otorhinolaryngology Head and Neck Surgery, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University, Shanghai, China
| | - Jia Fang
- Department of Otorhinolaryngology Head and Neck Surgery, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University, Shanghai, China
| | - Tao Xu
- Department of Anesthesiology, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University, Shanghai, China
| | - Ti-Fei Yuan
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- *Correspondence: Ti-Fei Yuan,
| | - Di Qian
- Department of Otolaryngology, People’s Hospital of Longhua, Shenzhen, China
- Di Qian,
| | - Hai-Bo Shi
- Department of Otorhinolaryngology Head and Neck Surgery, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University, Shanghai, China
- Hai-Bo Shi,
| | - Shan-Kai Yin
- Department of Otorhinolaryngology Head and Neck Surgery, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University, Shanghai, China
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21
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Uncovering hidden resting state dynamics: A new perspective on auditory verbal hallucinations. Neuroimage 2022; 255:119188. [PMID: 35398281 DOI: 10.1016/j.neuroimage.2022.119188] [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: 12/01/2021] [Revised: 02/25/2022] [Accepted: 03/13/2022] [Indexed: 11/24/2022] Open
Abstract
In the absence of sensory stimulation, the brain transits between distinct functional networks. Network dynamics such as transition patterns and the time the brain stays in each network link to cognition and behavior and are subject to much investigation. Auditory verbal hallucinations (AVH), the temporally fluctuating unprovoked experience of hearing voices, are associated with aberrant resting state network activity. However, we lack a clear understanding of how different networks contribute to aberrant activity over time. An accurate characterization of latent network dynamics and their relation to neurocognitive changes necessitates methods that capture the sub-second temporal fluctuations of the networks' functional connectivity signatures. Here, we critically evaluate the assumptions and sensitivity of several approaches commonly used to assess temporal dynamics of brain connectivity states in M/EEG and fMRI research, highlighting methodological constraints and their clinical relevance to AVH. Identifying altered brain connectivity states linked to AVH can facilitate the detection of predictive disease markers and ultimately be valuable for generating individual risk profiles, differential diagnosis, targeted intervention, and treatment strategies.
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22
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Artoni F, Maillard J, Britz J, Seeber M, Lysakowski C, Bréchet L, Tramèr MR, Michel CM. EEG microstate dynamics indicate a U-shaped path to propofol-induced loss of consciousness. Neuroimage 2022; 256:119156. [PMID: 35364276 DOI: 10.1016/j.neuroimage.2022.119156] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Revised: 03/22/2022] [Accepted: 03/27/2022] [Indexed: 11/16/2022] Open
Abstract
Evidence suggests that the stream of consciousness is parsed into transient brain states manifesting themselves as discrete spatiotemporal patterns of global neuronal activity. Electroencephalographical (EEG) microstates are proposed as the neurophysiological correlates of these transiently stable brain states that last for fractions of seconds. To further understand the link between EEG microstate dynamics and consciousness, we continuously recorded high-density EEG in 23 surgical patients from their awake state to unconsciousness, induced by step-wise increasing concentrations of the intravenous anesthetic propofol. Besides the conventional parameters of microstate dynamics, we introduce a new implementation of a method to estimate the complexity of microstate sequences. The brain activity under the surgical anesthesia showed a decreased sequence complexity of the stereotypical microstates, which became sparser and longer-lasting. However, we observed an initial increase in microstates' temporal dynamics and complexity with increasing depth of sedation leading to a distinctive "U-shape" that may be linked to the paradoxical excitation induced by moderate levels of propofol. Our results support the idea that the brain is in a metastable state under normal conditions, balancing between order and chaos in order to flexibly switch from one state to another. The temporal dynamics of EEG microstates indicate changes of this critical balance between stability and transition that lead to altered states of consciousness.
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Affiliation(s)
- Fiorenzo Artoni
- Functional Brain Mapping Laboratory, Department of Basic Neurosciences, University of Geneva, Campus Biotech, Switzerland.
| | - Julien Maillard
- Division of Anesthesiology, Department of Anesthesiology, Clinical Pharmacology, Intensive Care and Emergency Medicine, Geneva University Hospitals, Geneva, Switzerland
| | - Juliane Britz
- Department of Psychology, University of Fribourg, Fribourg, Switzerland; CIBM Center for Biomedical Imaging, Lausanne, Geneva, Switzerland
| | - Martin Seeber
- Functional Brain Mapping Laboratory, Department of Basic Neurosciences, University of Geneva, Campus Biotech, Switzerland
| | - Christopher Lysakowski
- Division of Anesthesiology, Department of Anesthesiology, Clinical Pharmacology, Intensive Care and Emergency Medicine, Geneva University Hospitals, Geneva, Switzerland
| | - Lucie Bréchet
- CIBM Center for Biomedical Imaging, Lausanne, Geneva, Switzerland; Functional Brain Mapping Laboratory, Department of Basic Neurosciences, University of Geneva, Campus Biotech, Switzerland
| | - Martin R Tramèr
- Division of Anesthesiology, Department of Anesthesiology, Clinical Pharmacology, Intensive Care and Emergency Medicine, Geneva University Hospitals, Geneva, Switzerland
| | - Christoph M Michel
- Functional Brain Mapping Laboratory, Department of Basic Neurosciences, University of Geneva, Campus Biotech, Switzerland; CIBM Center for Biomedical Imaging, Lausanne, Geneva, Switzerland.
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23
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Zanin M, Güntekin B, Aktürk T, Yıldırım E, Yener G, Kiyi I, Hünerli-Gündüz D, Sequeira H, Papo D. Telling functional networks apart using ranked network features stability. Sci Rep 2022; 12:2562. [PMID: 35169227 PMCID: PMC8847658 DOI: 10.1038/s41598-022-06497-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Accepted: 01/12/2022] [Indexed: 11/09/2022] Open
Abstract
Over the past few years, it has become standard to describe brain anatomical and functional organisation in terms of complex networks, wherein single brain regions or modules and their connections are respectively identified with network nodes and the links connecting them. Often, the goal of a given study is not that of modelling brain activity but, more basically, to discriminate between experimental conditions or populations, thus to find a way to compute differences between them. This in turn involves two important aspects: defining discriminative features and quantifying differences between them. Here we show that the ranked dynamical stability of network features, from links or nodes to higher-level network properties, discriminates well between healthy brain activity and various pathological conditions. These easily computable properties, which constitute local but topographically aspecific aspects of brain activity, greatly simplify inter-network comparisons and spare the need for network pruning. Our results are discussed in terms of microstate stability. Some implications for functional brain activity are discussed.
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Affiliation(s)
- Massimiliano Zanin
- Instituto de Física Interdisciplinar y Sistemas Complejos IFISC (CSIC-UIB), Campus UIB, 07122, Palma de Mallorca, Spain.
| | - Bahar Güntekin
- Department of Biophysics, School of Medicine, Istanbul Medipol University, Istanbul, Turkey.,Health Sciences and Technology Research Institute (SABITA), Istanbul Medipol University, Istanbul, Turkey
| | - Tuba Aktürk
- Program of Electroneurophysiology, Vocational School, Istanbul Medipol University, Istanbul, Turkey
| | - Ebru Yıldırım
- Program of Electroneurophysiology, Vocational School, Istanbul Medipol University, Istanbul, Turkey
| | - Görsev Yener
- Department of Neurosciences, Health Sciences Institute, Dokuz Eylül University, Izmir, Turkey.,School of Medicine, Izmir University of Economics, Izmir, Turkey
| | - Ilayda Kiyi
- Department of Neurosciences, Health Sciences Institute, Dokuz Eylül University, Izmir, Turkey
| | - Duygu Hünerli-Gündüz
- Department of Neurosciences, Health Sciences Institute, Dokuz Eylül University, Izmir, Turkey
| | - Henrique Sequeira
- University of Lille, CNRS, UMR 9193-SCALab-Sciences Cognitives et Sciences Affectives, 59000, Lille, France
| | - David Papo
- Department of Neuroscience and Rehabilitation, Section of Physiology, University of Ferrara, Ferrara, Italy.,Fondazione Istituto Italiano di Tecnologia, Ferrara, Italy
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24
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Chang Q, Li C, Zhang J, Wang C. Dynamic brain functional network based on EEG microstate during sensory gating in schizophrenia. J Neural Eng 2022; 19. [PMID: 35130537 DOI: 10.1088/1741-2552/ac5266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 02/07/2022] [Indexed: 11/12/2022]
Abstract
OBJECTIVE Cognitive impairment is one of the core symptoms of schizophrenia, with an emphasis on dysfunctional information processing. Sensory gating deficits have consistently been reported in schizophrenia, but the underlying physiological mechanism is not well-understood. We report the discovery and characterization of P50 dynamic brain connections based on microstate analysis. APPROACH We identify five main microstates associated with the P50 response and the difference between the first and second click presentation (S1-S2-P50) in first-episode schizophrenia patients (FESZ), ultra-high-risk individuals (UHR) and healthy controls (HC). The we used the signal segments composed of consecutive time points with the same microstate label to construct brain functional networks. MAIN RESULTS The microstate with a prefrontal extreme location during the response to the S1 of P50 are statistically different in duration, occurrence and coverage among the FESZ, UHR and HC groups. In addition, a microstate with anterior-posterior orientation was found to be associated with S1-S2-P50 and its coverage was found to differ among the FESZ, UHR and HC groups. Source location of microstates showed that activated brain regions were mainly concentrated in the right temporal lobe. Furthermore, the connectivities between brain regions involved in P50 processing of HC were widely different from those of FESZ and UHR. SIGNIFICANCE Our results indicate that P50 suppression deficits in schizophrenia may be due to both aberrant baseline sensory perception and adaptation to repeated stimulus. Our findings provide new insight into the mechanisms of P50 suppression in the early stage of schizophrenia.
