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Liu M, Gu H, Hu J, Liu M, Luo Y, Yuan Y, Wu J, Zhou Y, Juan R, Cheng X, Zhuang S, Shen Y, Jin H, Chen J, Li K, Wang F, Liu C, Mao C. Higher cortical excitability to negative emotions involved in musculoskeletal pain in Parkinson's disease. Neurophysiol Clin 2024; 54:102936. [PMID: 38382137 DOI: 10.1016/j.neucli.2023.102936] [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: 08/14/2023] [Revised: 12/13/2023] [Accepted: 12/13/2023] [Indexed: 02/23/2024] Open
Abstract
OBJECTIVE Changes in brain structure and neurotransmitter systems are involved in pain in Parkinson's disease (PD), and emotional factors are closely related to pain. Our study applied electroencephalography (EEG) to investigate the role of emotion in PD patients with chronic musculoskeletal pain. METHODS Forty-two PD patients with chronic musculoskeletal pain and 38 without were enrolled. EEG data were recorded under resting conditions, and while viewing pictures with neutral, positive, and negative content. We compared spectrum power, functional connectivity, and late positive potential (LPP), an event-related potential (ERP), between the groups. RESULTS PD patients with pain tended to have higher scores for the Hamilton Rating Scale for Depression (HRSD). In the resting EEG, mean β-band amplitude was significantly higher in patients with pain than in those without. Logistic regression analysis showed that higher HRSD scores and higher mean β-band amplitude were associated with pain. ERP analysis revealed that the amplitudes of LPP difference waves (the absolute difference between positive and negative condition LPP and neutral condition LPP) at the central-parietal region were significantly reduced in patients with pain (P = 0.029). Spearman correlation analysis showed that the amplitudes of late (700-1000 ms) negative versus neutral condition LPP difference waves were negatively correlated with pain intensity, assessed by visual analogue scale, (r = -0.393, P = 0.010) and HRSD scores (r = -0.366, P = 0.017). CONCLUSION Dopaminergic and non-dopaminergic systems may be involved in musculoskeletal pain in PD by increasing β-band activity and weakening the connection of the θ-band at the central-parietal region. PD patients with musculoskeletal pain have higher cortical excitability to negative emotions. The changes in pain-related EEG may be used as electrophysiological markers and therapeutic targets in PD patients with chronic pain.
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Affiliation(s)
- Ming Liu
- Department of Neurology and Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, China; The First People's Hospital of Zhangjiagang City, Suzhou, China
| | - Hanying Gu
- Department of Neurology and Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Jingzhe Hu
- Department of Neurology and Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Manhua Liu
- Department of Neurology and Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Yajun Luo
- Department of Neurology and Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Yuan Yuan
- Department of Neurology and Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Jiayu Wu
- Department of Neurology and Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Yan Zhou
- Department of Neurology and Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Ru Juan
- Department of Neurology and Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Xiaoyu Cheng
- Department of Neurology and Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Sheng Zhuang
- Department of Neurology and Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Yun Shen
- Department of Neurology and Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Hong Jin
- Department of Neurology and Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Jing Chen
- Department of Neurology and Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Kai Li
- Department of Neurology and Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Fen Wang
- Jiangsu Key Laboratory of Neuropsychiatric Diseases and Institute of Neuroscience, Soochow University, Suzhou, China
| | - Chunfeng Liu
- Department of Neurology and Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, China; Jiangsu Key Laboratory of Neuropsychiatric Diseases and Institute of Neuroscience, Soochow University, Suzhou, China
| | - Chengjie Mao
- Department of Neurology and Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, China.
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Liu C, Jiang Z, Liu S, Chu C, Wang J, Liu W, Sun Y, Dong M, Shi Q, Huang P, Zhu X. Frequency-Dependent Microstate Characteristics for Mild Cognitive Impairment in Parkinson's Disease. IEEE Trans Neural Syst Rehabil Eng 2023; 31:4115-4124. [PMID: 37831557 DOI: 10.1109/tnsre.2023.3324343] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/15/2023]
Abstract
Cognitive impairment is typically reflected in the time and frequency variations of electroencephalography (EEG). Integrating time-domain and frequency-domain analysis methods is essential to better understand and assess cognitive ability. Timely identification of cognitive levels in early Parkinson's disease (ePD) patients can help mitigate the risk of future dementia. For the investigation of the brain activity and states related to cognitive levels, this study recruited forty ePD patients for EEG microstate analysis, including 13 with mild cognitive impairment (MCI) and 27 without MCI (control group). To determine the specific frequency band on which the microstate analysis relies, a deep learning framework was employed to discern the frequency dependence of the cognitive level in ePD patients. The input to the convolutional neural network consisted of the power spectral density of multi-channel multi-point EEG signals. The visualization technique of gradient-weighted class activation mapping was utilized to extract the optimal frequency band for identifying MCI samples. Within this frequency band, microstate analysis was conducted and correlated with the Montreal Cognitive Assessment (MoCA) Scale. The deep neural network revealed significant differences in the 1-11.5Hz spectrum of the ePD-MCI group compared to the control group. In this characteristic frequency band, ePD-MCI patients exhibited a pattern of global microstate disorder. The coverage rate and occurrence frequency of microstate A and D increased significantly and were both negatively correlated with the MoCA scale. Meanwhile, the coverage, frequency and duration of microstate C decreased significantly and were positively correlated with the MoCA scale. Our work unveils abnormal microstate characteristics in ePD-MCI based on time-frequency fusion, enhancing our understanding of cognitively related brain dynamics and providing electrophysiological markers for ePD-MCI recognition.
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Fischer MHF, Zibrandtsen IC, Høgh P, Musaeus CS. Systematic Review of EEG Coherence in Alzheimer's Disease. J Alzheimers Dis 2023; 91:1261-1272. [PMID: 36641665 DOI: 10.3233/jad-220508] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
BACKGROUND Magnitude-squared coherence (MSCOH) is an electroencephalography (EEG) measure of functional connectivity. MSCOH has been widely applied to investigate pathological changes in patients with Alzheimer's disease (AD). However, significant heterogeneity exists between the studies using MSOCH. OBJECTIVE We systematically reviewed the literature on MSCOH changes in AD as compared to healthy controls to investigate the clinical utility of MSCOH as a marker of AD. METHODS We searched PubMed, Embase, and Scopus to identify studies reporting EEG MSCOH used in patients with AD. The identified studies were independently screened by two researchers and the data was extracted, which included cognitive scores, preprocessing steps, and changes in MSCOH across frequency bands. RESULTS A total of 35 studies investigating changes in MSCOH in patients with AD were included in the review. Alpha coherence was significantly decreased in patients with AD in 24 out of 34 studies. Differences in other frequency bands were less consistent. Some studies showed that MSCOH may serve as a diagnostic marker of AD. CONCLUSION Reduced alpha MSCOH is present in patients with AD and MSCOH may serve as a diagnostic marker. However, studies validating MSCOH as a diagnostic marker are needed.
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Affiliation(s)
| | | | - Peter Høgh
- Department of Neurology, University Hospital of Zealand, Roskilde, Denmark.,Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Christian Sandøe Musaeus
- Department of Neurology, Danish Dementia Research Centre (DDRC), Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
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The Increase of Theta Power and Decrease of Alpha/Theta Ratio as a Manifestation of Cognitive Impairment in Parkinson's Disease. J Clin Med 2023; 12:jcm12041569. [PMID: 36836103 PMCID: PMC9965386 DOI: 10.3390/jcm12041569] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 02/06/2023] [Accepted: 02/13/2023] [Indexed: 02/18/2023] Open
Abstract
In this study, we aim to assess and examine cognitive functions in Parkinson's Disease patients using EEG recordings, with a central focus on characteristics associated with a cognitive decline. Based on neuropsychological evaluation using Mini-Mental State Examination, Montreal Cognitive Assessment, and Addenbrooke's Cognitive Examination-III, 98 participants were divided into three cognitive groups. All the particpants of the study underwent EEG recordings with spectral analysis. The results revealed an increase in the absolute theta power in patients with Parkinson's disease dementia (PD-D) compared to cognitively normal status (PD-CogN, p=0.00997) and a decrease in global relative beta power in PD-D compared to PD-CogN (p=0.0413). An increase in theta relative power in the left temporal region (p=0.0262), left occipital region (p=0.0109), and right occipital region (p=0.0221) were observed in PD-D compared to PD-N. The global alpha/theta ratio and global power spectral ratio significantly decreased in PD-D compared to PD-N (p = 0.001). In conclusion, the increase in relative theta power and the decrease in relative beta power are characteristic changes in EEG recordings in PD patients with cognitive impairment. Identifying these changes can be a useful biomarker and a complementary tool in the neuropsychological diagnosis of cognitive impairment in Parkinson's Disease.
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Liu H, Huang Z, Deng B, Chang Z, Yang X, Guo X, Yuan F, Yang Q, Wang L, Zou H, Li M, Zhu Z, Jin K, Wang Q. QEEG Signatures are Associated with Nonmotor Dysfunctions in Parkinson's Disease and Atypical Parkinsonism: An Integrative Analysis. Aging Dis 2023; 14:204-218. [PMID: 36818554 PMCID: PMC9937709 DOI: 10.14336/ad.2022.0514] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2022] [Accepted: 05/14/2022] [Indexed: 11/18/2022] Open
Abstract
Parkinson's disease (PD) and atypical parkinsonism (AP), including progressive supranuclear palsy (PSP) and multiple system atrophy (MSA), share similar nonmotor symptoms. Quantitative electroencephalography (QEEG) can be used to examine the nonmotor symptoms. This study aimed to characterize the patterns of QEEG and functional connectivity (FC) that differentiate PD from PSP or MSA, and explore the correlation between the differential QEEG indices and nonmotor dysfunctions in PD and AP. We enrolled 52 patients with PD, 31 with MSA, 22 with PSP, and 50 age-matched health controls to compare QEEG indices among specific brain regions. One-way analysis of variance was applied to assess QEEG indices between groups; Spearman's correlations were used to examine the relationship between QEEG indices and nonmotor symptoms scale (NMSS) and mini-mental state examination (MMSE). FCs using weighted phase lag index were compared between patients with PD and those with MSA/PSP. Patients with PSP revealed higher scores on the NMSS and lower MMSE scores than those with PD and MSA, with similar disease duration. The delta and theta powers revealed a significant increase in PSP, followed by PD and MSA. Patients with PD presented a significantly lower slow-to-fast ratio than those with PSP in the frontal region, while patients with PD presented significantly higher EEG-slowing indices than patients with MSA. The frontal slow-to-fast ratio showed a negative correlation with MMSE scores in patients with PD and PSP, and a positive correlation with NMSS in the perception and mood domain in patients with PSP but not in those with PD. Compared to PD, MSA presented enhanced FC in theta and delta bands in the posterior region, while PSP revealed decreased FC in the delta band within the frontal-temporal cortex. These findings suggest that QEEG might be a useful tool for evaluating the nonmotor dysfunctions in PD and AP. Our QEEG results suggested that with similar disease duration, the cortical neurodegenerative process was likely exacerbated in patients with PSP, followed by those with PD, and lastly in patients with MSA.
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Affiliation(s)
- Hailing Liu
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, China.,Department of Neurology, Maoming People's Hospital, Maoming, Guangdong, China.
| | - Zifeng Huang
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, China.
| | - Bin Deng
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, China.
| | - Zihan Chang
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, China.
| | - Xiaohua Yang
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, China.
| | - Xingfang Guo
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, China.
| | - Feilan Yuan
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, China.
| | - Qin Yang
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, China.
| | - Liming Wang
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
| | - Haiqiang Zou
- Department of Neurosurgery, General Hospital of Southern Theater Command of PLA, Guangdong, China.
| | - Mengyan Li
- Department of Neurology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China.
| | - Zhaohua Zhu
- Clinical Research Centre, Orthopedic Centre, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, China.
| | - Kunlin Jin
- Department of Pharmacology and Neuroscience, University of North Texas Health Science Center, Fort Worth, TX 76107, USA
| | - Qing Wang
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, China.,Correspondence should be addressed to: Dr. Qing Wang, Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong 510282, China. .
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6
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Lopez S, Del Percio C, Lizio R, Noce G, Padovani A, Nobili F, Arnaldi D, Famà F, Moretti DV, Cagnin A, Koch G, Benussi A, Onofrj M, Borroni B, Soricelli A, Ferri R, Buttinelli C, Giubilei F, Güntekin B, Yener G, Stocchi F, Vacca L, Bonanni L, Babiloni C. Patients with Alzheimer's disease dementia show partially preserved parietal 'hubs' modeled from resting-state alpha electroencephalographic rhythms. Front Aging Neurosci 2023; 15:780014. [PMID: 36776437 PMCID: PMC9908964 DOI: 10.3389/fnagi.2023.780014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Accepted: 01/05/2023] [Indexed: 01/28/2023] Open
Abstract
Introduction Graph theory models a network by its nodes (the fundamental unit by which graphs are formed) and connections. 'Degree' hubs reflect node centrality (the connection rate), while 'connector' hubs are those linked to several clusters of nodes (mainly long-range connections). Methods Here, we compared hubs modeled from measures of interdependencies of between-electrode resting-state eyes-closed electroencephalography (rsEEG) rhythms in normal elderly (Nold) and Alzheimer's disease dementia (ADD) participants. At least 5 min of rsEEG was recorded and analyzed. As ADD is considered a 'network disease' and is typically associated with abnormal rsEEG delta (<4 Hz) and alpha rhythms (8-12 Hz) over associative posterior areas, we tested the hypothesis of abnormal posterior hubs from measures of interdependencies of rsEEG rhythms from delta to gamma bands (2-40 Hz) using eLORETA bivariate and multivariate-directional techniques in ADD participants versus Nold participants. Three different definitions of 'connector' hub were used. Results Convergent results showed that in both the Nold and ADD groups there were significant parietal 'degree' and 'connector' hubs derived from alpha rhythms. These hubs had a prominent outward 'directionality' in the two groups, but that 'directionality' was lower in ADD participants than in Nold participants. Discussion In conclusion, independent methodologies and hub definitions suggest that ADD patients may be characterized by low outward 'directionality' of partially preserved parietal 'degree' and 'connector' hubs derived from rsEEG alpha rhythms.
