EEG Microstate Dynamics during Different Physiological Developmental Stages and the Effects of Medication in Schizophrenia
Background: Schizophrenia (SCZ) is associated with abnormal neural activities and brain connectivity. Electroencephalography (EEG) microstate is a voltage topographical representation of temporary brain network activations. Most research on EEG microstates in SCZ has focused on di...
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IMR Press
2025-03-01
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| Series: | Journal of Integrative Neuroscience |
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| Online Access: | https://www.imrpress.com/journal/JIN/24/3/10.31083/JIN27059 |
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| author | Shihai Ling Lingyan Du Xi Tan Guozhi Tang Yue Che Shirui Song |
| author_facet | Shihai Ling Lingyan Du Xi Tan Guozhi Tang Yue Che Shirui Song |
| author_sort | Shihai Ling |
| collection | DOAJ |
| description | Background: Schizophrenia (SCZ) is associated with abnormal neural activities and brain connectivity. Electroencephalography (EEG) microstate is a voltage topographical representation of temporary brain network activations. Most research on EEG microstates in SCZ has focused on differences between patients and healthy controls (HC). However, changes in EEG microstates among SCZ patients across various stages of physiological and cognitive development have not been thoroughly assessed. Consequently, we stratified patients with SCZ into four age-specific cohorts (20–29 years (brain maturation), 30–39 years (stabilization), 40–49 years (early aging), and 50–59 years (advanced aging)) to evaluate EEG microstate alterations. Additionally, we assessed changes in EEG microstates in first-episode psychosis (FEP) before and after an 8-week treatment period. Methods: We acquired 19-channel resting-state EEG from 140 chronic SCZ patients, aged 20 to 59 years, as well as from 19 FEP and 20 healthy controls. FEP patients underwent an 8-week inpatient follow-up. After pre-processing, EEG data from different groups were subjected to microstate analysis, and the K-Means clustering algorithm was applied to classify the data into 4 microstates. Subsequently, templates of these microstates were used to fit EEG signals from each patient, and the collected microstate parameters were analyzed. Results: Patients with SCZ aged 20 to 29 years demonstrated an increased time coverage of microstate class D compared to other age cohorts. In individuals aged 30–39 years, the parameters of microstate class B—specifically time coverage and occurrence—exhibited significant reductions relative to those in the 40–49 and 50–59 years age groups. Compared to healthy controls, microstates class A parameters were significantly reduced in SCZ patients, while microstates class C parameters were prolonged; after 8 weeks of treatment, microstates class A parameters increased and microstates class C parameters decreased. Conclusions: Alterations in microstate dynamics were observed among SCZ patients across developmental stages, suggesting potential changes in brain activity patterns. Changes in microstates A and C may serve as potential biomarkers for evaluating treatment efficacy, establishing a foundation for personalized therapeutic approaches. |
| format | Article |
| id | doaj-art-8600a6ec6e854f94a7ed09666d290a3d |
| institution | Kabale University |
| issn | 0219-6352 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | IMR Press |
| record_format | Article |
| series | Journal of Integrative Neuroscience |
| spelling | doaj-art-8600a6ec6e854f94a7ed09666d290a3d2025-08-20T03:42:23ZengIMR PressJournal of Integrative Neuroscience0219-63522025-03-012432705910.31083/JIN27059S0219-6352(24)00900-8EEG Microstate Dynamics during Different Physiological Developmental Stages and the Effects of Medication in SchizophreniaShihai Ling0Lingyan Du1Xi Tan2Guozhi Tang3Yue Che4Shirui Song5School of Automation and Information Engineering, Sichuan University of Science and Engineering, 643002 Zigong, Sichuan, ChinaSchool of Automation and Information Engineering, Sichuan University of Science and Engineering, 643002 Zigong, Sichuan, ChinaZigong Institute of Brain Science, Zigong Mental Health Center, The Zigong Affiliated Hospital of Southwest Medical University, 643020 Zigong, Sichuan, ChinaSchool of Automation and Information Engineering, Sichuan University of Science and Engineering, 643002 Zigong, Sichuan, ChinaSchool of Automation and Information Engineering, Sichuan University of Science and Engineering, 643002 Zigong, Sichuan, ChinaSchool of Automation and Information Engineering, Sichuan University of Science and Engineering, 643002 Zigong, Sichuan, ChinaBackground: Schizophrenia (SCZ) is associated with abnormal neural activities and brain connectivity. Electroencephalography (EEG) microstate is a voltage topographical representation of temporary brain network activations. Most research on EEG microstates in SCZ has focused on differences between patients and healthy controls (HC). However, changes in EEG microstates among SCZ patients across various stages of physiological and cognitive development have not been thoroughly assessed. Consequently, we stratified patients with SCZ into four age-specific cohorts (20–29 years (brain maturation), 30–39 years (stabilization), 40–49 years (early aging), and 50–59 years (advanced aging)) to evaluate EEG microstate alterations. Additionally, we assessed changes in EEG microstates in first-episode psychosis (FEP) before and after an 8-week treatment period. Methods: We acquired 19-channel resting-state EEG from 140 chronic SCZ patients, aged 20 to 59 years, as well as from 19 FEP and 20 healthy controls. FEP patients underwent an 8-week inpatient follow-up. After pre-processing, EEG data from different groups were subjected to microstate analysis, and the K-Means clustering algorithm was applied to classify the data into 4 microstates. Subsequently, templates of these microstates were used to fit EEG signals from each patient, and the collected microstate parameters were analyzed. Results: Patients with SCZ aged 20 to 29 years demonstrated an increased time coverage of microstate class D compared to other age cohorts. In individuals aged 30–39 years, the parameters of microstate class B—specifically time coverage and occurrence—exhibited significant reductions relative to those in the 40–49 and 50–59 years age groups. Compared to healthy controls, microstates class A parameters were significantly reduced in SCZ patients, while microstates class C parameters were prolonged; after 8 weeks of treatment, microstates class A parameters increased and microstates class C parameters decreased. Conclusions: Alterations in microstate dynamics were observed among SCZ patients across developmental stages, suggesting potential changes in brain activity patterns. Changes in microstates A and C may serve as potential biomarkers for evaluating treatment efficacy, establishing a foundation for personalized therapeutic approaches.https://www.imrpress.com/journal/JIN/24/3/10.31083/JIN27059eeg microstatesschizophreniaresting state networksmedicationaging |
| spellingShingle | Shihai Ling Lingyan Du Xi Tan Guozhi Tang Yue Che Shirui Song EEG Microstate Dynamics during Different Physiological Developmental Stages and the Effects of Medication in Schizophrenia Journal of Integrative Neuroscience eeg microstates schizophrenia resting state networks medication aging |
| title | EEG Microstate Dynamics during Different Physiological Developmental Stages and the Effects of Medication in Schizophrenia |
| title_full | EEG Microstate Dynamics during Different Physiological Developmental Stages and the Effects of Medication in Schizophrenia |
| title_fullStr | EEG Microstate Dynamics during Different Physiological Developmental Stages and the Effects of Medication in Schizophrenia |
| title_full_unstemmed | EEG Microstate Dynamics during Different Physiological Developmental Stages and the Effects of Medication in Schizophrenia |
| title_short | EEG Microstate Dynamics during Different Physiological Developmental Stages and the Effects of Medication in Schizophrenia |
| title_sort | eeg microstate dynamics during different physiological developmental stages and the effects of medication in schizophrenia |
| topic | eeg microstates schizophrenia resting state networks medication aging |
| url | https://www.imrpress.com/journal/JIN/24/3/10.31083/JIN27059 |
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