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Affiliation(s)
- Qi Chang
- BeiHang University School of Biological Science and Medical Engineering, Xueyuan Road 37#, Haidian district, Beijing, 100191, P.R. China, Beijing, 100191, CHINA
| | - Cancheng Li
- School of Biological and Medical Engineering , Beihang University, Xueyuan Road 37#, Haidian district, Beijing, Beijing, 100083, CHINA
| | - Jicong Zhang
- School of Biological Science and Medical Engineering, Beihang University, Xueyuan Road 37#, Haidian district, Beijing, Beijing, 100083, CHINA
| | - Chuanyue Wang
- Beijing An Ding Hospital, 5 Ankang Hutong, Dewai Avenue, Xicheng District, Beijing, Beijing, 100088, CHINA
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25
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Li X, Dong F, Zhang Y, Wang J, Wang Z, Sun Y, Zhang M, Xue T, Ren Y, Lv X, Yuan K, Yu D. Altered resting-state electroencephalography microstate characteristics in young male smokers. Front Psychiatry 2022; 13:1008007. [PMID: 36267852 PMCID: PMC9577082 DOI: 10.3389/fpsyt.2022.1008007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Accepted: 09/06/2022] [Indexed: 11/24/2022] Open
Abstract
The development of nicotine addiction was associated with the abnormalities of intrinsic functional networks during the resting state in young adult smokers. As a whole-brain imaging approach, EEG microstate analysis treated multichannel EEG recordings as a series of quasi-steady microscopic states which were related to the resting-state networks (RSNs) found by fMRI. The aim of this study was to examine whether the resting-state EEG microstate analysis may provide novel insights into the abnormal temporal properties of intrinsic brain activities in young smokers. We used 64-channel resting-state EEG datasets to investigate alterations in microstate characteristics between twenty-five young smokers and 25 age- and gender-matched non-smoking controls. Four classic EEG microstates (microstate A, B, C, and D) were obtained, and the four temporal parameters of each microstate were extracted, i.e., duration, occurrence, coverage, and transition probabilities. Compared with non-smoking controls, young smokers showed decreased occurrence of microstate C and increased duration of microstate D. Furthermore, both the duration and coverage of microstate D were significantly negatively correlated with Fagerstrom Test of Nicotine Dependence (FTND) in young smoker group. The complex changes in the microstate time-domain parameters might correspond to the abnormalities of RSNs in analyses of FC measured with fMRI in the previous studies and indicate the altered specific brain functions in young smokers. Microstate D could be potentially represented as a selective biomarker for predicting the dependence degree of adolescent smokers on cigarettes. These results suggested that EEG microstate analysis might detect the deviant functions of large-scale cortical activities in young smokers and provide a new perspective for the study of brain networks of adolescent smokers.
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Affiliation(s)
- Xiaojian Li
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Fang Dong
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Yunmiao Zhang
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Juan Wang
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Zhengxi Wang
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Yaning Sun
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Ming Zhang
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Ting Xue
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Yan Ren
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Xiaoqi Lv
- College of Information Engineering, Inner Mongolia University of Technology, Hohhot, China
| | - Kai Yuan
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China.,School of Life Sciences and Technology, Xidian University, Xi'an, Shaanxi, China
| | - Dahua Yu
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
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26
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Lin G, Wu Z, Chen B, Zhang M, Wang Q, Liu M, Zhang S, Yang M, Ning Y, Zhong X. Altered Microstate Dynamics and Spatial Complexity in Late-Life Schizophrenia. Front Psychiatry 2022; 13:907802. [PMID: 35832599 PMCID: PMC9271628 DOI: 10.3389/fpsyt.2022.907802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 06/03/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Resting-state EEG microstate and omega complexity analyses have been widely used to explore deviant brain function in various neuropsychiatric disorders. This study aimed to investigate the features of microstate dynamics and spatial complexity in patients with late-life schizophrenia (LLS). METHOD Microstate and omega complexity analyses were performed on resting-state EEG data from 39 in patients with LLS and compared with 40 elderly normal controls (NCs). RESULT The duration of microstate classes A and D were significantly higher in patients with LLS compared with NCs. The occurrence of microstate classes A, B, and C was significantly lower in patients with LLS compared with NCs. LLS patients have a lower time coverage of microstate class A and a higher time coverage of class D than NCs. Transition probabilities from microstate class A to B and from class A to C were significantly lower in patients with LLS compared with NCs. Transition probabilities between microstate class B and D were significantly higher in patients with LLS compared with NCs. Global omega complexity and anterior omega complexity were significantly higher in patients with LLS compared with NCs. CONCLUSION This study revealed an altered pattern of microstate dynamics and omega complexity in patients with LLS. This may reflect the disturbed neural basis underlying LLS and enhance the understanding of the pathophysiology of LLS.
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Affiliation(s)
- Gaohong Lin
- Center for Geriatric Neuroscience, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Zhangying Wu
- Center for Geriatric Neuroscience, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Ben Chen
- Center for Geriatric Neuroscience, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Min Zhang
- Center for Geriatric Neuroscience, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Qiang Wang
- Center for Geriatric Neuroscience, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Meiling Liu
- Center for Geriatric Neuroscience, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Si Zhang
- Center for Geriatric Neuroscience, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Mingfeng Yang
- The First School of Clinical Medicine, Southern Medical University, Guangzhou, China
| | - Yuping Ning
- Center for Geriatric Neuroscience, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China.,The First School of Clinical Medicine, Southern Medical University, Guangzhou, China.,Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
| | - Xiaomei Zhong
- Center for Geriatric Neuroscience, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
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27
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Sun Q, Zhao L, Tan L. Abnormalities of Electroencephalography Microstates in Drug-Naïve, First-Episode Schizophrenia. Front Psychiatry 2022; 13:853602. [PMID: 35360139 PMCID: PMC8964053 DOI: 10.3389/fpsyt.2022.853602] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 02/22/2022] [Indexed: 01/12/2023] Open
Abstract
OBJECTIVE Microstate analysis is a powerful tool to probe the brain functions, and changes in microstates under electroencephalography (EEG) have been repeatedly reported in patients with schizophrenia. This study aimed to investigate the dynamics of EEG microstates in drug-naïve, first-episode schizophrenia (FE-SCH) and to test the relationship between EEG microstates and clinical symptoms. METHODS Resting-state EEG were recorded for 23 patients with FE-SCH and 23 healthy controls using a 64-channel cap. Three parameters, i.e., contribution, duration, and occurrence, of the four microstate classes were calculated. Group differences in EEG microstates and their clinical symptoms [assessed using the Positive and Negative Syndrome Scale (PANSS)] were analyzed. RESULTS Compared with healthy controls, patients with FE-SCH showed increased duration, occurrence and contribution of microstate class C and decreased contribution and occurrence of microstate class D. In addition, the score of positive symptoms in PANSS was negatively correlated with the occurrence of microstate D. CONCLUSION Our findings showed abnormal patterns of EEG microstates in drug-naïve, first-episode schizophrenia, which might help distinguish individuals with schizophrenia in the early stage and develop early intervention strategies.