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Affiliation(s)
- Susanna Lopez
- Department of Physiology and Pharmacology “Vittorio Erspamer”, Sapienza University of Rome, Rome, Italy,*Correspondence: Susanna Lopez, ✉
| | - Claudio Del Percio
- Department of Physiology and Pharmacology “Vittorio Erspamer”, Sapienza University of Rome, Rome, Italy
| | - Roberta Lizio
- Department of Physiology and Pharmacology “Vittorio Erspamer”, Sapienza University of Rome, Rome, Italy
| | | | - Alessandro Padovani
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Flavio Nobili
- Clinica Neurologica, IRCCS Ospedale Policlinico San Martino, Genova, Italy,Dipartimento di Neuroscienze, Oftalmologia, Genetica, Riabilitazione e Scienze Materno-infantili (DiNOGMI), Università di Genova, Genova, Italy
| | - Dario Arnaldi
- Clinica Neurologica, IRCCS Ospedale Policlinico San Martino, Genova, Italy,Dipartimento di Neuroscienze, Oftalmologia, Genetica, Riabilitazione e Scienze Materno-infantili (DiNOGMI), Università di Genova, Genova, Italy
| | - Francesco Famà
- Dipartimento di Neuroscienze, Oftalmologia, Genetica, Riabilitazione e Scienze Materno-infantili (DiNOGMI), Università di Genova, Genova, Italy
| | - Davide V. Moretti
- Alzheimer’s Disease Rehabilitation Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | | | - Giacomo Koch
- Non-Invasive Brain Stimulation Unit/Department of Behavioral and Clinical Neurology, Santa Lucia Foundation IRCCS, Rome, Italy,Stroke Unit, Department of Neuroscience, Tor Vergata Policlinic, Rome, Italy
| | - Alberto Benussi
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Marco Onofrj
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University “G. D’Annunzio” of Chieti-Pescara, Chieti, Italy
| | - Barbara Borroni
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Andrea Soricelli
- IRCCS Synlab SDN, Naples, Italy,Department of Motor Sciences and Healthiness, University of Naples Parthenope, Naples, Italy
| | | | - Carla Buttinelli
- Department of Neuroscience, Mental Health and Sensory Organs, Sapienza University of Rome, Rome, Italy
| | - Franco Giubilei
- Department of Neuroscience, Mental Health and Sensory Organs, Sapienza University of Rome, Rome, Italy
| | - Bahar Güntekin
- Department of Biophysics, School of Medicine, Istanbul Medipol University, Istanbul, Türkiye,Research Institute for Health Sciences and Technologies (SABITA), Istanbul Medipol University, Istanbul, Türkiye
| | - Görsev Yener
- Department of Neurology, Dokuz Eylül University Medical School, Izmir, Türkiye,Faculty of Medicine, Izmir University of Economics, Izmir, Türkiye
| | - Fabrizio Stocchi
- Institute for Research and Medical Care, IRCCS San Raffaele Roma, Rome, Italy,Telematic University San Raffaele, Rome, Italy
| | - Laura Vacca
- Institute for Research and Medical Care, IRCCS San Raffaele Roma, Rome, Italy
| | - Laura Bonanni
- Department of Medicine and Aging Sciences, University G. D’Annunzio of Chieti-Pescara, Chieti, Italy
| | - Claudio Babiloni
- Department of Physiology and Pharmacology “Vittorio Erspamer”, Sapienza University of Rome, Rome, Italy,San Raffaele of Cassino, Cassino, Italy
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Buján A, Sampaio A, Pinal D. Resting-state electroencephalographic correlates of cognitive reserve: Moderating the age-related worsening in cognitive function. Front Aging Neurosci 2022; 14:854928. [PMID: 36185469 PMCID: PMC9521492 DOI: 10.3389/fnagi.2022.854928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Accepted: 08/08/2022] [Indexed: 11/23/2022] Open
Abstract
This exploratory study aimed to investigate the resting-state electroencephalographic (rsEEG) correlates of the cognitive reserve from a life span perspective. Current source density (CSD) and lagged-linear connectivity (LLC) measures were assessed to this aim. We firstly explored the relationship between rsEEG measures for the different frequency bands and a socio-behavioral proxy of cognitive reserve, the Cognitive Reserve Index (CRI). Secondly, we applied moderation analyses to assess whether any of the correlated rsEEG measures showed a moderating role in the relationship between age and cognitive function. Moderate negative correlations were found between the CRI and occipital CSD of delta and beta 2. Moreover, inter- and intrahemispheric LLC measures were correlated with the CRI, showing a negative association with delta and positive associations with alpha 1, beta 1, and beta 2. Among those correlated measures, just two rsEEG variables were significant moderators of the relationship between age and cognition: occipital delta CSD and right hemispheric beta 2 LLC between occipital and limbic regions. The effect of age on cognitive performance was stronger for higher values of both measures. Therefore, lower values of occipital delta CSD and lower beta 2 LLC between right occipital and limbic regions might protect or compensate for the effects of age on cognition. Results of this exploratory study might be helpful to allocate more preventive efforts to curb the progression of cognitive decline in adults with less CR, possibly characterized by these rsEEG parameters at a neural level. However, given the exploratory nature of this study, more conclusive work on these rsEEG measures is needed to firmly establish their role in the cognition–age relationship, for example, verifying if these measures moderate the relationship between brain structure and cognition.
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Parmera JB, Tumas V, Ferraz HB, Spitz M, Barbosa MT, Smid J, Barbosa BJAP, Schilling LP, Balthazar MLF, Souza LCD, Vale FAC, Caramelli P, Bertolucci PHF, Chaves MLF, Brucki SMD, Nitrini R, Castilhos RM, Frota NAF. Diagnóstico e manejo da demência da doença de Parkinson e demência com corpos de Lewy: recomendações do Departamento Científico de Neurologia Cognitiva e do Envelhecimento da Academia Brasileira de Neurologia. Dement Neuropsychol 2022; 16:73-87. [DOI: 10.1590/1980-5764-dn-2022-s105pt] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Revised: 10/13/2021] [Accepted: 04/27/2022] [Indexed: 11/29/2022] Open
Abstract
RESUMO A demência da doença de Parkinson (DDP) e a demência com corpos de Lewy (DCL) representam a segunda causa mais comum de demência neurodegenerativa em pessoas com mais de 65 anos, ocasionando progressivo declínio cognitivo e comprometimento da qualidade de vida. O presente estudo tem como objetivo prover um consenso de especialistas sobre a DDP e DCL, baseado em revisão sistemática da literatura brasileira e revisão não-sistemática de literatura internacional. Ademais, tal estudo visa promover informação e conceder recomendações sobre abordagem diagnóstica, com foco nos níveis de atenção primária e secundária em saúde. Com base nos dados disponíveis, recomendamos que os profissionais realizem pelo menos um breve instrumento cognitivo global, como o Mini-Exame do Estado Mental, contudo de preferência optem pela Avaliação Cognitiva de Montreal e o Exame Cognitivo de Addenbrooke-Revisado. Observa-se uma carência de instrumentos validados para a avaliação precisa das habilidades funcionais em pacientes brasileiros com DDP e DCL. Além disso, mais estudos focando em biomarcadores com coortes brasileiras também são necessários.
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Affiliation(s)
| | | | | | | | - Maira Tonidandel Barbosa
- Universidade Federal de Minas Gerais, Brasil; Faculdade Ciências Médicas de Minas Gerais, Brasil
| | | | - Breno José Alencar Pires Barbosa
- Universidade de São Paulo, Brasil; Universidade Federal de Pernambuco, Brasil; Instituto de Medicina Integral Prof. Fernando Figueira, Brasil
| | - Lucas Porcello Schilling
- Pontifícia Universidade do Rio Grande do Sul, Brasil; Pontifícia Universidade do Rio Grande do Sul, Brasil; Pontifícia Universidade do Rio Grande do Sul, Brasil
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9
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Parmera JB, Tumas V, Ferraz HB, Spitz M, Barbosa MT, Smid J, Barbosa BJAP, Schilling LP, Balthazar MLF, Souza LCD, Vale FAC, Caramelli P, Bertolucci PHF, Chaves MLF, Brucki SMD, Nitrini R, Castilhos RM, Frota NAF. Diagnosis and management of Parkinson’s disease dementia and dementia with Lewy bodies: recommendations of the Scientific Department of Cognitive Neurology and Aging of the Brazilian Academy of Neurology. Dement Neuropsychol 2022. [DOI: 10.1590/1980-5764-dn-2022-s105en] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
ABSTRACT Parkinson’s disease dementia (PDD) and dementia with Lewy bodies (DLB) represent the second most common type of degenerative dementia in patients aged 65 years and older, leading to progressive cognitive dysfunction and impaired quality of life. This study aims to provide a consensus based on a systematic Brazilian literature review and a comprehensive international review concerning PDD and DLB. Moreover, we sought to report on and give recommendations about the best diagnostic approaches focusing on primary and secondary care. Based on the available data, we recommend clinicians to apply at least one brief global cognitive instrument to assess PDD, such as the Mini-Mental State Examination and preferably the Montreal Cognitive Assessment and the Addenbrooke’s Cognitive Examination-Revised. Validated instruments to accurately assess functional abilities in Brazilian PD patients are still incipient. Further studies should focus on biomarkers with Brazilian cohorts.
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Affiliation(s)
| | | | | | | | - Maira Tonidandel Barbosa
- Universidade Federal de Minas Gerais, Brasil; Faculdade Ciências Médicas de Minas Gerais, Brasil
| | | | - Breno José Alencar Pires Barbosa
- Universidade de São Paulo, Brasil; Universidade Federal de Pernambuco, Brasil; Instituto de Medicina Integral Prof. Fernando Figueira, Brasil
| | - Lucas Porcello Schilling
- Pontifícia Universidade do Rio Grande do Sul, Brasil; Pontifícia Universidade do Rio Grande do Sul, Brasil; Pontifícia Universidade do Rio Grande do Sul, Brasil
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10
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Wu EQ, Peng XY, Chen SD, Zhao XY, Tang ZR. Detecting Alzheimer’s Dementia Degree. IEEE Trans Cogn Dev Syst 2022. [DOI: 10.1109/tcds.2020.3015131] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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11
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Weighted Brain Network Analysis on Different Stages of Clinical Cognitive Decline. Bioengineering (Basel) 2022; 9:bioengineering9020062. [PMID: 35200415 PMCID: PMC8869328 DOI: 10.3390/bioengineering9020062] [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: 12/14/2021] [Revised: 01/26/2022] [Accepted: 01/29/2022] [Indexed: 11/25/2022] Open
Abstract
This study addresses brain network analysis over different clinical severity stages of cognitive dysfunction using electroencephalography (EEG). We exploit EEG data of subjective cognitive impairment (SCI) patients, mild cognitive impairment (MCI) patients and Alzheimer’s disease (AD) patients. We propose a new framework to study the topological networks with a spatiotemporal entropy measure for estimating the connectivity. Our results show that functional connectivity and graph analysis are frequency-band dependent, and alterations start at the MCI stage. In delta, the SCI group exhibited a decrease of clustering coefficient and an increase of path length compared to MCI and AD. In alpha, the opposite behavior appeared, suggesting a rapid and high efficiency in information transmission across the SCI network. Modularity analysis showed that electrodes of the same brain region were distributed over several modules, and some obtained modules in SCI were extended from anterior to posterior regions. These results demonstrate that the SCI network was more resilient to neuronal damage compared to that of MCI and even more compared to that of AD. Finally, we confirm that MCI is a transitional stage between SCI and AD, with a predominance of high-strength intrinsic connectivity, which may reflect the compensatory response to the neuronal damage occurring early in the disease process.
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Polverino P, Ajčević M, Catalan M, Mazzon G, Bertolotti C, Manganotti P. Brain oscillatory patterns in mild cognitive impairment due to Alzheimer’s and Parkinson’s disease: an exploratory high-density EEG study. Clin Neurophysiol 2022; 138:1-8. [DOI: 10.1016/j.clinph.2022.01.136] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Revised: 12/08/2021] [Accepted: 01/31/2022] [Indexed: 01/06/2023]
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A Comparative Study of Functional Connectivity Measures for Brain Network Analysis in the Context of AD Detection with EEG. ENTROPY 2021; 23:e23111553. [PMID: 34828251 PMCID: PMC8623641 DOI: 10.3390/e23111553] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Revised: 11/12/2021] [Accepted: 11/17/2021] [Indexed: 12/15/2022]
Abstract
This work addresses brain network analysis considering different clinical severity stages of cognitive dysfunction, based on resting-state electroencephalography (EEG). We use a cohort acquired in real-life clinical conditions, which contains EEG data of subjective cognitive impairment (SCI) patients, mild cognitive impairment (MCI) patients, and Alzheimer’s disease (AD) patients. We propose to exploit an epoch-based entropy measure to quantify the connectivity links in the networks. This entropy measure relies on a refined statistical modeling of EEG signals with Hidden Markov Models, which allow a better estimation of the spatiotemporal characteristics of EEG signals. We also propose to conduct a comparative study by considering three other measures largely used in the literature: phase lag index, coherence, and mutual information. We calculated such measures at different frequency bands and computed different local graph parameters considering different proportional threshold values for a binary network analysis. After applying a feature selection procedure to determine the most relevant features for classification performance with a linear Support Vector Machine algorithm, our study demonstrates the effectiveness of the statistical entropy measure for analyzing the brain network in patients with different stages of cognitive dysfunction.
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Zinn MA, Jason LA. Cortical autonomic network connectivity predicts symptoms in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Int J Psychophysiol 2021; 170:89-101. [PMID: 34662673 DOI: 10.1016/j.ijpsycho.2021.10.004] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 09/17/2021] [Accepted: 10/08/2021] [Indexed: 01/28/2023]
Abstract
Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) represents a significant public health challenge given the presence of many unexplained patient symptoms. Research has shown that many features in ME/CFS may result from a dysfunctional autonomic nervous system (ANS). We explored the role of the cortical autonomic network (CAN) involved in higher-order control of ANS functioning in 34 patients with ME/CFS and 34 healthy controls under task-free conditions. All participants underwent resting-state quantitative electroencephalographic (qEEG) scalp recordings during an eyes-closed condition. Source analysis was performed using exact low-resolution electromagnetic tomography (eLORETA), and lagged coherence was used to estimate intrinsic functional connectivity between each node across 7 frequency bands: delta (1-3 Hz), theta (4-7 Hz), alpha-1 (8-10 Hz), alpha-2 (10-12 Hz), beta-1 (13-18 Hz), beta-2 (19-21 Hz), and beta-3 (22-30 Hz). Symptom ratings were measured using the DePaul Symptom Questionnaire and the Short Form (SF-36) health survey. Graph theoretical analysis of weighted, undirected connections revealed significant group differences in baseline CAN organization. Regression results showed that cognitive, affective, and somatomotor symptom cluster ratings were associated with alteration to CAN topology in patients, depending on the frequency band. These findings provide evidence for reduced higher-order homeostatic regulation and adaptability in ME/CFS. If confirmed, these findings address the CAN as a potential therapeutic target for managing patient symptoms.
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Affiliation(s)
- Mark A Zinn
- DePaul University, Center for Community Research, 990 W. Fullerton Ave., Chicago, IL 60614, United States of America.
| | - Leonard A Jason
- DePaul University, Center for Community Research, 990 W. Fullerton Ave., Chicago, IL 60614, United States of America
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Livinț Popa L, Dragoș HM, Strilciuc Ș, Pantelemon C, Mureșanu I, Dina C, Văcăraș V, Mureșanu D. Added Value of QEEG for the Differential Diagnosis of Common Forms of Dementia. Clin EEG Neurosci 2021; 52:201-210. [PMID: 33166175 DOI: 10.1177/1550059420971122] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
INTRODUCTION Quantitative electroencephalography (QEEG) has been documented as a helpful tool in the differential diagnosis of Alzheimer's disease (AD) with common forms of dementia. The main objective of the study was to assess the role of QEEG in AD differential diagnosis with other forms of dementia: Lewy body dementia (LBD), Parkinson's disease dementia (PDD), frontotemporal dementia (FTD), and vascular dementia (VaD). METHODS We searched PubMed, Embase, and PsycNET, for articles in English published in peer-reviewed journals from January 1, 1980 to April 23, 2019 using adapted search strategies containing keywords quantitative EEG and Alzheimer. The risk of bias was assessed by applying the QUADAS tool. The systematic review was conducted in line with the PRISMA methodology. RESULTS We identified 10 articles showcasing QEEG features used in diagnosing dementia, EEG slowing phenomena in AD and PDD, coherence changes in AD and VaD, the role of LORETA in dementia, and the controversial QEEG pattern in FTD. Results vary significantly in terms of sociodemographic features of the studied population, neuropsychological assessment, signal acquisition and processing, and methods of analysis. DISCUSSION This article provides a comparative synthesis of existing evidence on the role of QEEG in diagnosing dementia, highlighting some specific features for different types of dementia (eg, the slow-wave activity has been remarked in both AD and PDD, but more pronounced in PDD patients, a diminution in anterior and posterior alpha coherence was noticed in AD, and a lower alpha coherence in the left temporal-parietal-occipital regions was observed in VaD). CONCLUSION QEEG may be a useful investigation for settling the diagnosis of common forms of dementia. Further research of quantitative analyses is warranted, particularly on the association between QEEG, neuropsychological, and imaging features. In conjunction, these methods may provide superior diagnostic accuracy in the diagnosis of dementia.
