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Baarbé J, Brown MJN, Saha U, Tran S, Weissbach A, Saravanamuttu J, Cheyne D, Hutchison WD, Chen R. Cortical modulations before lower limb motor blocks are associated with freezing of gait in Parkinson's disease: an EEG source localization study. Neurobiol Dis 2024; 199:106557. [PMID: 38852752 DOI: 10.1016/j.nbd.2024.106557] [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: 03/26/2024] [Revised: 05/15/2024] [Accepted: 06/05/2024] [Indexed: 06/11/2024] Open
Abstract
BACKGROUND Freezing of gait (FOG) is a debilitating symptom of Parkinson's disease (PD) characterized by paroxysmal episodes in which patients are unable to step forward. A research priority is identifying cortical changes before freezing in PD-FOG. METHODS We tested 19 patients with PD who had been assessed for FOG (n=14 with FOG and 5 without FOG). While seated, patients stepped bilaterally on pedals to progress forward through a virtual hallway while 64-channel EEG was recorded. We assessed cortical activities before and during lower limb motor blocks (LLMB), defined as a break in rhythmic pedaling, and stops, defined as movement cessation following an auditory stop cue. This task was selected because LLMB correlates with FOG severity in PD and allows recording of high-quality EEG. Patients were tested after overnight withdrawal from dopaminergic medications ("off" state) and in the "on" medications state. EEG source activities were evaluated using individual MRI and standardized low resolution brain electromagnetic tomography (sLORETA). Functional connectivity was evaluated by phase lag index between seeds and pre-defined cortical regions of interest. RESULTS EEG source activities for LLMB vs. cued stops localized to right posterior parietal area (Brodmann area 39), lateral premotor area (Brodmann area 6), and inferior frontal gyrus (Brodmann area 47). In these areas, PD-FOG (n=14) increased alpha rhythms (8-12 Hz) before LLMB vs. typical stepping, whereas PD without FOG (n=5) decreased alpha power. Alpha rhythms were linearly correlated with LLMB severity, and the relationship became an inverted U-shape when assessing alpha rhythms as a function of percent time in LLMB in the "off" medication state. Right inferior frontal gyrus and supplementary motor area connectivity was observed before LLMB in the beta band (13-30 Hz). This same pattern of connectivity was seen before stops. Dopaminergic medication improved FOG and led to less alpha synchronization and increased functional connections between frontal and parietal areas. CONCLUSIONS Right inferior parietofrontal structures are implicated in PD-FOG. The predominant changes were in the alpha rhythm, which increased before LLMB and with LLMB severity. Similar connectivity was observed for LLMB and stops between the right inferior frontal gyrus and supplementary motor area, suggesting that FOG may be a form of "unintended stopping." These findings may inform approaches to neurorehabilitation of PD-FOG.
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Affiliation(s)
- Julianne Baarbé
- Department of Medicine, University of Toronto and Division of Brain, Imaging & Behaviour, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada; Faculty of Health, York University, Toronto, Ontario, Canada.
| | - Matt J N Brown
- Department of Kinesiology, California State University, Sacramento, CA, USA
| | - Utpal Saha
- Department of Medicine, University of Toronto and Division of Brain, Imaging & Behaviour, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
| | - Stephanie Tran
- Department of Medicine, University of Toronto and Division of Brain, Imaging & Behaviour, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
| | - Anne Weissbach
- Institute of Systems Motor Science, Center of Brain, Behavior and Metabolism, University of Lübeck, Germany
| | - James Saravanamuttu
- Department of Medicine, University of Toronto and Division of Brain, Imaging & Behaviour, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
| | - Douglas Cheyne
- Program in Neurosciences and Mental Health, Hospital for Sick Children Research Institute, Toronto, ON, Canada
| | - William D Hutchison
- Department of Medicine, University of Toronto and Division of Brain, Imaging & Behaviour, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada; Edmond J. Safra Program in Parkinson's Disease, Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada
| | - Robert Chen
- Department of Medicine, University of Toronto and Division of Brain, Imaging & Behaviour, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada; Edmond J. Safra Program in Parkinson's Disease, Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada
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van der Plas MC, Rasing I, Geraedts VJ, Tromp SC, Terwindt GM, van Dort R, Kaushik K, van Zwet EW, Tannemaat MR, Wermer MJH. Quantitative electroencephalography in cerebral amyloid angiopathy. Clin Neurophysiol 2024; 164:111-118. [PMID: 38861875 DOI: 10.1016/j.clinph.2024.05.013] [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: 07/20/2023] [Revised: 04/14/2024] [Accepted: 05/22/2024] [Indexed: 06/13/2024]
Abstract
OBJECTIVE We investigated whether quantitative electroencephalography (qEEG) correlates with cognition and cortical superficial siderosis (cSS) in cerebral amyloid angiopathy. METHODS We included patients with sporadic (sCAA) and hereditary Dutch-type CAA (D-CAA). Spectral measures and the phase lag index (PLI) were analyzed on qEEG. Cognition was assessed with the MoCA and cSS presence was scored on 3T-MRI. Linear regression analyses were performed to investigate these qEEG measures and cognition. Independent samples T-tests were used to analyze the qEEG measure differences between participants with and without cSS. RESULTS We included 92 participants (44 D-CAA; 48 sCAA). A lower average peak frequency (β[95 %CI] = 0.986[0.252-1.721]; P = 0.009) and a higher spectral ratio (β[95 %CI] = -0.918[-1.761--0.075]; P = 0.033) on qEEG correlated with a lower MoCA score, irrespective of a history of symptomatic intracerebral hemorrhage (sICH). The PLI showed no correlation to the MoCA. qEEG slowing was not different in those with or without cSS. CONCLUSIONS Spectral qEEG (but not PLI) reflects cognitive performance in patients with CAA with and without a history of sICH. We found no association between qEEG slowing and cSS. SIGNIFICANCE qEEG could be a valuable biomarker, especially in challenging cognitive testing situations in CAA, and a potential predictive tool in future studies.