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Affiliation(s)
- Qiaoling Sun
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, China National Technology Institute on Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Linlin Zhao
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, China National Technology Institute on Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Liwen Tan
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, China National Technology Institute on Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
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28
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Qiu S, Wang S, Peng W, Yi W, Zhang C, Zhang J, He H. Continuous theta-burst stimulation modulates resting-state EEG microstates in healthy subjects. Cogn Neurodyn 2021; 16:621-631. [DOI: 10.1007/s11571-021-09726-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 09/03/2021] [Accepted: 09/28/2021] [Indexed: 11/24/2022] Open
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29
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Mishra A, Marzban N, Cohen MX, Englitz B. Dynamics of Neural Microstates in the VTA-Striatal-Prefrontal Loop during Novelty Exploration in the Rat. J Neurosci 2021; 41:6864-6877. [PMID: 34193560 PMCID: PMC8360694 DOI: 10.1523/jneurosci.2256-20.2021] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2020] [Revised: 05/17/2021] [Accepted: 05/21/2021] [Indexed: 11/21/2022] Open
Abstract
Neural activity at the large-scale population level has been suggested to be consistent with a sequence of brief, quasistable spatial patterns. These "microstates" and their temporal dynamics have been linked to myriad cognitive functions and brain diseases. Most of this research has been performed using EEG, leaving many questions, such as the existence, dynamics, and behavioral relevance of microstates at the level of local field potentials (LFPs), unaddressed. Here, we adapted the standard EEG microstate analysis to triple-area LFP recordings from 192 electrodes in rats to investigate the mesoscopic dynamics of neural microstates within and across brain regions during novelty exploration. We performed simultaneous recordings from the prefrontal cortex, striatum, and ventral tegmental area in male rats during awake behavior (object novelty and exploration). We found that the LFP data can be accounted for by multiple, recurring microstates that were stable for ∼60-100 ms. The simultaneous microstate activity across brain regions revealed rhythmic patterns of coactivations, which we interpret as a novel indicator of inter-regional, mesoscale synchronization. Furthermore, these rhythmic coactivation patterns across microstates were modulated by behavioral states such as movement and exploration of a novel object. These results support the existence of a functional mesoscopic organization across multiple brain areas and present a possible link of the origin of macroscopic EEG microstates to zero-lag neuronal synchronization within and between brain areas, which is of particular interest to the human research community.SIGNIFICANCE STATEMENT The coordination of neural activity across the entire brain has remained elusive. Here we combine large-scale neural recordings at fine spatial resolution with the analysis of microstates (i.e., short-lived, recurring spatial patterns of neural activity). We demonstrate that the local activity in different brain areas can be accounted for by only a few microstates per region. These microstates exhibited temporal dynamics that were correlated across regions in rhythmic patterns. We demonstrate that these microstates are linked to behavior and exhibit different properties in the frequency domain during different behavioral states. In summary, LFP microstates provide an insightful approach to studying both mesoscopic and large-scale brain activation within and across regions.
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Affiliation(s)
- Ashutosh Mishra
- Synchronisation in Neural Systems Laboratory, Department of Neuroinformatics, Donders Institute for Brain, Cognition and Behavior, Radboud University Nijmegen, 6500 HB, Nijmegen, The Netherlands
- Computational Neuroscience Laboratory, Department of Neurophysiology, Donders Institute for Brain, Cognition and Behavior, Radboud University Nijmegen, 6525 AJ, Nijmegen, The Netherlands
| | - Nader Marzban
- Synchronisation in Neural Systems Laboratory, Department of Neuroinformatics, Donders Institute for Brain, Cognition and Behavior, Radboud University Nijmegen, 6500 HB, Nijmegen, The Netherlands
| | - Michael X Cohen
- Synchronisation in Neural Systems Laboratory, Department of Neuroinformatics, Donders Institute for Brain, Cognition and Behavior, Radboud University Nijmegen, 6500 HB, Nijmegen, The Netherlands
| | - Bernhard Englitz
- Computational Neuroscience Laboratory, Department of Neurophysiology, Donders Institute for Brain, Cognition and Behavior, Radboud University Nijmegen, 6525 AJ, Nijmegen, The Netherlands
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30
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Shanker A, Abel JH, Schamberg G, Brown EN. Etiology of Burst Suppression EEG Patterns. Front Psychol 2021; 12:673529. [PMID: 34177731 PMCID: PMC8222661 DOI: 10.3389/fpsyg.2021.673529] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Accepted: 05/14/2021] [Indexed: 12/14/2022] Open
Abstract
Burst-suppression electroencephalography (EEG) patterns of electrical activity, characterized by intermittent high-power broad-spectrum oscillations alternating with isoelectricity, have long been observed in the human brain during general anesthesia, hypothermia, coma and early infantile encephalopathy. Recently, commonalities between conditions associated with burst-suppression patterns have led to new insights into the origin of burst-suppression EEG patterns, their effects on the brain, and their use as a therapeutic tool for protection against deleterious neural states. These insights have been further supported by advances in mechanistic modeling of burst suppression. In this Perspective, we review the origins of burst-suppression patterns and use recent insights to weigh evidence in the controversy regarding the extent to which burst-suppression patterns observed during profound anesthetic-induced brain inactivation are associated with adverse clinical outcomes. Whether the clinical intent is to avoid or maintain the brain in a state producing burst-suppression patterns, monitoring and controlling neural activity presents a technical challenge. We discuss recent advances that enable monitoring and control of burst suppression.
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Affiliation(s)
- Akshay Shanker
- Department of Anesthesiology, Lewis Katz School of Medicine at Temple University, Philadelphia, PA, United States
- Department of Anesthesia, Critical Care, and Pain Medicine, Beth Israel Deaconess Medical Center, Boston, MA, United States
| | - John H. Abel
- Massachusetts Institute of Technology, Picower Institute for Learning and Memory, Cambridge, MA, United States
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, United States
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, United States
| | - Gabriel Schamberg
- Massachusetts Institute of Technology, Picower Institute for Learning and Memory, Cambridge, MA, United States
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, United States
| | - Emery N. Brown
- Massachusetts Institute of Technology, Picower Institute for Learning and Memory, Cambridge, MA, United States
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, United States
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31
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Kim K, Duc NT, Choi M, Lee B. EEG microstate features for schizophrenia classification. PLoS One 2021; 16:e0251842. [PMID: 33989352 PMCID: PMC8121321 DOI: 10.1371/journal.pone.0251842] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Accepted: 05/04/2021] [Indexed: 12/11/2022] Open
Abstract
Electroencephalography (EEG) microstate analysis is a method wherein spontaneous EEG activity is segmented at sub-second levels to analyze quasi-stable states. In particular, four archetype microstates and their features are known to reflect changes in brain state in neuropsychiatric diseases. However, previous studies have only reported differences in each microstate feature and have not determined whether microstate features are suitable for schizophrenia classification. Therefore, it is necessary to validate microstate features for schizophrenia classification. Nineteen microstate features, including duration, occurrence, and coverage as well as thirty-one conventional EEG features, including statistical, frequency, and temporal characteristics were obtained from resting-state EEG recordings of 14 patients diagnosed with schizophrenia and from 14 healthy (control) subjects. Machine-learning based multivariate analysis was used to evaluate classification performance. EEG recordings of patients and controls showed different microstate features. More importantly, when differentiating among patients and controls, EEG microstate features outperformed conventional EEG ones. The performance of the microstate features exceeded that of conventional EEG, even after optimization using recursive feature elimination. EEG microstate features applied with conventional EEG features also showed better classification performance than conventional EEG features alone. The current study is the first to validate the use of microstate features to discriminate schizophrenia, suggesting that EEG microstate features are useful for schizophrenia classification.