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Affiliation(s)
- Livia Livinț Popa
- Department of Neurosciences, 37576"Iuliu Hatieganu" University of Medicine and Pharmacy, Cluj-Napoca, Cluj, Romania.,RoNeuro Institute for Neurological Research and Diagnostic, Cluj-Napoca, Cluj, Romania
| | - Hanna-Maria Dragoș
- RoNeuro Institute for Neurological Research and Diagnostic, Cluj-Napoca, Cluj, Romania
| | - Ștefan Strilciuc
- Department of Neurosciences, 37576"Iuliu Hatieganu" University of Medicine and Pharmacy, Cluj-Napoca, Cluj, Romania.,RoNeuro Institute for Neurological Research and Diagnostic, Cluj-Napoca, Cluj, Romania
| | - Cristina Pantelemon
- Department of Neurosciences, 37576"Iuliu Hatieganu" University of Medicine and Pharmacy, Cluj-Napoca, Cluj, Romania.,RoNeuro Institute for Neurological Research and Diagnostic, Cluj-Napoca, Cluj, Romania
| | - Ioana Mureșanu
- Department of Neurosciences, 37576"Iuliu Hatieganu" University of Medicine and Pharmacy, Cluj-Napoca, Cluj, Romania.,RoNeuro Institute for Neurological Research and Diagnostic, Cluj-Napoca, Cluj, Romania
| | - Constantin Dina
- 112969Faculty of Medicine, "Ovidius University," Constanta, Romania
| | - Vitalie Văcăraș
- Department of Neurosciences, 37576"Iuliu Hatieganu" University of Medicine and Pharmacy, Cluj-Napoca, Cluj, Romania.,RoNeuro Institute for Neurological Research and Diagnostic, Cluj-Napoca, Cluj, Romania
| | - Dafin Mureșanu
- Department of Neurosciences, 37576"Iuliu Hatieganu" University of Medicine and Pharmacy, Cluj-Napoca, Cluj, Romania.,RoNeuro Institute for Neurological Research and Diagnostic, Cluj-Napoca, Cluj, Romania
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Liu W, Zhang R, Feng H, Zhu H. Fluoxetine tunes the abnormal hippocampal oscillations in association with cognitive impairments in 6-OHDA lesioned rats. Behav Brain Res 2021; 409:113314. [PMID: 33894299 DOI: 10.1016/j.bbr.2021.113314] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Revised: 04/15/2021] [Accepted: 04/19/2021] [Indexed: 11/16/2022]
Abstract
Cognitive decline is a common clinical symptom in Parkinson's disease (PD) patients. Fluoxetine (FLU), a selective serotonin reuptake inhibitor, can improve cognitive deficits in demented patients. The present study investigated the effects of FLU on spatial learning and memory cognitions in 6-OHDA lesioned rats. Morris water maze (MWM) test showed that FLU significantly improved spatial cognitive deficits in rats with unilateral 6-OHDA injection at 4 and 7 weeks after 6-OHDA injection. Electrophysiological recordings demonstrated that the number and duration of high voltage spindles(HVSs)in the ipsilateral hippocampus of 6-OHDA lesioned rats were decreased by the administration of FLU. Furthermore, the spectral analysis of per frequency revealed increases in δ and θ rhythm power and decreases in α, β and γ rhythm power in the ipsilateral hippocampus of 6-OHDA lesioned rats in contrast to the saline-treated rats. Acute FLU treatment can reduce δ and θ rhythm power, and enhance α, β and γ rhythm power in the ipsilateral hippocampus of 6-OHDA lesioned rats. These findings suggest that FLU improves impaired cognition by tuning oscillatory activities in the hippocampus of 6-OHDA lesioned rats.
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Affiliation(s)
- Weitang Liu
- School of Life Science, Shanghai University, Shanghai, China
| | - Renxing Zhang
- School of Life Science, Shanghai University, Shanghai, China
| | - Hu Feng
- School of Life Science, Shanghai University, Shanghai, China
| | - Hongyan Zhu
- School of Life Science, Shanghai University, Shanghai, China.
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17
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Babiloni C, Arakaki X, Azami H, Bennys K, Blinowska K, Bonanni L, Bujan A, Carrillo MC, Cichocki A, de Frutos-Lucas J, Del Percio C, Dubois B, Edelmayer R, Egan G, Epelbaum S, Escudero J, Evans A, Farina F, Fargo K, Fernández A, Ferri R, Frisoni G, Hampel H, Harrington MG, Jelic V, Jeong J, Jiang Y, Kaminski M, Kavcic V, Kilborn K, Kumar S, Lam A, Lim L, Lizio R, Lopez D, Lopez S, Lucey B, Maestú F, McGeown WJ, McKeith I, Moretti DV, Nobili F, Noce G, Olichney J, Onofrj M, Osorio R, Parra-Rodriguez M, Rajji T, Ritter P, Soricelli A, Stocchi F, Tarnanas I, Taylor JP, Teipel S, Tucci F, Valdes-Sosa M, Valdes-Sosa P, Weiergräber M, Yener G, Guntekin B. Measures of resting state EEG rhythms for clinical trials in Alzheimer's disease: Recommendations of an expert panel. Alzheimers Dement 2021; 17:1528-1553. [PMID: 33860614 DOI: 10.1002/alz.12311] [Citation(s) in RCA: 64] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Revised: 12/28/2020] [Accepted: 01/01/2021] [Indexed: 12/25/2022]
Abstract
The Electrophysiology Professional Interest Area (EPIA) and Global Brain Consortium endorsed recommendations on candidate electroencephalography (EEG) measures for Alzheimer's disease (AD) clinical trials. The Panel reviewed the field literature. As most consistent findings, AD patients with mild cognitive impairment and dementia showed abnormalities in peak frequency, power, and "interrelatedness" at posterior alpha (8-12 Hz) and widespread delta (< 4 Hz) and theta (4-8 Hz) rhythms in relation to disease progression and interventions. The following consensus statements were subscribed: (1) Standardization of instructions to patients, resting state EEG (rsEEG) recording methods, and selection of artifact-free rsEEG periods are needed; (2) power density and "interrelatedness" rsEEG measures (e.g., directed transfer function, phase lag index, linear lagged connectivity, etc.) at delta, theta, and alpha frequency bands may be use for stratification of AD patients and monitoring of disease progression and intervention; and (3) international multisectoral initiatives are mandatory for regulatory purposes.
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Affiliation(s)
- Claudio Babiloni
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy.,San Raffaele of Cassino, Cassino (FR), Italy
| | | | - Hamed Azami
- Department of Neurology and Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts, USA
| | - Karim Bennys
- Centre Mémoire de Ressources et de Recherche (CMRR), Centre Hospitalier, Universitaire de Montpellier, Montpellier, France
| | - Katarzyna Blinowska
- Institute of Biocybernetics, Warsaw, Poland.,Faculty of Physics University of Warsaw and Nalecz, Warsaw, Poland
| | - Laura Bonanni
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University "G. D'Annunzio" of Chieti-Pescara, Chieti, Italy
| | - Ana Bujan
- Psychological Neuroscience Lab, School of Psychology, University of Minho, Minho, Portugal
| | - Maria C Carrillo
- Division of Medical & Scientific Relations, Alzheimer's Association, Chicago, Illinois, USA
| | - Andrzej Cichocki
- Skolkowo Institute of Science and Technology (SKOLTECH), Moscow, Russia.,Systems Research Institute PAS, Warsaw, Poland.,Nicolaus Copernicus University (UMK), Torun, Poland
| | - Jaisalmer de Frutos-Lucas
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain
| | - Claudio Del Percio
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | - Bruno Dubois
- Department of Neurology, Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l'hôpital, Institute of Memory and Alzheimer's Disease (IM2A), Paris, France.,ICM, INSERM U1127, CNRS UMR 7225, Sorbonne Université, Institut du Cerveau et de la Moelle épinière, Paris, France
| | - Rebecca Edelmayer
- Division of Medical & Scientific Relations, Alzheimer's Association, Chicago, Illinois, USA
| | - Gary Egan
- Foundation Director of the Monash Biomedical Imaging (MBI) Research Facilities, Monash University, Clayton, Australia
| | - Stephane Epelbaum
- Department of Neurology, Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l'hôpital, Institute of Memory and Alzheimer's Disease (IM2A), Paris, France.,ICM, INSERM U1127, CNRS UMR 7225, Sorbonne Université, Institut du Cerveau et de la Moelle épinière, Paris, France
| | - Javier Escudero
- School of Engineering, Institute for Digital Communications, The University of Edinburgh, Edinburgh, UK
| | - Alan Evans
- Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
| | - Francesca Farina
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Keith Fargo
- Division of Medical & Scientific Relations, Alzheimer's Association, Chicago, Illinois, USA
| | - Alberto Fernández
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain
| | | | - Giovanni Frisoni
- IRCCS San Giovanni di Dio Fatebenefratelli, Brescia, Italy.,Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Harald Hampel
- GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l'hôpital, Sorbonne University, Paris, France
| | | | - Vesna Jelic
- Division of Clinical Geriatrics, NVS Department, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
| | - Jaeseung Jeong
- Department of Bio and Brain Engineering/Program of Brain and Cognitive Engineering Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea
| | - Yang Jiang
- Department of Behavioral Science, College of Medicine, University of Kentucky, Lexington, Kentucky, USA
| | - Maciej Kaminski
- Faculty of Physics University of Warsaw and Nalecz, Warsaw, Poland
| | - Voyko Kavcic
- Institute of Gerontology, Wayne State University, Detroit, Michigan, USA
| | - Kerry Kilborn
- School of Psychology, University of Glasgow, Glasgow, UK
| | - Sanjeev Kumar
- Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Alice Lam
- MGH Epilepsy Service, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Lew Lim
- Vielight Inc., Toronto, Ontario, Canada
| | | | - David Lopez
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain
| | - Susanna Lopez
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | - Brendan Lucey
- Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA
| | - Fernando Maestú
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain
| | - William J McGeown
- School of Psychological Sciences and Health, University of Strathclyde, Glasgow, UK
| | - Ian McKeith
- Newcastle upon Tyne, Translational and Clinical Research Institute, Newcastle University, UK
| | | | - Flavio Nobili
- Department of Neuroscience (DINOGMI), University of Genoa, Genoa, Italy.,Clinica Neurologica, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | | | - John Olichney
- UC Davis Department of Neurology and Center for Mind and Brain, Davis, California, USA
| | - Marco Onofrj
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University "G. D'Annunzio" of Chieti-Pescara, Chieti, Italy
| | - Ricardo Osorio
- Center for Brain Health, Department of Psychiatry, NYU Langone Medical Center, New York, New York, USA
| | | | - Tarek Rajji
- Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Petra Ritter
- Brain Simulation Section, Department of Neurology, Charité Universitätsmedizin and Berlin Institute of Health, Berlin, Germany.,Bernstein Center for Computational Neuroscience, Berlin, Germany
| | - Andrea Soricelli
- IRCCS SDN, Napoli, Italy.,Department of Motor Sciences and Healthiness, University of Naples Parthenope, Naples, Italy
| | | | - Ioannis Tarnanas
- Global Brain Health Institute, University of California San Francisco, San Francisco, USA.,Global Brain Health Institute, Trinity College Dublin, Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - John Paul Taylor
- Newcastle upon Tyne, Translational and Clinical Research Institute, Newcastle University, UK
| | - Stefan Teipel
- Department of Psychosomatic Medicine, University of Rostock, Rostock, Germany.,German Center for Neurodegenerative Diseases (DZNE) - Rostock/Greifswald, Rostock, Germany
| | - Federico Tucci
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | | | - Pedro Valdes-Sosa
- Cuban Neuroscience Center, Havana, Cuba.,Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Marco Weiergräber
- Experimental Neuropsychopharmacology, BfArM), Federal Institute for Drugs and Medical Devices (Bundesinstitut für Arzneimittel und Medizinprodukte, Bonn, Germany
| | - Gorsev Yener
- Departments of Neurosciences and Department of Neurology, Dokuz Eylül University Medical School, Izmir, Turkey
| | - Bahar Guntekin
- Department of Biophysics, School of Medicine, Istanbul Medipol University, Istanbul, Turkey.,REMER, Clinical Electrophysiology, Neuroimaging and Neuromodulation Lab, Istanbul Medipol University, Istanbul, Turkey
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Pal A, Pegwal N, Behari M, Sharma R. High delta and gamma EEG power in resting state characterise dementia in Parkinson’s patients. Biomark Neuropsychiatry 2020. [DOI: 10.1016/j.bionps.2020.100027] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
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19
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Berman MH, Nichols TW. Treatment of Neurodegeneration: Integrating Photobiomodulation and Neurofeedback in Alzheimer's Dementia and Parkinson's: A Review. PHOTOBIOMODULATION PHOTOMEDICINE AND LASER SURGERY 2020; 37:623-634. [PMID: 31647776 DOI: 10.1089/photob.2019.4685] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Objective: A review of photobiomodulation (PBM) in Alzheimer's dementia is submitted. The addition of PBM in neurodegenerative diseases is a dual modality that is at present gaining traction as it is safe, antiviral, and anti-inflammatory for treating neurodegeneration with photons that stimulate mitochondria increasing adenosine triphosphate and proteasomes increasing misfolded protein removal. Neurofeedback provides neural plasticity with an increase in brain-derived nerve factor mRNA and an increase in dendrite production and density in the hippocampus coupled with overall growth in dendrites, density, and neuronal survival. Background: Alzheimer's disease pathophysiology is the accumulation of hyperphosphorylated tau protein neurofibrillary tangles and subsequently amyloid-beta (Aβ) plaques. PBM and neurobiofeedback (NBF)address the multiple gene expression and upregulation of multiple pathogenic pathway inflammation, reactive oxidative stress, mitochondrial disorders, insulin resistance, methylation defects, regulation of neuroprotective factors, and regional hypoperfusion of the brain. There is no human evidence to suggest a clinical therapeutic benefit from using consistent light sources while significantly increasing safety concerns. Methods: A PBM test with early- to mid-Alzheimer's was reported in 2017, consisting of a double-blind, placebo-controlled trial in a small pilot group of early- to mid-dementia subjects under Institutional Review Board (IRB)-approved Food and Drug Administration (FDA) Clinical Trial. Results: PBM-treated subjects showed that active treatment subjects tended to show greater improvement in the functioning of the executive: clock drawing, immediate recall, practical memory, and visual attention and task switching (Trails A&B). A larger study using the CerebroLite helmet in Temple Texas again of subjects in a double-blind, placebo-controlled IRB-approved FDA Clinical Trial demonstrated gain in memory and cognition by increased clock drawing. Conclusions: Next-generation trials with the Cognitolite for Parkinson's disease subjects will incorporate the insights regarding significant bilateral occipital hypocoherence deficits gained from the quantitative EEG analyses. Future applications will integrate noninvasive stimulation delivery, including full-body and transcranial and infrared light with pulsed electromagnetic frequencies.
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Waninger S, Berka C, Stevanovic Karic M, Korszen S, Mozley PD, Henchcliffe C, Kang Y, Hesterman J, Mangoubi T, Verma A. Neurophysiological Biomarkers of Parkinson's Disease. JOURNAL OF PARKINSON'S DISEASE 2020; 10:471-480. [PMID: 32116262 PMCID: PMC7242849 DOI: 10.3233/jpd-191844] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
BACKGROUND There is a need for reliable and robust Parkinson's disease biomarkers that reflect severity and are sensitive to disease modifying investigational therapeutics. OBJECTIVE To demonstrate the utility of EEG as a reliable, quantitative biomarker with potential as a pharmacodynamic endpoint for use in clinical assessments of neuroprotective therapeutics for Parkison's disease. METHODS A multi modal study was performed including aquisition of resting state EEG data and dopamine transporter PET imaging from Parkinson's disease patients off medication and compared against age-matched controls. RESULTS Qualitative and test/retest analysis of the EEG data demonstrated the reliability of the methods. Source localization using low resolution brain electromagnetic tomography identified significant differences in Parkinson's patients versus control subjects in the anterior cingulate and temporal lobe, areas with established association to Parkinson's disease pathology. Changes in cortico-cortical and cortico-thalamic coupling were observed as excessive EEG beta coherence in Parkinson's disease patients, and correlated with UPDRS scores and dopamine transporter activity, supporting the potential for cortical EEG coherence to serve as a reliable measure of disease severity. Using machine learning approaches, an EEG discriminant function analysis classifier was identified that parallels the loss of dopamine synapses as measured by dopamine transporter PET. CONCLUSION Our results support the utility of EEG in characterizing alterations in neurophysiological oscillatory activity associated with Parkinson's disease and highlight potential as a reliable method for monitoring disease progression and as a pharmacodynamic endpoint for Parkinson's disease modification therapy.
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Affiliation(s)
- Shani Waninger
- Advanced Brain Monitoring Inc., Carlsbad, CA, USA,Correspondence to: Shani Waninger, Advanced Brain Monitoring, Inc., 2237 Faraday Avenue, Suite 100,
Carlsbad, CA 92008, USA. E-mail:
| | - Chris Berka
- Advanced Brain Monitoring Inc., Carlsbad, CA, USA
| | | | | | | | | | - Yeona Kang
- Weill Cornell Medical College, New York, NY, USA
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21
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Carmona Arroyave JA, Tobón Quintero CA, Suárez Revelo JJ, Ochoa Gómez JF, García YB, Gómez LM, Pineda Salazar DA. Resting functional connectivity and mild cognitive impairment in Parkinson’s disease. An electroencephalogram study. FUTURE NEUROLOGY 2019. [DOI: 10.2217/fnl-2018-0048] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Objective: Parkinson’s disease (PD) is characterized by cognitive deficits. There is not clarity about electroencephalogram (EEG) connectivity related to the cognitive profile of patients. Our objective was to evaluate connectivity over resting EEG in nondemented PD. Methods: PD subjects with and without mild cognitive impairment (MCI) were assessed using coherence from resting EEG for local, intra and interhemispheric connectivity. Results: PD subjects without MCI (PD-nMCI) had lower intra and interhemispheric coherence in alpha2 compared with controls. PD with MCI (PD-MCI) showed higher intra and posterior interhemispheric coherence in alpha2 and beta1, respectively, in comparison to PD-nMCI. PD-MCI presented lower frontal coherence in beta frequencies compared with PD-nMCI. Conclusion: EEG coherence measures indicate distinct cortical activity in PD with and without MCI.
