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Guo Q, Liu S, Wang L, Feng K, Yang S. Analysis of microstate features for Parkinson's disease based on reliability validation. J Neurosci Methods 2024; 406:110115. [PMID: 38531478 DOI: 10.1016/j.jneumeth.2024.110115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 03/13/2024] [Accepted: 03/20/2024] [Indexed: 03/28/2024]
Abstract
BACKGROUND Parkinson's disease (PD) is a disorder with abnormal changes in brain activity. The lack of objective indicators makes the assessment of PD progression difficult. Assessment of brain activity changes in PD may offer a potential solution. NEW METHOD Electroencephalogram (EEG) microstates reflect global dynamic changes in the brain. Therefore, we utilized microstates to assess changes in PD brain activity. However, the effect of epoch duration on the reliability of microstate analyses in PD is unclear. Thus, we first assessed the effect of data duration on the reliability of microstate topography and temporal features in PD and older healthy individuals. According to the reliability assessment, EEG epochs with high reliability were selected for microstate analysis in PD. Finally, we investigated the correlation between microstate features and clinical scales to determine whether these features could serve as objective indicators to evaluate PD progression. RESULTS Microstate analysis features that show high reliability for 3 min and above epoch durations. The topology of microstate D was significantly changed in PD compared to healthy controls, as well as the temporal features of microstates C and D. Additionally, the occurrence of C was negatively correlated with MoCA, and the duration of D was positively correlated with UPDRS. COMPARISON WITH EXISTING METHOD(S) High reliability of PD microstate features obtained by our approach. CONCLUSION EEG for PD microstate analysis should be at least 3 min. Microstate analysis is expected to provide new ideas and objective indicators for assessing Parkinson's disease progression in the clinical setting.
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Affiliation(s)
- Qingfang Guo
- Hebei Key Laboratory of Bioelectromagnetics and Neural Engineering, School of Health Sciences and Biomedical Engineering, Hebei University of Technology, Tianjin 300131, China; State Key Laboratory of Reliable and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China
| | - Shuo Liu
- Hebei Key Laboratory of Bioelectromagnetics and Neural Engineering, School of Health Sciences and Biomedical Engineering, Hebei University of Technology, Tianjin 300131, China; State Key Laboratory of Reliable and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China
| | - Lei Wang
- Hebei Key Laboratory of Bioelectromagnetics and Neural Engineering, School of Health Sciences and Biomedical Engineering, Hebei University of Technology, Tianjin 300131, China; State Key Laboratory of Reliable and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China
| | - Keke Feng
- Department of Neurosurgery, Tianjin Huanhu Hospital, Tianjin, China.
| | - Shuo Yang
- Hebei Key Laboratory of Bioelectromagnetics and Neural Engineering, School of Health Sciences and Biomedical Engineering, Hebei University of Technology, Tianjin 300131, China; State Key Laboratory of Reliable and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China.
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Lamoš M, Bočková M, Goldemundová S, Baláž M, Chrastina J, Rektor I. The effect of deep brain stimulation in Parkinson's disease reflected in EEG microstates. NPJ Parkinsons Dis 2023; 9:63. [PMID: 37069159 PMCID: PMC10110608 DOI: 10.1038/s41531-023-00508-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2022] [Accepted: 04/03/2023] [Indexed: 04/19/2023] Open
Abstract
Mechanisms of deep brain stimulation (DBS) on cortical networks were explored mainly by fMRI. Advanced analysis of high-density EEG is a source of additional information and may provide clinically useful biomarkers. The presented study evaluates EEG microstates in Parkinson's disease and the effect of DBS of the subthalamic nucleus (STN). The association between revealed spatiotemporal dynamics of brain networks and changes in oscillatory activity and clinical examination were assessed. Thirty-seven patients with Parkinson's disease treated by STN-DBS underwent two sessions (OFF and ON stimulation conditions) of resting-state EEG. EEG microstates were analyzed in patient recordings and in a matched healthy control dataset. Microstate parameters were then compared across groups and were correlated with clinical and neuropsychological scores. Of the five revealed microstates, two differed between Parkinson's disease patients and healthy controls. Another microstate differed between ON and OFF stimulation conditions in the patient group and restored parameters in the ON stimulation state toward to healthy values. The mean beta power of that microstate was the highest in patients during the OFF stimulation condition and the lowest in healthy controls; sources were localized mainly in the supplementary motor area. Changes in microstate parameters correlated with UPDRS and neuropsychological scores. Disease specific alterations in the spatiotemporal dynamics of large-scale brain networks can be described by EEG microstates. The approach can reveal changes reflecting the effect of DBS on PD motor symptoms as well as changes probably related to non-motor symptoms not influenced by DBS.