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Affiliation(s)
- Kyungwon Kim
- Department of Biomedical Science and Engineering (BMSE), Institute Integrated Technology (IIT), Gwangju Institute of Science and Technology (GIST), Cheomdan-gwagiro, Gwangju, South Korea
- Department of Psychiatry and Biomedical Research Institute, Pusan National University Hospital, Busan, South Korea
| | - Nguyen Thanh Duc
- Department of Biomedical Science and Engineering (BMSE), Institute Integrated Technology (IIT), Gwangju Institute of Science and Technology (GIST), Cheomdan-gwagiro, Gwangju, South Korea
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Canada
- McConnel Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal, Canada
- Ludmer Centre for Neuroinformatics and Mental Health, McGill University, Montreal, Canada
| | - Min Choi
- Department of Biomedical Science and Engineering (BMSE), Institute Integrated Technology (IIT), Gwangju Institute of Science and Technology (GIST), Cheomdan-gwagiro, Gwangju, South Korea
| | - Boreom Lee
- Department of Biomedical Science and Engineering (BMSE), Institute Integrated Technology (IIT), Gwangju Institute of Science and Technology (GIST), Cheomdan-gwagiro, Gwangju, South Korea
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Resting-State EEG Microstates Parallel Age-Related Differences in Allocentric Spatial Working Memory Performance. Brain Topogr 2021; 34:442-460. [PMID: 33871737 PMCID: PMC8195770 DOI: 10.1007/s10548-021-00835-3] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2020] [Accepted: 03/30/2021] [Indexed: 11/08/2022]
Abstract
Alterations of resting-state EEG microstates have been associated with various neurological disorders and behavioral states. Interestingly, age-related differences in EEG microstate organization have also been reported, and it has been suggested that resting-state EEG activity may predict cognitive capacities in healthy individuals across the lifespan. In this exploratory study, we performed a microstate analysis of resting-state brain activity and tested allocentric spatial working memory performance in healthy adult individuals: twenty 25–30-year-olds and twenty-five 64–75-year-olds. We found a lower spatial working memory performance in older adults, as well as age-related differences in the five EEG microstate maps A, B, C, C′ and D, but especially in microstate maps C and C′. These two maps have been linked to neuronal activity in the frontal and parietal brain regions which are associated with working memory and attention, cognitive functions that have been shown to be sensitive to aging. Older adults exhibited lower global explained variance and occurrence of maps C and C′. Moreover, although there was a higher probability to transition from any map towards maps C, C′ and D in young and older adults, this probability was lower in older adults. Finally, although age-related differences in resting-state EEG microstates paralleled differences in allocentric spatial working memory performance, we found no evidence that any individual or combination of resting-state EEG microstate parameter(s) could reliably predict individual spatial working memory performance. Whether the temporal dynamics of EEG microstates may be used to assess healthy cognitive aging from resting-state brain activity requires further investigation.
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Hamilton A, Northoff G. Abnormal ERPs and Brain Dynamics Mediate Basic Self Disturbance in Schizophrenia: A Review of EEG and MEG Studies. Front Psychiatry 2021; 12:642469. [PMID: 33912085 PMCID: PMC8072007 DOI: 10.3389/fpsyt.2021.642469] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Accepted: 03/11/2021] [Indexed: 11/05/2022] Open
Abstract
Background: Interest in disordered sense of self in schizophrenia has recently re-emerged in the literature. It has been proposed that there is a basic self disturbance, underlying the diagnostic symptoms of schizophrenia, in which the person's sense of being a bounded individual continuous through time loses stability. This disturbance has been documented phenomenologically and at the level of cognitive tasks. However, the neural correlates of basic self disorder in schizophrenia are poorly understood. Methods: A search of PubMed was used to identify studies on self and schizophrenia that reported EEG or MEG data. Results: Thirty-three studies were identified, 32 using EEG and one using MEG. Their operationalizations of the self were divided into six paradigms: self-monitoring for errors, proprioception, self-other integration, self-referential processing, aberrant salience, and source monitoring. Participants with schizophrenia were less accurate on self-referential processing tasks and had slower response times across most studies. Event-related potential amplitudes differed across many early and late components, with reduced N100 suppression in source monitoring paradigms being the most replicated finding. Several studies found differences in one or more frequency band, but no coherent overall finding emerged in this area. Various other measures of brain dynamics also showed differences in single studies. Only some of the study designs were adequate to establish a causal relationship between the self and EEG or MEG measures. Conclusion: The broad range of changes suggests a global self disturbance at the neuronal level, possibly carried over from the resting state. Further studies that successfully isolate self-related effects are warranted to better understand the temporal-dynamic and spatial-topographic basis of self disorder and its relationship to basic self disturbance on the phenomenological level.
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Affiliation(s)
- Arthur Hamilton
- Department of Cognitive Science, Carleton University, Ottawa, ON, Canada
| | - Georg Northoff
- Mind, Brain Imaging and Neuroethics Unit, Institute of Mental Health Research, University of Ottawa, Ottawa, ON, Canada
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Faramarzi M, Kasten FH, Altaş G, Aleman A, Ćurčić-Blake B, Herrmann CS. Similar EEG Activity Patterns During Experimentally-Induced Auditory Illusions and Veridical Perceptions. Front Neurosci 2021; 15:602437. [PMID: 33867913 PMCID: PMC8047478 DOI: 10.3389/fnins.2021.602437] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Accepted: 03/12/2021] [Indexed: 12/31/2022] Open
Abstract
Hallucinations and illusions are two instances of perceptual experiences illustrating how perception might diverge from external sensory stimulations and be generated or altered based on internal brain states. The occurrence of these phenomena is not constrained to patient populations. Similar experiences can be elicited in healthy subjects by means of suitable experimental procedures. Studying the neural mechanisms underlying these experiences not only has the potential to expand our understanding of the brain's perceptual machinery but also of how it might get impaired. In the current study, we employed an auditory signal detection task to induce auditory illusions by presenting speech snippets at near detection threshold intensity embedded in noise. We investigated the neural correlates of auditory false perceptions by examining the EEG activity preceding the responses in speech absent (false alarm, FA) trials and comparing them to speech present (hit) trials. The results of the comparison of event-related potentials (ERPs) in the activation period vs. baseline revealed the presence of an early negativity (EN) and a late positivity (LP) similar in both hits and FAs, which were absent in misses, correct rejections (CR) and control button presses (BPs). We postulate that the EN and the LP might represent the auditory awareness negativity (AAN) and centro-parietal positivity (CPP) or P300, respectively. The event-related spectral perturbations (ERSPs) exhibited a common power enhancement in low frequencies (<4 Hz) in hits and FAs. The low-frequency power enhancement has been frequently shown to be accompanied with P300 as well as separately being a marker of perceptual awareness, referred to as slow cortical potentials (SCP). Furthermore, the comparison of hits vs. FAs showed a significantly higher LP amplitude and low frequency power in hits compared to FAs. Generally, the observed patterns in the present results resembled some of the major neural correlates associated with perceptual awareness in previous studies. Our findings provide evidence that the neural correlates associated with conscious perception, can be elicited in similar ways in both presence and absence of externally presented sensory stimuli. The present findings did not reveal any pre-stimulus alpha and beta modulations distinguishing conscious vs. unconscious perceptions.
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Affiliation(s)
- Maryam Faramarzi
- Experimental Psychology Lab, Department of Psychology, European Medical School, Cluster of Excellence “Hearing4All,” Carl von Ossietzky University, Oldenburg, Germany
- Department of Biomedical Sciences of Cells and Systems, Cognitive Neuroscience Center, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Florian H. Kasten
- Experimental Psychology Lab, Department of Psychology, European Medical School, Cluster of Excellence “Hearing4All,” Carl von Ossietzky University, Oldenburg, Germany
- Neuroimaging Unit, European Medical School, Carl von Ossietzky University, Oldenburg, Germany
| | - Gamze Altaş
- Experimental Psychology Lab, Department of Psychology, European Medical School, Cluster of Excellence “Hearing4All,” Carl von Ossietzky University, Oldenburg, Germany
| | - André Aleman
- Department of Biomedical Sciences of Cells and Systems, Cognitive Neuroscience Center, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Branislava Ćurčić-Blake
- Department of Biomedical Sciences of Cells and Systems, Cognitive Neuroscience Center, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Christoph S. Herrmann
- Experimental Psychology Lab, Department of Psychology, European Medical School, Cluster of Excellence “Hearing4All,” Carl von Ossietzky University, Oldenburg, Germany
- Neuroimaging Unit, European Medical School, Carl von Ossietzky University, Oldenburg, Germany
- Research Center Neurosensory Science, Carl von Ossietzky University, Oldenburg, Germany
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35
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Kim K, Duc NT, Choi M, Lee B. EEG microstate features according to performance on a mental arithmetic task. Sci Rep 2021; 11:343. [PMID: 33431963 PMCID: PMC7801706 DOI: 10.1038/s41598-020-79423-7] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Accepted: 11/30/2020] [Indexed: 11/16/2022] Open
Abstract
In this study, we hypothesized that task performance could be evaluated applying EEG microstate to mental arithmetic task. This pilot study also aimed at evaluating the efficacy of microstates as novel features to discriminate task performance. Thirty-six subjects were divided into good and poor performers, depending on how well they performed the task. Microstate features were derived from EEG recordings during resting and task states. In the good performers, there was a decrease in type C and an increase in type D features during the task compared to the resting state. Mean duration and occurrence decreased and increased, respectively. In the poor performers, occurrence of type D feature, mean duration and occurrence showed greater changes. We investigated whether microstate features were suitable for task performance classification and eleven features including four archetypes were selected by recursive feature elimination (RFE). The model that implemented them showed the highest classification performance for differentiating between groups. Our pilot findings showed that the highest mean Area Under Curve (AUC) was 0.831. This study is the first to apply EEG microstate features to specific cognitive tasks in healthy subjects, suggesting that EEG microstate features can reflect task achievement.