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Affiliation(s)
- M C van der Plas
- Department of Neurology, Leiden University Medical Center, Albinusdreef 2, 2300 RC, Leiden, the Netherlands.
| | - I Rasing
- Department of Neurology, Leiden University Medical Center, Albinusdreef 2, 2300 RC, Leiden, the Netherlands
| | - V J Geraedts
- Department of Neurology, Leiden University Medical Center, Albinusdreef 2, 2300 RC, Leiden, the Netherlands
| | - S C Tromp
- Department of Neurology, Leiden University Medical Center, Albinusdreef 2, 2300 RC, Leiden, the Netherlands
| | - G M Terwindt
- Department of Neurology, Leiden University Medical Center, Albinusdreef 2, 2300 RC, Leiden, the Netherlands
| | - R van Dort
- Department of Neurology, Leiden University Medical Center, Albinusdreef 2, 2300 RC, Leiden, the Netherlands
| | - K Kaushik
- Department of Neurology, Leiden University Medical Center, Albinusdreef 2, 2300 RC, Leiden, the Netherlands
| | - E W van Zwet
- Department of Biomedical Data Sciences, Leiden University Medical Center, Albinusdreef 2, 2300 RC Leiden, the Netherlands
| | - M R Tannemaat
- Department of Neurology, Leiden University Medical Center, Albinusdreef 2, 2300 RC, Leiden, the Netherlands
| | - M J H Wermer
- Department of Neurology, Leiden University Medical Center, Albinusdreef 2, 2300 RC, Leiden, the Netherlands; Department of Neurology, University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, the Netherlands
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Kemp AF, Kinnerup M, Johnsen B, Jakobsen S, Nahimi A, Gjedde A. EEG Frequency Correlates with α 2-Receptor Density in Parkinson's Disease. Biomolecules 2024; 14:209. [PMID: 38397446 PMCID: PMC10886955 DOI: 10.3390/biom14020209] [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: 12/17/2023] [Revised: 01/31/2024] [Accepted: 02/06/2024] [Indexed: 02/25/2024] Open
Abstract
INTRODUCTION Increased theta and delta power and decreased alpha and beta power, measured with quantitative electroencephalography (EEG), have been demonstrated to have utility for predicting the development of dementia in patients with Parkinson's disease (PD). Noradrenaline modulates cortical activity and optimizes cognitive processes. We claim that the loss of noradrenaline may explain cognitive impairment and the pathological slowing of EEG waves. Here, we test the relationship between the number of noradrenergic α2 adrenoceptors and changes in the spectral EEG ratio in patients with PD. METHODS We included nineteen patients with PD and thirteen healthy control (HC) subjects in the study. We used positron emission tomography (PET) with [11C]yohimbine to quantify α2 adrenoceptor density. We used EEG power in the delta (δ, 1.5-3.9 Hz), theta (θ, 4-7.9 Hz), alpha (α, 8-12.9 Hz) and beta (β, 13-30 Hz) bands in regression analyses to test the relationships between α2 adrenoceptor density and EEG band power. RESULTS PD patients had higher power in the theta and delta bands compared to the HC volunteers. Patients' theta band power was inversely correlated with α2 adrenoceptor density in the frontal cortex. In the HC subjects, age was correlated with, and occipital background rhythm frequency (BRF) was inversely correlated with, α2 adrenoceptor density in the frontal cortex, while occipital BRF was inversely correlated with α2 adrenoceptor density in the thalamus. CONCLUSIONS The findings support the claim that the loss or dysfunction of noradrenergic neurotransmission may relate to the parallel processes of cognitive decline and EEG slowing.
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Affiliation(s)
- Adam F. Kemp
- Department of Nuclear Medicine, Odense University Hospital, 5000 Odense, Denmark;
| | - Martin Kinnerup
- Department of Clinical Medicine, Aarhus University, 8000 Aarhus, Denmark; (M.K.); (B.J.); (S.J.)
| | - Birger Johnsen
- Department of Clinical Medicine, Aarhus University, 8000 Aarhus, Denmark; (M.K.); (B.J.); (S.J.)
- Department of Clinical Neurophysiology, Aarhus University Hospital, 8200 Aarhus, Denmark
| | - Steen Jakobsen
- Department of Clinical Medicine, Aarhus University, 8000 Aarhus, Denmark; (M.K.); (B.J.); (S.J.)
| | - Adjmal Nahimi
- Clinical Memory Research Unit, Department of Clinical Sciences, 211 46 Malmö, Sweden;
- Department of Neurology, Skåne University Hospital, 221 85 Lund, Sweden
| | - Albert Gjedde
- Department of Clinical Medicine, Aarhus University, 8000 Aarhus, Denmark; (M.K.); (B.J.); (S.J.)
