EEG Multiscale Complexity in Schizophrenia During Picture Naming

Introduction: Patients with schizophrenia show cognitive deficits that are evident both behaviourally and with EEG recordings. Recent studies have suggested that non-linear analyses of EEG might more adequately reflect the complex, irregular, non-stationary behavior of neural processes than more tra...

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Main Authors: Antonio J. Ibáñez-Molina, Vanessa Lozano, María. F. Soriano, José. I. Aznarte, Carlos J. Gómez-Ariza, M. T. Bajo
Format: Article
Language:English
Published: Frontiers Media S.A. 2018-09-01
Series:Frontiers in Physiology
Subjects:
EEG
Online Access:https://www.frontiersin.org/article/10.3389/fphys.2018.01213/full
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spelling doaj-459f480e249440c998beac22562b08d22020-11-24T20:52:22ZengFrontiers Media S.A.Frontiers in Physiology1664-042X2018-09-01910.3389/fphys.2018.01213401044EEG Multiscale Complexity in Schizophrenia During Picture NamingAntonio J. Ibáñez-Molina0Vanessa Lozano1María. F. Soriano2José. I. Aznarte3Carlos J. Gómez-Ariza4M. T. Bajo5Department of Psychology, University of Jaén, Jaén, SpainDepartment of Experimental Psychology, University of Granada, Granada, SpainHospital San Agustín, Jaén, SpainHospital San Agustín, Jaén, SpainDepartment of Psychology, University of Jaén, Jaén, SpainDepartment of Experimental Psychology, University of Granada, Granada, SpainIntroduction: Patients with schizophrenia show cognitive deficits that are evident both behaviourally and with EEG recordings. Recent studies have suggested that non-linear analyses of EEG might more adequately reflect the complex, irregular, non-stationary behavior of neural processes than more traditional ERP measures. Non-linear analyses have been mainly applied to EEGs from patients at rest, whereas differences in complexity might be more evident during task performance.Objective: We aimed to investigate changes in non-linear brain dynamics of patients with schizophrenia during cognitive processing.Method: 18 patients and 17 matched healthy controls were asked to name pictures. EEG data were collected at rest and while they were performing a naming task. EEGs were analyzed with the classical Lempel-Ziv Complexity (LZC) and with the Multiscale LZC. Electrodes were grouped in seven regions of interest (ROI).Results: As expected, controls had fewer naming errors than patients. Regarding EEG complexity, the interaction between Group, Task and ROI indicated that patients showed higher complexity values in right frontal regions only at rest, where no differences in complexity between patients and controls were found during the naming task. EEG complexity increased from rest to task in controls in left temporal-parietal regions, while no changes from rest to task were observed in patients. Finally, differences in complexity between patients and controls depended on the frequency bands: higher values of complexity in patients at rest were only observed in fast bands, indicating greater heterogeneity in patients in local dynamics of neuronal assemblies.Conclusion: Consistent with previous studies, schizophrenic patients showed higher complexity than controls in frontal regions at rest. Interestingly, we found different modulations of brain complexity during a simple cognitive task between patients and controls. These data can be interpreted as indicating schizophrenia-related failures to adapt brain functioning to the task, which is reflected in poorer behavioral performance.Highlights:    - We measured classical and multiscale Lempel-Ziv Complexity (LZCN and MLZC) of the EEG signal of patients with schizophrenia and controls at rest and while performing a cognitive task.    - We found that patients and controls showed a different pattern of brain complexity depending on their cognitive state (at rest or under cognitive challenge).    - Our results illustrate the value of the MLZC in the characterization of the pattern of brain complexity in schizophrenia on function of frequency bands.    - Nonlinear methodologies of EEG analysis can help to characterize brain dysfunction in schizophrenia.https://www.frontiersin.org/article/10.3389/fphys.2018.01213/fullschizophreniaEEGnon-linear analysismultiscale lempel-ziv complexitynaming task
collection DOAJ
language English
format Article
sources DOAJ
author Antonio J. Ibáñez-Molina
Vanessa Lozano
María. F. Soriano
José. I. Aznarte
Carlos J. Gómez-Ariza
M. T. Bajo
spellingShingle Antonio J. Ibáñez-Molina
Vanessa Lozano
María. F. Soriano
José. I. Aznarte
Carlos J. Gómez-Ariza
M. T. Bajo
EEG Multiscale Complexity in Schizophrenia During Picture Naming
Frontiers in Physiology
schizophrenia
EEG
non-linear analysis
multiscale lempel-ziv complexity
naming task
author_facet Antonio J. Ibáñez-Molina
Vanessa Lozano
María. F. Soriano
José. I. Aznarte
Carlos J. Gómez-Ariza
M. T. Bajo
author_sort Antonio J. Ibáñez-Molina
title EEG Multiscale Complexity in Schizophrenia During Picture Naming
title_short EEG Multiscale Complexity in Schizophrenia During Picture Naming
title_full EEG Multiscale Complexity in Schizophrenia During Picture Naming
title_fullStr EEG Multiscale Complexity in Schizophrenia During Picture Naming
title_full_unstemmed EEG Multiscale Complexity in Schizophrenia During Picture Naming
title_sort eeg multiscale complexity in schizophrenia during picture naming
publisher Frontiers Media S.A.
series Frontiers in Physiology
issn 1664-042X
publishDate 2018-09-01
description Introduction: Patients with schizophrenia show cognitive deficits that are evident both behaviourally and with EEG recordings. Recent studies have suggested that non-linear analyses of EEG might more adequately reflect the complex, irregular, non-stationary behavior of neural processes than more traditional ERP measures. Non-linear analyses have been mainly applied to EEGs from patients at rest, whereas differences in complexity might be more evident during task performance.Objective: We aimed to investigate changes in non-linear brain dynamics of patients with schizophrenia during cognitive processing.Method: 18 patients and 17 matched healthy controls were asked to name pictures. EEG data were collected at rest and while they were performing a naming task. EEGs were analyzed with the classical Lempel-Ziv Complexity (LZC) and with the Multiscale LZC. Electrodes were grouped in seven regions of interest (ROI).Results: As expected, controls had fewer naming errors than patients. Regarding EEG complexity, the interaction between Group, Task and ROI indicated that patients showed higher complexity values in right frontal regions only at rest, where no differences in complexity between patients and controls were found during the naming task. EEG complexity increased from rest to task in controls in left temporal-parietal regions, while no changes from rest to task were observed in patients. Finally, differences in complexity between patients and controls depended on the frequency bands: higher values of complexity in patients at rest were only observed in fast bands, indicating greater heterogeneity in patients in local dynamics of neuronal assemblies.Conclusion: Consistent with previous studies, schizophrenic patients showed higher complexity than controls in frontal regions at rest. Interestingly, we found different modulations of brain complexity during a simple cognitive task between patients and controls. These data can be interpreted as indicating schizophrenia-related failures to adapt brain functioning to the task, which is reflected in poorer behavioral performance.Highlights:    - We measured classical and multiscale Lempel-Ziv Complexity (LZCN and MLZC) of the EEG signal of patients with schizophrenia and controls at rest and while performing a cognitive task.    - We found that patients and controls showed a different pattern of brain complexity depending on their cognitive state (at rest or under cognitive challenge).    - Our results illustrate the value of the MLZC in the characterization of the pattern of brain complexity in schizophrenia on function of frequency bands.    - Nonlinear methodologies of EEG analysis can help to characterize brain dysfunction in schizophrenia.
topic schizophrenia
EEG
non-linear analysis
multiscale lempel-ziv complexity
naming task
url https://www.frontiersin.org/article/10.3389/fphys.2018.01213/full
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