[en] Objective.Schizophrenia is a psychiatric disorder that has been shown to disturb the dynamic top-down processing of sensory information. Various imaging techniques have revealed abnormalities in brain activity associated with this disorder, both locally and between cerebral regions. However, there is increasing interest in investigating dynamic network response to novel and relevant events at the network level during an attention-demanding task with high-temporal-resolution techniques. The aim of the work was: (i) to test the capacity of a novel algorithm to detect recurrent brain meta-states from auditory oddball task recordings; and (ii) to evaluate how the dynamic activation and behavior of the aforementioned meta-states were altered in schizophrenia, since it has been shown to impair top-down processing of sensory information.Approach.A novel unsupervised method for the detection of brain meta-states based on recurrence plots and community detection algorithms, previously tested on resting-state data, was used on auditory oddball task recordings. Brain meta-states and several properties related to their activation during target trials in the task were extracted from electroencephalography data from patients with schizophrenia and cognitively healthy controls.Main results.The methodology successfully detected meta-states during an auditory oddball task, and they appeared to show both frequency-dependent time-locked and non-time-locked activity with respect to the stimulus onset. Moreover, patients with schizophrenia displayed higher network diversity, and showed more sluggish meta-state transitions, reflected in increased dwell times, less complex meta-state sequences, decreased meta-state space speed, and abnormal ratio of negative meta-state correlations.Significance.Abnormal cognition in schizophrenia is also reflected in decreased brain flexibility at the dynamic network level, which may hamper top-down processing, possibly indicating impaired decision-making linked to dysfunctional predictive coding. Moreover, the results showed the ability of the methodology to find meaningful and task-relevant changes in dynamic connectivity and pathology-related group differences.
Disciplines :
Neurology
Author, co-author :
Nunez Novo, Pablo ; Biomedical Engineering Group, Universidad de Valladolid, Valladolid, Spain
Gómez, Carlos ; Biomedical Engineering Group, Universidad de Valladolid, Valladolid, Spain ; Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Madrid, Spain
Rodríguez-González, Víctor ; Biomedical Engineering Group, Universidad de Valladolid, Valladolid, Spain
Hillebrand, Arjan ; Department of Clinical Neurophysiology and MEG Center, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
Tewarie, Prejaas ; Department of Clinical Neurophysiology and MEG Center, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
Gomez-Pilar, Javier ; Biomedical Engineering Group, Universidad de Valladolid, Valladolid, Spain ; Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Madrid, Spain
Molina, Vicente ; Department of Psychiatry, School of Medicine, University of Valladolid, Valladolid, Spain ; Psychiatry Service, Clinical Hospital of Valladolid, Valladolid, Spain ; Neurosciences Institute of Castilla y León (INCYL), University of Salamanca, Salamanca, Spain
Hornero, Roberto ; Biomedical Engineering Group, Universidad de Valladolid, Valladolid, Spain ; Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Madrid, Spain ; IMUVA, Instituto de Investigación en Matemáticas, University of Valladolid, Valladolid, Spain
Poza, Jesús ; Biomedical Engineering Group, Universidad de Valladolid, Valladolid, Spain ; Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Madrid, Spain ; IMUVA, Instituto de Investigación en Matemáticas, University of Valladolid, Valladolid, Spain
Language :
English
Title :
Schizophrenia induces abnormal frequency-dependent patterns of dynamic brain network reconfiguration during an auditory oddball task.
ERDF - European Regional Development Fund MICINN - Ministerio de Ciencia e Innovacion EC - European Commission UVA - Universidad de Valladolid
Funding text :
This research was supported by ‘Ministerio de Ciencia e Innovación—Agencia Estatal de Investigación’ and ‘European Regional Development Fund’ (FEDER) and ‘Ministerio de Ciencia, Innovación y Universidades’ under Project PGC2018-098214-A-I00, the ‘European Commission’ and FEDER under project ‘Análisis y correlación entre la epigenética y la actividad cerebral para evaluar el riesgo de migraña crónica y episódica en mujeres’ (‘Cooperation Programme Interreg V-A Spain-Portugal POCTEP 2014–2020’), and by CIBER-BBN (ISCIII) co-funded with FEDER funds. P Núñez was in receipt of a predoctoral scholarship ‘Ayuda para contratos predoctorales para la Formación de Profesorado Universitario (FPU)’ grant from the ‘Ministerio de Educación, Cultura y Deporte’ (FPU17/00850). V Rodríguez-González was in receipt of a PIF-UVa grant from the ‘University of Valladolid’.
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