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Plaza-Rosales I, Brunetti E, Montefusco-Siegmund R, Madariaga S, Hafelin R, Ponce DP, Behrens MI, Maldonado PE, Paula-Lima A. Visual-spatial processing impairment in the occipital-frontal connectivity network at early stages of Alzheimer's disease. Front Aging Neurosci 2023; 15:1097577. [PMID: 36845655 PMCID: PMC9947357 DOI: 10.3389/fnagi.2023.1097577] [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: 11/15/2022] [Accepted: 01/20/2023] [Indexed: 02/11/2023] Open
Abstract
Introduction Alzheimer's disease (AD) is the leading cause of dementia worldwide, but its pathophysiological phenomena are not fully elucidated. Many neurophysiological markers have been suggested to identify early cognitive impairments of AD. However, the diagnosis of this disease remains a challenge for specialists. In the present cross-sectional study, our objective was to evaluate the manifestations and mechanisms underlying visual-spatial deficits at the early stages of AD. Methods We combined behavioral, electroencephalography (EEG), and eye movement recordings during the performance of a spatial navigation task (a virtual version of the Morris Water Maze adapted to humans). Participants (69-88 years old) with amnesic mild cognitive impairment-Clinical Dementia Rating scale (aMCI-CDR 0.5) were selected as probable early AD (eAD) by a neurologist specialized in dementia. All patients included in this study were evaluated at the CDR 0.5 stage but progressed to probable AD during clinical follow-up. An equal number of matching healthy controls (HCs) were evaluated while performing the navigation task. Data were collected at the Department of Neurology of the Clinical Hospital of the Universidad de Chile and the Department of Neuroscience of the Faculty of Universidad de Chile. Results Participants with aMCI preceding AD (eAD) showed impaired spatial learning and their visual exploration differed from the control group. eAD group did not clearly prefer regions of interest that could guide solving the task, while controls did. The eAD group showed decreased visual occipital evoked potentials associated with eye fixations, recorded at occipital electrodes. They also showed an alteration of the spatial spread of activity to parietal and frontal regions at the end of the task. The control group presented marked occipital activity in the beta band (15-20 Hz) at early visual processing time. The eAD group showed a reduction in beta band functional connectivity in the prefrontal cortices reflecting poor planning of navigation strategies. Discussion We found that EEG signals combined with visual-spatial navigation analysis, yielded early and specific features that may underlie the basis for understanding the loss of functional connectivity in AD. Still, our results are clinically promising for early diagnosis required to improve quality of life and decrease healthcare costs.
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Affiliation(s)
- Iván Plaza-Rosales
- Department of Medical Technology, Faculty of Medicine, Universidad de Chile, Santiago, Chile,Biomedical Neuroscience Institute, Faculty of Medicine, Universidad de Chile, Santiago, Chile
| | - Enzo Brunetti
- Biomedical Neuroscience Institute, Faculty of Medicine, Universidad de Chile, Santiago, Chile,Institute of Neurosurgery and Brain Research Dr. Alfonso Asenjo, Santiago, Chile,Department of Neuroscience, Faculty of Medicine, Universidad de Chile, Santiago, Chile
| | - Rodrigo Montefusco-Siegmund
- Faculty of Medicine, Institute of Locomotor System and Rehabilitation, Universidad Austral de Chile, Valdivia, Chile
| | - Samuel Madariaga
- Biomedical Neuroscience Institute, Faculty of Medicine, Universidad de Chile, Santiago, Chile
| | - Rodrigo Hafelin
- Biomedical Neuroscience Institute, Faculty of Medicine, Universidad de Chile, Santiago, Chile
| | - Daniela P. Ponce
- Department of Neurology and Neurosurgery, Hospital Clínico Universidad de Chile, Santiago, Chile,Faculty of Medicine, Center for Advanced Clinical Research, Universidad de Chile, Santiago, Chile
| | - María Isabel Behrens
- Department of Neuroscience, Faculty of Medicine, Universidad de Chile, Santiago, Chile,Department of Neurology and Neurosurgery, Hospital Clínico Universidad de Chile, Santiago, Chile,Faculty of Medicine, Center for Advanced Clinical Research, Universidad de Chile, Santiago, Chile,Department of Neurology and Psychiatry, Clínica Alemana-Universidad del Desarrollo, Santiago, Chile
| | - Pedro E. Maldonado
- Biomedical Neuroscience Institute, Faculty of Medicine, Universidad de Chile, Santiago, Chile,Department of Neuroscience, Faculty of Medicine, Universidad de Chile, Santiago, Chile,Pedro E. Maldonado,
| | - Andrea Paula-Lima
- Biomedical Neuroscience Institute, Faculty of Medicine, Universidad de Chile, Santiago, Chile,Department of Neuroscience, Faculty of Medicine, Universidad de Chile, Santiago, Chile,Institute for Research in Dental Sciences, Faculty of Dentistry, Universidad de Chile, Santiago, Chile,*Correspondence: Andrea Paula-Lima,
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Martin T, Kero K, Požar R, Giordani B, Kavcic V. Mild Cognitive Impairment in African Americans Is Associated with Differences in EEG Theta/Beta Ratio. J Alzheimers Dis 2023; 94:347-357. [PMID: 37248895 DOI: 10.3233/jad-220981] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
BACKGROUND Identification of older individuals with increased risk for cognitive decline can contribute not only to personal benefits (e.g., early treatment, evaluation of treatment), but could also benefit clinical trials (e.g., patient selection). We propose that baseline resting-state electroencephalography (rsEEG) could provide markers for early identification of cognitive decline. OBJECTIVE To determine whether rsEEG theta/beta ratio (TBR) differed between mild cognitively impaired (MCI) and healthy older adults. METHODS We analyzed rsEEG from a sample of 99 (ages 60-90) consensus-diagnosed, community-dwelling older African Americans (58 cognitively typical and 41 MCI). Eyes closed rsEEGs were acquired before and after participants engaged in a visual motion direction discrimination task. rsEEG TBR was calculated for four midline locations and assessed for differences as a function of MCI status. Hemispheric asymmetry of TBR was also analyzed at equidistant lateral electrode sites. RESULTS Results showed that MCI participants had a higher TBR than controls (p = 0.04), and that TBR significantly differed across vertex location (p < 0.001) with the highest TBR at parietal site. MCI and cognitively normal controls also differed in hemispheric asymmetries, such that MCI show higher TBR at frontal sites, with TBR greater over right frontal electrodes in the MCI group (p = 0.003) and no asymmetries found in the cognitively normal group. Lastly, we found a significant task aftereffect (post-task compared to pre-task measures) with higher TBR at posterior locations (Oz p = 0.002, Pz p = 0.057). CONCLUSION TBR and TBR asymmetries differ between MCI and cognitively normal older adults and may reflect neurodegenerative processes underlying MCI symptoms.