- Department of Neuroscience, University of Copenhagen, 1172 Copenhagen, Denmark
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC H3A 0G4, Canada
- Translational Neuropsychiatry Unit, Department of Clinical Medicine, Aarhus University, 8000 Aarhus, Denmark
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Yassine S, Gschwandtner U, Auffret M, Duprez J, Verin M, Fuhr P, Hassan M. Identification of Parkinson's Disease Subtypes from Resting-State Electroencephalography. Mov Disord 2023; 38:1451-1460. [PMID: 37310340 DOI: 10.1002/mds.29451] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 04/11/2023] [Accepted: 05/05/2023] [Indexed: 06/14/2023] Open
Abstract
BACKGROUND Parkinson's disease (PD) patients present with a heterogeneous clinical phenotype, including motor, cognitive, sleep, and affective disruptions. However, this heterogeneity is often either ignored or assessed using only clinical assessments. OBJECTIVES We aimed to identify different PD sub-phenotypes in a longitudinal follow-up analysis and their electrophysiological profile based on resting-state electroencephalography (RS-EEG) and to assess their clinical significance over the course of the disease. METHODS Using electrophysiological features obtained from RS-EEG recordings and data-driven methods (similarity network fusion and source-space spectral analysis), we have performed a clustering analysis to identify disease sub-phenotypes and we examined whether their different patterns of disruption are predictive of disease outcome. RESULTS We showed that PD patients (n = 44) can be sub-grouped into three phenotypes with distinct electrophysiological profiles. These clusters are characterized by different levels of disruptions in the somatomotor network (Δ and β band), the frontotemporal network (α2 band) and the default mode network (α1 band), which consistently correlate with clinical profiles and disease courses. These clusters are classified into either moderate (only-motor) or mild-to-severe (diffuse) disease. We showed that EEG features can predict cognitive evolution of PD patients from baseline, when the cognitive clinical scores were overlapped. CONCLUSIONS The identification of novel PD subtypes based on electrical brain activity signatures may provide a more accurate prognosis in individual patients in clinical practice and help to stratify subgroups in clinical trials. Innovative profiling in PD can also support new therapeutic strategies that are brain-based and designed to modulate brain activity disruption. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Sahar Yassine
- LTSI - INSERM U1099, University of Rennes, Rennes, France
- NeuroKyma, Rennes, France
- Behavior and Basal Ganglia, CIC1414, CIC-IT, CHU Rennes, Rennes, France
| | - Ute Gschwandtner
- Department of Neurology, Hospitals of the University of Basel, Basel, Switzerland
| | - Manon Auffret
- LTSI - INSERM U1099, University of Rennes, Rennes, France
- Behavior and Basal Ganglia, CIC1414, CIC-IT, CHU Rennes, Rennes, France
- Institut des Neurosciences Cliniques de Rennes (INCR), Rennes, France
- France Développement Electronique, Monswiller, France
| | - Joan Duprez
- LTSI - INSERM U1099, University of Rennes, Rennes, France
| | - Marc Verin
- LTSI - INSERM U1099, University of Rennes, Rennes, France
- Behavior and Basal Ganglia, CIC1414, CIC-IT, CHU Rennes, Rennes, France
- Institut des Neurosciences Cliniques de Rennes (INCR), Rennes, France
- Movement Disorders Unit, Neurology Department, Pontchaillou University Hospital, Rennes, France
| | - Peter Fuhr
- Department of Neurology, Hospitals of the University of Basel, Basel, Switzerland
| | - Mahmoud Hassan
- Behavior and Basal Ganglia, CIC1414, CIC-IT, CHU Rennes, Rennes, France
- School of Science and Engineering, Reykjavik University, Reykjavik, Iceland
- MINDIG, Rennes, France
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Boon LI, Hillebrand A, Schoonheim MM, Twisk JW, Stam CJ, Berendse HW. Cortical and Subcortical Changes in MEG Activity Reflect Parkinson's Progression over a Period of 7 Years. Brain Topogr 2023:10.1007/s10548-023-00965-w. [PMID: 37154884 DOI: 10.1007/s10548-023-00965-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 04/15/2023] [Indexed: 05/10/2023]
Abstract
In this study of early functional changes in Parkinson's disease (PD), we aimed to provide a comprehensive assessment of the development of changes in both cortical and subcortical neurophysiological brain activity, including their association with clinical measures of disease severity. Repeated resting-state MEG recordings and clinical assessments were obtained in the context of a unique longitudinal cohort study over a seven-year period using a multiple longitudinal design. We used linear mixed-models to analyze the relationship between neurophysiological (spectral power and functional connectivity) and clinical data. At baseline, early-stage (drug-naïve) PD patients demonstrated spectral slowing compared to healthy controls in both subcortical and cortical brain regions, most outspoken in the latter. Over time, spectral slowing progressed in strong association with clinical measures of disease progression (cognitive and motor). Global functional connectivity was not different between groups at baseline and hardly changed over time. Therefore, investigation of associations with clinical measures of disease progression were not deemed useful. An analysis of individual connections demonstrated differences between groups at baseline (higher frontal theta, lower parieto-occipital alpha2 band functional connectivity) and over time in PD patients (increase in frontal delta and theta band functional connectivity). Our results suggest that spectral measures are promising candidates in the search for non-invasive markers of both early-stage PD and of the ongoing disease process.
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Affiliation(s)
- Lennard I Boon
- Department of Neurology, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands.
- Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands.
| | - Arjan Hillebrand
- Department of Neurology, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
- Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
| | - Jos W Twisk
- Department of Epidemiology and Biostatistics, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
| | - Cornelis J Stam
- Department of Neurology, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
- Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
| | - Henk W Berendse
- Department of Neurology, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
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Zawiślak-Fornagiel K, Ledwoń D, Bugdol M, Romaniszyn-Kania P, Małecki A, Gorzkowska A, Mitas AW. Specific patterns of coherence and phase lag index in particular regions as biomarkers of cognitive impairment in Parkinson's disease. Parkinsonism Relat Disord 2023; 111:105436. [PMID: 37167834 DOI: 10.1016/j.parkreldis.2023.105436] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 04/25/2023] [Accepted: 05/01/2023] [Indexed: 05/13/2023]
Abstract
INTRODUCTION Cognitive impairment is a persistent and increasingly reported symptom of patients with Parkinson's disease (PD), significantly affecting daily functioning quality. This study aims to evaluate the functional connectivity of the brain network in patients with Parkinson's disease with various severities of cognitive decline using quantitative electroencephalography (EEG) analysis. METHODS Based on the EEG recorded in the resting state, the coherence and phase lag index were calculated to evaluate functional connectivity in 108 patients with Parkinson's disease divided into three groups according to their cognitive condition: dementia due to PD (PD-D), PD and mild cognitive impairment (PD-MCI) and cognitively normal patients (PD-CogN). RESULTS It was found that there were significantly different coherence values in the PD-D group compared to PD-CogN in different frequency bands. In most cases, there was a decrease in coherence in PD-D compared to PD-CogN. The most specific changes were revealed in the theta frequency band in the temporal right-frontal left and temporal right-frontal right regions. In the alpha frequency band, the most significant decreases were shown in the occipital right-frontal left and occipital left-frontal right areas. There were also statistically significant differences in phase lag index between many areas, especially in the theta frequency range. CONCLUSIONS These findings indicate that the functional connectivity patterns of coherence and phase lag index - found in a particular frequency band and region - could become a reliable biomarker for identifying cognitive impairment and differentiating its severity in PD patients.
