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      Neurophysiological explorations across the spectrum of psychosis, autism, and depression, during wakefulness and sleep: protocol of a prospective case–control transdiagnostic multimodal study (DEMETER)

      research-article
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      BMC Psychiatry
      BioMed Central
      Neurophysiology, EEG microstates, Sleep, Sensorimotor integration, Speech, Virtual reality, Psychosis, Autism, Depression, Sense of self

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          Abstract

          Background

          Quantitative electroencephalography (EEG) analysis offers the opportunity to study high-level cognitive processes across psychiatric disorders. In particular, EEG microstates translate the temporal dynamics of neuronal networks throughout the brain. Their alteration may reflect transdiagnostic anomalies in neurophysiological functions that are impaired in mood, psychosis, and autism spectrum disorders, such as sensorimotor integration, speech, sleep, and sense of self. The main questions this study aims to answer are as follows: 1) Are EEG microstate anomalies associated with clinical and functional prognosis, both in resting conditions and during sleep, across psychiatric disorders? 2) Are EEG microstate anomalies associated with differences in sensorimotor integration, speech, sense of self, and sleep? 3) Can the dynamic of EEG microstates be modulated by a non-drug intervention such as light hypnosis?

          Methods

          This prospective cohort will include a population of adolescents and young adults, aged 15 to 30 years old, with ultra-high-risk of psychosis (UHR), first-episode psychosis (FEP), schizophrenia (SCZ), autism spectrum disorder (ASD), and major depressive disorder (MDD), as well as healthy controls (CTRL) ( N = 21 × 6), who will be assessed at baseline and after one year of follow-up. Participants will undergo deep phenotyping based on psychopathology, neuropsychological assessments, 64-channel EEG recordings, and biological sampling at the two timepoints. At baseline, the EEG recording will also be coupled to a sensorimotor task and a recording of the characteristics of their speech (prosody and turn-taking), a one-night polysomnography, a self-reference effect task in virtual reality (only in UHR, FEP, and CTRL). An interventional ancillary study will involve only healthy controls, in order to assess whether light hypnosis can modify the EEG microstate architecture in a direction opposite to what is seen in disease.

          Discussion

          This transdiagnostic longitudinal case–control study will provide a multimodal neurophysiological assessment of clinical dimensions (sensorimotor integration, speech, sleep, and sense of self) that are disrupted across mood, psychosis, and autism spectrum disorders. It will further test the relevance of EEG microstates as dimensional functional biomarkers.

          Trial registration

          ClinicalTrials.gov Identifier NCT06045897.

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          Most cited references90

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          Age at onset of mental disorders worldwide: large-scale meta-analysis of 192 epidemiological studies