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Affiliation(s)
- Tim Martin
- Department of Psychological Science, Kennesaw State University, GA, USA
| | - Katherine Kero
- Institute of Gerontology, Wayne State University, Detroit, MI, USA
| | - Rok Požar
- University of Primorska, Faculty of Mathematics, Natural Sciences and Information Technologies, Koper, Slovenia
- University of Primorska, Andrej Marušič Institute, Koper, Slovenia
- Institute of Mathematics, Physics and Mechanics, Ljubljana, Slovenia
| | - Bruno Giordani
- Departments of Psychiatry, Neurology, and Psychology and School of Nursing, University of Michigan, Ann Arbor, MI, USA
| | - Voyko Kavcic
- Institute of Gerontology, Wayne State University, Detroit, MI, USA
- International Institute of Applied Gerontology, Ljubljana, Slovenia
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Martin T, Giordani B, Kavcic V. EEG asymmetry and cognitive testing in MCI identification. Int J Psychophysiol 2022; 177:213-219. [PMID: 35618112 PMCID: PMC10756646 DOI: 10.1016/j.ijpsycho.2022.05.012] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Revised: 04/05/2022] [Accepted: 05/18/2022] [Indexed: 01/18/2023]
Abstract
BACKGROUND Finding the baseline resting-state EEG markers for early identification of cognitive decline can contribute to the identification of individuals at risk of further change. Potential applications include identifying participants for clinical trials, early treatment, and evaluation of treatment, accessible even from a community setting. METHODS Analyses were completed on a sample of 99 (ages 60-90) consensus-diagnosed, community-dwelling African Americans (58 cognitively typical/HC, and 41 mildly cognitively impaired/MCI), who were recruited from the Michigan Alzheimer's Disease Research Center (MADRC) and the Wayne State University Institute of Gerontology. In addition to neuropsychological testing with CogState and Toolbox computerized batteries, resting-state EEGs (rsEEG, eyes closed) were acquired before and after participants were engaged in a visual motion direction discrimination task. rsEEG frontal alpha asymmetry (FAA) and frontal beta asymmetry (FBA) were calculated. RESULTS FAA showed no difference across groups for the pre-task resting state. FBA was significantly different between groups, with more asymmetric frontal beta in MCI. Both physiological indices, however, along with computerized neuropsychological tests were significant predictors in logistic regression classification of MCI vs. control participants. CONCLUSION rsEEG asymmetries can contribute significantly to successful discrimination of older persons with MCI from those without, over and above cognitive testing, alone.
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Affiliation(s)
- Tim Martin
- Department of Psychological Sciences, Kennesaw State University, GA, USA
| | - Bruno Giordani
- Departments of Psychiatry, Neurology, and Psychology and School of Nursing, University of Michigan, Ann Arbor, MI, USA
| | - Voyko Kavcic
- Institute of Gerontology, Wayne State University, USA; International Institute of Applied Gerontology, Ljubljana, Slovenia.
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4
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de Frutos-Lucas J, Cuesta P, Ramírez-Toraño F, Nebreda A, Cuadrado-Soto E, Peral-Suárez Á, Lopez-Sanz D, Bruña R, Marcos-de Pedro S, Delgado-Losada ML, López-Sobaler AM, Concepción Rodríguez-Rojo I, Barabash A, Serrano Rodriguez JM, Laws SM, Dolado AM, López-Higes R, Brown BM, Maestú F. Age and APOE genotype affect the relationship between objectively measured physical activity and power in the alpha band, a marker of brain disease. Alzheimers Res Ther 2020; 12:113. [PMID: 32962736 PMCID: PMC7507658 DOI: 10.1186/s13195-020-00681-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Accepted: 09/10/2020] [Indexed: 02/06/2023]
Abstract
BACKGROUND Electrophysiological studies show that reductions in power within the alpha band are associated with the Alzheimer's disease (AD) continuum. Physical activity (PA) is a protective factor that has proved to reduce AD risk and pathological brain burden. Previous research has confirmed that exercise increases power in the alpha range. However, little is known regarding whether other non-modifiable risk factors for AD, such as increased age or APOE ε4 carriage, alter the association between PA and power in the alpha band. METHODS The relationship between PA and alpha band power was examined in a sample of 113 healthy adults using magnetoencephalography. Additionally, we explored whether ε4 carriage and age modulate this association. The correlations between alpha power and gray matter volumes and cognition were also investigated. RESULTS We detected a parieto-occipital cluster in which PA positively correlated with alpha power. The association between PA and alpha power remained following stratification of the cohort by genotype. Younger and older adults were investigated separately, and only younger adults exhibited a positive relationship between PA and alpha power. Interestingly, when four groups were created based on age (younger-older adult) and APOE (E3/E3-E3/E4), only younger E3/E3 (least predicted risk) and older E3/E4 (greatest predicted risk) had associations between greater alpha power and higher PA. Among older E3/E4, greater alpha power in these regions was associated with improved memory and preserved brain structure. CONCLUSION PA could protect against the slowing of brain activity that characterizes the AD continuum, where it is of benefit for all individuals, especially E3/E4 older adults.
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Affiliation(s)
- Jaisalmer de Frutos-Lucas
- Collaborative Genomics Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, 6027, Australia.
- Biological and Health Psychology Department, School of Psychology, Universidad Autonoma de Madrid, 28049, Madrid, Spain.
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology, Parque Científico y Tecnológico de la UPM, Crta. M40, Km. 38, 28223, Pozuelo de Alarcón, Madrid, Spain.
| | - Pablo Cuesta
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology, Parque Científico y Tecnológico de la UPM, Crta. M40, Km. 38, 28223, Pozuelo de Alarcón, Madrid, Spain
- Experimental Psychology Department, School of Psychology, Universidad Complutense de Madrid, 28223, Pozuelo de Alarcon, Spain
| | - Federico Ramírez-Toraño
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology, Parque Científico y Tecnológico de la UPM, Crta. M40, Km. 38, 28223, Pozuelo de Alarcón, Madrid, Spain
- Experimental Psychology Department, School of Psychology, Universidad Complutense de Madrid, 28223, Pozuelo de Alarcon, Spain
| | - Alberto Nebreda
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology, Parque Científico y Tecnológico de la UPM, Crta. M40, Km. 38, 28223, Pozuelo de Alarcón, Madrid, Spain
- Experimental Psychology Department, School of Psychology, Universidad Complutense de Madrid, 28223, Pozuelo de Alarcon, Spain
| | - Esther Cuadrado-Soto
- Departamento de Nutricion y Ciencia de los Alimentos, Facultad de Farmacia, Universidad Complutense de Madrid, 28040, Madrid, Spain
- IMDEA-Food, CEI UAM + CSIC, Madrid, 28049, Spain
| | - África Peral-Suárez
- Departamento de Nutricion y Ciencia de los Alimentos, Facultad de Farmacia, Universidad Complutense de Madrid, 28040, Madrid, Spain
| | - David Lopez-Sanz
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology, Parque Científico y Tecnológico de la UPM, Crta. M40, Km. 38, 28223, Pozuelo de Alarcón, Madrid, Spain
- Department of Psychobiology and Methodology in Behavioral Sciences, Universidad Complutense de Madrid (UCM), Pozuelo de Alarcón, 28223, Spain
| | - Ricardo Bruña
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology, Parque Científico y Tecnológico de la UPM, Crta. M40, Km. 38, 28223, Pozuelo de Alarcón, Madrid, Spain
- Experimental Psychology Department, School of Psychology, Universidad Complutense de Madrid, 28223, Pozuelo de Alarcon, Spain
- Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), 28029, Madrid, Spain
| | - Silvia Marcos-de Pedro
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology, Parque Científico y Tecnológico de la UPM, Crta. M40, Km. 38, 28223, Pozuelo de Alarcón, Madrid, Spain
- Departamento de Especialidades Medicas y Salud Pública, Universidad Rey Juan Carlos, 28922, Alcorcon, Spain
| | - María Luisa Delgado-Losada
- Experimental Psychology Department, School of Psychology, Universidad Complutense de Madrid, 28223, Pozuelo de Alarcon, Spain
| | - Ana María López-Sobaler
- Departamento de Nutricion y Ciencia de los Alimentos, Facultad de Farmacia, Universidad Complutense de Madrid, 28040, Madrid, Spain
| | - Inmaculada Concepción Rodríguez-Rojo
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology, Parque Científico y Tecnológico de la UPM, Crta. M40, Km. 38, 28223, Pozuelo de Alarcón, Madrid, Spain
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas, 28040, Madrid, Spain
- Physiotherapy and Nursing Faculty, University of Castilla-La Mancha, Toledo, 45004, Spain
| | - Ana Barabash
- Endocrinology and Nutrition Department, Hospital Clinico San Carlos and Instituto de Investigación Sanitaria del Hospital Clínico San Carlos, 28040, Madrid, Spain