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Affiliation(s)
- Katarzyna Zawiślak-Fornagiel
- Department of Neurology, University Clinical Center prof. K. Gibiński of the Medical University of Silesia, 40-752, Katowice, Poland
| | - Daniel Ledwoń
- Faculty of Biomedical Engineering, Silesian University of Technology, Roosevelta 40, 41-800, Zabrze, Poland.
| | - Monika Bugdol
- Faculty of Biomedical Engineering, Silesian University of Technology, Roosevelta 40, 41-800, Zabrze, Poland
| | - Patrycja Romaniszyn-Kania
- Faculty of Biomedical Engineering, Silesian University of Technology, Roosevelta 40, 41-800, Zabrze, Poland
| | - Andrzej Małecki
- Institute of Physiotherapy and Health Science, Academy of Physical Education in Katowice, Mikołowska 72A, 40-065, Katowice, Poland
| | - Agnieszka Gorzkowska
- Department of Neurorehabilitation, Faculty of Medical Sciences in Katowice, Medical University of Silesia, 40-752, Katowice, Poland
| | - Andrzej W Mitas
- Faculty of Biomedical Engineering, Silesian University of Technology, Roosevelta 40, 41-800, Zabrze, Poland
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Costa TDDC, Machado CBDS, Lemos Segundo RP, Silva JPDS, Silva ACT, Andrade RDS, Rosa MRD, Smaili SM, Morya E, Costa-Ribeiro A, Lindquist ARR, Andrade SM, Machado DGDS. Are the EEG microstates correlated with motor and non-motor parameters in patients with Parkinson's disease? Neurophysiol Clin 2023; 53:102839. [PMID: 36716585 DOI: 10.1016/j.neucli.2022.102839] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 11/05/2022] [Accepted: 12/17/2022] [Indexed: 01/30/2023] Open
Abstract
OBJECTIVES This study compared electroencephalography microstates (EEG-MS) of patients with Parkinson's disease (PD) to healthy controls and correlated EEG-MS with motor and non-motor aspects of PD. METHODS This cross-sectional exploratory study was conducted with patients with PD (n = 10) and healthy controls (n = 10) matched by sex and age. We recorded EEG-MS using 32 channels during eyes-closed and eyes-open conditions and analyzed the four classic EEG-MS maps (A, B, C, D). Clinical information (e.g., disease duration, medications, levodopa equivalent daily dose), motor (Movement Disorder Society - Unified Parkinson Disease Rating Scale II and III, Timed Up and Go simple and dual-task, and Mini-Balance Evaluation Systems Test) and non-motor aspects (Mini-Mental State Exam [MMSE], verbal fluency, Hospital Anxiety and Depression Scale, and Parkinson's Disease Questionnaire-39 [PDQ-39]) were assessed in the PD group. Mann-Whitney U test was used to compare groups, and Spearman's correlation coefficient to analyze the correlations between coverage of EEG-MS and clinical aspects of PD. RESULTS The PD group showed a shorter duration of EEG-MS C in the eyes-closed condition than the control group. We observed correlations (rho = 0.64 to 0.82) between EEG-MS B, C, and D and non-motor aspects of PD (MMSE, verbal fluency, PDQ-39, and levodopa equivalent daily dose). CONCLUSION Alterations in EEG-MS and correlations between topographies and cognitive aspects, quality of life, and medication dose indicate that EEG could be used as a PD biomarker. Future studies should investigate these associations using a longitudinal design.
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Affiliation(s)
- Thaísa Dias de Carvalho Costa
- Aging and Neuroscience Laboratory, Federal University of Paraíba, João Pessoa, Brazil; Graduate Program in Cognitive and Behavioural Neuroscience, Federal University of Paraíba, João Pessoa, Brazil
| | | | | | | | | | - Rafael de Souza Andrade
- Division of Neurology, Lauro Wanderley University Hospital, Federal University of Paraíba, João Pessoa, Brazil
| | - Marine Raquel Diniz Rosa
- Graduate Program in Cognitive and Behavioural Neuroscience, Federal University of Paraíba, João Pessoa, Brazil
| | | | - Edgard Morya
- Edmond and Lily Safra International Institute of Neurosciences, Santos Dumont Institute, Natal, Brazil
| | - Adriana Costa-Ribeiro
- NeuroMove Laboratory, Department of Physiotherapy, Federal University of Paraíba, Joao Pessoa, Brazil
| | - Ana Raquel Rodrigues Lindquist
- Laboratory of Intervention and Analysis of Movement, Department of Physiotherapy, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Suellen Marinho Andrade
- Aging and Neuroscience Laboratory, Federal University of Paraíba, João Pessoa, Brazil; Graduate Program in Cognitive and Behavioural Neuroscience, Federal University of Paraíba, João Pessoa, Brazil
| | - Daniel Gomes da Silva Machado
- Research Group in Neuroscience of Human Movement (NeuroMove), Department of Physical Education, Federal University of Rio Grande do Norte, Natal, RN, Brazil.
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Kim D, Kim T, Hwang Y, Lee CY, Joo EY, Seo DW, Hong SB, Shon YM. Prediction of the Responsiveness to Vagus-Nerve Stimulation in Patients with Drug-Resistant Epilepsy via Directed-Transfer-Function Analysis of Their Perioperative Scalp EEGs. J Clin Med 2022; 11:jcm11133695. [PMID: 35806980 PMCID: PMC9267399 DOI: 10.3390/jcm11133695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Revised: 06/18/2022] [Accepted: 06/22/2022] [Indexed: 02/04/2023] Open
Abstract
This study aims to compare directed transfer function (DTF), which is an effective connectivity analysis, derived from scalp EEGs between responder and nonresponder groups implanted with vagus-nerve stimulation (VNS). Twelve patients with drug-resistant epilepsy (six responders and six nonresponders) and ten controls were recruited. A good response to VNS was defined as a reduction of ≥50% in seizure frequency compared with the presurgical baseline. DTF was calculated in five frequency bands (delta, theta, alpha, beta, and broadband) and seven grouped electrode regions (left and right frontal, temporal, parieto-occipital, and midline) in three different states (presurgical, stimulation-on, and stimulation-off states). Responders showed presurgical nodal strength close to the control group in both inflow and outflow, whereas nonresponders exhibited increased inward and outward connectivity measures. Nonresponders also had increased inward and outward connectivity measures in the various brain regions and various frequency bands assessed compared with the control group when the stimulation was on or off. Our study demonstrated that the presurgical DTF profiles of responders were different from those of nonresponders. Moreover, a presurgical normal DTF profile may predict good responsiveness to VNS.