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Grants
- NU21-04-00445 Agentura Pro Zdravotnický Výzkum České Republiky (Czech Health Research Council)
- NU21-04-00445 Agentura Pro Zdravotnický Výzkum České Republiky (Czech Health Research Council)
- NU21-04-00445 Agentura Pro Zdravotnický Výzkum České Republiky (Czech Health Research Council)
- NU21-04-00445 Agentura Pro Zdravotnický Výzkum České Republiky (Czech Health Research Council)
- NU21-04-00445 Agentura Pro Zdravotnický Výzkum České Republiky (Czech Health Research Council)
- NU21-04-00445 Agentura Pro Zdravotnický Výzkum České Republiky (Czech Health Research Council)
- LM2018129 Ministerstvo Školství, Mládeže a Tělovýchovy (Ministry of Education, Youth and Sports)
- LM2018129 Ministerstvo Školství, Mládeže a Tělovýchovy (Ministry of Education, Youth and Sports)
- LM2018129 Ministerstvo Školství, Mládeže a Tělovýchovy (Ministry of Education, Youth and Sports)
- LM2018129 Ministerstvo Školství, Mládeže a Tělovýchovy (Ministry of Education, Youth and Sports)
- LM2018129 Ministerstvo Školství, Mládeže a Tělovýchovy (Ministry of Education, Youth and Sports)
- LM2018129 Ministerstvo Školství, Mládeže a Tělovýchovy (Ministry of Education, Youth and Sports)
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Affiliation(s)
- Martin Lamoš
- Brain and Mind Research Program, Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Martina Bočková
- Brain and Mind Research Program, Central European Institute of Technology, Masaryk University, Brno, Czech Republic
- Movement Disorders Center, First Department of Neurology, Masaryk University School of Medicine, St. Anne's Hospital, Brno, Czech Republic
| | - Sabina Goldemundová
- Brain and Mind Research Program, Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Marek Baláž
- Brain and Mind Research Program, Central European Institute of Technology, Masaryk University, Brno, Czech Republic
- Movement Disorders Center, First Department of Neurology, Masaryk University School of Medicine, St. Anne's Hospital, Brno, Czech Republic
| | - Jan Chrastina
- Brain and Mind Research Program, Central European Institute of Technology, Masaryk University, Brno, Czech Republic
- Department of Neurosurgery, Masaryk University School of Medicine, St. Anne's Hospital, Brno, Czech Republic
| | - Ivan Rektor
- Brain and Mind Research Program, Central European Institute of Technology, Masaryk University, Brno, Czech Republic.
- Movement Disorders Center, First Department of Neurology, Masaryk University School of Medicine, St. Anne's Hospital, Brno, Czech Republic.
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Keser Z, Buchl SC, Seven NA, Markota M, Clark HM, Jones DT, Lanzino G, Brown RD, Worrell GA, Lundstrom BN. Electroencephalogram (EEG) With or Without Transcranial Magnetic Stimulation (TMS) as Biomarkers for Post-stroke Recovery: A Narrative Review. Front Neurol 2022; 13:827866. [PMID: 35273559 PMCID: PMC8902309 DOI: 10.3389/fneur.2022.827866] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 01/31/2022] [Indexed: 01/20/2023] Open
Abstract
Stroke is one of the leading causes of death and disability. Despite the high prevalence of stroke, characterizing the acute neural recovery patterns that follow stroke and predicting long-term recovery remains challenging. Objective methods to quantify and characterize neural injury are still lacking. Since neuroimaging methods have a poor temporal resolution, EEG has been used as a method for characterizing post-stroke recovery mechanisms for various deficits including motor, language, and cognition as well as predicting treatment response to experimental therapies. In addition, transcranial magnetic stimulation (TMS), a form of non-invasive brain stimulation, has been used in conjunction with EEG (TMS-EEG) to evaluate neurophysiology for a variety of indications. TMS-EEG has significant potential for exploring brain connectivity using focal TMS-evoked potentials and oscillations, which may allow for the system-specific delineation of recovery patterns after stroke. In this review, we summarize the use of EEG alone or in combination with TMS in post-stroke motor, language, cognition, and functional/global recovery. Overall, stroke leads to a reduction in higher frequency activity (≥8 Hz) and intra-hemispheric connectivity in the lesioned hemisphere, which creates an activity imbalance between non-lesioned and lesioned hemispheres. Compensatory activity in the non-lesioned hemisphere leads mostly to unfavorable outcomes and further aggravated interhemispheric imbalance. Balanced interhemispheric activity with increased intrahemispheric coherence in the lesioned networks correlates with improved post-stroke recovery. TMS-EEG studies reveal the clinical importance of cortical reactivity and functional connectivity within the sensorimotor cortex for motor recovery after stroke. Although post-stroke motor studies support the prognostic value of TMS-EEG, more studies are needed to determine its utility as a biomarker for recovery across domains including language, cognition, and hemispatial neglect. As a complement to MRI-based technologies, EEG-based technologies are accessible and valuable non-invasive clinical tools in stroke neurology.
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Affiliation(s)
- Zafer Keser
- Department of Neurology, Mayo Clinic, Rochester, MN, United States
| | - Samuel C. Buchl
- Department of Neurology, Mayo Clinic, Rochester, MN, United States
| | - Nathan A. Seven
- Department of Neurology, Mayo Clinic, Rochester, MN, United States
| | - Matej Markota
- Department of Psychiatry, Mayo Clinic, Rochester, MN, United States
| | - Heather M. Clark
- Department of Neurology, Mayo Clinic, Rochester, MN, United States
| | - David T. Jones
- Department of Neurology, Mayo Clinic, Rochester, MN, United States
- Department of Radiology, Mayo Clinic, Rochester, MN, United States
| | - Giuseppe Lanzino
- Department of Neurosurgery, Mayo Clinic, Rochester, MN, United States
| | - Robert D. Brown
- Department of Neurology, Mayo Clinic, Rochester, MN, United States
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