- Facultad de Psicología, Centro Universitario Villanueva, 28034, Madrid, Spain
| | - Juan Manuel Serrano Rodriguez
- Biological and Health Psychology Department, School of Psychology, Universidad Autonoma de Madrid, 28049, Madrid, Spain
| | - Simon M Laws
- Collaborative Genomics Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, 6027, Australia
- School of Pharmacy and Biomedical Sciences, Faculty of Health Sciences, Curtin Health Innovation Research Institute, Curtin University, Bentley, Western Australia, 6102, Australia
| | - Alberto Marcos Dolado
- Neurology Department, Hospital Clinico San Carlos and Instituto de Investigación Sanitaria del Hospital Clínico San Carlos, 28040, Madrid, Spain
| | - Ramón López-Higes
- Experimental Psychology Department, School of Psychology, Universidad Complutense de Madrid, 28223, Pozuelo de Alarcon, Spain
| | - Belinda M Brown
- Discipline of Exercise Science, College of Science, Health, Engineering and Education, Murdoch University, Murdoch, Western Australia, 6150, Australia
| | - Fernando Maestú
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology, Parque Científico y Tecnológico de la UPM, Crta. M40, Km. 38, 28223, Pozuelo de Alarcón, Madrid, Spain
- Experimental Psychology Department, School of Psychology, Universidad Complutense de Madrid, 28223, Pozuelo de Alarcon, Spain
- Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), 28029, Madrid, Spain
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Musaeus CS, Nielsen MS, Høgh P. Altered Low-Frequency EEG Connectivity in Mild Cognitive Impairment as a Sign of Clinical Progression. J Alzheimers Dis 2020; 68:947-960. [PMID: 30883355 DOI: 10.3233/jad-181081] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Mild cognitive impairment (MCI) is associated with clinical progression to Alzheimer's disease (AD) but not all patients with MCI convert to AD. However, it is important to have methods that can differentiate between patients with MCI who progress (pMCI) and those who remain stable (sMCI), i.e., for timely administration of disease-modifying drugs. OBJECTIVE In the current study, we wanted to investigate whether quantitative EEG coherence and imaginary part of coherency (iCoh) could be used to differentiate between pMCI and sMCI. METHODS 17 patients with AD, 27 patients with MCI, and 38 older healthy controls were recruited and followed for three years and 2nd year was used to determine progression. EEGs were recorded at baseline and coherence and iCoh were calculated after thorough preprocessing. RESULTS Between pMCI and sMCI, the largest difference in total coherence was found in the theta and delta bands. Here, the significant differences for coherence and iCoh were found in the lower frequency bands involving the temporal-frontal connections for coherence and parietal-frontal connections for iCoh. Furthermore, we found a significant negative correlation between theta coherence and the Addenbrooke's Cognitive Examination (ACE) (p = 0.0378; rho = -0.2388). CONCLUSION These findings suggest that low frequency coherence and iCoh can be used to determine, which patients with MCI will progress to AD and is associated with the ACE score. Low-frequency coherence has previously been associated with increased hippocampal atrophy and degeneration of the cholinergic system and may be an early marker of AD pathology.
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Affiliation(s)
- Christian Sandøe Musaeus
- Department of Neurology, Danish Dementia Research Centre (DDRC), Rigshospitalet, University of Copenhagen, Denmark
| | - Malene Schjønning Nielsen
- Regional Dementia Research Centre, Department of Neurology, Zealand University Hospital, Roskilde, Denmark
| | - Peter Høgh
- Regional Dementia Research Centre, Department of Neurology, Zealand University Hospital, Roskilde, Denmark.,Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
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Benwell CSY, Davila-Pérez P, Fried PJ, Jones RN, Travison TG, Santarnecchi E, Pascual-Leone A, Shafi MM. EEG spectral power abnormalities and their relationship with cognitive dysfunction in patients with Alzheimer's disease and type 2 diabetes. Neurobiol Aging 2020; 85:83-95. [PMID: 31727363 PMCID: PMC6942171 DOI: 10.1016/j.neurobiolaging.2019.10.004] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2018] [Revised: 09/30/2019] [Accepted: 10/07/2019] [Indexed: 12/13/2022]
Abstract
Rhythmic neural activity has been proposed to play a fundamental role in cognition. Both healthy and pathological aging are characterized by frequency-specific changes in oscillatory activity. However, the cognitive relevance of these changes across the spectrum from normal to pathological aging remains unknown. We examined electroencephalography (EEG) correlates of cognitive function in healthy aging and 2 of the most prominent and debilitating age-related disorders: type 2 diabetes mellitus (T2DM) and Alzheimer's disease (AD). Relative to healthy controls (HC), patients with AD were impaired on nearly every cognitive measure, whereas patients with T2DM performed worse mainly on learning and memory tests. A continuum of alterations in resting-state EEG was associated with pathological aging, generally characterized by reduced alpha (α) and beta (β) power (AD < T2DM < HC) and increased delta (δ) and theta (θ) power (AD > T2DM > HC), with some variations across different brain regions. There were also reductions in the frequency and power density of the posterior dominant rhythm in AD. The ratio of (α + β)/(δ + θ) was specifically associated with cognitive function in a domain- and diagnosis-specific manner. The results thus captured both similarities and differences in the pathophysiology of cerebral oscillations in T2DM and AD. Overall, pathological brain aging is marked by a shift in oscillatory power from higher to lower frequencies, which can be captured by a single cognitively relevant measure of the ratio of (α + β) over (δ + θ) power.
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Affiliation(s)
- Christopher S Y Benwell
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Division of Psychology, School of Social Sciences, University of Dundee, Dundee, UK.
| | - Paula Davila-Pérez
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Neuroscience and Motor Control Group (NEUROcom), Institute for Biomedical Research (INIBIC), Universidade da Coruña, A Coruña, Spain
| | - Peter J Fried
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Richard N Jones
- Department of Psychiatry and Human Behavior, Warren Alpert Medical School, Brown University, Butler Hospital, Providence, RI, USA
| | - Thomas G Travison
- Hinda and Arthur Marcus Institute for Aging Research, Hebrew Senior Life, Boston, MA, USA
| | - Emiliano Santarnecchi
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Alvaro Pascual-Leone
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Hinda and Arthur Marcus Institute for Aging Research, Hebrew Senior Life, Boston, MA, USA; Institut Guttman, Universitat Autonoma de Barcelona, Badalona, Barcelona, Spain; Center for Memory Health, Hebrew Senior Life, Boston, MA, USA
| | - Mouhsin M Shafi
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Comprehensive Epilepsy Center, Department of Neurology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA.
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Abstract
Currently established and employed biomarkers of Alzheimer's disease (AD) predominantly mirror AD-associated molecular and structural brain changes. While they are necessary for identifying disease-specific neuropathology, they lack a clear and robust relationship with the clinical presentation of dementia; they can be altered in healthy individuals, while they often inadequately mirror the degree of cognitive and functional deficits in affected subjects. There is growing evidence that synaptic loss and dysfunction are early events during the trajectory of AD pathogenesis that best correlate with the clinical symptoms, suggesting measures of brain functional deficits as candidate early markers of AD. Resting-state electroencephalography (EEG) is a widely available and noninvasive diagnostic method that provides direct insight into brain synaptic activity in real time. Quantitative EEG (qEEG) analysis additionally provides information on physiologically meaningful frequency components, dynamic alterations and topography of EEG signal generators, i.e. neuronal signaling. Numerous studies have shown that qEEG measures can detect disruptions in activity, topographical distribution and synchronization of neuronal (synaptic) activity such as generalized EEG slowing, reduced global synchronization and anteriorization of neuronal generators of fast-frequency resting-state EEG activity in patients along the AD continuum. Moreover, qEEG measures appear to correlate well with surrogate markers of AD neuropathology and discriminate between different types of dementia, making them promising low-cost and noninvasive markers of AD. Future large-scale longitudinal clinical studies are needed to elucidate the diagnostic and prognostic potential of qEEG measures as early functional markers of AD on an individual subject level.