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Affiliation(s)
- Kyungwon Kim
- Department of Biomedical Science and Engineering (BMSE), Institute Integrated Technology (IIT), Gwangju Institute of Science and Technology (GIST), 123 Cheomdan-gwagiro, Buk-gu, Gwangju, 61005, South Korea
| | - Nguyen Thanh Duc
- Department of Biomedical Science and Engineering (BMSE), Institute Integrated Technology (IIT), Gwangju Institute of Science and Technology (GIST), 123 Cheomdan-gwagiro, Buk-gu, Gwangju, 61005, South Korea
| | - Min Choi
- Department of Biomedical Science and Engineering (BMSE), Institute Integrated Technology (IIT), Gwangju Institute of Science and Technology (GIST), 123 Cheomdan-gwagiro, Buk-gu, Gwangju, 61005, South Korea
| | - Boreom Lee
- Department of Biomedical Science and Engineering (BMSE), Institute Integrated Technology (IIT), Gwangju Institute of Science and Technology (GIST), 123 Cheomdan-gwagiro, Buk-gu, Gwangju, 61005, South Korea.
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36
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Wang F, Hujjaree K, Wang X. Electroencephalographic Microstates in Schizophrenia and Bipolar Disorder. Front Psychiatry 2021; 12:638722. [PMID: 33716831 PMCID: PMC7952514 DOI: 10.3389/fpsyt.2021.638722] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Accepted: 02/08/2021] [Indexed: 12/19/2022] Open
Abstract
Schizophrenia (SCH) and bipolar disorder (BD) are characterized by many types of symptoms, damaged cognitive function, and abnormal brain connections. The microstates are considered to be the cornerstones of the mental states shown in EEG data. In our study, we investigated the use of microstates as biomarkers to distinguish patients with bipolar disorder from those with schizophrenia by analyzing EEG data measured in an eyes-closed resting state. The purpose of this article is to provide an electron directional physiological explanation for the observed brain dysfunction of schizophrenia and bipolar disorder patients. Methods: We used microstate resting EEG data to explore group differences in the duration, coverage, occurrence, and transition probability of 4 microstate maps among 20 SCH patients, 26 BD patients, and 35 healthy controls (HCs). Results: Microstate analysis revealed 4 microstates (A-D) in global clustering across SCH patients, BD patients, and HCs. The samples were chosen to be matched. We found the greater presence of microstate B in BD patients, and the less presence of microstate class A and B, the greater presence of microstate class C, and less presence of D in SCH patients. Besides, a greater frequent switching between microstates A and B and between microstates B and A in BD patients than in SCH patients and HCs and less frequent switching between microstates C and D and between microstates D and C in BD patients compared with SCH patients. Conclusion: We found abnormal features of microstate A, B in BD patients and abnormal features of microstate A, B, C, and D in SCH patients. These features may indicate the potential abnormalities of SCH patients and BD patients in distributing neural resources and influencing opportune transitions between different states of activity.
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Affiliation(s)
- Fanglan Wang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Khamlesh Hujjaree
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Xiaoping Wang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
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37
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Sun Q, Zhou J, Guo H, Gou N, Lin R, Huang Y, Guo W, Wang X. EEG Microstates and Its Relationship With Clinical Symptoms in Patients With Schizophrenia. Front Psychiatry 2021; 12:761203. [PMID: 34777062 PMCID: PMC8581189 DOI: 10.3389/fpsyt.2021.761203] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Accepted: 10/08/2021] [Indexed: 12/15/2022] Open
Abstract
Schizophrenia is a complex and devastating disorder with unclear pathogenesis. Electroencephalogram (EEG) microstates have been suggested as a potential endophenotype for this disorder. However, no clear dynamic pattern of microstates has been found. This study aims to identify the dynamics of EEG microstates in schizophrenia and to test whether schizophrenia patients with altered clinical symptoms severity showed different microstates abnormalities compared with healthy controls. Resting-state EEG data in 46 individuals who met the ICD-10 diagnostic criteria for schizophrenia and 39 healthy controls was recorded. The patients with schizophrenia were divided into subgroups based on the level of their negative or positive symptoms assessed using the Positive and Negative Syndrome Scale. Microstate parameters (contribution, occurrence, and duration) of four prototypical microstate classes (A-D) were investigated. Compared with healthy controls, individuals with schizophrenia showed increased duration and contribution of microstate class C, decreased contribution and occurrence of microstate class B. Different microstate patterns were found between subgroups and healthy controls. Results in this study support the consistent observation of abnormal EEG microstates patterns in patients with schizophrenia and highlight the necessity to divide subjects into subgroups according to their clinical symptoms.
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Affiliation(s)
- Qiaoling Sun
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Jiansong Zhou
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Huijuan Guo
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Ningzhi Gou
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Ruoheng Lin
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Ying Huang
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Weilong Guo
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Xiaoping Wang
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
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38
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Faber PL, Milz P, Reininghaus EZ, Mörkl S, Holl AK, Kapfhammer HP, Pascual-Marqui RD, Kochi K, Achermann P, Painold A. Fundamentally altered global- and microstate EEG characteristics in Huntington's disease. Clin Neurophysiol 2020; 132:13-22. [PMID: 33249251 DOI: 10.1016/j.clinph.2020.10.006] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2020] [Revised: 08/25/2020] [Accepted: 10/14/2020] [Indexed: 01/14/2023]
Abstract
OBJECTIVE Huntington's disease (HD) is characterized by psychiatric, cognitive, and motor disturbances. The study aimed to determine electroencephalography (EEG) global state and microstate changes in HD and their relationship with cognitive and behavioral impairments. METHODS EEGs from 20 unmedicated HD patients and 20 controls were compared using global state properties (connectivity and dimensionality) and microstate properties (EEG microstate analysis). For four microstate classes (A, B, C, D), three parameters were computed: duration, occurrence, coverage. Global- and microstate properties were compared between groups and correlated with cognitive test scores for patients. RESULTS Global state analysis showed reduced connectivity in HD and an increasing dimensionality with increasing HD severity. Microstate analysis revealed parameter increases for classes A and B (coverage), decreases for C (occurrence) and D (coverage and occurrence). Disease severity and poorer test performances correlated with parameter increases for class A (coverage and occurrence), decreases for C (coverage and duration) and a dimensionality increase. CONCLUSIONS Global state changes may reflect higher functional dissociation between brain areas and the complex microstate changes possibly the widespread neuronal death and corresponding functional deficits in brain regions associated with HD symptomatology. SIGNIFICANCE Combining global- and microstate analyses can be useful for a better understanding of progressive brain deterioration in HD.
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Affiliation(s)
- Pascal L Faber
- The KEY Institute for Brain-Mind Research, Department of Psychiatry, Psychotherapy and Psychosomatics, University Hospital of Psychiatry, Zurich, Switzerland
| | - Patricia Milz
- The KEY Institute for Brain-Mind Research, Department of Psychiatry, Psychotherapy and Psychosomatics, University Hospital of Psychiatry, Zurich, Switzerland
| | - Eva Z Reininghaus
- Department of Psychiatry and Psychotherapy, Medical University of Graz, Graz, Austria
| | - Sabrina Mörkl
- Department of Psychiatry and Psychotherapy, Medical University of Graz, Graz, Austria
| | - Anna K Holl
- Department of Psychiatry and Psychotherapy, Medical University of Graz, Graz, Austria
| | - Hans-Peter Kapfhammer
- Department of Psychiatry and Psychotherapy, Medical University of Graz, Graz, Austria
| | - Roberto D Pascual-Marqui
- The KEY Institute for Brain-Mind Research, Department of Psychiatry, Psychotherapy and Psychosomatics, University Hospital of Psychiatry, Zurich, Switzerland
| | - Kieko Kochi
- The KEY Institute for Brain-Mind Research, Department of Psychiatry, Psychotherapy and Psychosomatics, University Hospital of Psychiatry, Zurich, Switzerland
| | - Peter Achermann
- The KEY Institute for Brain-Mind Research, Department of Psychiatry, Psychotherapy and Psychosomatics, University Hospital of Psychiatry, Zurich, Switzerland
| | - Annamaria Painold
- Department of Psychiatry and Psychotherapy, Medical University of Graz, Graz, Austria.