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Affiliation(s)
- Jairo Alexander Carmona Arroyave
- Neuroscience Group, Medical School, University of Antioquia, SIU, Calle 62 No. 52–59, Medellín, Colombia
- Neuropsychology & Behavior Group (GRUNECO), Medical School, University of Antioquia, SIU – Área Asistencial, Calle 62 No. 52–59, Medellín, Colombia
| | - Carlos Andrés Tobón Quintero
- Neuroscience Group, Medical School, University of Antioquia, SIU, Calle 62 No. 52–59, Medellín, Colombia
- Neuropsychology & Behavior Group (GRUNECO), Medical School, University of Antioquia, SIU – Área Asistencial, Calle 62 No. 52–59, Medellín, Colombia
| | - Jasmín Jimena Suárez Revelo
- Neuroscience Group, Medical School, University of Antioquia, SIU, Calle 62 No. 52–59, Medellín, Colombia
- Bioinstrumentation & Clinical Engineering Research Group (GIBIC), Bioengineering Program, University of Antioquia, Calle 70 No. 52–21, Medellín, Colombia
| | - John Fredy Ochoa Gómez
- Neuroscience Group, Medical School, University of Antioquia, SIU, Calle 62 No. 52–59, Medellín, Colombia
- Bioinstrumentation & Clinical Engineering Research Group (GIBIC), Bioengineering Program, University of Antioquia, Calle 70 No. 52–21, Medellín, Colombia
| | - Yamile Bocanegra García
- Neuroscience Group, Medical School, University of Antioquia, SIU, Calle 62 No. 52–59, Medellín, Colombia
- Neuropsychology & Behavior Group (GRUNECO), Medical School, University of Antioquia, SIU – Área Asistencial, Calle 62 No. 52–59, Medellín, Colombia
| | - Leonardo Moreno Gómez
- Neurology Unit, Pablo Tobón Uribe Hospital, Calle 78B No. 69–240, Medellín, Colombia
| | - David Antonio Pineda Salazar
- Neuroscience Group, Medical School, University of Antioquia, SIU, Calle 62 No. 52–59, Medellín, Colombia
- Neuropsychology & Behavior Group (GRUNECO), Medical School, University of Antioquia, SIU – Área Asistencial, Calle 62 No. 52–59, Medellín, Colombia
- Neuropsychology & Behavior Group (GRUNECO), Psychology Department, University of San Buenaventura, Carrera 56 C No. 51–110, Medellín, Colombia
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22
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Mostile G, Giuliano L, Monastero R, Luca A, Cicero CE, Donzuso G, Dibilio V, Baschi R, Terranova R, Restivo V, Sofia V, Zappia M, Nicoletti A. Electrocortical networks in Parkinson's disease patients with Mild Cognitive Impairment. The PaCoS study. Parkinsonism Relat Disord 2019; 64:156-162. [PMID: 30981665 DOI: 10.1016/j.parkreldis.2019.03.027] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/23/2018] [Revised: 03/27/2019] [Accepted: 03/30/2019] [Indexed: 01/03/2023]
Abstract
INTRODUCTION Parkinson's Disease (PD) is frequently associated with cognitive dysfunction ranging from Mild Cognitive Impairment (PD-MCI) to dementia. Few electrophysiological studies are available evaluating potential pathogenetic mechanisms linked to cognitive impairment in PD since its initial phases. The objective of the study is to analyze electrocortical networks related with cognitive decline in PD-MCI for identifying possible early electrophysiological markers of cognitive impairment in PD. METHODS From the PaCoS (Parkinson's disease Cognitive impairment Study) cohort, a sample of 102 subjects including 46 PD-MCI and 56 PD with normal cognition (PD-NC) was selected based on the presence of a neuropsychological assessment and at least one EEG recording. EEG signal epochs were analysed using Independent Component Analysis LORETA and spectral analysis by computing the Power Spectral Density (PSD) of site-specific signal epochs. RESULTS LORETA analysis revealed significant differences in PD-MCI patients compared to PD-NC, with a decreased network involving alpha activity over the occipital lobe, an increased network involving beta activity over the frontal lobe associated with a reduction over the parietal lobe, an increased network involving theta and delta activity over the frontal lobe and a reduction of networks involving theta and delta activity in the parietal lobe. Quantitative EEG analysis showed a significant decrease of alpha PSD over the occipital regions and an increase of delta PSD over the left temporal region in PD-MCI as compared to PD-NC. CONCLUSION Electrocortical abnormalities detected in PD-MCI patients may represent the instrumental counterpart of early cognitive decline in PD.
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Affiliation(s)
- Giovanni Mostile
- Department "G.F. Ingrassia", Section of Neurosciences, University of Catania, Via S. Sofia 78, 95123, Catania, Italy
| | - Loretta Giuliano
- Department "G.F. Ingrassia", Section of Neurosciences, University of Catania, Via S. Sofia 78, 95123, Catania, Italy
| | - Roberto Monastero
- Department of Biomedicine, Neuroscience and Advanced Diagnostics, Section of Neurology, University of Palermo, Via La Loggia 1, 90129, Palermo, Italy
| | - Antonina Luca
- Department "G.F. Ingrassia", Section of Neurosciences, University of Catania, Via S. Sofia 78, 95123, Catania, Italy
| | - Calogero Edoardo Cicero
- Department "G.F. Ingrassia", Section of Neurosciences, University of Catania, Via S. Sofia 78, 95123, Catania, Italy
| | - Giulia Donzuso
- Department "G.F. Ingrassia", Section of Neurosciences, University of Catania, Via S. Sofia 78, 95123, Catania, Italy
| | - Valeria Dibilio
- Department "G.F. Ingrassia", Section of Neurosciences, University of Catania, Via S. Sofia 78, 95123, Catania, Italy
| | - Roberta Baschi
- Department of Biomedicine, Neuroscience and Advanced Diagnostics, Section of Neurology, University of Palermo, Via La Loggia 1, 90129, Palermo, Italy
| | - Roberta Terranova
- Department "G.F. Ingrassia", Section of Neurosciences, University of Catania, Via S. Sofia 78, 95123, Catania, Italy
| | - Vincenzo Restivo
- Department of Sciences for Health Promotion and Mother-Child Care, University of Palermo, Via Del Vespro 133, 90127, Palermo, Italy
| | - Vito Sofia
- Department "G.F. Ingrassia", Section of Neurosciences, University of Catania, Via S. Sofia 78, 95123, Catania, Italy
| | - Mario Zappia
- Department "G.F. Ingrassia", Section of Neurosciences, University of Catania, Via S. Sofia 78, 95123, Catania, Italy
| | - Alessandra Nicoletti
- Department "G.F. Ingrassia", Section of Neurosciences, University of Catania, Via S. Sofia 78, 95123, Catania, Italy.
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23
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Maestú F, Cuesta P, Hasan O, Fernandéz A, Funke M, Schulz PE. The Importance of the Validation of M/EEG With Current Biomarkers in Alzheimer's Disease. Front Hum Neurosci 2019; 13:17. [PMID: 30792632 PMCID: PMC6374629 DOI: 10.3389/fnhum.2019.00017] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2018] [Accepted: 01/15/2019] [Indexed: 12/22/2022] Open
Abstract
Current biomarkers used in research and in clinical practice in Alzheimer's Disease (AD) are the analysis of cerebral spinal fluid (CSF) to detect levels of Aβ42 and phosphorylated-tau, amyloid and FDG-PET, and MRI volumetry. Some of these procedures are still invasive for patients or expensive. Electroencephalography (EEG) and Magnetoencephalography (MEG) are two non-invasive techniques able to detect the early synaptic dysfunction and track the course of the disease. However, in spite of its added value they are not part of the standard of care in clinical practice in dementia. In this paper we review what these neurophysiological techniques can add to the early diagnosis of AD, whether results in both modalities are related to each other or not, as well as the need of its validation against current biomarkers. We discuss their potential implications for the better understanding of the pathophysiological mechanisms of the disease as well as the need of performing simultaneous M/EEG recordings to better understand discrepancies between these two techniques. Finally, more studies are needed studying M/EEG with amyloid and Tau biomarkers.
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Affiliation(s)
- Fernando Maestú
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain
- Department of Experimental Psychology, Universidad Complutense de Madrid, Madrid, Spain
- Magnetic Source Imaging Unit, Department of Pediatrics, McGovern Medical School, University of Texas Health Science Center, Houston, TX, United States
| | - Pablo Cuesta
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain
- Electrical Engineering and Bioengineering Lab, Department of Industrial Engineering & IUNE Universidad de La Laguna, Tenerife, Spain
| | - Omar Hasan
- McGovern Medical School University of Texas Health Science Center, Houston, TX, United States
| | - Alberto Fernandéz
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain
- Department of Legal Medicine, Psychiatry, and Pathology, Universidad Complutense de Madrid, Madrid, Spain
| | - Michael Funke
- Magnetic Source Imaging Unit, Department of Pediatrics, McGovern Medical School, University of Texas Health Science Center, Houston, TX, United States
| | - Paul E. Schulz
- McGovern Medical School University of Texas Health Science Center, Houston, TX, United States
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24
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Abnormalities of functional cortical source connectivity of resting-state electroencephalographic alpha rhythms are similar in patients with mild cognitive impairment due to Alzheimer's and Lewy body diseases. Neurobiol Aging 2019; 77:112-127. [PMID: 30797169 DOI: 10.1016/j.neurobiolaging.2019.01.013] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2018] [Revised: 01/15/2019] [Accepted: 01/16/2019] [Indexed: 02/01/2023]
Abstract
Previous evidence has shown different resting-state eyes-closed electroencephalographic delta (<4 Hz) and alpha (8-10.5 Hz) source connectivity in subjects with dementia due to Alzheimer's (ADD) and Lewy body (DLB) diseases. The present study tested if the same differences may be observed in the prodromal stages of mild cognitive impairment (MCI). Here, clinical and resting-state eyes-closed electroencephalographic data in age-, gender-, and education-matched 30 ADMCI, 23 DLBMCI, and 30 healthy elderly (Nold) subjects were available in our international archive. Mini-Mental State Evaluation (MMSE) score was matched in the ADMCI and DLBMCI groups. The eLORETA freeware estimated delta and alpha source connectivity by the tool called lagged linear connectivity (LLC). Area under receiver operating characteristic curve (AUROCC) indexed the classification accuracy among individuals. Results showed that widespread interhemispheric and intrahemispheric LLC solutions in alpha sources were abnormally lower in both MCI groups compared with the Nold group, but with no differences were found between the 2 MCI groups. AUROCCs of LLC solutions in alpha sources exhibited significant accuracies (0.72-0.75) in the discrimination of Nold versus ADMCI-DLBMCI individuals, but not between the 2 MCI groups. These findings disclose similar abnormalities in ADMCI and DLBMCI patients as revealed by alpha source connectivity. It can be speculated that source connectivity mostly reflects common cholinergic impairment in prodromal state of both AD and DLB, before a substantial dopaminergic derangement in the dementia stage of DLB.
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25
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Abstract
After more than 85 years of development and use in clinical practice, the electroencephalogram (EEG) remains a dependable, inexpensive, and useful diagnostic tool for the investigation of the electrophysiologic activity of the brain. The advent of digital technology has led to greater sophistication and multiple software applications to extend the utility of EEG beyond the confines of the laboratory. Despite the discovery of new waveforms, basic neurophysiologic principles remain essential to the clinical care of patients. Patterns in the interictal EEG make it possible to clarify the differential diagnosis of paroxysmal neurological events, classify seizure type and epilepsy syndromes, and characterize and quantify seizures when ictal recordings are obtained. EEG can also demonstrate cerebral dysfunction when structural imaging is normal to detect focal or lateralized abnormalities in patients with encephalopathy. High-density EEG with electrical source imaging has improved localization in candidates for epilepsy surgery. Quantitative EEG and broadband EEG are advancing our understanding of the functional processes of the brain itself.
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Affiliation(s)
- Anteneh M Feyissa
- Department of Neurology, Mayo Clinic College of Medicine and Health Sciences, Jacksonville, FL, United States.
| | - William O Tatum
- Department of Neurology, Mayo Clinic College of Medicine and Health Sciences, Jacksonville, FL, United States
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26
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Zinn MA, Zinn ML, Valencia I, Jason LA, Montoya JG. Cortical hypoactivation during resting EEG suggests central nervous system pathology in patients with chronic fatigue syndrome. Biol Psychol 2018; 136:87-99. [PMID: 29802861 DOI: 10.1016/j.biopsycho.2018.05.016] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2017] [Revised: 03/29/2018] [Accepted: 05/20/2018] [Indexed: 01/22/2023]
Abstract
We investigated central fatigue in 50 patients with chronic fatigue syndrome (CFS) and 50 matched healthy controls (HC). Resting state EEG was collected from 19 scalp locations during a 3 min, eyes-closed condition. Current densities were localized using exact low-resolution electromagnetic tomography (eLORETA). The Multidimensional Fatigue Inventory (MFI-20) and the Fatigue Severity Scale (FSS) were administered to all participants. Independent t-tests and linear regression analyses were used to evaluate group differences in current densities, followed by statistical non-parametric mapping (SnPM) correction procedures. Significant differences were found in the delta (1-3 Hz) and beta-2 (19-21 Hz) frequency bands. Delta sources were found predominately in the frontal lobe, while beta-2 sources were found in the medial and superior parietal lobe. Left-lateralized, frontal delta sources were associated with a clinical reduction in motivation. The implications of abnormal cortical sources in patients with CFS are discussed.
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Affiliation(s)
- M A Zinn
- Department of Psychology, Center for Community Research, DePaul University, 990 West Fullerton Ave., Suite 3100, Chicago, IL 60614, USA
| | - M L Zinn
- Department of Psychology, Center for Community Research, DePaul University, 990 West Fullerton Ave., Suite 3100, Chicago, IL 60614, USA
| | - I Valencia
- Department of Medicine, Division of Infectious Diseases, Stanford University School of Medicine, Stanford, CA, USA
| | - L A Jason
- Department of Psychology, Center for Community Research, DePaul University, 990 West Fullerton Ave., Suite 3100, Chicago, IL 60614, USA.
| | - J G Montoya
- Department of Medicine, Division of Infectious Diseases, Stanford University School of Medicine, Stanford, CA, USA
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27
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Babiloni C, Del Percio C, Lizio R, Noce G, Cordone S, Lopez S, Soricelli A, Ferri R, Pascarelli MT, Nobili F, Arnaldi D, Famà F, Aarsland D, Orzi F, Buttinelli C, Giubilei F, Onofrj M, Stocchi F, Stirpe P, Fuhr P, Gschwandtner U, Ransmayr G, Caravias G, Garn H, Sorpresi F, Pievani M, D'Antonio F, De Lena C, Güntekin B, Hanoğlu L, Başar E, Yener G, Emek-Savaş DD, Triggiani AI, Franciotti R, Frisoni GB, Bonanni L, De Pandis MF. Abnormalities of Cortical Neural Synchronization Mechanisms in Subjects with Mild Cognitive Impairment due to Alzheimer's and Parkinson's Diseases: An EEG Study. J Alzheimers Dis 2018. [PMID: 28621693 DOI: 10.3233/jad-160883] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
The aim of this retrospective and exploratory study was that the cortical sources of resting state eyes-closed electroencephalographic (rsEEG) rhythms might reveal different abnormalities in cortical neural synchronization in groups of patients with mild cognitive impairment due to Alzheimer's disease (ADMCI) and Parkinson's disease (PDMCI) as compared to healthy subjects. Clinical and rsEEG data of 75 ADMCI, 75 PDMCI, and 75 cognitively normal elderly (Nold) subjects were available in an international archive. Age, gender, and education were carefully matched in the three groups. The Mini-Mental State Evaluation (MMSE) was matched between the ADMCI and PDMCI groups. Individual alpha frequency peak (IAF) was used to determine the delta, theta, alpha1, alpha2, and alpha3 frequency band ranges. Fixed beta1, beta2, and gamma bands were also considered. eLORETA estimated the rsEEG cortical sources. Receiver operating characteristic curve (ROC) classified these sources across individuals. Results showed that compared to the Nold group, the posterior alpha2 and alpha3 source activities were more abnormal in the ADMCI than the PDMCI group, while the parietal delta source activities were more abnormal in the PDMCI than the ADMCI group. The parietal delta and alpha sources correlated with MMSE score and correctly classified the Nold and diseased individuals (area under the ROC = 0.77-0.79). In conclusion, the PDMCI and ADMCI patients showed different features of cortical neural synchronization at delta and alpha frequencies underpinning brain arousal and vigilance in the quiet wakefulness. Future prospective cross-validation studies will have to test these rsEEG markers for clinical applications and drug discovery.