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Affiliation(s)
- Una Smailovic
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Huddinge, Sweden.
| | - Vesna Jelic
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Clinic for Cognitive Disorders, Theme Aging, Karolinska University Hospital, Huddinge, Sweden
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Song Z, Deng B, Wang J, Wang R. Biomarkers for Alzheimer's Disease Defined by a Novel Brain Functional Network Measure. IEEE Trans Biomed Eng 2019; 66:41-49. [DOI: 10.1109/tbme.2018.2834546] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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9
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Ishii R, Canuet L, Aoki Y, Hata M, Iwase M, Ikeda S, Nishida K, Ikeda M. Healthy and Pathological Brain Aging: From the Perspective of Oscillations, Functional Connectivity, and Signal Complexity. Neuropsychobiology 2018; 75:151-161. [PMID: 29466802 DOI: 10.1159/000486870] [Citation(s) in RCA: 95] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/06/2017] [Accepted: 01/14/2018] [Indexed: 12/24/2022]
Abstract
Healthy aging is associated with impairment in cognitive information processing. Several neuroimaging methods such as functional magnetic resonance imaging, positron emission tomography and near-infrared spectroscopy have been used to explore healthy and pathological aging by relying on hemodynamic or metabolic changes that occur in response to brain activity. Since electroencephalography (EEG) and magnetoencephalography (MEG) are able to measure neural activity directly with a high temporal resolution of milliseconds, these neurophysiological techniques are particularly important to investigate the dynamics of brain activity underlying neurocognitive aging. It is well known that age is a major risk factor for Alzheimer's disease (AD), and that synaptic dysfunction represents an early sign of this disease associated with hallmark neuropathological findings. However, the neurophysiological mechanisms underlying AD are not fully elucidated. This review addresses healthy and pathological brain aging from a neurophysiological perspective, focusing on oscillatory activity changes during the resting state, event-related potentials and stimulus-induced oscillatory responses during cognitive or motor tasks, functional connectivity between brain regions, and changes in signal complexity. We also highlight the accumulating evidence on age-related EEG/MEG changes and biological markers of brain neurodegeneration, including genetic factors, structural abnormalities on magnetic resonance images, and the biochemical changes associated with Aβ deposition and tau pathology.
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Affiliation(s)
- Ryouhei Ishii
- Department of Psychiatry, Osaka University Graduate School of Medicine, Suita, Japan.,Department of Palliative Care, Ashiya Municipal Hospital, Ashiya, Japan
| | - Leonides Canuet
- Department of Cognitive, Social and Organizational Psychology, La Laguna University, Tenerife, Spain
| | - Yasunori Aoki
- Department of Psychiatry, Osaka University Graduate School of Medicine, Suita, Japan.,Department of Psychiatry, Nissay Hospital, Osaka, Japan
| | - Masahiro Hata
- Department of Psychiatry, Osaka University Graduate School of Medicine, Suita, Japan
| | - Masao Iwase
- Department of Psychiatry, Osaka University Graduate School of Medicine, Suita, Japan
| | - Shunichiro Ikeda
- Department of Psychiatry, Kansai Medical University, Moriguchi, Japan
| | - Keiichiro Nishida
- Department of Psychiatry, Kansai Medical University, Moriguchi, Japan
| | - Manabu Ikeda
- Department of Psychiatry, Osaka University Graduate School of Medicine, Suita, Japan
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10
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Gouw AA, Alsema AM, Tijms BM, Borta A, Scheltens P, Stam CJ, van der Flier WM. EEG spectral analysis as a putative early prognostic biomarker in nondemented, amyloid positive subjects. Neurobiol Aging 2017. [PMID: 28646686 DOI: 10.1016/j.neurobiolaging.2017.05.017] [Citation(s) in RCA: 72] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
We studied whether electroencephalography (EEG)-derived measures of brain oscillatory activity are related to clinical progression in nondemented, amyloid positive subjects. We included 205 nondemented amyloid positive subjects (63 subjective cognitive decline [SCD]; 142 mild cognitive impairment [MCI]) with a baseline resting-state EEG data and ≥1-year follow-up. Peak frequency and relative power of 4 frequency bands were calculated. Relationships between normalized EEG measures and time to clinical progression (conversion from SCD to MCI/dementia or from MCI to dementia) were analyzed using Cox proportional hazard models. One hundred eight (53%) subjects clinically progressed after 2.1 (IQR 1.3-3.0) years. In the total sample, none of the EEG spectral measures were significant predictors. Stratified for baseline diagnosis, we found that in SCD patients higher delta and theta power (HR [95% CI] = 1.7 [1.0-2.7] resp. 2.3 [1.2-4.4]), and lower alpha power and peak frequency (HR [95% CI] = 0.5 [0.3-1.0] resp. 0.6 [0.4-1.0]) were associated with clinical progression over time. In amyloid positive subjects with normal cognition, slowing of oscillatory brain activity is related to clinical progression.
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Affiliation(s)
- Alida A Gouw
- Alzheimer Center and Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, the Netherlands; Department of Clinical Neurophysiology and MEG Center, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, the Netherlands.
| | - Astrid M Alsema
- Alzheimer Center and Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, the Netherlands; Department of Clinical Neurophysiology and MEG Center, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, the Netherlands
| | - Betty M Tijms
- Alzheimer Center and Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, the Netherlands
| | - Andreas Borta
- Boehringer Ingelheim Pharma GmbH Co KG, Ingelheim am Rhein, Germany
| | - Philip Scheltens
- Alzheimer Center and Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, the Netherlands
| | - Cornelis J Stam
- Department of Clinical Neurophysiology and MEG Center, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, the Netherlands
| | - Wiesje M van der Flier
- Alzheimer Center and Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, the Netherlands; Department of Epidemiology and Biostatistics, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, the Netherlands
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11
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Triggiani AI, Bevilacqua V, Brunetti A, Lizio R, Tattoli G, Cassano F, Soricelli A, Ferri R, Nobili F, Gesualdo L, Barulli MR, Tortelli R, Cardinali V, Giannini A, Spagnolo P, Armenise S, Stocchi F, Buenza G, Scianatico G, Logroscino G, Lacidogna G, Orzi F, Buttinelli C, Giubilei F, Del Percio C, Frisoni GB, Babiloni C. Classification of Healthy Subjects and Alzheimer's Disease Patients with Dementia from Cortical Sources of Resting State EEG Rhythms: A Study Using Artificial Neural Networks. Front Neurosci 2017; 10:604. [PMID: 28184183 PMCID: PMC5266711 DOI: 10.3389/fnins.2016.00604] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2016] [Accepted: 12/19/2016] [Indexed: 11/13/2022] Open
Abstract
Previous evidence showed a 75.5% best accuracy in the classification of 120 Alzheimer's disease (AD) patients with dementia and 100 matched normal elderly (Nold) subjects based on cortical source current density and linear lagged connectivity estimated by eLORETA freeware from resting state eyes-closed electroencephalographic (rsEEG) rhythms (Babiloni et al., 2016a). Specifically, that accuracy was reached using the ratio between occipital delta and alpha1 current density for a linear univariate classifier (receiver operating characteristic curves). Here we tested an innovative approach based on an artificial neural network (ANN) classifier from the same database of rsEEG markers. Frequency bands of interest were delta (2–4 Hz), theta (4–8 Hz Hz), alpha1 (8–10.5 Hz), and alpha2 (10.5–13 Hz). ANN classification showed an accuracy of 77% using the most 4 discriminative rsEEG markers of source current density (parietal theta/alpha 1, temporal theta/alpha 1, occipital theta/alpha 1, and occipital delta/alpha 1). It also showed an accuracy of 72% using the most 4 discriminative rsEEG markers of source lagged linear connectivity (inter-hemispherical occipital delta/alpha 2, intra-hemispherical right parietal-limbic alpha 1, intra-hemispherical left occipital-temporal theta/alpha 1, intra-hemispherical right occipital-temporal theta/alpha 1). With these 8 markers combined, an accuracy of at least 76% was reached. Interestingly, this accuracy based on 8 (linear) rsEEG markers as inputs to ANN was similar to that obtained with a single rsEEG marker (Babiloni et al., 2016a), thus unveiling their information redundancy for classification purposes. In future AD studies, inputs to ANNs should include other classes of independent linear (i.e., directed transfer function) and non-linear (i.e., entropy) rsEEG markers to improve the classification.