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Affiliation(s)
- Dongyeop Kim
- Department of Neurology, Seoul Hospital, Ewha Womans University College of Medicine, Seoul 07804, Korea;
| | - Taekyung Kim
- Department of Medical Device Management and Research, Samsung Advanced Institute for Health Sciences and Technology (SAHIST), Sungkyunkwan University, Seoul 06355, Korea;
- Biomedical Engineering Research Center, Samsung Medical Center, Seoul 06351, Korea
| | - Yoonha Hwang
- Department of Neurology, The Catholic University of Korea Eunpyeong St. Mary’s Hospital, Seoul 03312, Korea;
| | - Chae Young Lee
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea; (C.Y.L.); (E.Y.J.); (D.-W.S.); (S.B.H.)
| | - Eun Yeon Joo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea; (C.Y.L.); (E.Y.J.); (D.-W.S.); (S.B.H.)
| | - Dae-Won Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea; (C.Y.L.); (E.Y.J.); (D.-W.S.); (S.B.H.)
| | - Seung Bong Hong
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea; (C.Y.L.); (E.Y.J.); (D.-W.S.); (S.B.H.)
| | - Young-Min Shon
- Department of Medical Device Management and Research, Samsung Advanced Institute for Health Sciences and Technology (SAHIST), Sungkyunkwan University, Seoul 06355, Korea;
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea; (C.Y.L.); (E.Y.J.); (D.-W.S.); (S.B.H.)
- Correspondence:
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The frontostriatal subtype of mild cognitive impairment in Parkinson’s disease, but not the posterior cortical one, is associated with specific EEG alterations. Cortex 2022; 153:166-177. [DOI: 10.1016/j.cortex.2022.04.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 01/27/2022] [Accepted: 04/07/2022] [Indexed: 11/22/2022]
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Bočková M, Výtvarová E, Lamoš M, Klimeš P, Jurák P, Halámek J, Goldemundová S, Baláž M, Rektor I. Cortical network organization reflects clinical response to subthalamic nucleus deep brain stimulation in Parkinson's disease. Hum Brain Mapp 2021; 42:5626-5635. [PMID: 34448523 PMCID: PMC8559467 DOI: 10.1002/hbm.25642] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Revised: 08/03/2021] [Accepted: 08/16/2021] [Indexed: 12/19/2022] Open
Abstract
The degree of response to subthalamic nucleus deep brain stimulation (STN‐DBS) is individual and hardly predictable. We hypothesized that DBS‐related changes in cortical network organization are related to the clinical effect. Network analysis based on graph theory was used to evaluate the high‐density electroencephalography (HDEEG) recorded during a visual three‐stimuli paradigm in 32 Parkinson's disease (PD) patients treated by STN‐DBS in stimulation “off” and “on” states. Preprocessed scalp data were reconstructed into the source space and correlated to the behavioral parameters. In the majority of patients (n = 26), STN‐DBS did not lead to changes in global network organization in large‐scale brain networks. In a subgroup of suboptimal responders (n = 6), identified according to reaction times (RT) and clinical parameters (lower Unified Parkinson's Disease Rating Scale [UPDRS] score improvement after DBS and worse performance in memory tests), decreased global connectivity in the 1–8 Hz frequency range and regional node strength in frontal areas were detected. The important role of the supplementary motor area for the optimal DBS response was demonstrated by the increased node strength and eigenvector centrality in good responders. This response was missing in the suboptimal responders. Cortical topologic architecture is modified by the response to STN‐DBS leading to a dysfunction of the large‐scale networks in suboptimal responders.