          Promotion of good mental health, prevention, and early intervention before/at the onset of mental disorders improve outcomes. However, the range and peak ages at onset for mental disorders are not fully established. To provide robust, global epidemiological estimates of age at onset for mental disorders, we conducted a PRISMA/MOOSE-compliant systematic review with meta-analysis of birth cohort/cross-sectional/cohort studies, representative of the general population, reporting age at onset for any ICD/DSM-mental disorders, identified in PubMed/Web of Science (up to 16/05/2020) (PROSPERO:CRD42019143015). Co-primary outcomes were the proportion of individuals with onset of mental disorders before age 14, 18, 25, and peak age at onset, for any mental disorder and across International Classification of Diseases 11 diagnostic blocks. Median age at onset of specific disorders was additionally investigated. Across 192 studies (n = 708,561) included, the proportion of individuals with onset of any mental disorders before the ages of 14, 18, 25 were 34.6%, 48.4%, 62.5%, and peak age was 14.5 years (k = 14, median = 18, interquartile range (IQR) = 11–34). For diagnostic blocks, the proportion of individuals with onset of disorder before the age of 14, 18, 25 and peak age were as follows: neurodevelopmental disorders: 61.5%, 83.2%, 95.8%, 5.5 years (k = 21, median=12, IQR = 7–16), anxiety/fear-related disorders: 38.1%, 51.8%, 73.3%, 5.5 years (k = 73, median = 17, IQR = 9–25), obsessive-compulsive/related disorders: 24.6%, 45.1%, 64.0%, 14.5 years (k = 20, median = 19, IQR = 14–29), feeding/eating disorders/problems: 15.8%, 48.1%, 82.4%, 15.5 years (k = 11, median = 18, IQR = 15–23), conditions specifically associated with stress disorders: 16.9%, 27.6%, 43.1%, 15.5 years (k = 16, median = 30, IQR = 17–48), substance use disorders/addictive behaviours: 2.9%, 15.2%, 48.8%, 19.5 years (k = 58, median = 25, IQR = 20–41), schizophrenia-spectrum disorders/primary psychotic states: 3%, 12.3%, 47.8%, 20.5 years (k = 36, median = 25, IQR = 20–34), personality disorders/related traits: 1.9%, 9.6%, 47.7%, 20.5 years (k = 6, median = 25, IQR = 20–33), and mood disorders: 2.5%, 11.5%, 34.5%, 20.5 years (k = 79, median = 31, IQR = 21–46). No significant difference emerged by sex, or definition of age of onset. Median age at onset for specific mental disorders mapped on a time continuum, from phobias/separation anxiety/autism spectrum disorder/attention deficit hyperactivity disorder/social anxiety (8-13 years) to anorexia nervosa/bulimia nervosa/obsessive-compulsive/binge eating/cannabis use disorders (17-22 years), followed by schizophrenia, personality, panic and alcohol use disorders (25-27 years), and finally post-traumatic/depressive/generalized anxiety/bipolar/acute and transient psychotic disorders (30-35 years), with overlap among groups and no significant clustering. These results inform the timing of good mental health promotion/preventive/early intervention, updating the current mental health system structured around a child/adult service schism at age 18.
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            MEG and EEG data analysis with MNE-Python

            Magnetoencephalography and electroencephalography (M/EEG) measure the weak electromagnetic signals generated by neuronal activity in the brain. Using these signals to characterize and locate neural activation in the brain is a challenge that requires expertise in physics, signal processing, statistics, and numerical methods. As part of the MNE software suite, MNE-Python is an open-source software package that addresses this challenge by providing state-of-the-art algorithms implemented in Python that cover multiple methods of data preprocessing, source localization, statistical analysis, and estimation of functional connectivity between distributed brain regions. All algorithms and utility functions are implemented in a consistent manner with well-documented interfaces, enabling users to create M/EEG data analysis pipelines by writing Python scripts. Moreover, MNE-Python is tightly integrated with the core Python libraries for scientific comptutation (NumPy, SciPy) and visualization (matplotlib and Mayavi), as well as the greater neuroimaging ecosystem in Python via the Nibabel package. The code is provided under the new BSD license allowing code reuse, even in commercial products. Although MNE-Python has only been under heavy development for a couple of years, it has rapidly evolved with expanded analysis capabilities and pedagogical tutorials because multiple labs have collaborated during code development to help share best practices. MNE-Python also gives easy access to preprocessed datasets, helping users to get started quickly and facilitating reproducibility of methods by other researchers. Full documentation, including dozens of examples, is available at http://martinos.org/mne.
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              Abnormal neural oscillations and synchrony in schizophrenia.