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Affiliation(s)
- Antonio I Triggiani
- Department of Clinical and Experimental Medicine, University of Foggia Foggia, Italy
| | | | - Antonio Brunetti
- Department of Electrical and Information Engineering, Polytechnic of Bari Bari, Italy
| | - Roberta Lizio
- Department of Physiology and Pharmacology "Vittorio Erspamer", University of Rome "La Sapienza"Rome, Italy; Department of Neuroscience, IRCCS San Raffaele PisanaRome, Italy
| | - Giacomo Tattoli
- Department of Electrical and Information Engineering, Polytechnic of Bari Bari, Italy
| | - Fabio Cassano
- Department of Electrical and Information Engineering, Polytechnic of Bari Bari, Italy
| | - Andrea Soricelli
- Department of Integrated Imaging, IRCCS Istituto di Ricerca Diagnostica e NucleareNapoli, Italy; Department of Motor Sciences and Healthiness, University of Naples ParthenopeNaples, Italy
| | - Raffaele Ferri
- Department of Neurology, IRCCS Oasi Institute for Research on Mental Retardation and Brain Aging Enna, Italy
| | - Flavio Nobili
- Clinical Neurology Unit, Department of Neuroscience, University of Genoa and IRCCS Azienda Ospedaliera Universitaria San Martino-IST Genoa, Italy
| | - Loreto Gesualdo
- Dipartimento Emergenza e Trapianti d'Organi, University of Bari Bari, Italy
| | - Maria R Barulli
- Unit of Neurodegenerative Diseases, Department of Clinical Research in Neurology, University of Bari "Aldo Moro", Pia Fondazione Cardinale G. Panico Lecce, Italy
| | - Rosanna Tortelli
- Department of Clinical Research in Neurology, University of Bari "Aldo Moro", Pia Fondazione Cardinale G. Panico Lecce, Italy
| | - Valentina Cardinali
- Department of Clinical Research in Neurology, University of Bari "Aldo Moro", Pia Fondazione Cardinale G. PanicoLecce, Italy; Department of Basic Medical Sciences, Neurosciences and Sense Organs, University of Bari "Aldo Moro"Bari, Italy
| | - Antonio Giannini
- Department of Imaging-Division of Radiology, Hospital "Di Venere" Bari, Italy
| | | | - Silvia Armenise
- Division of Neuroradiology, "F. Ferrari" Hospital Lecce, Italy
| | - Fabrizio Stocchi
- Department of Neuroscience, IRCCS San Raffaele Pisana Rome, Italy
| | - Grazia Buenza
- Department of Clinical Research in Neurology, University of Bari "Aldo Moro", Pia Fondazione Cardinale G. Panico Lecce, Italy
| | - Gaetano Scianatico
- Unit of Neurodegenerative Diseases, Department of Clinical Research in Neurology, University of Bari "Aldo Moro", Pia Fondazione Cardinale G. Panico Lecce, Italy
| | - Giancarlo Logroscino
- Unit of Neurodegenerative Diseases, Department of Clinical Research in Neurology, University of Bari "Aldo Moro", Pia Fondazione Cardinale G. PanicoLecce, Italy; Department of Basic Medical Sciences, Neurosciences and Sense Organs, University of Bari "Aldo Moro"Bari, Italy
| | - Giordano Lacidogna
- Center for Neuropsychological Research, Institute of Neurology of the Policlinico Gemelli/Catholic University of Rome Italy
| | - 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
| | - Claudio Del Percio
- Department of Integrated Imaging, IRCCS Istituto di Ricerca Diagnostica e Nucleare Napoli, Italy
| | - Giovanni B Frisoni
- Laboratory of Epidemiology, Neuroimaging and Telemedicine, IRCCS Centro "S. Giovanni di Dio-F.B.F."Brescia, Italy; Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging, University Hospitals and University of GenevaGeneva, Switzerland
| | - Claudio Babiloni
- Department of Physiology and Pharmacology "Vittorio Erspamer", University of Rome "La Sapienza"Rome, Italy; Department of Neuroscience, IRCCS San Raffaele PisanaRome, Italy
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12
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Babiloni C, Del Percio C, Caroli A, Salvatore E, Nicolai E, Marzano N, Lizio R, Cavedo E, Landau S, Chen K, Jagust W, Reiman E, Tedeschi G, Montella P, De Stefano M, Gesualdo L, Frisoni GB, Soricelli A. Cortical sources of resting state EEG rhythms are related to brain hypometabolism in subjects with Alzheimer's disease: an EEG-PET study. Neurobiol Aging 2016; 48:122-134. [DOI: 10.1016/j.neurobiolaging.2016.08.021] [Citation(s) in RCA: 43] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2014] [Revised: 08/05/2016] [Accepted: 08/24/2016] [Indexed: 11/24/2022]
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13
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Kavcic V, Zalar B, Giordani B. The relationship between baseline EEG spectra power and memory performance in older African Americans endorsing cognitive concerns in a community setting. Int J Psychophysiol 2016; 109:116-123. [PMID: 27613569 DOI: 10.1016/j.ijpsycho.2016.09.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2016] [Revised: 09/01/2016] [Accepted: 09/03/2016] [Indexed: 01/22/2023]
Abstract
The finding that some older individuals report declines in aspects of cognitive functioning is becoming a frequently used criteria to identify elderly at risk for mild cognitive impairment (MCI) and dementia. Once concerns are identified in a community setting, however, effective means are necessary to pinpoint those individuals who should go on to more complex and costly diagnostic evaluations (e.g., functional imaging). We tested 44 African American volunteers endorsing cognitive concerns (37 females, 7 males) age≥65years with CogState battery subtests and recorded resting-state EEG, with eyes closed. After current source density (CSD) transformations of EEG recordings we obtained spectral power for delta, theta, alpha, and beta frequency bands. We characterized CogState One Card Back Learning (OCL, memory) with diffusion model parameters drift rate, boundary and non-decision time (NDT). Forward regression models showed that lower OCL drift rate, slower accumulation of information needed for decision making was linked to increased absolute and relative delta at occipital region. Lower drift rate was also linked to decrease in OCL theta power at parietal region, with no findings for ONB. Results show that cortical resting, eyes closed EEG rhythms are related to memory in African American seniors endorsing cognitive concerns. This study further supports the use of EEG as an easily accessible, cost-effective, culture-fair, and noninvasive clinical measurement that could provide potentially reliable diagnostic (and perhaps prognostic) information to differentiate at-risk from stable African American seniors.
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Affiliation(s)
- Voyko Kavcic
- Institute of Gerontology, Wayne State University, Detroit, MI, USA; Biomedical Research Institute, Ljubljana, Slovenia.
| | - Bojan Zalar
- Biomedical Research Institute, Ljubljana, Slovenia; University Psychiatric Clinic, Ljubljana, Slovenia
| | - Bruno Giordani
- Departments of Psychiatry, Neurology, and Psychology and School of Nursing, University of Michigan, Ann Arbor, MI, USA
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14
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Atrophy of amygdala and abnormal memory-related alpha oscillations over posterior cingulate predict conversion to Alzheimer's disease. Sci Rep 2016; 6:31859. [PMID: 27546195 PMCID: PMC4992828 DOI: 10.1038/srep31859] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2016] [Accepted: 07/28/2016] [Indexed: 12/30/2022] Open
Abstract
Synaptic dysfunction, a key pathophysiological hallmark of Alzheimer’s disease (AD), may account for abnormal memory-related EEG patterns in prodromal AD. Here, we investigate to what extent oscillatory EEG changes during memory encoding and/or retrieval enhance the accuracy of medial temporal lobe (MTL) atrophy in predicting conversion from amnestic mild cognitive impairment (aMCI) to AD. As expected, aMCI individuals that, within a 2-year follow-up period, developed dementia (N = 16) compared to healthy older (HO) (N = 26) and stable aMCI (N = 18) showed poorer associative memory, greater MTL atrophy, and lower capacity to recruit alpha oscillatory cortical networks. Interestingly, encoding-induced abnormal alpha desynchronized activity over the posterior cingulate cortex (PCC) at baseline showed significantly higher accuracy in predicting AD than the magnitude of amygdala atrophy. Nevertheless, the best accuracy was obtained when the two markers were fitted into the model (sensitivity = 78%, specificity = 82%). These results support the idea that synaptic integrity/function in the PCC is affected during prodromal AD and has the potential of improving early detection when combined with MRI biomarkers.