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Affiliation(s)
- Claudio Babiloni
- Department of Physiology and Pharmacology "Vittorio Erspamer", University of Rome "La Sapienza", Rome, Italy.,Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | | | - Roberta Lizio
- Department of Physiology and Pharmacology "Vittorio Erspamer", University of Rome "La Sapienza", Rome, Italy.,Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | - Giuseppe Noce
- Department of Integrated Imaging, IRCCS SDN, Naples, Italy
| | - Susanna Cordone
- Department of Physiology and Pharmacology "Vittorio Erspamer", University of Rome "La Sapienza", Rome, Italy
| | - Susanna Lopez
- Department of Physiology and Pharmacology "Vittorio Erspamer", University of Rome "La Sapienza", Rome, Italy
| | - Andrea Soricelli
- Department of Integrated Imaging, IRCCS SDN, Naples, Italy.,Department of Motor Sciences and Healthiness, University of Naples Parthenope, Naples, Italy
| | - Raffaele Ferri
- Department of Neurology, IRCCS Oasi Institute for Research on Mental Retardation and Brain Aging, Troina, Enna, Italy
| | - Maria Teresa Pascarelli
- Department of Neurology, IRCCS Oasi Institute for Research on Mental Retardation and Brain Aging, Troina, Enna, Italy
| | - Flavio Nobili
- Clinical Neurology, dept of Neuroscience (DiNOGMI), University of Genoa and IRCCS AOU S Martino-IST, Genoa, Italy
| | - Dario Arnaldi
- Clinical Neurology, dept of Neuroscience (DiNOGMI), University of Genoa and IRCCS AOU S Martino-IST, Genoa, Italy
| | - Francesco Famà
- Clinical Neurology, dept of Neuroscience (DiNOGMI), University of Genoa and IRCCS AOU S Martino-IST, Genoa, Italy
| | - Dag Aarsland
- Department of Old Age Psychiatry, King's College University, London, UK
| | - Francesco Orzi
- Department of Neuroscience, Mental Health and Sensory Organs, University of Rome "La Sapienza", Rome, Italy
| | - Carla Buttinelli
- Department of Neuroscience, Mental Health and Sensory Organs, University of Rome "La Sapienza", Rome, Italy
| | - Franco Giubilei
- Department of Neuroscience, Mental Health and Sensory Organs, University of Rome "La Sapienza", Rome, Italy
| | - Marco Onofrj
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University G d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Fabrizio Stocchi
- Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | - Paola Stirpe
- Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | - Peter Fuhr
- Universitätsspital Basel, Abteilung Neurophysiologie, Basel, Switzerland
| | - Ute Gschwandtner
- Universitätsspital Basel, Abteilung Neurophysiologie, Basel, Switzerland
| | - Gerhard Ransmayr
- Department of Neurology and Psychiatry and Faculty of Medicine, Johannes Kepler University Linz, General Hospital of the City of Linz, Linz, Austria
| | - Georg Caravias
- Department of Neurology and Psychiatry and Faculty of Medicine, Johannes Kepler University Linz, General Hospital of the City of Linz, Linz, Austria
| | - Heinrich Garn
- AIT Austrian Institute of Technology GmbH, Vienna, Austria
| | | | - Michela Pievani
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Fabrizia D'Antonio
- Department of Neurology and Psychiatry, Sapienza, University of Rome, Italy
| | - Carlo De Lena
- Department of Neurology and Psychiatry, Sapienza, University of Rome, Italy
| | - Bahar Güntekin
- Department of Biophysics, Istanbul Medipol University, Istanbul, Turkey
| | - Lutfu Hanoğlu
- Department of Neurology, University of Istanbul-Medipol, Istanbul, Turkey
| | - Erol Başar
- Department of Neurosciences and Department of Neurology, Dokuz Eylül University Medical School, Izmir, Turkey
| | - Görsev Yener
- Department of Psychology and Department of Neurosciences, Dokuz Eylül University, Izmir, Turkey
| | - Derya Durusu Emek-Savaş
- Department of Psychology and Department of Neurosciences, Dokuz Eylül University, Izmir, Turkey
| | | | - Raffaella Franciotti
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University G d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Giovanni B Frisoni
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.,Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Laura Bonanni
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University G d'Annunzio of Chieti-Pescara, Chieti, Italy
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28
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Abstract
Alzheimer's disease (AD), a cognitive disability is analysed using a long range dependence parameter, hurst exponent (HE), calculated based on the time domain analysis of the measured electrical activity of brain. The electroencephalogram (EEG) signals of controls and mild cognitive impairment (MCI)-AD patients are evaluated under normal resting and mental arithmetic conditions. Simultaneous low pass filtering and total variation denoising algorithm is employed for preprocessing. Larger values of HE observed in the right hemisphere of the brain for AD patients indicated a decrease in irregularity of the EEG signal under cognitive task conditions. Correlations between HE and the neuropsychological indices are analysed using bivariate correlation analysis. The observed reduction in the values of Auto mutual information and cross mutual information in the local antero-frontal and distant regions in the brain hemisphere indicates the loss of information transmission in MCI-AD patients.
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29
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Functional cortical source connectivity of resting state electroencephalographic alpha rhythms shows similar abnormalities in patients with mild cognitive impairment due to Alzheimer's and Parkinson's diseases. Clin Neurophysiol 2018; 129:766-782. [PMID: 29448151 DOI: 10.1016/j.clinph.2018.01.009] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2017] [Revised: 11/30/2017] [Accepted: 01/10/2018] [Indexed: 11/22/2022]
Abstract
OBJECTIVE This study tested the hypothesis that markers of functional cortical source connectivity of resting state eyes-closed electroencephalographic (rsEEG) rhythms may be abnormal in subjects with mild cognitive impairment due to Alzheimer's (ADMCI) and Parkinson's (PDMCI) diseases compared to healthy elderly subjects (Nold). METHODS rsEEG data had been collected in ADMCI, PDMCI, and Nold subjects (N = 75 for any group). eLORETA freeware estimated functional lagged linear connectivity (LLC) from rsEEG cortical sources. Area under receiver operating characteristic (AUROC) curve indexed the accuracy in the classification of Nold and MCI individuals. RESULTS Posterior interhemispheric and widespread intrahemispheric alpha LLC solutions were abnormally lower in both MCI groups compared to the Nold group. At the individual level, AUROC curves of LLC solutions in posterior alpha sources exhibited moderate accuracies (0.70-0.72) in the discrimination of Nold vs. ADMCI-PDMCI individuals. No differences in the LLC solutions were found between the two MCI groups. CONCLUSIONS These findings unveil similar abnormalities in functional cortical connectivity estimated in widespread alpha sources in ADMCI and PDMCI. This was true at both group and individual levels. SIGNIFICANCE The similar abnormality of alpha source connectivity in ADMCI and PDMCI subjects might reflect common cholinergic impairment.
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30
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Nimmy John T, D Puthankattil S, Menon R. Analysis of long range dependence in the EEG signals of Alzheimer patients. Cogn Neurodyn 2018; 12:183-199. [PMID: 29564027 DOI: 10.1007/s11571-017-9467-8] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2017] [Revised: 11/14/2017] [Accepted: 12/19/2017] [Indexed: 11/28/2022] Open
Abstract
Alzheimer's disease (AD), a cognitive disability is analysed using a long range dependence parameter, hurst exponent (HE), calculated based on the time domain analysis of the measured electrical activity of brain. The electroencephalogram (EEG) signals of controls and mild cognitive impairment (MCI)-AD patients are evaluated under normal resting and mental arithmetic conditions. Simultaneous low pass filtering and total variation denoising algorithm is employed for preprocessing. Larger values of HE observed in the right hemisphere of the brain for AD patients indicated a decrease in irregularity of the EEG signal under cognitive task conditions. Correlations between HE and the neuropsychological indices are analysed using bivariate correlation analysis. The observed reduction in the values of Auto mutual information and cross mutual information in the local antero-frontal and distant regions in the brain hemisphere indicates the loss of information transmission in MCI-AD patients.
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Affiliation(s)
- T Nimmy John
- 1Department of Electrical Engineering, National Institute of Technology Calicut, Kozhikode, India
| | - Subha D Puthankattil
- 1Department of Electrical Engineering, National Institute of Technology Calicut, Kozhikode, India
| | - Ramshekhar Menon
- 2Department of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, India
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31
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Hampel H, Toschi N, Babiloni C, Baldacci F, Black KL, Bokde AL, Bun RS, Cacciola F, Cavedo E, Chiesa PA, Colliot O, Coman CM, Dubois B, Duggento A, Durrleman S, Ferretti MT, George N, Genthon R, Habert MO, Herholz K, Koronyo Y, Koronyo-Hamaoui M, Lamari F, Langevin T, Lehéricy S, Lorenceau J, Neri C, Nisticò R, Nyasse-Messene F, Ritchie C, Rossi S, Santarnecchi E, Sporns O, Verdooner SR, Vergallo A, Villain N, Younesi E, Garaci F, Lista S. Revolution of Alzheimer Precision Neurology. Passageway of Systems Biology and Neurophysiology. J Alzheimers Dis 2018; 64:S47-S105. [PMID: 29562524 PMCID: PMC6008221 DOI: 10.3233/jad-179932] [Citation(s) in RCA: 95] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
The Precision Neurology development process implements systems theory with system biology and neurophysiology in a parallel, bidirectional research path: a combined hypothesis-driven investigation of systems dysfunction within distinct molecular, cellular, and large-scale neural network systems in both animal models as well as through tests for the usefulness of these candidate dynamic systems biomarkers in different diseases and subgroups at different stages of pathophysiological progression. This translational research path is paralleled by an "omics"-based, hypothesis-free, exploratory research pathway, which will collect multimodal data from progressing asymptomatic, preclinical, and clinical neurodegenerative disease (ND) populations, within the wide continuous biological and clinical spectrum of ND, applying high-throughput and high-content technologies combined with powerful computational and statistical modeling tools, aimed at identifying novel dysfunctional systems and predictive marker signatures associated with ND. The goals are to identify common biological denominators or differentiating classifiers across the continuum of ND during detectable stages of pathophysiological progression, characterize systems-based intermediate endophenotypes, validate multi-modal novel diagnostic systems biomarkers, and advance clinical intervention trial designs by utilizing systems-based intermediate endophenotypes and candidate surrogate markers. Achieving these goals is key to the ultimate development of early and effective individualized treatment of ND, such as Alzheimer's disease. The Alzheimer Precision Medicine Initiative (APMI) and cohort program (APMI-CP), as well as the Paris based core of the Sorbonne University Clinical Research Group "Alzheimer Precision Medicine" (GRC-APM) were recently launched to facilitate the passageway from conventional clinical diagnostic and drug development toward breakthrough innovation based on the investigation of the comprehensive biological nature of aging individuals. The APMI movement is gaining momentum to systematically apply both systems neurophysiology and systems biology in exploratory translational neuroscience research on ND.
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Affiliation(s)
- Harald Hampel
- AXA Research Fund & Sorbonne Université Chair, Paris, France
- Sorbonne Université, AP-HP, GRC n° 21, Alzheimer Precision Medicine (APM), Hôpital de la Pitié-Salpêtrière, Boulevard de l’hôpital, F-75013, Paris, France
- Institut du Cerveau et de la Moelle Épinière (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l’hôpital, F-75013, Paris, France
- Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A), Département de Neurologie, Hôpital de la Pitié-Salpêtrière, AP-HP, Boulevard de l’hôpital, F-75013, Paris, France
| | - Nicola Toschi
- Department of Biomedicine and Prevention, University of Rome “Tor Vergata”, Rome, Italy
- Department of Radiology, “Athinoula A. Martinos” Center for Biomedical Imaging, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Claudio Babiloni
- Department of Physiology and Pharmacology “Vittorio Erspamer”, University of Rome “La Sapienza”, Rome, Italy
- Institute for Research and Medical Care, IRCCS “San Raffaele Pisana”, Rome, Italy
| | - Filippo Baldacci
- AXA Research Fund & Sorbonne Université Chair, Paris, France
- Sorbonne Université, AP-HP, GRC n° 21, Alzheimer Precision Medicine (APM), Hôpital de la Pitié-Salpêtrière, Boulevard de l’hôpital, F-75013, Paris, France
- Institut du Cerveau et de la Moelle Épinière (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l’hôpital, F-75013, Paris, France
- Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A), Département de Neurologie, Hôpital de la Pitié-Salpêtrière, AP-HP, Boulevard de l’hôpital, F-75013, Paris, France
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Keith L. Black
- Department of Neurosurgery, Maxine Dunitz Neurosurgical Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Arun L.W. Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience (TCIN), Trinity College Dublin, Dublin, Ireland
| | - René S. Bun
- AXA Research Fund & Sorbonne Université Chair, Paris, France
- Sorbonne Université, AP-HP, GRC n° 21, Alzheimer Precision Medicine (APM), Hôpital de la Pitié-Salpêtrière, Boulevard de l’hôpital, F-75013, Paris, France
- Institut du Cerveau et de la Moelle Épinière (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l’hôpital, F-75013, Paris, France
- Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A), Département de Neurologie, Hôpital de la Pitié-Salpêtrière, AP-HP, Boulevard de l’hôpital, F-75013, Paris, France
| | - Francesco Cacciola
- Unit of Neurosurgery, Azienda Ospedaliera Universitaria Senese, Siena, Italy
| | - Enrica Cavedo
- AXA Research Fund & Sorbonne Université Chair, Paris, France
- Sorbonne Université, AP-HP, GRC n° 21, Alzheimer Precision Medicine (APM), Hôpital de la Pitié-Salpêtrière, Boulevard de l’hôpital, F-75013, Paris, France
- Institut du Cerveau et de la Moelle Épinière (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l’hôpital, F-75013, Paris, France
- Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A), Département de Neurologie, Hôpital de la Pitié-Salpêtrière, AP-HP, Boulevard de l’hôpital, F-75013, Paris, France
- IRCCS “San Giovanni di Dio-Fatebenefratelli”, Brescia, Italy
| | - Patrizia A. Chiesa
- AXA Research Fund & Sorbonne Université Chair, Paris, France
- Sorbonne Université, AP-HP, GRC n° 21, Alzheimer Precision Medicine (APM), Hôpital de la Pitié-Salpêtrière, Boulevard de l’hôpital, F-75013, Paris, France
- Institut du Cerveau et de la Moelle Épinière (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l’hôpital, F-75013, Paris, France
- Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A), Département de Neurologie, Hôpital de la Pitié-Salpêtrière, AP-HP, Boulevard de l’hôpital, F-75013, Paris, France
| | - Olivier Colliot
- Inserm, U1127, Paris, France; CNRS, UMR 7225 ICM, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR S 1127, Paris, France; Institut du Cerveau et de la Moelle Épinière (ICM) Paris, France; Inria, Aramis project-team, Centre de Recherche de Paris, France; Department of Neuroradiology, AP-HP, Hôpital de la Pitié-Salpêtrière, Paris, France; Department of Neurology, AP-HP, Hôpital de la Pitié-Salpêtrière, Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A), Paris, France
| | - Cristina-Maria Coman
- AXA Research Fund & Sorbonne Université Chair, Paris, France
- Sorbonne Université, AP-HP, GRC n° 21, Alzheimer Precision Medicine (APM), Hôpital de la Pitié-Salpêtrière, Boulevard de l’hôpital, F-75013, Paris, France
- Institut du Cerveau et de la Moelle Épinière (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l’hôpital, F-75013, Paris, France
- Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A), Département de Neurologie, Hôpital de la Pitié-Salpêtrière, AP-HP, Boulevard de l’hôpital, F-75013, Paris, France
| | - Bruno Dubois
- Sorbonne Université, Inserm, CNRS, Institut du Cerveau et de la Moelle Épinière (ICM), Département de Neurologie, Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A), Hôpital Pitié-Salpêtrière, Boulevard de l’hôpital, F-75013, Paris, France
| | - Andrea Duggento
- Department of Biomedicine and Prevention, University of Rome “Tor Vergata”, Rome, Italy
| | - Stanley Durrleman