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Nagabhushan Kalburgi S, Whitten AP, Key AP, Bodfish JW. Children With Autism Produce a Unique Pattern of EEG Microstates During an Eyes Closed Resting-State Condition. Front Hum Neurosci 2020; 14:288. [PMID: 33132865 PMCID: PMC7579608 DOI: 10.3389/fnhum.2020.00288] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Accepted: 06/26/2020] [Indexed: 11/23/2022] Open
Abstract
Although fMRI studies have produced considerable evidence for differences in the spatial connectivity of resting-state brain networks in persons with autism spectrum disorder (ASD) relative to typically developing (TD) peers, little is known about the temporal dynamics of these brain networks in ASD. The aim of this study was to examine the EEG microstate architecture in children with ASD as compared to TD at rest in two separate conditions – eyes-closed (EC) and eyes-open (EO). EEG microstate analysis was performed on resting-state data of 13 ASD and 13 TD children matched on age, gender, and IQ. We found that children with ASD and TD peers produced topographically similar canonical microstates at rest. Group differences in the duration and frequency of these microstates were found primarily in the EC resting-state condition. In line with previous fMRI findings that have reported differences in spatial connectivity within the salience network (previously correlated with the activity of microstate C) in ASD, we found that the duration of activation of microstate C was increased, and the frequency of microstate C was decreased in ASD as compared to TD in EC resting-state. Functionally, these results may be reflective of alterations in interoceptive processes in ASD. These results suggest a unique pattern of EEG microstate architecture in ASD relative to TD during resting-states and also that EEG microstate parameters in ASD are susceptible to differences in resting-state conditions.
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Affiliation(s)
| | | | - Alexandra P Key
- Vanderbilt Kennedy Center, Nashville, TN, United States.,Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
| | - James W Bodfish
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, United States.,Vanderbilt University Medical Center, Nashville, TN, United States.,Vanderbilt Kennedy Center, Nashville, TN, United States.,Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
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40
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Pal A, Behari M, Goyal V, Sharma R. Study of EEG microstates in Parkinson's disease: a potential biomarker? Cogn Neurodyn 2020; 15:463-471. [PMID: 34040672 DOI: 10.1007/s11571-020-09643-0] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Revised: 09/23/2020] [Accepted: 10/06/2020] [Indexed: 11/30/2022] Open
Abstract
The spontaneous activity of the brain is dynamic even at rest and the deviation from this normal pattern of dynamics can lead to different pathological states. EEG microstate analysis of resting-state neuronal activity in Parkinson's disease (PD) could provide insight into altered brain dynamics of patients exhibiting dementia. Resting-state EEG microstate maps were derived from 128 channel EEG data in 20 PD without dementia (PDND), 18 PD with dementia (PDD) and 20 Healthy controls (CON) using Cartool and sLORETA softwares. Microstate map parameters including global explained variance, mean duration, frequency of occurrence (TF) and time coverage were compared statistically among the groups. Eight maps that explained 72% of the topographic variance were identified and only three maps differed significantly across the groups. TF of Map1 was lower in both PDND and PDD (p < 0.001) and that of Map3 (p = 0.02) in PDND compared to control. Cortical sources showed higher activation in precuneus, cuneus and superior parietal lobe (Threshold: Log-F = 1.74, p < 0.05) with maximum activity in the precuneus region (MNI co-ordinates: - 25, - 75, - 40; Log-F = 1.9) in PDND compared to control only for Map1. Lower TF of Map1 (prototypical microstate D) may potentially serve as a biomarker for PD with or without dementia whereas higher activation of precuneus, cuneus and superior parietal lobe at resting-state could favour signal processing, lack of which could be associated with dementia in Parkinson's disorder.
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Affiliation(s)
- Anita Pal
- Stress and Cognitive Electroimaging Laboratory, Department of Physiology, All India Institute of Medical Sciences, New Delhi, 110029 India
| | - Madhuri Behari
- Department of Neurology, All India Institute of Medical Sciences, New Delhi, 110029 India
| | - Vinay Goyal
- Department of Neurology, All India Institute of Medical Sciences, New Delhi, 110029 India
| | - Ratna Sharma
- Stress and Cognitive Electroimaging Laboratory, Department of Physiology, All India Institute of Medical Sciences, New Delhi, 110029 India
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41
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Nagabhushan Kalburgi S, Whitten AP, Key AP, Bodfish JW. Children With Autism Produce a Unique Pattern of EEG Microstates During an Eyes Closed Resting-State Condition. Front Hum Neurosci 2020; 14:288. [PMID: 33132865 DOI: 10.3389/fnhum.2020.00288/bibtex] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Accepted: 06/26/2020] [Indexed: 05/25/2023] Open
Abstract
Although fMRI studies have produced considerable evidence for differences in the spatial connectivity of resting-state brain networks in persons with autism spectrum disorder (ASD) relative to typically developing (TD) peers, little is known about the temporal dynamics of these brain networks in ASD. The aim of this study was to examine the EEG microstate architecture in children with ASD as compared to TD at rest in two separate conditions - eyes-closed (EC) and eyes-open (EO). EEG microstate analysis was performed on resting-state data of 13 ASD and 13 TD children matched on age, gender, and IQ. We found that children with ASD and TD peers produced topographically similar canonical microstates at rest. Group differences in the duration and frequency of these microstates were found primarily in the EC resting-state condition. In line with previous fMRI findings that have reported differences in spatial connectivity within the salience network (previously correlated with the activity of microstate C) in ASD, we found that the duration of activation of microstate C was increased, and the frequency of microstate C was decreased in ASD as compared to TD in EC resting-state. Functionally, these results may be reflective of alterations in interoceptive processes in ASD. These results suggest a unique pattern of EEG microstate architecture in ASD relative to TD during resting-states and also that EEG microstate parameters in ASD are susceptible to differences in resting-state conditions.
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Affiliation(s)
| | | | - Alexandra P Key
- Vanderbilt Kennedy Center, Nashville, TN, United States
- Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
| | - James W Bodfish
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, United States
- Vanderbilt University Medical Center, Nashville, TN, United States
- Vanderbilt Kennedy Center, Nashville, TN, United States
- Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
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Krylova M, Alizadeh S, Izyurov I, Teckentrup V, Chang C, van der Meer J, Erb M, Kroemer N, Koenig T, Walter M, Jamalabadi H. Evidence for modulation of EEG microstate sequence by vigilance level. Neuroimage 2020; 224:117393. [PMID: 32971266 DOI: 10.1016/j.neuroimage.2020.117393] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Revised: 09/11/2020] [Accepted: 09/16/2020] [Indexed: 12/25/2022] Open
Abstract
The momentary global functional state of the brain is reflected in its electric field configuration and cluster analytical approaches have consistently shown four configurations, referred to as EEG microstate classes A to D. Changes in microstate parameters are associated with a number of neuropsychiatric disorders, task performance, and mental state establishing their relevance for cognition. However, the common practice to use eye-closed resting state data to assess the temporal dynamics of microstate parameters might induce systematic confounds related to vigilance levels. Here, we studied the dynamics of microstate parameters in two independent data sets and showed that the parameters of microstates are strongly associated with vigilance level assessed both by EEG power analysis and fMRI global signal. We found that the duration and contribution of microstate class C, as well as transition probabilities towards microstate class C were positively associated with vigilance, whereas the sign was reversed for microstate classes A and B. Furthermore, in looking for the origins of the correspondence between microstates and vigilance level, we found Granger-causal effects of vigilance levels on microstate sequence parameters. Collectively, our findings suggest that duration and occurrence of microstates have a different origin and possibly reflect different physiological processes. Finally, our findings indicate the need for taking vigilance levels into consideration in resting-sate EEG investigations.