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15
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Martínez-Sánchez F, Meilán JJG, Vera-Ferrandiz JA, Carro J, Pujante-Valverde IM, Ivanova O, Carcavilla N. Speech rhythm alterations in Spanish-speaking individuals with Alzheimer's disease. AGING NEUROPSYCHOLOGY AND COGNITION 2016; 24:418-434. [PMID: 27684109 DOI: 10.1080/13825585.2016.1220487] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
Rhythm is the speech property related to the temporal organization of sounds. Considerable evidence is now available for suggesting that dementia of Alzheimer's type is associated with impairments in speech rhythm. The aim of this study is to assess the use of an automatic computerized system for measuring speech rhythm characteristics in an oral reading task performed by 45 patients with Alzheimer's disease (AD) compared with those same characteristics among 82 healthy older adults without a diagnosis of dementia, and matched by age, sex and cultural background. Ranges of rhythmic-metric and clinical measurements were applied. The results show rhythmic differences between the groups, with higher variability of syllabic intervals in AD patients. Signal processing algorithms applied to oral reading recordings prove to be capable of differentiating between AD patients and older adults without dementia with an accuracy of 87% (specificity 81.7%, sensitivity 82.2%), based on the standard deviation of the duration of syllabic intervals. Experimental results show that the syllabic variability measurements extracted from the speech signal can be used to distinguish between older adults without a diagnosis of dementia and those with AD, and may be useful as a tool for the objective study and quantification of speech deficits in AD.
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Affiliation(s)
| | - Juan J G Meilán
- b Department of Psychology , University of Salamanca , Salamanca , Spain.,c Institute of Neurosciences of Castile and Leon (INCYL) , Salamanca , Spain
| | | | - Juan Carro
- b Department of Psychology , University of Salamanca , Salamanca , Spain.,c Institute of Neurosciences of Castile and Leon (INCYL) , Salamanca , Spain
| | | | - Olga Ivanova
- b Department of Psychology , University of Salamanca , Salamanca , Spain.,c Institute of Neurosciences of Castile and Leon (INCYL) , Salamanca , Spain
| | - Nuria Carcavilla
- b Department of Psychology , University of Salamanca , Salamanca , Spain.,c Institute of Neurosciences of Castile and Leon (INCYL) , Salamanca , Spain
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16
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Babiloni C, Lizio R, Marzano N, Capotosto P, Soricelli A, Triggiani AI, Cordone S, Gesualdo L, Del Percio C. Brain neural synchronization and functional coupling in Alzheimer's disease as revealed by resting state EEG rhythms. Int J Psychophysiol 2016; 103:88-102. [PMID: 25660305 DOI: 10.1016/j.ijpsycho.2015.02.008] [Citation(s) in RCA: 201] [Impact Index Per Article: 25.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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17
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Babiloni C, Triggiani AI, Lizio R, Cordone S, Tattoli G, Bevilacqua V, Soricelli A, Ferri R, Nobili F, Gesualdo L, Millán-Calenti JC, Buján A, Tortelli R, Cardinali V, Barulli MR, Giannini A, Spagnolo P, Armenise S, Buenza G, Scianatico G, Logroscino G, Frisoni GB, del Percio C. Classification of Single Normal and Alzheimer's Disease Individuals from Cortical Sources of Resting State EEG Rhythms. Front Neurosci 2016; 10:47. [PMID: 26941594 PMCID: PMC4763025 DOI: 10.3389/fnins.2016.00047] [Citation(s) in RCA: 61] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2015] [Accepted: 02/02/2016] [Indexed: 12/03/2022] Open
Abstract
Previous studies have shown abnormal power and functional connectivity of resting state electroencephalographic (EEG) rhythms in groups of Alzheimer's disease (AD) compared to healthy elderly (Nold) subjects. Here we tested the best classification rate of 120 AD patients and 100 matched Nold subjects using EEG markers based on cortical sources of power and functional connectivity of these rhythms. EEG data were recorded during resting state eyes-closed condition. Exact low-resolution brain electromagnetic tomography (eLORETA) estimated the power and functional connectivity of cortical sources in frontal, central, parietal, occipital, temporal, and limbic regions. Delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), beta 2 (20-30 Hz), and gamma (30-40 Hz) were the frequency bands of interest. The classification rates of interest were those with an area under the receiver operating characteristic curve (AUROC) higher than 0.7 as a threshold for a moderate classification rate (i.e., 70%). Results showed that the following EEG markers overcame this threshold: (i) central, parietal, occipital, temporal, and limbic delta/alpha 1 current density; (ii) central, parietal, occipital temporal, and limbic delta/alpha 2 current density; (iii) frontal theta/alpha 1 current density; (iv) occipital delta/alpha 1 inter-hemispherical connectivity; (v) occipital-temporal theta/alpha 1 right and left intra-hemispherical connectivity; and (vi) parietal-limbic alpha 1 right intra-hemispherical connectivity. Occipital delta/alpha 1 current density showed the best classification rate (sensitivity of 73.3%, specificity of 78%, accuracy of 75.5%, and AUROC of 82%). These results suggest that EEG source markers can classify Nold and AD individuals with a moderate classification rate higher than 80%.