- Inserm, U1127, Paris, France; CNRS, UMR 7225 ICM, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR S 1127, Paris, France; Institut du Cerveau et de la Moelle Épinière (ICM) Paris, France; Inria, Aramis project-team, Centre de Recherche de Paris, France
| | - Maria-Teresa Ferretti
- IREM, Institute for Regenerative Medicine, University of Zurich, Zürich, Switzerland
- ZNZ Neuroscience Center Zurich, Zürich, Switzerland
| | - Nathalie George
- Sorbonne Universités, UPMC Univ Paris 06 UMR S 1127, Inserm U 1127, CNRS UMR 7225, Institut du Cerveau et de la Moelle Épinière, ICM, Ecole Normale Supérieure, ENS, Centre MEG-EEG, F-75013, Paris, France
| | - Remy Genthon
- Sorbonne Université, Inserm, CNRS, Institut du Cerveau et de la Moelle Épinière (ICM), Département de Neurologie, Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A), Hôpital Pitié-Salpêtrière, Boulevard de l’hôpital, F-75013, Paris, France
| | - Marie-Odile Habert
- Département de Médecine Nucléaire, Hôpital de la Pitié-Salpêtrière, AP-HP, Paris, France
- Laboratoire d’Imagerie Biomédicale, Sorbonne Universités, UPMC Univ Paris 06, Inserm U 1146, CNRS UMR 7371, Paris, France
| | - Karl Herholz
- Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, UK
- Division of Informatics, Imaging and Data Sciences, University of Manchester, Wolfson Molecular Imaging Centre, Manchester, UK
| | - Yosef Koronyo
- Department of Neurosurgery, Maxine Dunitz Neurosurgical Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Maya Koronyo-Hamaoui
- Department of Neurosurgery, Maxine Dunitz Neurosurgical Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Foudil Lamari
- AP-HP, UF Biochimie des Maladies Neuro-métaboliques, Service de Biochimie Métabolique, Groupe Hospitalier Pitié-Salpêtrière, Paris, France
| | | | - Stéphane Lehéricy
- Centre de NeuroImagerie de Recherche - CENIR, Institut du Cerveau et de la Moelle Épinière - ICM, F-75013, Paris, France
- Sorbonne Universités, UPMC Univ Paris 06 UMR S 1127, Inserm U 1127, CNRS UMR 7225, ICM, F-75013, Paris, France
| | - Jean Lorenceau
- Institut de la Vision, INSERM, Sorbonne Universités, UPMC Univ Paris 06, UMR_S968, CNRS UMR7210, Paris, France
| | - Christian Neri
- Sorbonne Universités, Université Pierre et Marie Curie (UPMC) Paris 06, CNRS UMR 8256, Institut de Biologie Paris-Seine (IBPS), Place Jussieu, F-75005, Paris, France
| | - Robert Nisticò
- Department of Biology, University of Rome “Tor Vergata” & Pharmacology of Synaptic Disease Lab, European Brain Research Institute (E.B.R.I.), Rome, Italy
| | - Francis Nyasse-Messene
- Sorbonne Université, Inserm, CNRS, Institut du Cerveau et de la Moelle Épinière (ICM), Département de Neurologie, Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A), Hôpital Pitié-Salpêtrière, Boulevard de l’hôpital, F-75013, Paris, France
| | - Craig Ritchie
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Simone Rossi
- Department of Medicine, Surgery and Neurosciences, Unit of Neurology and Clinical Neurophysiology, Brain Investigation & Neuromodulation Lab. (Si-BIN Lab.), University of Siena, Siena, Italy
- Department of Medicine, Surgery and Neurosciences, Section of Human Physiology University of Siena, Siena, Italy
| | - Emiliano Santarnecchi
- Department of Medicine, Surgery and Neurosciences, Unit of Neurology and Clinical Neurophysiology, Brain Investigation & Neuromodulation Lab. (Si-BIN Lab.), University of Siena, Siena, Italy
- Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Olaf Sporns
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
- IU Network Science Institute, Indiana University, Bloomington, IN, USA
| | | | - Andrea Vergallo
- AXA Research Fund & Sorbonne Université Chair, Paris, France
- Sorbonne Université, AP-HP, GRC n° 21, Alzheimer Precision Medicine (APM), Hôpital de la Pitié-Salpêtrière, Boulevard de l’hôpital, F-75013, Paris, France
- Institut du Cerveau et de la Moelle Épinière (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l’hôpital, F-75013, Paris, France
- Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A), Département de Neurologie, Hôpital de la Pitié-Salpêtrière, AP-HP, Boulevard de l’hôpital, F-75013, Paris, France
| | - Nicolas Villain
- Sorbonne Université, AP-HP, GRC n° 21, Alzheimer Precision Medicine (APM), Hôpital de la Pitié-Salpêtrière, Boulevard de l’hôpital, F-75013, Paris, France
- Institut du Cerveau et de la Moelle Épinière (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l’hôpital, F-75013, Paris, France
- Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A), Département de Neurologie, Hôpital de la Pitié-Salpêtrière, AP-HP, Boulevard de l’hôpital, F-75013, Paris, France
| | | | - Francesco Garaci
- Department of Biomedicine and Prevention, University of Rome “Tor Vergata”, Rome, Italy
- Casa di Cura “San Raffaele Cassino”, Cassino, Italy
| | - Simone Lista
- AXA Research Fund & Sorbonne Université Chair, Paris, France
- Sorbonne Université, AP-HP, GRC n° 21, Alzheimer Precision Medicine (APM), Hôpital de la Pitié-Salpêtrière, Boulevard de l’hôpital, F-75013, Paris, France
- Institut du Cerveau et de la Moelle Épinière (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l’hôpital, F-75013, Paris, France
- Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A), Département de Neurologie, Hôpital de la Pitié-Salpêtrière, AP-HP, Boulevard de l’hôpital, F-75013, Paris, France
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Babiloni C, Del Percio C, Lizio R, Noce G, Lopez S, Soricelli A, Ferri R, Nobili F, Arnaldi D, Famà F, Aarsland D, Orzi F, Buttinelli C, Giubilei F, Onofrj M, Stocchi F, Stirpe P, Fuhr P, Gschwandtner U, Ransmayr G, Garn H, Fraioli L, Pievani M, Frisoni GB, D'Antonio F, De Lena C, Güntekin B, Hanoğlu L, Başar E, Yener G, Emek-Savaş DD, Triggiani AI, Franciotti R, Taylor JP, Vacca L, De Pandis MF, Bonanni L. Abnormalities of resting-state functional cortical connectivity in patients with dementia due to Alzheimer's and Lewy body diseases: an EEG study. Neurobiol Aging 2017; 65:18-40. [PMID: 29407464 DOI: 10.1016/j.neurobiolaging.2017.12.023] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2017] [Revised: 12/21/2017] [Accepted: 12/21/2017] [Indexed: 11/30/2022]
Abstract
Previous evidence showed abnormal posterior sources of resting-state delta (<4 Hz) and alpha (8-12 Hz) rhythms in patients with Alzheimer's disease with dementia (ADD), Parkinson's disease with dementia (PDD), and Lewy body dementia (DLB), as cortical neural synchronization markers in quiet wakefulness. Here, we tested the hypothesis of additional abnormalities in functional cortical connectivity computed in those sources, in ADD, considered as a "disconnection cortical syndrome", in comparison with PDD and DLB. Resting-state eyes-closed electroencephalographic (rsEEG) rhythms had been collected in 42 ADD, 42 PDD, 34 DLB, and 40 normal healthy older (Nold) participants. Exact low-resolution brain electromagnetic tomography (eLORETA) freeware estimated the functional lagged linear connectivity (LLC) from rsEEG cortical sources in delta, theta, alpha, beta, and gamma bands. The area under receiver operating characteristic (AUROC) curve indexed the classification accuracy between Nold and diseased individuals (only values >0.7 were considered). Interhemispheric and intrahemispheric LLCs in widespread delta sources were abnormally higher in the ADD group and, unexpectedly, normal in DLB and PDD groups. Intrahemispheric LLC was reduced in widespread alpha sources dramatically in ADD, markedly in DLB, and moderately in PDD group. Furthermore, the interhemispheric LLC in widespread alpha sources showed lower values in ADD and DLB than PDD groups. At the individual level, AUROC curves of LLC in alpha sources exhibited better classification accuracies for the discrimination of ADD versus Nold individuals (0.84) than for DLB versus Nold participants (0.78) and PDD versus Nold participants (0.75). Functional cortical connectivity markers in delta and alpha sources suggest a more compromised neurophysiological reserve in ADD than DLB, at both group and individual levels.
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Affiliation(s)
- Claudio Babiloni
- Department of Physiology and Pharmacology "Vittorio Erspamer", University of Rome "La Sapienza", Rome, Italy; Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy.
| | | | - Roberta Lizio
- Department of Physiology and Pharmacology "Vittorio Erspamer", University of Rome "La Sapienza", Rome, Italy; Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | - Giuseppe Noce
- Department of Integrated Imaging, IRCCS SDN, Naples, Italy
| | - Susanna Lopez
- Department of Physiology and Pharmacology "Vittorio Erspamer", University of Rome "La Sapienza", Rome, Italy
| | - Andrea Soricelli
- Department of Integrated Imaging, IRCCS SDN, Naples, Italy; Department of Motor Sciences and Healthiness, University of Naples Parthenope, Naples, Italy
| | - Raffaele Ferri
- Department of Neurology, IRCCS Oasi Institute for Research on Mental Retardation and Brain Aging, Troina, Enna, Italy
| | - Flavio Nobili
- Clinical Neurology, Department of Neuroscience (DiNOGMI), University of Genoa and IRCCS AOU S Martino-IST, Genoa, Italy
| | - Dario Arnaldi
- Clinical Neurology, Department of Neuroscience (DiNOGMI), University of Genoa and IRCCS AOU S Martino-IST, Genoa, Italy
| | - Francesco Famà
- Clinical Neurology, Department of Neuroscience (DiNOGMI), University of Genoa and IRCCS AOU S Martino-IST, Genoa, Italy
| | - Dag Aarsland
- Department of Old Age Psychiatry, King's College University, London, UK
| | - Francesco Orzi
- Department of Neuroscience, Mental Health and Sensory Organs, University of Rome "La Sapienza", Rome, Italy
| | - Carla Buttinelli
- Department of Neuroscience, Mental Health and Sensory Organs, University of Rome "La Sapienza", Rome, Italy
| | - Franco Giubilei
- Department of Neuroscience, Mental Health and Sensory Organs, University of Rome "La Sapienza", Rome, Italy
| | - Marco Onofrj
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University G d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Fabrizio Stocchi
- Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | - Paola Stirpe
- Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | - Peter Fuhr
- Universitätsspital Basel, Abteilung Neurophysiologie, Basel, Switzerland
| | - Ute Gschwandtner
- Universitätsspital Basel, Abteilung Neurophysiologie, Basel, Switzerland
| | - Gerhard Ransmayr
- Department of Neurology and Psychiatry and Faculty of Medicine, Johannes Kepler University Linz, General Hospital of the City of Linz, Linz, Austria
| | - Heinrich Garn
- AIT Austrian Institute of Technology GmbH, Vienna, Austria
| | | | - Michela Pievani
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Giovanni B Frisoni
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy; Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Fabrizia D'Antonio
- Department of Neurology and Psychiatry, Sapienza, University of Rome, Rome, Italy
| | - Carlo De Lena
- Department of Neurology and Psychiatry, Sapienza, University of Rome, Rome, Italy
| | - Bahar Güntekin
- Department of Biophysics, Istanbul Medipol University, Istanbul, Turkey
| | - Lutfu Hanoğlu
- Department of Neurology, University of Istanbul-Medipol, Istanbul, Turkey
| | - Erol Başar
- IBG, Departments of Neurology and Neurosciences, Dokuz Eylül University, Izmir, Turkey
| | - Görsev Yener
- IBG, Departments of Neurology and Neurosciences, Dokuz Eylül University, Izmir, Turkey
| | - Derya Durusu Emek-Savaş
- Department of Psychology and Department of Neurosciences, Dokuz Eylül University, Izmir, Turkey
| | | | - Raffaella Franciotti
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University G d'Annunzio of Chieti-Pescara, Chieti, Italy
| | | | - Laura Vacca
- Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy; Casa di Cura Privata del Policlinico (CCPP) Milano SpA, Milan, Italy
| | | | - Laura Bonanni
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University G d'Annunzio of Chieti-Pescara, Chieti, Italy
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Jellinger KA. Dementia with Lewy bodies and Parkinson's disease-dementia: current concepts and controversies. J Neural Transm (Vienna) 2017; 125:615-650. [PMID: 29222591 DOI: 10.1007/s00702-017-1821-9] [Citation(s) in RCA: 172] [Impact Index Per Article: 24.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2017] [Accepted: 11/28/2017] [Indexed: 12/15/2022]
Abstract
Dementia with Lewy bodies (DLB) and Parkinson's disease-dementia (PDD), although sharing many clinical, neurochemical and morphological features, according to DSM-5, are two entities of major neurocognitive disorders with Lewy bodies of unknown etiology. Despite considerable clinical overlap, their diagnosis is based on an arbitrary distinction between the time of onset of motor and cognitive symptoms: dementia often preceding parkinsonism in DLB and onset of cognitive impairment after onset of motor symptoms in PDD. Both are characterized morphologically by widespread cortical and subcortical α-synuclein/Lewy body plus β-amyloid and tau pathologies. Based on recent publications, including the fourth consensus report of the DLB Consortium, a critical overview is given. The clinical features of DLB and PDD include cognitive impairment, parkinsonism, visual hallucinations, and fluctuating attention. Intravitam PET and post-mortem studies revealed more pronounced cortical atrophy, elevated cortical and limbic Lewy pathologies (with APOE ε4), apart from higher prevalence of Alzheimer pathology in DLB than PDD. These changes may account for earlier onset and greater severity of cognitive defects in DLB, while multitracer PET studies showed no differences in cholinergic and dopaminergic deficits. DLB and PDD sharing genetic, neurochemical, and morphologic factors are likely to represent two subtypes of an α-synuclein-associated disease spectrum (Lewy body diseases), beginning with incidental Lewy body disease-PD-nondemented-PDD-DLB (no parkinsonism)-DLB with Alzheimer's disease (DLB-AD) at the most severe end, although DLB does not begin with PD/PDD and does not always progress to DLB-AD, while others consider them as the same disease. Both DLB and PDD show heterogeneous pathology and neurochemistry, suggesting that they share important common underlying molecular pathogenesis with AD and other proteinopathies. Cognitive impairment is not only induced by α-synuclein-caused neurodegeneration but by multiple regional pathological scores. Recent animal models and human post-mortem studies have provided important insights into the pathophysiology of DLB/PDD showing some differences, e.g., different spreading patterns of α-synuclein pathology, but the basic pathogenic mechanisms leading to the heterogeneity between both disorders deserve further elucidation. In view of the controversies about the nosology and pathogenesis of both syndromes, there remains a pressing need to differentiate them more clearly and to understand the processes leading these synucleinopathies to cause one disorder or the other. Clinical management of both disorders includes cholinesterase inhibitors, other pharmacologic and nonpharmacologic strategies, but these have only a mild symptomatic effect. Currently, no disease-modifying therapies are available.
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Affiliation(s)
- Kurt A Jellinger
- Institute of Clinical Neurobiology, Alberichgasse 5/13, 1150, Vienna, Austria.
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34
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Lee PS, Low I, Chen YS, Tu CH, Chao HT, Hsieh JC, Chen LF. Encoding of menstrual pain experience with theta oscillations in women with primary dysmenorrhea. Sci Rep 2017; 7:15977. [PMID: 29167518 PMCID: PMC5700160 DOI: 10.1038/s41598-017-16039-4] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2017] [Accepted: 11/06/2017] [Indexed: 01/08/2023] Open
Abstract
Theta oscillation (4–7 Hz) is well documented for its association with neural processes of memory. Pronounced increase of theta activity is commonly observed in patients with chronic neurogenic pain. However, its association with encoding of pain experience in patients with chronic pain is still unclear. The goal of the present study is to investigate the theta encoding of sensory and emotional information of long-term menstrual pain in women with primary dysmenorrhea (PDM). Forty-six young women with PDM and 46 age-matched control subjects underwent resting-state magnetoencephalography study during menstrual and periovulatory phases. Our results revealed increased theta activity in brain regions of pain processing in women with PDM, including the right parahippocampal gyrus, right posterior insula, and left anterior/middle cingulate gyrus during the menstrual phase and the left anterior insula and the left middle/inferior temporal gyrus during the periovulatory phase. The correlations between theta activity and the psychological measures pertaining to pain experience (depression, state anxiety, and pain rating index) implicate the role of theta oscillations in emotional and sensory processing of pain. The present study provides evidence for the role of theta oscillations in encoding the immediate and sustained effects of pain experience in young women with PDM.