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Affiliation(s)
- Martina Bočková
- Central European Institute of Technology (CEITEC), Brain and Mind Research Program, Masaryk University, Brno, Czech Republic.,Movement Disorders Center, First Department of Neurology, Masaryk University School of Medicine, St. Anne's Hospital, Brno, Czech Republic
| | - Eva Výtvarová
- Central European Institute of Technology (CEITEC), Brain and Mind Research Program, Masaryk University, Brno, Czech Republic.,Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Martin Lamoš
- Central European Institute of Technology (CEITEC), Brain and Mind Research Program, Masaryk University, Brno, Czech Republic
| | - Petr Klimeš
- Institute of Scientific Instruments of the Czech Academy of Sciences, v.v.i., Brno, Czech Republic
| | - Pavel Jurák
- Institute of Scientific Instruments of the Czech Academy of Sciences, v.v.i., Brno, Czech Republic
| | - Josef Halámek
- Institute of Scientific Instruments of the Czech Academy of Sciences, v.v.i., Brno, Czech Republic
| | - Sabina Goldemundová
- Central European Institute of Technology (CEITEC), Brain and Mind Research Program, Masaryk University, Brno, Czech Republic
| | - Marek Baláž
- Central European Institute of Technology (CEITEC), Brain and Mind Research Program, Masaryk University, Brno, Czech Republic.,Movement Disorders Center, First Department of Neurology, Masaryk University School of Medicine, St. Anne's Hospital, Brno, Czech Republic
| | - Ivan Rektor
- Central European Institute of Technology (CEITEC), Brain and Mind Research Program, 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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11
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Geraedts VJ, Koch M, Kuiper R, Kefalas M, Bäck THW, van Hilten JJ, Wang H, Middelkoop HAM, van der Gaag NA, Contarino MF, Tannemaat MR. Preoperative Electroencephalography-Based Machine Learning Predicts Cognitive Deterioration after Subthalamic Deep Brain Stimulation. Mov Disord 2021; 36:2324-2334. [PMID: 34080712 PMCID: PMC8596544 DOI: 10.1002/mds.28661] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 04/12/2021] [Accepted: 05/05/2021] [Indexed: 12/15/2022] Open
Abstract
Background Subthalamic deep brain stimulation (STN DBS) may relieve refractory motor complications in Parkinson's disease (PD) patients. Despite careful screening, it remains difficult to determine severity of alpha‐synucleinopathy involvement which influences the risk of postoperative complications including cognitive deterioration. Quantitative electroencephalography (qEEG) reflects cognitive dysfunction in PD and may provide biomarkers of postoperative cognitive decline. Objective To develop an automated machine learning model based on preoperative EEG data to predict cognitive deterioration 1 year after STN DBS. Methods Sixty DBS candidates were included; 42 patients had available preoperative EEGs to compute a fully automated machine learning model. Movement Disorder Society criteria classified patients as cognitively stable or deteriorated at 1‐year follow‐up. A total of 16,674 EEG‐features were extracted per patient; a Boruta algorithm selected EEG‐features to reflect representative neurophysiological signatures for each class. A random forest classifier with 10‐fold cross‐validation with Bayesian optimization provided class‐differentiation. Results Tweny‐five patients were classified as cognitively stable and 17 patients demonstrated cognitive decline. The model differentiated classes with a mean (SD) accuracy of 0.88 (0.05), with a positive predictive value of 91.4% (95% CI 82.9, 95.9) and negative predictive value of 85.0% (95% CI 81.9, 91.4). Predicted probabilities between classes were highly differential (hazard ratio 11.14 [95% CI 7.25, 17.12]); the risk of cognitive decline in patients with high probabilities of being prognosticated as cognitively stable (>0.5) was very limited. Conclusions Preoperative EEGs can predict cognitive deterioration after STN DBS with high accuracy. Cortical neurophysiological alterations may indicate future cognitive decline and can be used as biomarkers during the DBS screening. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society
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Affiliation(s)
- Victor J Geraedts
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands.,Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Milan Koch
- Leiden Institute of Advanced Computer Science, Leiden, The Netherlands
| | - Roy Kuiper
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands.,Department of Neurology, Haga Teaching Hospital, Den Haag, The Netherlands
| | - Marios Kefalas
- Leiden Institute of Advanced Computer Science, Leiden, The Netherlands
| | - Thomas H W Bäck
- Leiden Institute of Advanced Computer Science, Leiden, The Netherlands
| | - Jacobus J van Hilten
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
| | - Hao Wang
- Leiden Institute of Advanced Computer Science, Leiden, The Netherlands
| | - Huub A M Middelkoop
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands.,Neuropsychology Unit, Leiden University Institute of Psychology, Leiden, The Netherlands
| | - Niels A van der Gaag
- Department of Neurosurgery, Leiden University Medical Center, Leiden, The Netherlands.,Department of Neurosurgery, Haga Teaching Hospital, Den Haag, The Netherlands
| | - Maria Fiorella Contarino
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands.,Department of Neurology, Haga Teaching Hospital, Den Haag, The Netherlands
| | - Martijn R Tannemaat
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
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12
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Machine learning for automated EEG-based biomarkers of cognitive impairment during Deep Brain Stimulation screening in patients with Parkinson’s Disease. Clin Neurophysiol 2021; 132:1041-1048. [DOI: 10.1016/j.clinph.2021.01.021] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Revised: 01/09/2021] [Accepted: 01/12/2021] [Indexed: 11/19/2022]
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13
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Maggioni E, Arienti F, Minella S, Mameli F, Borellini L, Nigro M, Cogiamanian F, Bianchi AM, Cerutti S, Barbieri S, Brambilla P, Ardolino G. Effective Connectivity During Rest and Music Listening: An EEG Study on Parkinson's Disease. Front Aging Neurosci 2021; 13:657221. [PMID: 33994997 PMCID: PMC8113619 DOI: 10.3389/fnagi.2021.657221] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Accepted: 03/31/2021] [Indexed: 11/30/2022] Open
Abstract
Music-based interventions seem to enhance motor, sensory and cognitive functions in Parkinson’s disease (PD), but the underlying action mechanisms are still largely unknown. This electroencephalography (EEG) study aimed to investigate the effective connectivity patterns characterizing PD in the resting state and during music listening. EEG recordings were obtained from fourteen non-demented PD patients and 12 healthy controls, at rest and while listening to three music tracks. Theta- and alpha-band power spectral density and multivariate partial directed coherence were computed. Power and connectivity measures were compared between patients and controls in the four conditions and in music vs. rest. Compared to controls, patients showed enhanced theta-band power and slightly enhanced alpha-band power, but markedly reduced theta- and alpha-band interactions among EEG channels, especially concerning the information received by the right central channel. EEG power differences were partially reduced by music listening, which induced power increases in controls but not in patients. Connectivity differences were slightly compensated by music, whose effects largely depended on the track. In PD, music enhanced the frontotemporal inter-hemispheric communication. Our findings suggest that PD is characterized by enhanced activity but reduced information flow within the EEG network, being only partially normalized by music. Nevertheless, music capability to facilitate inter-hemispheric communication might underlie its beneficial effects on PD pathophysiology and should be further investigated.