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Affiliation(s)
- Claudio Babiloni
- Department of Physiology and Pharmacology “Vittorio Erspamer”, University of Rome “La Sapienza”Rome, Italy
- Department of Neuroscience, IRCCS San Raffaele PisanaRome, Italy
| | - Antonio I. Triggiani
- Department of Clinical and Experimental Medicine, University of FoggiaFoggia, Italy
| | - Roberta Lizio
- Department of Physiology and Pharmacology “Vittorio Erspamer”, University of Rome “La Sapienza”Rome, Italy
- Department of Neuroscience, IRCCS San Raffaele PisanaRome, Italy
| | - Susanna Cordone
- Department of Physiology and Pharmacology “Vittorio Erspamer”, University of Rome “La Sapienza”Rome, Italy
| | - Giacomo Tattoli
- Department of Electrical and Information Engineering, Polytechnic of BariBari, Italy
| | | | - Andrea Soricelli
- Department of Integrated Imaging, IRCCS SDN - Istituto di Ricerca Diagnostica e NucleareNapoli, Italy
- Department of Motor Sciences and Healthiness, University of Naples ParthenopeNaples, Italy
| | - Raffaele Ferri
- Department of Neurology, IRCCS Oasi Institute for Research on Mental Retardation and Brain AgingTroina, Italy
| | - Flavio Nobili
- Service of Clinical Neurophysiology (DiNOGMI; DipTeC), IRCCS Azienda Ospedaliera Universitaria San Martino - ISTGenoa, Italy
| | - Loreto Gesualdo
- Dipartimento Emergenza e Trapianti d'Organi, University of BariBari, Italy
| | - José C. Millán-Calenti
- Gerontology Research Group, Department of Medicine, Faculty of Health Sciences, University of A CoruñaA Coruña, Spain
| | - Ana Buján
- Gerontology Research Group, Department of Medicine, Faculty of Health Sciences, University of A CoruñaA Coruña, Spain
| | - Rosanna Tortelli
- Department of Clinical Research in Neurology, University of Bari “Aldo Moro”, Pia Fondazione Cardinale G. PanicoLecce, Italy
| | - Valentina Cardinali
- Department of Clinical Research in Neurology, University of Bari “Aldo Moro”, Pia Fondazione Cardinale G. PanicoLecce, Italy
- Department of Basic Medical Sciences, Neurosciences and Sense Organs, University of Bari “Aldo Moro”Bari, Italy
| | - Maria Rosaria Barulli
- Unit of Neurodegenerative Diseases, Department of Clinical Research in Neurology, University of Bari “Aldo Moro”, Pia Fondazione Cardinale G. PanicoLecce, Italy
| | - Antonio Giannini
- Department of Imaging - Division of Radiology, Hospital “Di Venere”Bari, Italy
| | | | - Silvia Armenise
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari “Aldo Moro”Bari, Italy
| | - Grazia Buenza
- Department of Clinical Research in Neurology, University of Bari “Aldo Moro”, Pia Fondazione Cardinale G. PanicoLecce, Italy
| | - Gaetano Scianatico
- Unit of Neurodegenerative Diseases, Department of Clinical Research in Neurology, University of Bari “Aldo Moro”, Pia Fondazione Cardinale G. PanicoLecce, Italy
| | - Giancarlo Logroscino
- Unit of Neurodegenerative Diseases, Department of Clinical Research in Neurology, University of Bari “Aldo Moro”, Pia Fondazione Cardinale G. PanicoLecce, Italy
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari “Aldo Moro”Bari, Italy
| | - Giovanni B. Frisoni
- Laboratory of Epidemiology, Neuroimaging and Telemedicine, IRCCS Centro “S. Giovanni di Dio-F.B.F.”Brescia, Italy
- Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of GenevaGeneva, Switzerland
| | - Claudio del Percio
- Department of Integrated Imaging, IRCCS SDN - Istituto di Ricerca Diagnostica e NucleareNapoli, Italy
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18
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Lizio R, Del Percio C, Marzano N, Soricelli A, Yener GG, Başar E, Mundi C, De Rosa S, Triggiani AI, Ferri R, Arnaldi D, Nobili FM, Cordone S, Lopez S, Carducci F, Santi G, Gesualdo L, Rossini PM, Cavedo E, Mauri M, Frisoni G, Babiloni C. Neurophysiological Assessment of Alzheimer’s Disease Individuals by a Single Electroencephalographic Marker. J Alzheimers Dis 2015; 49:159-77. [DOI: 10.3233/jad-143042] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Affiliation(s)
- Roberta Lizio
- IRCCS San Raffaele Pisana, Rome, Italy
- Department of Physiology and Pharmacology, University of Rome “La Sapienza”, Rome, Italy
| | | | | | - Andrea Soricelli
- IRCCS SDN, Naples, Italy
- Department of Studies of Institutions and Territorial Systems, University of Naples Parthenope, Naples, Italy
| | - Görsev G. Yener
- Brain Dynamics, Cognition and Complex Systems Research Center, Istanbul Kültür University, Istanbul, Turkey
- Department of Neurosciences, Brain Dynamics Multidisciplinary Research Center, Department of Neurology, Dokuz Eylül University, Izmir, Turkey
| | - Erol Başar
- Brain Dynamics, Cognition and Complex Systems Research Center, Istanbul Kültür University, Istanbul, Turkey
| | - Ciro Mundi
- Department of Neurology, Ospedali Riuniti, Foggia, Italy
| | | | | | | | - Dario Arnaldi
- Service of Clinical Neurophysiology (DiNOGMI; DipTeC), IRCCS AOU S Martino-IST, Genoa, Italy
| | - Flavio Mariano Nobili
- Service of Clinical Neurophysiology (DiNOGMI; DipTeC), IRCCS AOU S Martino-IST, Genoa, Italy
| | - Susanna Cordone
- Department of Physiology and Pharmacology, University of Rome “La Sapienza”, Rome, Italy
| | - Susanna Lopez
- Department of Physiology and Pharmacology, University of Rome “La Sapienza”, Rome, Italy
| | - Filippo Carducci
- Department of Physiology and Pharmacology, University of Rome “La Sapienza”, Rome, Italy
| | - Giulia Santi
- Department of Physiology and Pharmacology, University of Rome “La Sapienza”, Rome, Italy
| | - Loreto Gesualdo
- Dipartimento Emergenza e Trapianti d’Organi (D.E.T.O), University of Bari, Bari, Italy
| | - Paolo M. Rossini
- IRCCS San Raffaele Pisana, Rome, Italy
- Department of Geriatrics, Neuroscience & Orthopedics, Institute of Neurology, Catholic University, Rome, Italy
| | - Enrica Cavedo
- LENITEM (Laboratory of Epidemiology, Neuroimaging and Telemedicine), IRCCS Centro “S. Giovanni di Dio-F.B.F.”, Brescia, Italy
| | - Margherita Mauri
- LENITEM (Laboratory of Epidemiology, Neuroimaging and Telemedicine), IRCCS Centro “S. Giovanni di Dio-F.B.F.”, Brescia, Italy
- Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Giovanni B. Frisoni
- LENITEM (Laboratory of Epidemiology, Neuroimaging and Telemedicine), IRCCS Centro “S. Giovanni di Dio-F.B.F.”, Brescia, Italy
- Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Claudio Babiloni
- IRCCS San Raffaele Pisana, Rome, Italy
- Department of Physiology and Pharmacology, University of Rome “La Sapienza”, Rome, Italy
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19
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Babiloni C, Del Percio C, Capotosto P, Noce G, Infarinato F, Muratori C, Marcotulli C, Bellagamba G, Righi E, Soricelli A, Onorati P, Lupattelli T. Cortical sources of resting state electroencephalographic rhythms differ in relapsing-remitting and secondary progressive multiple sclerosis. Clin Neurophysiol 2015; 127:581-590. [PMID: 26111485 DOI: 10.1016/j.clinph.2015.05.029] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2014] [Revised: 05/05/2015] [Accepted: 05/26/2015] [Indexed: 11/29/2022]
Abstract
OBJECTIVE Resting state electroencephalographic (EEG) rhythms are abnormal in multiple sclerosis (MS) patients, but it is unclear if they can reflect different neurophysiologic abnormalities in MS sub-types (phenotypes) such as relapsing-remitting (RR) and secondary progressive (SP). METHODS We tested whether cortical sources of resting state EEG rhythms are abnormal in MS patients and differ between MS phenotypes. Resting state eyes-closed EEG activity was recorded in 36 RR, 23 SP, and 41 matched healthy subjects. EEG bands of interest were individually identified based on Transition frequency (TF), Individual alpha frequency (IAF), and Individual beta frequency (IBF). LORETA freeware estimated cortical EEG sources. RESULTS Widespread TF -4Hz (delta) and IAF (alpha) cortical sources were abnormal in the MS sub-groups compared to the control group. Furthermore, TF -4Hz sources in central, parietal, and limbic regions were higher in amplitude in the SP compared to the RR sub-group. CONCLUSION Cortical sources of resting state EEG rhythms are abnormal in MS patients at group level and differ between RR and SP sub-groups. SIGNIFICANCE Future studies should test the utility of these EEG markers in the diagnosis and management of MS clinical phenotypes and in the therapy evaluation.