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Affiliation(s)
- Pin-Shiuan Lee
- Institute of Biomedical Informatics, National Yang-Ming University, Taipei, Taiwan
| | - Intan Low
- Institute of Biomedical Informatics, National Yang-Ming University, Taipei, Taiwan
| | - Yong-Sheng Chen
- Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan
| | - Cheng-Hao Tu
- Integrated Brain Research Unit, Division of Clinical Research, Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Hsiang-Tai Chao
- Department of Obstetrics and Gynecology, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Jen-Chuen Hsieh
- Integrated Brain Research Unit, Division of Clinical Research, Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan. .,Institute of Brain Science, National Yang-Ming University, Taipei, Taiwan.
| | - Li-Fen Chen
- Institute of Biomedical Informatics, National Yang-Ming University, Taipei, Taiwan. .,Integrated Brain Research Unit, Division of Clinical Research, Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan. .,Institute of Brain Science, National Yang-Ming University, Taipei, Taiwan.
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Guner D, Tiftikcioglu BI, Tuncay N, Zorlu Y. Contribution of Quantitative EEG to the Diagnosis of Early Cognitive Impairment in Patients With Idiopathic Parkinson's Disease. Clin EEG Neurosci 2017; 48:348-354. [PMID: 27491643 DOI: 10.1177/1550059416662412] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Cognitive dysfunction can emerge during the clinical course of Parkinson's disease (PD) even beginning in early stages, which requires extended neuropsychological tests for diagnosis. There is need for rapid, feasible, and practical tests in clinical practice to diagnose and monitor the patients without causing any discomfort. We investigated the utility of quantitative analysis of digital EEG (qEEG) for diagnosing subtle cognitive impairment in PD patients without evident cognitive deficits (ie, "normal cognition"). We enrolled 45 patients with PD and age- matched 39 healthy controls in the study. All participants had Mini-Mental State Examination (MMSE) score greater than 25. qEEG analysis and extensive neuropsychological assessment battery were applied to all participants. Test scores for frontal executive functions, verbal memory processes, attention span, and visuospatial functions were significantly lower than healthy controls ( P < .01). qEEG analysis revealed a significant increase in delta, theta, and beta frequencies, and decrease in alpha frequency band in cerebral bioelectrical activity in patient group. In addition, power spectral ratios ([alpha + beta] / [delta + theta]) in frontal, central, temporal, parietal, and occipital regions were significantly decreased in patients compared with the controls. The slowing in EEG was moderately correlated with MMSE scores ( r = 0.411-0.593; P < .01). However, qEEG analysis and extensive neuropsychological assessment battery were only in weak correlation ( r = 0.230-0.486; P < .05). In conclusion, qEEG analysis could increase the diagnostic power in detecting subtle cognitive impairment in PD patients without evident cognitive deficit, perhaps years before the clinical onset of dementia.
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Affiliation(s)
- Derya Guner
- 1 Department of Neurology, Tepecik Education and Research Hospital, Izmir, Turkey
| | | | - Nilgun Tuncay
- 1 Department of Neurology, Tepecik Education and Research Hospital, Izmir, Turkey
| | - Yasar Zorlu
- 1 Department of Neurology, Tepecik Education and Research Hospital, Izmir, Turkey
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36
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Hassan M, Chaton L, Benquet P, Delval A, Leroy C, Plomhause L, Moonen AJH, Duits AA, Leentjens AFG, van Kranen-Mastenbroek V, Defebvre L, Derambure P, Wendling F, Dujardin K. Functional connectivity disruptions correlate with cognitive phenotypes in Parkinson's disease. NEUROIMAGE-CLINICAL 2017; 14:591-601. [PMID: 28367403 PMCID: PMC5361870 DOI: 10.1016/j.nicl.2017.03.002] [Citation(s) in RCA: 65] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/13/2016] [Revised: 02/28/2017] [Accepted: 03/04/2017] [Indexed: 01/21/2023]
Abstract
Cognitive deficits in Parkinson's disease are thought to be related to altered functional brain connectivity. To date, cognitive-related changes in Parkinson's disease have never been explored with dense-EEG with the aim of establishing a relationship between the degree of cognitive impairment, on the one hand, and alterations in the functional connectivity of brain networks, on the other hand. This study was aimed at identifying altered brain networks associated with cognitive phenotypes in Parkinson's disease using dense-EEG data recorded during rest with eyes closed. Three groups of Parkinson's disease patients (N = 124) with different cognitive phenotypes coming from a data-driven cluster analysis, were studied: G1) cognitively intact patients (63), G2) patients with mild cognitive deficits (46) and G3) patients with severe cognitive deficits (15). Functional brain networks were identified using a dense-EEG source connectivity method. Pairwise functional connectivity was computed for 68 brain regions in different EEG frequency bands. Network statistics were assessed at both global (network topology) and local (inter-regional connections) level. Results revealed progressive disruptions in functional connectivity between the three patient groups, typically in the alpha band. Differences between G1 and G2 (p < 0.001, corrected using permutation test) were mainly frontotemporal alterations. A statistically significant correlation (ρ = 0.49, p < 0.001) was also obtained between a proposed network-based index and the patients' cognitive score. Global properties of network topology in patients were relatively intact. These findings indicate that functional connectivity decreases with the worsening of cognitive performance and loss of frontotemporal connectivity may be a promising neuromarker of cognitive impairment in Parkinson's disease. We test the use of dense-EEG to identify altered brain networks associated with cognitive phenotypes in Parkinson's disease. The functional connectivity decreases with the worsening of cognitive performance The loss of frontotemporal connectivity may be a promising neuromarker of cognitive impairment in Parkinson's disease.
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Affiliation(s)
- M Hassan
- INSERM, U1099, F-35000 Rennes, France; University of Rennes 1, LTSI, F-35000 Rennes, France
| | - L Chaton
- CHU Lille, Clinical Neurophysiology Department, F-59000 Lille, France
| | - P Benquet
- INSERM, U1099, F-35000 Rennes, France; University of Rennes 1, LTSI, F-35000 Rennes, France
| | - A Delval
- University of Lille, U1171 - Degenerative & Vascular Cognitive Disorders, F-59000 Lille, France; INSERM, U1171, F-59000 Lille, France; CHU Lille, Clinical Neurophysiology Department, F-59000 Lille, France
| | - C Leroy
- University of Lille, U1171 - Degenerative & Vascular Cognitive Disorders, F-59000 Lille, France; INSERM, U1171, F-59000 Lille, France; CHU Lille, Clinical Neurophysiology Department, F-59000 Lille, France
| | - L Plomhause
- University of Lille, U1171 - Degenerative & Vascular Cognitive Disorders, F-59000 Lille, France; INSERM, U1171, F-59000 Lille, France; CHU Lille, Clinical Neurophysiology Department, F-59000 Lille, France
| | - A J H Moonen
- Maastricht University Medical Center, Maastricht, The Netherlands
| | - A A Duits
- Maastricht University Medical Center, Maastricht, The Netherlands
| | - A F G Leentjens
- Maastricht University Medical Center, Maastricht, The Netherlands
| | | | - L Defebvre
- University of Lille, U1171 - Degenerative & Vascular Cognitive Disorders, F-59000 Lille, France; INSERM, U1171, F-59000 Lille, France; CHU Lille, Neurology and Movement Disorders Department, F-59000 Lille, France
| | - P Derambure
- University of Lille, U1171 - Degenerative & Vascular Cognitive Disorders, F-59000 Lille, France; INSERM, U1171, F-59000 Lille, France; CHU Lille, Clinical Neurophysiology Department, F-59000 Lille, France
| | - F Wendling
- INSERM, U1099, F-35000 Rennes, France; University of Rennes 1, LTSI, F-35000 Rennes, France
| | - K Dujardin
- University of Lille, U1171 - Degenerative & Vascular Cognitive Disorders, F-59000 Lille, France; INSERM, U1171, F-59000 Lille, France; CHU Lille, Neurology and Movement Disorders Department, F-59000 Lille, France
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Abstract
Dementia is a frequent problem encountered in advanced stages of Parkinson disease (PD). In recent years, research has focused on the pre-dementia stages of cognitive impairment in PD, including mild cognitive impairment (MCI). Several longitudinal studies have shown that MCI is a harbinger of dementia in PD, although the course is variable, and stabilization of cognition - or even reversal to normal cognition - is not uncommon. In addition to limbic and cortical spread of Lewy pathology, several other mechanisms are likely to contribute to cognitive decline in PD, and a variety of biomarker studies, some using novel structural and functional imaging techniques, have documented in vivo brain changes associated with cognitive impairment. The evidence consistently suggests that low cerebrospinal fluid levels of amyloid-β42, a marker of comorbid Alzheimer disease (AD), predict future cognitive decline and dementia in PD. Emerging genetic evidence indicates that in addition to the APOE*ε4 allele (an established risk factor for AD), GBA mutations and SCNA mutations and triplications are associated with cognitive decline in PD, whereas the findings are mixed for MAPT polymorphisms. Cognitive enhancing medications have some effect in PD dementia, but no convincing evidence that progression from MCI to dementia can be delayed or prevented is available, although cognitive training has shown promising results.
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Differential diagnosis between patients with probable Alzheimer's disease, Parkinson's disease dementia, or dementia with Lewy bodies and frontotemporal dementia, behavioral variant, using quantitative electroencephalographic features. J Neural Transm (Vienna) 2017; 124:569-581. [PMID: 28243755 PMCID: PMC5399050 DOI: 10.1007/s00702-017-1699-6] [Citation(s) in RCA: 45] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2016] [Accepted: 02/14/2017] [Indexed: 12/29/2022]
Abstract
The objective of this work was to develop and evaluate a classifier for differentiating probable Alzheimer’s disease (AD) from Parkinson’s disease dementia (PDD) or dementia with Lewy bodies (DLB) and from frontotemporal dementia, behavioral variant (bvFTD) based on quantitative electroencephalography (QEEG). We compared 25 QEEG features in 61 dementia patients (20 patients with probable AD, 20 patients with PDD or probable DLB (DLBPD), and 21 patients with bvFTD). Support vector machine classifiers were trained to distinguish among the three groups. Out of the 25 features, 23 turned out to be significantly different between AD and DLBPD, 17 for AD versus bvFTD, and 12 for bvFTD versus DLBPD. Using leave-one-out cross validation, the classification achieved an accuracy, sensitivity, and specificity of 100% using only the QEEG features Granger causality and the ratio of theta and beta1 band powers. These results indicate that classifiers trained with selected QEEG features can provide a valuable input in distinguishing among AD, DLB or PDD, and bvFTD patients. In this study with 61 patients, no misclassifications occurred. Therefore, further studies should investigate the potential of this method to be applied not only on group level but also in diagnostic support for individual subjects.
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Abstract
Pain is an integrative phenomenon that results from dynamic interactions between sensory and contextual (i.e., cognitive, emotional, and motivational) processes. In the brain the experience of pain is associated with neuronal oscillations and synchrony at different frequencies. However, an overarching framework for the significance of oscillations for pain remains lacking. Recent concepts relate oscillations at different frequencies to the routing of information flow in the brain and the signaling of predictions and prediction errors. The application of these concepts to pain promises insights into how flexible routing of information flow coordinates diverse processes that merge into the experience of pain. Such insights might have implications for the understanding and treatment of chronic pain.
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Affiliation(s)
- Markus Ploner
- Department of Neurology and TUMNeuroimaging Center, Technische Universität München, Munich, Germany.
| | - Christian Sorg
- Departments of Neuroradiology and Psychiatry and TUMNeuroimaging Center, Technische Universität München, Munich, Germany
| | - Joachim Gross
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, UK
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Cozac VV, Chaturvedi M, Hatz F, Meyer A, Fuhr P, Gschwandtner U. Increase of EEG Spectral Theta Power Indicates Higher Risk of the Development of Severe Cognitive Decline in Parkinson's Disease after 3 Years. Front Aging Neurosci 2016; 8:284. [PMID: 27965571 PMCID: PMC5126063 DOI: 10.3389/fnagi.2016.00284] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2016] [Accepted: 11/11/2016] [Indexed: 11/25/2022] Open
Abstract
Objective: We investigated quantitative electroencephalography (qEEG) and clinical parameters as potential risk factors of severe cognitive decline in Parkinson’s disease. Methods: We prospectively investigated 37 patients with Parkinson’s disease at baseline and follow-up (after 3 years). Patients had no severe cognitive impairment at baseline. We used a summary score of cognitive tests as the outcome at follow-up. At baseline we assessed motor, cognitive, and psychiatric factors; qEEG variables [global relative median power (GRMP) spectra] were obtained by a fully automated processing of high-resolution EEG (256-channels). We used linear regression models with calculation of the explained variance to evaluate the relation of baseline parameters with cognitive deterioration. Results: The following baseline parameters significantly predicted severe cognitive decline: GRMP theta (4–8 Hz), cognitive task performance in executive functions and working memory. Conclusions: Combination of neurocognitive tests and qEEG improves identification of patients with higher risk of cognitive decline in PD.
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Affiliation(s)
- Vitalii V Cozac
- Department of Neurology, Hospital of the University of Basel Basel, Switzerland
| | - Menorca Chaturvedi
- Department of Neurology, Hospital of the University of BaselBasel, Switzerland; Department of Mathematics and Computer Science, University of BaselBasel, Switzerland
| | - Florian Hatz
- Department of Neurology, Hospital of the University of Basel Basel, Switzerland
| | - Antonia Meyer
- Department of Neurology, Hospital of the University of Basel Basel, Switzerland
| | - Peter Fuhr
- Department of Neurology, Hospital of the University of Basel Basel, Switzerland
| | - Ute Gschwandtner
- Department of Neurology, Hospital of the University of Basel Basel, Switzerland
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Relation between Resting State Front-Parietal EEG Coherence and Executive Function in Parkinson's Disease. BIOMED RESEARCH INTERNATIONAL 2016; 2016:2845754. [PMID: 27433473 PMCID: PMC4940525 DOI: 10.1155/2016/2845754] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 11/12/2015] [Revised: 04/11/2016] [Accepted: 06/05/2016] [Indexed: 11/18/2022]
Abstract
Objective. To assess the relation between executive dysfunction (ED) in Parkinson's disease (PD) and resting state functional connectivity evaluated using electroencephalography (EEG) coherence. Methods. Sixty-eight nondemented sporadic PD patients were assessed using the Behavioural Assessment of the Dysexecutive Syndrome (BADS) to evaluate executive function. EEG coherence in the left frontoparietal electrode pair (F3-P3) and the right frontoparietal electrode pair (F4-P4) was analyzed in the alpha and theta range. The BADS scores were compared across the coherence groups, and the multiple logistic regression analysis was performed to assess the contribution of confounders. Results. The standardized BADS score was significantly lower in the low F3-P3 coherence group in the alpha range (Mann-Whitney U test, p = 0.032), though there was no difference between F4-P4 coherence group in the alpha range, F3-P3, and F4-P4 coherence groups in the theta range and the standardized BADS score. The multiple logistic regression analysis revealed the significant relation between the F3-P3 coherence group in alpha range and age-controlled standardized BADS score (p = 0.039, 95% CI = 1.002-1.062). Conclusion. The decrease in resting state functional connectivity between the frontal and parietal cortices especially in the left side is related to ED in PD.