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Affiliation(s)
- Eleonora Maggioni
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Federica Arienti
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Stella Minella
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Francesca Mameli
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Linda Borellini
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Martina Nigro
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Filippo Cogiamanian
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Anna Maria Bianchi
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy
| | - Sergio Cerutti
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy
| | - Sergio Barbieri
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Paolo Brambilla
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.,Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Gianluca Ardolino
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
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Electrophysiological Frequency Band Ratio Measures Conflate Periodic and Aperiodic Neural Activity. eNeuro 2020; 7:ENEURO.0192-20.2020. [PMID: 32978216 PMCID: PMC7768281 DOI: 10.1523/eneuro.0192-20.2020] [Citation(s) in RCA: 57] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Revised: 09/01/2020] [Accepted: 09/08/2020] [Indexed: 12/11/2022] Open
Abstract
Band ratio measures, computed as the ratio of power between two frequency bands, are a common analysis measure in neuroelectrophysiological recordings. Band ratio measures are typically interpreted as reflecting quantitative measures of periodic, or oscillatory, activity. This assumes that the measure reflects relative powers of distinct periodic components that are well captured by predefined frequency ranges. However, electrophysiological signals contain periodic components and a 1/f-like aperiodic component, the latter of which contributes power across all frequencies. Here, we investigate whether band ratio measures truly reflect oscillatory power differences, and/or to what extent ratios may instead reflect other periodic changes, such as in center frequency or bandwidth, and/or aperiodic activity. In simulation, we investigate how band ratio measures relate to changes in multiple spectral features, and show how multiple periodic and aperiodic features influence band ratio measures. We validate these findings in human electroencephalography (EEG) data, comparing band ratio measures to parameterizations of power spectral features and find that multiple disparate features influence ratio measures. For example, the commonly applied θ/β ratio is most reflective of differences in aperiodic activity, and not oscillatory θ or β power. Collectively, we show that periodic and aperiodic features can create the same observed changes in band ratio measures, and that this is inconsistent with their typical interpretations as measures of periodic power. We conclude that band ratio measures are a non-specific measure, conflating multiple possible underlying spectral changes, and recommend explicit parameterization of neural power spectra as a more specific approach.
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15
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Sangare A, Marchi A, Pruvost-Robieux E, Soufflet C, Crepon B, Ramdani C, Chassoux F, Turak B, Landre E, Gavaret M. The Effectiveness of Vagus Nerve Stimulation in Drug-Resistant Epilepsy Correlates with Vagus Nerve Stimulation-Induced Electroencephalography Desynchronization. Brain Connect 2020; 10:566-577. [PMID: 33073582 PMCID: PMC7757623 DOI: 10.1089/brain.2020.0798] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Introduction: VNS is an adjunctive neuromodulation therapy for patients with drug-refractory epilepsy. The antiseizure effect of VNS is thought to be related to a diffuse modulation of functional connectivity but remains to be confirmed. Aim: To investigate electroencephalographic (EEG) metrics of functional connectivity in patients with drug-refractory epilepsy treated by vagus nerve stimulation (VNS), between VNS-stimulated “ON” and nonstimulated “OFF” periods and between responder (R) and nonresponder (NR) patients. Methods: Scalp-EEG was performed for 35 patients treated by VNS, using 21 channels and 2 additional electrodes on the neck to detect the VNS stimulation. Patients were defined as VNS responders if a reduction of seizure frequency of ∼50% was documented. We analyzed the synchronization in EEG time series during “ON” and “OFF” periods of stimulation, using average phase lag index (PLI) in signal space and phase-locking value (PLV) between 10 sources. Based on graph theory, we computed brain network models and analyzed minimum spanning tree (MST) for responder and nonresponder patients. Results: Among 35 patients treated by VNS for a median time of 7 years (range 4 months to 22 years), 20 were R and 15 were NR. For responder patients, PLI during ON periods was significantly lower than that during OFF periods in delta (p = 0.009), theta (p = 0.02), and beta (p = 0.04) frequency bands. For nonresponder patients, there were no significant differences between ON and OFF periods. Moreover, variations of seizure frequency with VNS correlated with the PLI OFF/ON ratio in delta (p = 0.02), theta (p = 0.04), and beta (p = 0.03) frequency bands. Our results were confirmed using PLV in theta band (p < 0.05). No significant differences in MST were observed between R and NR patients. Conclusion: The correlation between VNS-induced interictal EEG time-series desynchronization and decrease in seizure frequency suggested that VNS therapeutic impact might be related to changes in interictal functional connectivity.
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Affiliation(s)
- Aude Sangare
- Neurophysiology Department, GHU Paris Psychiatrie et Neurosciences, Sainte-Anne Hospital, Paris, France
| | - Angela Marchi
- Neurophysiology Department, GHU Paris Psychiatrie et Neurosciences, Sainte-Anne Hospital, Paris, France
| | - Estelle Pruvost-Robieux
- Neurophysiology Department, GHU Paris Psychiatrie et Neurosciences, Sainte-Anne Hospital, Paris, France.,Université de Paris, Paris, France
| | - Christine Soufflet
- Neurophysiology Department, GHU Paris Psychiatrie et Neurosciences, Sainte-Anne Hospital, Paris, France
| | - Benoit Crepon
- Neurophysiology Department, GHU Paris Psychiatrie et Neurosciences, Sainte-Anne Hospital, Paris, France
| | - Céline Ramdani
- Institut de Recherche Biomédicale des Armées (IRBA), Paris, France
| | - Francine Chassoux
- Neurosurgery and Epileptology Department, GHU Paris Psychiatrie et Neurosciences, Sainte-Anne Hospital, Paris, France
| | - Baris Turak