              Converging evidence from electrophysiological, physiological and anatomical studies suggests that abnormalities in the synchronized oscillatory activity of neurons may have a central role in the pathophysiology of schizophrenia. Neural oscillations are a fundamental mechanism for the establishment of precise temporal relationships between neuronal responses that are in turn relevant for memory, perception and consciousness. In patients with schizophrenia, the synchronization of beta- and gamma-band activity is abnormal, suggesting a crucial role for dysfunctional oscillations in the generation of the cognitive deficits and other symptoms of the disorder. Dysfunctional oscillations may arise owing to anomalies in the brain's rhythm-generating networks of GABA (gamma-aminobutyric acid) interneurons and in cortico-cortical connections.
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                Author and article information

                Contributors
                anton.iftimovici@ghu-paris.fr
                Journal
                BMC Psychiatry
                BMC Psychiatry
                BMC Psychiatry
                BioMed Central (London )
                1471-244X
                21 November 2023
                21 November 2023
                2023
                : 23
                : 860
                Affiliations
                [1 ]GRID grid.512035.0, Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, Team “Pathophysiology of psychiatric disorders”, GDR 3557-Institut de Psychiatrie, ; 102-108 Rue de la Santé, Paris, 75014 France
                [2 ]GHU Paris Psychiatrie et Neurosciences, Pôle Hospitalo-Universitaire d’évaluation, Prévention, et Innovation Thérapeutique (PEPIT), ( https://ror.org/040pk9f39) Paris, France
                [3 ]GRID grid.512035.0, Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, Team “Stroke: from prognostic determinants and translational research to personalized interventions”, ; Paris, 75014 France
                [4 ]Laboratoire Mémoire, Cerveau et Cognition, UR7536, Université Paris Cité, ( https://ror.org/05f82e368) Boulogne-Billancourt, F-92100 France
                [5 ]GRID grid.411394.a, ISNI 0000 0001 2191 1995, Centre du Sommeil et de la Vigilance, , AP-HP, Hôtel-Dieu, ; Paris, France
                [6 ]Collège International de Thérapies d’orientation de l’Attention et de la Conscience (CITAC), Paris, France
                [7 ]Service de Neurophysiologie Clinique, GHU Paris Psychiatrie et Neurosciences, ( https://ror.org/040pk9f39) Paris, France
                [8 ]GRID grid.411266.6, ISNI 0000 0001 0404 1115, Epileptology and Cerebral Rhythmology, , APHM, Timone Hospital, ; Marseille, France
                [9 ]GRID grid.460789.4, ISNI 0000 0004 4910 6535, Department of Child and Adolescent Psychiatry, Fondation Vallee, UNIACT Neurospin CEA - INSERM UMR 1129, , Universite Paris Saclay, ; Gentilly, France
                [10 ]IfL-Phonetics, University of Cologne, ( https://ror.org/00rcxh774) Cologne, Germany
                [11 ]INCC UMR 8002, CNRS, Université Paris Cité, ( https://ror.org/05f82e368) Paris, F-75006 France
                [12 ]Inserm, INRAE, Center for Research in Epidemiology and StatisticS (CRESS), Service de Psychiatrie de l’adulte, AP-HP, Hôpital Hôtel-Dieu, Université Paris Cité and Université Sorbonne Paris Nord, ( https://ror.org/02vjkv261) Paris, France
                [13 ]VIFASOM, ERC 7330, Université Paris Cité, ( https://ror.org/05f82e368) Paris, France
                Article
                5347
                10.1186/s12888-023-05347-x
                10662684
                59c7c259-d0b2-4b7e-b9fb-ac301ae65559
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 31 October 2023
                : 3 November 2023
                Funding
                Funded by: Fondation FondaMental - Fondation Bettencourt-Schueller
                Award ID: "Young Talents in Psychiatry 2021"
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001665, Agence Nationale de la Recherche;
                Award ID: ANR-18-RHUS-0014, "PsyCARE"
                Award Recipient :
                Funded by: GHU Paris Psychiatrie et Neurosciences
                Award ID: GHU-Starting-Grant
                Award Recipient :
                Categories
                Study Protocol
                Custom metadata
                © BioMed Central Ltd., part of Springer Nature 2023

                Clinical Psychology & Psychiatry
                neurophysiology,eeg microstates,sleep,sensorimotor integration,speech,virtual reality,psychosis,autism,depression,sense of self

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