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Delgado-Alvarado M, Gago B, Navalpotro-Gomez I, Jiménez-Urbieta H, Rodriguez-Oroz MC. Biomarkers for dementia and mild cognitive impairment in Parkinson's disease. Mov Disord 2016; 31:861-81. [PMID: 27193487 DOI: 10.1002/mds.26662] [Citation(s) in RCA: 109] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2016] [Revised: 04/15/2016] [Accepted: 04/18/2016] [Indexed: 12/27/2022] Open
Abstract
Cognitive decline is one of the most frequent and disabling nonmotor features of Parkinson's disease. Around 30% of patients with Parkinson's disease experience mild cognitive impairment, a well-established risk factor for the development of dementia. However, mild cognitive impairment in patients with Parkinson's disease is a heterogeneous entity that involves different types and extents of cognitive deficits. Because it is not currently known which type of mild cognitive impairment confers a higher risk of progression to dementia, it would be useful to define biomarkers that could identify these patients to better study disease progression and possible interventions. In this sense, the identification among patients with Parkinson's disease and mild cognitive impairment of biomarkers associated with dementia would allow the early detection of this process. This review summarizes studies from the past 25 years that have assessed the potential biomarkers of dementia and mild cognitive impairment in Parkinson's disease patients. Despite the potential importance, no biomarker has as yet been validated. However, features such as low levels of epidermal and insulin-like growth factors or uric acid in plasma/serum and of Aß in CSF, reduction of cerebral cholinergic innervation and metabolism measured by PET mainly in posterior areas, and hippocampal atrophy in MRI might be indicative of distinct deficits with a distinct risk of dementia in subgroups of patients. Longitudinal studies combining the existing techniques and new approaches are needed to identify patients at higher risk of dementia. © 2016 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Manuel Delgado-Alvarado
- Biodonostia Health Research Institute, San Sebastián, Spain.,Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| | - Belén Gago
- Biodonostia Health Research Institute, San Sebastián, Spain.,Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| | - Irene Navalpotro-Gomez
- Biodonostia Health Research Institute, San Sebastián, Spain.,Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| | - Haritz Jiménez-Urbieta
- Biodonostia Health Research Institute, San Sebastián, Spain.,Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| | - María C Rodriguez-Oroz
- Biodonostia Health Research Institute, San Sebastián, Spain.,Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain.,Neurology Department, University Hospital Donostia, San Sebastián, Spain.,Ikerbasque (Basque Foundation for Science), Bilbao, Spain.,Basque Center on Cognition, Brain and Language (BCBL), San Sebastián, Spain.,Physiology Department, Medical School University of Navarra, Pamplona, Spain
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Quantitative EEG and Cognitive Decline in Parkinson's Disease. PARKINSONS DISEASE 2016; 2016:9060649. [PMID: 27148466 PMCID: PMC4842380 DOI: 10.1155/2016/9060649] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/16/2015] [Accepted: 03/14/2016] [Indexed: 12/14/2022]
Abstract
Cognitive decline is common with the progression of Parkinson's disease (PD). Different candidate biomarkers are currently studied for the risk of dementia in PD. Several studies have shown that quantitative EEG (QEEG) is a promising predictor of PD-related cognitive decline. In this paper we briefly outline the basics of QEEG analysis and analyze the recent publications addressing the predictive value of QEEG in the context of cognitive decline in PD. The MEDLINE database was searched for relevant publications from January 01, 2005, to March 02, 2015. Twenty-four studies reported QEEG findings in various cognitive states in PD. Spectral and connectivity markers of QEEG could help to discriminate between PD patients with different level of cognitive decline. QEEG variables correlate with tools for cognitive assessment over time and are associated with significant hazard ratios to predict PD-related dementia. QEEG analysis shows high test-retest reliability and avoids learning effects associated with some neuropsychological testing; it is noninvasive and relatively easy to repeat.
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44
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Wavelet Energy and Wavelet Coherence as EEG Biomarkers for the Diagnosis of Parkinson’s Disease-Related Dementia and Alzheimer’s Disease. ENTROPY 2015. [DOI: 10.3390/e18010008] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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45
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Fonseca LC, Tedrus GMAS, Rezende ALRA, Giordano HF. Coherence of brain electrical activity: a quality of life indicator in Alzheimer’s disease?Coerência da atividade elétrica cerebral: indicador da qualidade de vida na doença de Alzheimer? ARQUIVOS DE NEURO-PSIQUIATRIA 2015; 73:396-401. [DOI: 10.1590/0004-282x20150035] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2014] [Accepted: 01/08/2015] [Indexed: 11/21/2022]
Abstract
Objective To investigate the relationships between quality of life (QOL) and clinical and electroencephalogram (EEG) aspects in patients with Alzheimer’s disease (AD). Method Twenty-eight patients with mild or moderate AD, 31 with Parkinson’s disease (PD), and 27 normal controls (NC) were submitted to: CERAD neuropsychological battery, Hamilton Depression and Anxiety Rating Scales, Functional Activities Questionnaire, QOL scale for patients with AD, and quantitative EEG measures. Results AD and PD patients had similar QOL (31.0 ± 5.8; 31.7 ± 4.8, respectively), worse than that of NC (37.5 ± 6.3). AD patients had lower global interhemispheric theta coherence (0.49 ± 0.04; 0.52 ± 0.05; 0.52 ± 0.05; respectively) than PD and NC. Multiple linear regression for QOL of AD patients revealed that global interhemispheric theta coherence, and Hamilton depression scores were significant factors (coefficients; 58.2 and -0.27, respectively; R2, 0.377). Conclusion Interhemispheric coherence correlates with QOL regardless of cognitive and functional variables and seems to be a neurophysiological indicator of QOL in AD patients.
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Benz N, Hatz F, Bousleiman H, Ehrensperger MM, Gschwandtner U, Hardmeier M, Ruegg S, Schindler C, Zimmermann R, Monsch AU, Fuhr P. Slowing of EEG background activity in Parkinson's and Alzheimer's disease with early cognitive dysfunction. Front Aging Neurosci 2014; 6:314. [PMID: 25477817 PMCID: PMC4235380 DOI: 10.3389/fnagi.2014.00314] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2014] [Accepted: 10/24/2014] [Indexed: 11/26/2022] Open
Abstract
Background: Slowing of the electroencephalogram (EEG) is frequent in Parkinson’s (PD) and Alzheimer’s disease (AD) and correlates with cognitive decline. As overlap pathology plays a role in the pathogenesis of dementia, it is likely that demented patients in PD show similar physiological alterations as in AD. Objective: To analyze distinctive quantitative EEG characteristics in early cognitive dysfunction in PD and AD. Methods: Forty patients (20 PD- and 20 AD patients with early cognitive impairment) and 20 normal controls (NC) were matched for gender, age, and education. Resting state EEG was recorded from 256 electrodes. Relative power spectra, median frequency (4–14 Hz), and neuropsychological outcome were compared between groups. Results: Relative theta power in left temporal region and median frequency separated the three groups significantly (p = 0.002 and p < 0.001). Relative theta power was increased and median frequency reduced in patients with both diseases compared to NC. Median frequency was higher in AD than in PD and classified groups significantly (p = 0.02). Conclusion: Increase of theta power in the left temporal region and a reduction of median frequency were associated with presence of AD or PD. PD patients are characterized by a pronounced slowing as compared to AD patients. Therefore, in both disorders EEG slowing might be a useful biomarker for beginning cognitive decline.
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Affiliation(s)
- Nina Benz
- Department of Neurology, Hospitals of University of Basel , Basel , Switzerland
| | - Florian Hatz
- Department of Neurology, Hospitals of University of Basel , Basel , Switzerland
| | - Habib Bousleiman
- Department of Neurology, Hospitals of University of Basel , Basel , Switzerland ; Swiss Tropical and Public Health Institute, University of Basel , Basel , Switzerland
| | - Michael M Ehrensperger
- Memory Clinic, University Center for Medicine of Aging Basel, Felix Platter Hospital , Basel , Switzerland
| | - Ute Gschwandtner
- Department of Neurology, Hospitals of University of Basel , Basel , Switzerland
| | - Martin Hardmeier
- Department of Neurology, Hospitals of University of Basel , Basel , Switzerland
| | - Stephan Ruegg
- Department of Neurology, Hospitals of University of Basel , Basel , Switzerland
| | - Christian Schindler
- Swiss Tropical and Public Health Institute, University of Basel , Basel , Switzerland
| | - Ronan Zimmermann
- Department of Neurology, Hospitals of University of Basel , Basel , Switzerland
| | - Andreas Urs Monsch
- Memory Clinic, University Center for Medicine of Aging Basel, Felix Platter Hospital , Basel , Switzerland
| | - Peter Fuhr
- Department of Neurology, Hospitals of University of Basel , Basel , Switzerland
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Bousleiman H, Zimmermann R, Ahmed S, Hardmeier M, Hatz F, Schindler C, Roth V, Gschwandtner U, Fuhr P. Power spectra for screening parkinsonian patients for mild cognitive impairment. Ann Clin Transl Neurol 2014; 1:884-90. [PMID: 25540802 PMCID: PMC4265059 DOI: 10.1002/acn3.129] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2014] [Revised: 09/09/2014] [Accepted: 09/15/2014] [Indexed: 11/07/2022] Open
Abstract
OBJECTIVE Mild cognitive impairment in Parkinson's disease (PD-MCI) is diagnosed based on the results of a standardized set of cognitive tests. We investigate whether quantitative EEG (qEEG) measures could identify differences between cognitively normal PD (PD-CogNL) and PD-MCI patients. METHODS High-resolution EEG was recorded in 53 patients with Parkinson's disease (PD). Relative power in five frequency bands was calculated globally and for ten regions. Peak and median frequencies were determined. qEEG results were compared between groups. Effect sizes of all variables were calculated. The best separating variable was used to demonstrate subject-wise classification. RESULTS Lower mean values were observed in global alpha1 power and alpha1 power in five brain regions (left hemisphere: frontal, central, temporal, occipital; right hemisphere: temporal, P < 0.05), differentiating between PD-CogNL and PD-MCI groups. Effect sizes were high, ranging from 0.79 to 0.87. Median frequency was 8.56 ± 0.74 Hz and was not different between the groups. The variable with the best subject-wise classification was the power in the alpha1 band in the right temporal region. The area under the corresponding receiver operating characteristic (ROC) curve was 0.72. The optimal classification threshold yielded a sensitivity of 65.9% and a specificity of 66.7%. The positive and negative predictive values were 87.1% and 36.4%, respectively. INTERPRETATION Reduction in alpha1 band power in nondemented PD patients, particularly in the right temporal region, is highly indicative of MCI in PD patients. The results might be used to assist in time-efficient diagnosis of PD-MCI and avoid the drawbacks of test-retest effect in repeated neuropsychological testing.
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Affiliation(s)
- Habib Bousleiman
- Department of Neurology, Hospital of the University of BaselPetersgraben 4, 4031, Basel, Switzerland
- Swiss Tropical and Public Health Institute, University of BaselSocinstrasse 57, 4051, Basel, Switzerland
| | - Ronan Zimmermann
- Department of Neurology, Hospital of the University of BaselPetersgraben 4, 4031, Basel, Switzerland
| | - Shaheen Ahmed
- Department of Neurology, Hospital of the University of BaselPetersgraben 4, 4031, Basel, Switzerland
| | - Martin Hardmeier
- Department of Neurology, Hospital of the University of BaselPetersgraben 4, 4031, Basel, Switzerland
| | - Florian Hatz
- Department of Neurology, Hospital of the University of BaselPetersgraben 4, 4031, Basel, Switzerland
| | - Christian Schindler
- Swiss Tropical and Public Health Institute, University of BaselSocinstrasse 57, 4051, Basel, Switzerland
| | - Volker Roth
- Department of Mathematics and Computer Science, University of BaselBernoullistrasse 16, 4056, Basel, Switzerland
| | - Ute Gschwandtner
- Department of Neurology, Hospital of the University of BaselPetersgraben 4, 4031, Basel, Switzerland
| | - Peter Fuhr
- Department of Neurology, Hospital of the University of BaselPetersgraben 4, 4031, Basel, Switzerland
- Correspondence: Peter Fuhr, Department of Neurology, Hospital of the University of Basel, Petersgraben 4, 4031 Basel, Switzerland. Tel: +41(0)612652525; Fax: +41(0)612655638; E-mail:
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Yuvaraj R, Murugappan M, Ibrahim NM, Sundaraj K, Omar MI, Mohamad K, Palaniappan R, Satiyan M. Inter-hemispheric EEG coherence analysis in Parkinson’s disease: Assessing brain activity during emotion processing. J Neural Transm (Vienna) 2014; 122:237-52. [DOI: 10.1007/s00702-014-1249-4] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2013] [Accepted: 05/20/2014] [Indexed: 11/24/2022]
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49
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Aoki Y, Kazui H, Tanaka T, Ishii R, Wada T, Ikeda S, Hata M, Canuet L, Musha T, Matsuzaki H, Imajo K, Yoshiyama K, Yoshida T, Shimizu Y, Nomura K, Iwase M, Takeda M. EEG and Neuronal Activity Topography analysis can predict effectiveness of shunt operation in idiopathic normal pressure hydrocephalus patients. NEUROIMAGE-CLINICAL 2013; 3:522-30. [PMID: 24273735 PMCID: PMC3830071 DOI: 10.1016/j.nicl.2013.10.009] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/05/2013] [Revised: 09/30/2013] [Accepted: 10/13/2013] [Indexed: 11/19/2022]
Abstract
Idiopathic normal pressure hydrocephalus (iNPH) is a neuropsychiatric syndrome characterized by gait disturbance, cognitive impairment and urinary incontinence that affect elderly individuals. These symptoms can potentially be reversed by cerebrospinal fluid (CSF) drainage or shunt operation. Prior to shunt operation, drainage of a small amount of CSF or "CSF tapping" is usually performed to ascertain the effect of the operation. Unfortunately, conventional neuroimaging methods such as single photon emission computed tomography (SPECT) and functional magnetic resonance imaging (fMRI), as well as electroencephalogram (EEG) power analysis seem to have failed to detect the effect of CSF tapping on brain function. In this work, we propose the use of Neuronal Activity Topography (NAT) analysis, which calculates normalized power variance (NPV) of EEG waves, to detect cortical functional changes induced by CSF tapping in iNPH. Based on clinical improvement by CSF tapping and shunt operation, we classified 24 iNPH patients into responders (N = 11) and nonresponders (N = 13), and performed both EEG power analysis and NAT analysis. We also assessed correlations between changes in NPV and changes in functional scores on gait and cognition scales before and after CSF tapping. NAT analysis showed that after CSF tapping there was a significant decrease in alpha NPV at the medial frontal cortex (FC) (Fz) in responders, while nonresponders exhibited an increase in alpha NPV at the right dorsolateral prefrontal cortex (DLPFC) (F8). Furthermore, we found correlations between cortical functional changes and clinical symptoms. In particular, delta and alpha NPV changes in the left-dorsal FC (F3) correlated with changes in gait status, while alpha and beta NPV changes in the right anterior prefrontal cortex (PFC) (Fp2) and left DLPFC (F7) as well as alpha NPV changes in the medial FC (Fz) correlated with changes in gait velocity. In addition, alpha NPV changes in the right DLPFC (F8) correlated with changes in WMS-R Mental Control scores in iNPH patients. An additional analysis combining the changes in values of alpha NPV over the left-dorsal FC (∆alpha-F3-NPV) and the medial FC (∆alpha-Fz-NPV) induced by CSF tapping (cut-off value of ∆alpha-F3-NPV + ∆alpha-Fz-NPV = 0), could correctly identified "shunt responders" and "shunt nonresponders" with a positive predictive value of 100% (10/10) and a negative predictive value of 66% (2/3). In contrast, EEG power spectral analysis showed no function related changes in cortical activity at the frontal cortex before and after CSF tapping. These results indicate that the clinical changes in gait and response suppression induced by CSF tapping in iNPH patients manifest as NPV changes, particularly in the alpha band, rather than as EEG power changes. Our findings suggest that NAT analysis can detect CSF tapping-induced functional changes in cortical activity, in a way that no other neuroimaging methods have been able to do so far, and can predict clinical response to shunt operation in patients with iNPH.
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Affiliation(s)
- Yasunori Aoki
- Department of Psychiatry, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
| | - Hiroaki Kazui
- Department of Psychiatry, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
| | - Toshihisa Tanaka
- Department of Psychiatry, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
| | - Ryouhei Ishii
- Department of Psychiatry, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
- Corresponding author at: Department of Psychiatry, Osaka University Graduate School of Medicine, D3 2-2 Yamada-oka, Suita, Osaka 565-0871, Japan. Tel.: + 81-6-6879-3051; fax: + 81-6-6879-3059.
| | - Tamiki Wada
- Department of Psychiatry, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
| | - Shunichiro Ikeda
- Department of Psychiatry, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
| | - Masahiro Hata
- Department of Psychiatry, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
| | - Leonides Canuet
- UCM-UPM Centre for Biomedical Technology, Department of Cognitive and Computational Neuroscience, Complutense University of Madrid, Madrid, Spain
| | | | | | - Kaoru Imajo
- Nihon Kohden Corporation, Shinjuku, Tokyo, Japan
| | - Kenji Yoshiyama
- Department of Psychiatry, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
| | - Tetsuhiko Yoshida
- Department of Psychiatry, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
| | - Yoshiro Shimizu
- Department of Psychiatry, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
| | - Keiko Nomura
- Department of Psychiatry, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
| | - Masao Iwase
- Department of Psychiatry, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
| | - Masatoshi Takeda
- Department of Psychiatry, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
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