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Unveiling the Associations between EEG Indices and Cognitive Deficits in Schizophrenia-Spectrum Disorders: A Systematic Review

Cognitive dysfunctions represent a core feature of schizophrenia-spectrum disorders due to their presence throughout different illness stages and their impact on functioning. Abnormalities in electrophysiology (EEG) measures are highly related to these impairments, but the use of EEG indices in clin...

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Autores principales: Perrottelli, Andrea, Giordano, Giulia Maria, Brando, Francesco, Giuliani, Luigi, Pezzella, Pasquale, Mucci, Armida, Galderisi, Silvana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9498272/
https://www.ncbi.nlm.nih.gov/pubmed/36140594
http://dx.doi.org/10.3390/diagnostics12092193
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author Perrottelli, Andrea
Giordano, Giulia Maria
Brando, Francesco
Giuliani, Luigi
Pezzella, Pasquale
Mucci, Armida
Galderisi, Silvana
author_facet Perrottelli, Andrea
Giordano, Giulia Maria
Brando, Francesco
Giuliani, Luigi
Pezzella, Pasquale
Mucci, Armida
Galderisi, Silvana
author_sort Perrottelli, Andrea
collection PubMed
description Cognitive dysfunctions represent a core feature of schizophrenia-spectrum disorders due to their presence throughout different illness stages and their impact on functioning. Abnormalities in electrophysiology (EEG) measures are highly related to these impairments, but the use of EEG indices in clinical practice is still limited. A systematic review of articles using Pubmed, Scopus and PsychINFO was undertaken in November 2021 to provide an overview of the relationships between EEG indices and cognitive impairment in schizophrenia-spectrum disorders. Out of 2433 screened records, 135 studies were included in a qualitative review. Although the results were heterogeneous, some significant correlations were identified. In particular, abnormalities in alpha, theta and gamma activity, as well as in MMN and P300, were associated with impairments in cognitive domains such as attention, working memory, visual and verbal learning and executive functioning during at-risk mental states, early and chronic stages of schizophrenia-spectrum disorders. The review suggests that machine learning approaches together with a careful selection of validated EEG and cognitive indices and characterization of clinical phenotypes might contribute to increase the use of EEG-based measures in clinical settings.
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spelling pubmed-94982722022-09-23 Unveiling the Associations between EEG Indices and Cognitive Deficits in Schizophrenia-Spectrum Disorders: A Systematic Review Perrottelli, Andrea Giordano, Giulia Maria Brando, Francesco Giuliani, Luigi Pezzella, Pasquale Mucci, Armida Galderisi, Silvana Diagnostics (Basel) Systematic Review Cognitive dysfunctions represent a core feature of schizophrenia-spectrum disorders due to their presence throughout different illness stages and their impact on functioning. Abnormalities in electrophysiology (EEG) measures are highly related to these impairments, but the use of EEG indices in clinical practice is still limited. A systematic review of articles using Pubmed, Scopus and PsychINFO was undertaken in November 2021 to provide an overview of the relationships between EEG indices and cognitive impairment in schizophrenia-spectrum disorders. Out of 2433 screened records, 135 studies were included in a qualitative review. Although the results were heterogeneous, some significant correlations were identified. In particular, abnormalities in alpha, theta and gamma activity, as well as in MMN and P300, were associated with impairments in cognitive domains such as attention, working memory, visual and verbal learning and executive functioning during at-risk mental states, early and chronic stages of schizophrenia-spectrum disorders. The review suggests that machine learning approaches together with a careful selection of validated EEG and cognitive indices and characterization of clinical phenotypes might contribute to increase the use of EEG-based measures in clinical settings. MDPI 2022-09-09 /pmc/articles/PMC9498272/ /pubmed/36140594 http://dx.doi.org/10.3390/diagnostics12092193 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Systematic Review
Perrottelli, Andrea
Giordano, Giulia Maria
Brando, Francesco
Giuliani, Luigi
Pezzella, Pasquale
Mucci, Armida
Galderisi, Silvana
Unveiling the Associations between EEG Indices and Cognitive Deficits in Schizophrenia-Spectrum Disorders: A Systematic Review
title Unveiling the Associations between EEG Indices and Cognitive Deficits in Schizophrenia-Spectrum Disorders: A Systematic Review
title_full Unveiling the Associations between EEG Indices and Cognitive Deficits in Schizophrenia-Spectrum Disorders: A Systematic Review
title_fullStr Unveiling the Associations between EEG Indices and Cognitive Deficits in Schizophrenia-Spectrum Disorders: A Systematic Review
title_full_unstemmed Unveiling the Associations between EEG Indices and Cognitive Deficits in Schizophrenia-Spectrum Disorders: A Systematic Review
title_short Unveiling the Associations between EEG Indices and Cognitive Deficits in Schizophrenia-Spectrum Disorders: A Systematic Review
title_sort unveiling the associations between eeg indices and cognitive deficits in schizophrenia-spectrum disorders: a systematic review
topic Systematic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9498272/
https://www.ncbi.nlm.nih.gov/pubmed/36140594
http://dx.doi.org/10.3390/diagnostics12092193
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