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Affiliation(s)
- Marina Krylova
- Department of Psychiatry and Psychotherapy, Division for Translational Psychiatry, University of Tübingen, Tübingen, Germany; Department of Psychiatry and Psychotherapy, Jena University Hospital, Philosophenweg 3, 07743 Jena, Germany
| | - Sarah Alizadeh
- Department of Psychiatry and Psychotherapy, Division for Translational Psychiatry, University of Tübingen, Tübingen, Germany
| | - Igor Izyurov
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Philosophenweg 3, 07743 Jena, Germany; Department of Psychiatry and Psychotherapy, Division for Translational Psychiatry, University of Tübingen, Tübingen, Germany
| | - Vanessa Teckentrup
- Department of Psychiatry and Psychotherapy, Division for Translational Psychiatry, University of Tübingen, Tübingen, Germany
| | - Catie Chang
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, USA
| | | | - Michael Erb
- Division of Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany
| | - Nils Kroemer
- Department of Psychiatry and Psychotherapy, Division for Translational Psychiatry, University of Tübingen, Tübingen, Germany
| | - Thomas Koenig
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Switzerland
| | - Martin Walter
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Philosophenweg 3, 07743 Jena, Germany; Department of Psychiatry and Psychotherapy, Division for Translational Psychiatry, University of Tübingen, Tübingen, Germany; Clinical Affective Neuroimaging Laboratory, Magdeburg, Germany; Leibniz Institute for Neurobiology, Magdeburg, Germany; Max Planck Institute for biological cybernetics, Tübingen, Germany.
| | - Hamidreza Jamalabadi
- Department of Psychiatry and Psychotherapy, Division for Translational Psychiatry, University of Tübingen, Tübingen, Germany.
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43
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EEG microstates as biomarker for psychosis in ultra-high-risk patients. Transl Psychiatry 2020; 10:300. [PMID: 32839449 PMCID: PMC7445239 DOI: 10.1038/s41398-020-00963-7] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2020] [Revised: 07/17/2020] [Accepted: 07/22/2020] [Indexed: 02/01/2023] Open
Abstract
Resting-state EEG microstates are brief (50-100 ms) periods, in which the spatial configuration of scalp global field power remains quasi-stable before rapidly shifting to another configuration. Changes in microstate parameters have been described in patients with psychotic disorders. These changes have also been observed in individuals with a clinical or genetic high risk, suggesting potential usefulness of EEG microstates as a biomarker for psychotic disorders. The present study aimed to investigate the potential of EEG microstates as biomarkers for psychotic disorders and future transition to psychosis in patients at ultra-high-risk (UHR). We used 19-channel clinical EEG recordings and orthogonal contrasts to compare temporal parameters of four normative microstate classes (A-D) between patients with first-episode psychosis (FEP; n = 29), UHR patients with (UHR-T; n = 20) and without (UHR-NT; n = 34) later transition to psychosis, and healthy controls (HC; n = 25). Microstate A was increased in patients (FEP & UHR-T & UHR-NT) compared to HC, suggesting an unspecific state biomarker of general psychopathology. Microstate B displayed a decrease in FEP compared to both UHR patient groups, and thus may represent a state biomarker specific to psychotic illness progression. Microstate D was significantly decreased in UHR-T compared to UHR-NT, suggesting its potential as a selective biomarker of future transition in UHR patients.
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44
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Geng H, Xu P, Sommer IE, Luo YJ, Aleman A, Ćurčić-Blake B. Abnormal dynamic resting-state brain network organization in auditory verbal hallucination. Brain Struct Funct 2020; 225:2315-2330. [PMID: 32813156 PMCID: PMC7544708 DOI: 10.1007/s00429-020-02119-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Accepted: 07/23/2020] [Indexed: 12/15/2022]
Abstract
Auditory-verbal hallucinations (AVH) are a key symptom of schizophrenia. Recent neuroimaging studies examining dynamic functional connectivity suggest that disrupted dynamic interactions between brain networks characterize complex symptoms in mental illness including schizophrenia. Studying dynamic connectivity may be especially relevant for hallucinations, given their fluctuating phenomenology. Indeed, it remains unknown whether AVH in schizophrenia are directly related to altered dynamic connectivity within and between key brain networks involved in auditory perception and language, emotion processing, and top-down control. In this study, we used dynamic connectivity approaches including sliding window and k-means to examine dynamic interactions among brain networks in schizophrenia patients with and without a recent history of AVH. Dynamic brain network analysis revealed that patients with AVH spent less time in a ‘network-antagonistic’ brain state where the default mode network (DMN) and the language network were anti-correlated, and had lower probability to switch into this brain state. Moreover, patients with AVH showed a lower connectivity within the language network and the auditory network, and lower connectivity was observed between the executive control and the language networks in certain dynamic states. Our study provides the first neuroimaging evidence of altered dynamic brain networks for understanding neural mechanisms of AVH in schizophrenia. The findings may inform and further strengthen cognitive models of AVH that aid the development of new coping strategies for patients.
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Affiliation(s)
- Haiyang Geng
- Center for Brain Disorders and Cognitive Sciences, Shenzhen University, Shenzhen, China. .,Department of Biomedical Sciences of Cells and Systems, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
| | - Pengfei Xu
- Beijing Key Laboratory of Applied Experimental Psychology, Faculty of Psychology, Beijing Normal University, Beijing, China. .,Center for Emotion and Brain, Shenzhen Institute of Neuroscience, Shenzhen, China. .,Great Bay Neuroscience and Technology Research Institute (Hong Kong), Kwun Tong, Hong Kong, China.
| | - Iris E Sommer
- Department of Biomedical Sciences of Cells and Systems, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Yue-Jia Luo
- Center for Brain Disorders and Cognitive Sciences, Shenzhen University, Shenzhen, China.,Center for Emotion and Brain, Shenzhen Institute of Neuroscience, Shenzhen, China.,Sichuan Center of Applied Psychology, Chengdu Medical College, Chengdu, China
| | - André Aleman
- Center for Brain Disorders and Cognitive Sciences, Shenzhen University, Shenzhen, China.,Department of Biomedical Sciences of Cells and Systems, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Branislava Ćurčić-Blake
- Department of Biomedical Sciences of Cells and Systems, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
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45
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Vellante F, Ferri F, Baroni G, Croce P, Migliorati D, Pettoruso M, De Berardis D, Martinotti G, Zappasodi F, Giannantonio MD. Euthymic bipolar disorder patients and EEG microstates: a neural signature of their abnormal self experience? J Affect Disord 2020; 272:326-334. [PMID: 32553374 DOI: 10.1016/j.jad.2020.03.175] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/19/2019] [Revised: 02/27/2020] [Accepted: 03/29/2020] [Indexed: 10/24/2022]
Abstract
BACKGROUND A growing number of neuroimaging studies have revealed spatial abnormalities of resting-state functional brain network activity in bipolar disorder (BD). Conversely, abnormalities of resting state temporal dynamics have been scarcely investigated so far. The aim of this study was to characterize the EEG microstates activity in BD patients with a history of manic predominant polarity. Patients were euthymic and pharmacologically stabilized. METHODS Nineteen BD patients (mean age 34.4 ± 11.0, 7 female) and 19 healthy controls (HC; mean age 38.2 ± 9.9, 7 female) were recruited. The psychometric evaluation included the Hamilton Depression Scale (HAMD), the Young Mania Rating Scale (YMRS), the Dissociative Experience Scale (DES), and the State-Trait Anxiety Inventory (STAI). Two runs of 2 minutes of EEG activity by a 128-channel system were acquired at rest and analyzed through microstate analysis. RESULTS We found a reduced presence of microstate B in BD patients compared to HC, since BD patients have a tendency to transit from the microstate B to the microstates C and D significantly more than HC. Furthermore, microstate B features were correlated with DES, state STAI and trait STAI scores. CONCLUSION The reduced presence of microstate B might be associated with episodic autobiographic memory deficit, exaggerated self-focusing and states of dissociations characteristic of BD. Strong correlations of microstate B metrics and dynamics with symptoms of dissociation and anxiety across the two groups supported this interpretation.