- Neurosurgery and Epileptology Department, GHU Paris Psychiatrie et Neurosciences, Sainte-Anne Hospital, Paris, France
| | - Elisabeth Landre
- Neurosurgery and Epileptology Department, GHU Paris Psychiatrie et Neurosciences, Sainte-Anne Hospital, Paris, France
| | - Martine Gavaret
- Neurophysiology Department, GHU Paris Psychiatrie et Neurosciences, Sainte-Anne Hospital, Paris, France.,Université de Paris, Paris, France.,INSERM UMR 1266, IPNP, Paris, France
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16
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Geraedts V, van Hilten J, Marinus J, Mosch A, Naarding K, Hoffmann C, van der Gaag N, Contarino M. Stimulation challenge test after STN DBS improves satisfaction in Parkinson's disease patients. Parkinsonism Relat Disord 2019; 69:30-33. [DOI: 10.1016/j.parkreldis.2019.10.014] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/17/2019] [Revised: 10/14/2019] [Accepted: 10/14/2019] [Indexed: 11/25/2022]
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17
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Geraedts VJ, Boon LI, Marinus J, Gouw AA, van Hilten JJ, Stam CJ, Tannemaat MR, Contarino MF. Clinical correlates of quantitative EEG in Parkinson disease: A systematic review. Neurology 2018; 91:871-883. [PMID: 30291182 DOI: 10.1212/wnl.0000000000006473] [Citation(s) in RCA: 80] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
OBJECTIVE To assess the relevance of quantitative EEG (qEEG) measures as outcomes of disease severity and progression in Parkinson disease (PD). METHODS Main databases were systematically searched (January 2018) for studies of sufficient methodologic quality that examined correlations between clinical symptoms of idiopathic PD and cortical (surface) qEEG metrics. RESULTS Thirty-six out of 605 identified studied were included. Results were classified into 4 domains: cognition (23 studies), motor function (13 studies), responsiveness to interventions (7 studies), and other (10 studies). In cross-sectional studies, EEG slowing correlated with global cognitive impairment and with diffuse deterioration in other domains. In longitudinal studies, decreased dominant frequency and increased θ power, reflecting EEG slowing, were biomarkers of cognitive deterioration at an individual level. Results on motor dysfunction and treatment yielded contrasting findings. Studies on functional connectivity at an individual level and longitudinal studies on other domains or on connectivity measures were lacking. CONCLUSION qEEG measures reflecting EEG slowing, particularly decreased dominant frequency and increased θ power, correlate with cognitive impairment and predict future cognitive deterioration. qEEG could provide reliable and widely available biomarkers for nonmotor disease severity and progression in PD, potentially promoting early diagnosis of nonmotor symptoms and an objective monitoring of progression. More studies are needed to clarify the role of functional connectivity and network analyses.
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Affiliation(s)
- Victor J Geraedts
- From the Department of Neurology (V.J.G., J.M., J.J.v.H., M.R.T., M.F.C.), Leiden University Medical Center; Department of Clinical Neurophysiology and MEG Center (V.J.G., L.I.B., A.A.G., C.J.S.) and Alzheimer Center, Department of Neurology (A.A.G.), VU University Medical Center, Amsterdam; and Department of Neurology (M.F.C.), Haga Teaching Hospital, The Hague, the Netherlands
| | - Lennard I Boon
- From the Department of Neurology (V.J.G., J.M., J.J.v.H., M.R.T., M.F.C.), Leiden University Medical Center; Department of Clinical Neurophysiology and MEG Center (V.J.G., L.I.B., A.A.G., C.J.S.) and Alzheimer Center, Department of Neurology (A.A.G.), VU University Medical Center, Amsterdam; and Department of Neurology (M.F.C.), Haga Teaching Hospital, The Hague, the Netherlands
| | - Johan Marinus
- From the Department of Neurology (V.J.G., J.M., J.J.v.H., M.R.T., M.F.C.), Leiden University Medical Center; Department of Clinical Neurophysiology and MEG Center (V.J.G., L.I.B., A.A.G., C.J.S.) and Alzheimer Center, Department of Neurology (A.A.G.), VU University Medical Center, Amsterdam; and Department of Neurology (M.F.C.), Haga Teaching Hospital, The Hague, the Netherlands
| | - Alida A Gouw
- From the Department of Neurology (V.J.G., J.M., J.J.v.H., M.R.T., M.F.C.), Leiden University Medical Center; Department of Clinical Neurophysiology and MEG Center (V.J.G., L.I.B., A.A.G., C.J.S.) and Alzheimer Center, Department of Neurology (A.A.G.), VU University Medical Center, Amsterdam; and Department of Neurology (M.F.C.), Haga Teaching Hospital, The Hague, the Netherlands
| | - Jacobus J van Hilten
- From the Department of Neurology (V.J.G., J.M., J.J.v.H., M.R.T., M.F.C.), Leiden University Medical Center; Department of Clinical Neurophysiology and MEG Center (V.J.G., L.I.B., A.A.G., C.J.S.) and Alzheimer Center, Department of Neurology (A.A.G.), VU University Medical Center, Amsterdam; and Department of Neurology (M.F.C.), Haga Teaching Hospital, The Hague, the Netherlands
| | - Cornelis J Stam
- From the Department of Neurology (V.J.G., J.M., J.J.v.H., M.R.T., M.F.C.), Leiden University Medical Center; Department of Clinical Neurophysiology and MEG Center (V.J.G., L.I.B., A.A.G., C.J.S.) and Alzheimer Center, Department of Neurology (A.A.G.), VU University Medical Center, Amsterdam; and Department of Neurology (M.F.C.), Haga Teaching Hospital, The Hague, the Netherlands
| | - Martijn R Tannemaat
- From the Department of Neurology (V.J.G., J.M., J.J.v.H., M.R.T., M.F.C.), Leiden University Medical Center; Department of Clinical Neurophysiology and MEG Center (V.J.G., L.I.B., A.A.G., C.J.S.) and Alzheimer Center, Department of Neurology (A.A.G.), VU University Medical Center, Amsterdam; and Department of Neurology (M.F.C.), Haga Teaching Hospital, The Hague, the Netherlands.
| | - Maria Fiorella Contarino
- From the Department of Neurology (V.J.G., J.M., J.J.v.H., M.R.T., M.F.C.), Leiden University Medical Center; Department of Clinical Neurophysiology and MEG Center (V.J.G., L.I.B., A.A.G., C.J.S.) and Alzheimer Center, Department of Neurology (A.A.G.), VU University Medical Center, Amsterdam; and Department of Neurology (M.F.C.), Haga Teaching Hospital, The Hague, the Netherlands
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18
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Decreased alpha2 connectivity in EEG is correlated with the cognitive and psychiatric manifestations of Parkinson’s disease. Clin Neurophysiol 2018; 129:1712-1713. [DOI: 10.1016/j.clinph.2018.06.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2018] [Accepted: 06/07/2018] [Indexed: 11/23/2022]
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