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Affiliation(s)
- Federica Vellante
- Department of Neuroscience, Imaging and Clinical Sciences, 'G. d'Annunzio' University of Chieti-Pescara, Italy.
| | - Francesca Ferri
- Department of Neuroscience, Imaging and Clinical Sciences, 'G. d'Annunzio' University of Chieti-Pescara, Italy
| | - Gaia Baroni
- Department of Neuroscience, Imaging and Clinical Sciences, 'G. d'Annunzio' University of Chieti-Pescara, Italy
| | - Pierpaolo Croce
- Department of Neuroscience, Imaging and Clinical Sciences, 'G. d'Annunzio' University of Chieti-Pescara, Italy
| | - Daniele Migliorati
- Department of Neuroscience, Imaging and Clinical Sciences, 'G. d'Annunzio' University of Chieti-Pescara, Italy
| | - Mauro Pettoruso
- Department of Neuroscience, Imaging and Clinical Sciences, 'G. d'Annunzio' University of Chieti-Pescara, Italy
| | - Domenico De Berardis
- Department of Neuroscience, Imaging and Clinical Sciences, 'G. d'Annunzio' University of Chieti-Pescara, Italy; Hospital "Giuseppe Mazzini", Teramo, Italy
| | - Giovanni Martinotti
- Department of Neuroscience, Imaging and Clinical Sciences, 'G. d'Annunzio' University of Chieti-Pescara, Italy
| | - Filippo Zappasodi
- Department of Neuroscience, Imaging and Clinical Sciences, 'G. d'Annunzio' University of Chieti-Pescara, Italy; Institute for Advanced Biomedical Technologies, "G. d'Annunzio" University of Chieti-Pescara, Italy
| | - Massimo Di Giannantonio
- Department of Neuroscience, Imaging and Clinical Sciences, 'G. d'Annunzio' University of Chieti-Pescara, Italy; Institute for Advanced Biomedical Technologies, "G. d'Annunzio" University of Chieti-Pescara, Italy
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46
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da Cruz JR, Favrod O, Roinishvili M, Chkonia E, Brand A, Mohr C, Figueiredo P, Herzog MH. EEG microstates are a candidate endophenotype for schizophrenia. Nat Commun 2020; 11:3089. [PMID: 32555168 PMCID: PMC7303216 DOI: 10.1038/s41467-020-16914-1] [Citation(s) in RCA: 96] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2019] [Accepted: 05/28/2020] [Indexed: 12/11/2022] Open
Abstract
Electroencephalogram microstates are recurrent scalp potential configurations that remain stable for around 90 ms. The dynamics of two of the four canonical classes of microstates, commonly labeled as C and D, have been suggested as a potential endophenotype for schizophrenia. For endophenotypes, unaffected relatives of patients must show abnormalities compared to controls. Here, we examined microstate dynamics in resting-state recordings of unaffected siblings of patients with schizophrenia, patients with schizophrenia, healthy controls, and patients with first episodes of psychosis (FEP). Patients with schizophrenia and their siblings showed increased presence of microstate class C and decreased presence of microstate class D compared to controls. No difference was found between FEP and chronic patients. Our findings suggest that the dynamics of microstate classes C and D are a candidate endophenotype for schizophrenia.
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Affiliation(s)
- Janir Ramos da Cruz
- Laboratory of Psychophysics, Brain Mind Institute, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
- Institute for Systems and Robotics-Lisbon (LARSyS) and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal.
| | - Ophélie Favrod
- Laboratory of Psychophysics, Brain Mind Institute, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Maya Roinishvili
- Laboratory of Vision Physiology, Beritashvili Centre of Experimental Biomedicine, Tbilisi, Georgia
- Institute of Cognitive Neurosciences, Free University of Tbilisi, Tbilisi, Georgia
| | - Eka Chkonia
- Institute of Cognitive Neurosciences, Free University of Tbilisi, Tbilisi, Georgia
- Department of Psychiatry, Tbilisi State Medical University, Tbilisi, Georgia
| | - Andreas Brand
- Laboratory of Psychophysics, Brain Mind Institute, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Christine Mohr
- Faculté des Sciences Sociales et Politiques, Institut de Psychologie, Bâtiment Geopolis, Lausanne, Switzerland
| | - Patrícia Figueiredo
- Institute for Systems and Robotics-Lisbon (LARSyS) and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Michael H Herzog
- Laboratory of Psychophysics, Brain Mind Institute, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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47
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Baradits M, Bitter I, Czobor P. Multivariate patterns of EEG microstate parameters and their role in the discrimination of patients with schizophrenia from healthy controls. Psychiatry Res 2020; 288:112938. [PMID: 32315875 DOI: 10.1016/j.psychres.2020.112938] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/09/2019] [Revised: 03/18/2020] [Accepted: 03/22/2020] [Indexed: 12/21/2022]
Abstract
Quasi-stable electrical fields in the EEG, called microstates carry information on the dynamics of large scale brain networks. Using machine learning techniques, we explored whether abnormalities in microstates can be used to classify patients with schizophrenia and healthy controls. We applied multivariate pattern analysis of microstate features to create a specified feature set to represent microstate characteristics. Machine learning approaches using these features for classification of patients with schizophrenia were compared with prior EEG based machine learning studies. Our microstate segmentation in both patients with schizophrenia and healthy controls yielded topographies that were similar to the normative database established earlier by Koenig et al. Our machine learning model was based on large sample size, low number of features and state-of-art K-fold cross-validation technique. The multivariate analysis revealed three patterns of correlated features, which yielded an AUC of 0.84 for the group separation (accuracy: 82.7%, sensitivity/specificity: 83.5%/85.3%). Microstate segmentation of resting state EEG results in informative features to discriminate patients with schizophrenia from healthy individuals. Moreover, alteration in microstate measures may represent disturbed activity of networks in patients with schizophrenia.
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Affiliation(s)
- Máté Baradits
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary.
| | - István Bitter
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
| | - Pál Czobor
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
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48
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Phang CR, Noman F, Hussain H, Ting CM, Ombao H. A Multi-Domain Connectome Convolutional Neural Network for Identifying Schizophrenia From EEG Connectivity Patterns. IEEE J Biomed Health Inform 2020; 24:1333-1343. [DOI: 10.1109/jbhi.2019.2941222] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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49
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EEG microstates as a continuous phenomenon. Neuroimage 2020; 208:116454. [DOI: 10.1016/j.neuroimage.2019.116454] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2019] [Revised: 10/05/2019] [Accepted: 12/06/2019] [Indexed: 11/18/2022] Open
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50
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Mackintosh AJ, Borgwardt S, Studerus E, Riecher-Rössler A, de Bock R, Andreou C. EEG Microstate Differences in Medicated vs. Medication-Naïve First-Episode Psychosis Patients. Front Psychiatry 2020; 11:600606. [PMID: 33329154 PMCID: PMC7732503 DOI: 10.3389/fpsyt.2020.600606] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2020] [Accepted: 10/30/2020] [Indexed: 12/21/2022] Open
Abstract
There has been considerable interest in the role of synchronous brain activity abnormalities in the pathophysiology of psychotic disorders and their relevance for treatment; one index of such activity are EEG resting-state microstates. These reflect electric field configurations of the brain that persist over 60-120 ms time periods. A set of quasi-stable microstates classes A, B, C, and D have been repeatedly identified across healthy participants. Changes in microstate parameters coverage, duration and occurrence have been found in medication-naïve as well as medicated patients with psychotic disorders compared to healthy controls. However, to date, only two studies have directly compared antipsychotic medication effects on EEG microstates either pre- vs. post-treatment or between medicated and unmedicated chronic schizophrenia patients. The aim of this study was therefore to directly compare EEG resting-state microstates between medicated and medication-naïve (untreated) first-episode (FEP) psychosis patients (mFEP vs. uFEP). We used 19-channel clinical EEG recordings to compare temporal parameters of four prototypical microstate classes (A-D) within an overall sample of 47 patients (mFEP n = 17; uFEP n = 30). The results demonstrated significant decreases of microstate class A and significant increases of microstate class B in mFEP compared to uFEP. No significant differences between groups were found for microstate classes C and D. Further studies are needed to replicate these results in longitudinal designs that assess antipsychotic medication effects on neural networks at the onset of the disorder and over time during illness progression. As treatment response and compliance in FEP patients are relatively low, such studies could contribute to better understand treatment outcomes and ultimately improve treatment strategies.
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Affiliation(s)
- Amatya J Mackintosh
- Division of Clinical Psychology and Epidemiology, Department of Psychology, University of Basel, Basel, Switzerland
| | - Stefan Borgwardt
- University Psychiatric Clinics (UPK) Basel, University of Basel, Basel, Switzerland.,Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck, Germany
| | - Erich Studerus
- Division of Personality and Developmental Psychology, Department of Psychology, University of Basel, Basel, Switzerland
| | | | - Renate de Bock
- Division of Clinical Psychology and Epidemiology, Department of Psychology, University of Basel, Basel, Switzerland.,University Psychiatric Clinics (UPK) Basel, University of Basel, Basel, Switzerland
| | - Christina Andreou
- Division of Clinical Psychology and Epidemiology, Department of Psychology, University of Basel, Basel, Switzerland.,Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck, Germany
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