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Affiliation(s)
- Claudio Babiloni
- Department of Physiology and Pharmacology, University of Rome "La Sapienza", Rome, Italy; IRCCS San Raffaele Pisana, Rome, Italy.
| | | | - Paolo Capotosto
- Department of Neuroscience and Imaging and Clinical Science, and ITAB, University "G. D'Annunzio", Chieti, Italy
| | | | | | - Chiara Muratori
- Istituto Clinico Cardiologico (ICC), Casalpalocco, Rome, Italy
| | - Christian Marcotulli
- Department of Sciences and Medical-Surgical Biotechnology, University of Rome "La Sapienza", Rome, Italy
| | | | - Elena Righi
- Istituto Clinico Cardiologico (ICC), Casalpalocco, Rome, Italy
| | - Andrea Soricelli
- IRCCS S.D.N., Naples, Italy; Department of Studies of Institutions and Territorial Systems, University of Naples "Parthenope", Naples, Italy
| | - Paolo Onorati
- Department of Physiology and Pharmacology, University of Rome "La Sapienza", Rome, Italy; Istituto Clinico Cardiologico (ICC), Casalpalocco, Rome, Italy
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Neuroplastic effects of combined computerized physical and cognitive training in elderly individuals at risk for dementia: an eLORETA controlled study on resting states. Neural Plast 2015; 2015:172192. [PMID: 25945260 PMCID: PMC4405298 DOI: 10.1155/2015/172192] [Citation(s) in RCA: 58] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2014] [Revised: 03/09/2015] [Accepted: 03/16/2015] [Indexed: 12/20/2022] Open
Abstract
The present study investigates whether a combined cognitive and physical training may induce changes in the cortical activity as measured via electroencephalogram (EEG) and whether this change may index a deceleration of pathological processes of brain aging. Seventy seniors meeting the clinical criteria of mild cognitive impairment (MCI) were equally divided into 5 groups: 3 experimental groups engaged in eight-week cognitive and/or physical training and 2 control groups: active and passive. A 5-minute long resting state EEG was measured before and after the intervention. Cortical EEG sources were modelled by exact low resolution brain electromagnetic tomography (eLORETA). Cognitive function was assessed before and after intervention using a battery of neuropsychological tests including the minimental state examination (MMSE). A significant training effect was identified only after the combined training scheme: a decrease in the post- compared to pre-training activity of precuneus/posterior cingulate cortex in delta, theta, and beta bands. This effect was correlated to improvements in cognitive capacity as evaluated by MMSE scores. Our results indicate that combined physical and cognitive training shows indices of a positive neuroplastic effect in MCI patients and that EEG may serve as a potential index of gains versus cognitive declines and neurodegeneration. This trial is registered with ClinicalTrials.gov Identifier NCT02313935.
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Antiretroviral therapy effects on sources of cortical rhythms in HIV subjects: Responders vs. Mild Responders. Clin Neurophysiol 2015; 126:68-81. [DOI: 10.1016/j.clinph.2014.03.036] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2013] [Revised: 03/10/2014] [Accepted: 03/31/2014] [Indexed: 11/17/2022]
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Cerebral and blood correlates of reduced functional connectivity in mild cognitive impairment. Brain Struct Funct 2014; 221:631-45. [PMID: 25366971 DOI: 10.1007/s00429-014-0930-6] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2014] [Accepted: 10/23/2014] [Indexed: 12/15/2022]
Abstract
Growing evidence suggests that decreased functional connectivity in cortical networks precedes clinical stages of Alzheimer's disease (AD), although our knowledge about cerebral and biological correlates of this phenomenon is limited. To shed light on this issue, we have investigated whether resting-state oscillatory connectivity patterns in healthy older (HO) and amnestic mild cognitive impairment (aMCI) subjects are related to anatomical grey matter (GM) and functional (2-[18F]fluoro-2-deoxy-D-glucose (FDG)-PET) changes of neuroelectric sources of alpha rhythms, and/or to changes in plasma amyloid-beta (Aβ) and serum lipid levels, blood markers tied to AD pathogenesis and aging-related cognitive decline. We found that aMCI subjects showed decreased levels of cortical connectivity, reduced FDG-PET intake of the precuneus, and GM atrophy of the thalamus, together with higher levels of Aβ and apolipoprotein B (ApoB) compared to HO. Interestingly, levels of high-density lipoprotein (HDL) cholesterol were positively correlated with the strength of neural-phase coupling in aMCI subjects, and increased triglycerides accompanied bilateral GM loss in the precuneus of aMCI subjects. Together, these findings provide peripheral blood correlates of reduced resting-state cortical connectivity in aMCI, supported by anatomo-functional changes in cerebral sources of alpha rhythms. This framework constitutes an integrated approach to assess functional changes in cortical networks through neuroimaging and peripheral blood markers during early stages of neurodegeneration.
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Garcés P, Angel Pineda-Pardo J, Canuet L, Aurtenetxe S, López ME, Marcos A, Yus M, Llanero-Luque M, Del-Pozo F, Sancho M, Maestú F. The Default Mode Network is functionally and structurally disrupted in amnestic mild cognitive impairment - a bimodal MEG-DTI study. NEUROIMAGE-CLINICAL 2014; 6:214-21. [PMID: 25379433 PMCID: PMC4215458 DOI: 10.1016/j.nicl.2014.09.004] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/06/2014] [Revised: 08/27/2014] [Accepted: 09/05/2014] [Indexed: 01/19/2023]
Abstract
Over the past years, several studies on Mild Cognitive Impairment (MCI) and Alzheimer's disease (AD) have reported Default Mode Network (DMN) deficits. This network is attracting increasing interest in the AD community, as it seems to play an important role in cognitive functioning and in beta amyloid deposition. Attention has been particularly drawn to how different DMN regions are connected using functional or structural connectivity. To this end, most studies have used functional Magnetic Resonance Imaging (fMRI), Positron Emission Tomography (PET) or Diffusion Tensor Imaging (DTI). In this study we evaluated (1) functional connectivity from resting state magnetoencephalography (MEG) and (2) structural connectivity from DTI in 26 MCI patients and 31 age-matched controls. Compared to controls, the DMN in the MCI group was functionally disrupted in the alpha band, while no differences were found for delta, theta, beta and gamma frequency bands. In addition, structural disconnection could be assessed through a decreased fractional anisotropy along tracts connecting different DMN regions. This suggests that the DMN functional and anatomical disconnection could represent a core feature of MCI. We studied functional and structural connectivity in MCI patients and controls. We focused on the connections between regions in the Default Mode Network. Resting state alpha-band functional connectivity was decreased in MCI. The integrity of the structural connections was lower for the MCI group. Functional and structural connectivity correlated in the alpha band in both groups.
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Affiliation(s)
- Pilar Garcés
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Centre for Biomedical Technology, Pozuelo de Alarcón, Madrid 28223, Spain ; Department of Applied Physics III, Faculty of Physics, Complutense University of Madrid, Madrid 28040, Spain
| | - José Angel Pineda-Pardo
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Centre for Biomedical Technology, Pozuelo de Alarcón, Madrid 28223, Spain
| | - Leonides Canuet
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Centre for Biomedical Technology, Pozuelo de Alarcón, Madrid 28223, Spain
| | - Sara Aurtenetxe
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Centre for Biomedical Technology, Pozuelo de Alarcón, Madrid 28223, Spain ; Department of Basic Psychology II, Faculty of Psychology, Complutense University of Madrid, Madrid 28223, Spain
| | - Maria Eugenia López
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Centre for Biomedical Technology, Pozuelo de Alarcón, Madrid 28223, Spain ; Department of Basic Psychology II, Faculty of Psychology, Complutense University of Madrid, Madrid 28223, Spain
| | - Alberto Marcos
- Neurology Department, Hospital Clínico San Carlos, Madrid 28040, Spain
| | - Miguel Yus
- Radiology Department, Hospital Clínico San Carlos, Madrid 28040, Spain
| | | | - Francisco Del-Pozo
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Centre for Biomedical Technology, Pozuelo de Alarcón, Madrid 28223, Spain
| | - Miguel Sancho
- Department of Applied Physics III, Faculty of Physics, Complutense University of Madrid, Madrid 28040, Spain
| | - Fernando Maestú
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Centre for Biomedical Technology, Pozuelo de Alarcón, Madrid 28223, Spain ; Department of Basic Psychology II, Faculty of Psychology, Complutense University of Madrid, Madrid 28223, Spain
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24
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Babiloni C, Buffo P, Vecchio F, Onorati P, Muratori C, Ferracuti S, Roma P, Battuello M, Donato N, Noce G, Di Campli F, Gianserra L, Teti E, Aceti A, Soricelli A, Viscione M, Andreoni M, Rossini PM, Pennica A. Cortical sources of resting-state EEG rhythms in “experienced” HIV subjects under antiretroviral therapy. Clin Neurophysiol 2014; 125:1792-802. [DOI: 10.1016/j.clinph.2014.01.024] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2012] [Revised: 12/30/2013] [Accepted: 01/20/2014] [Indexed: 11/26/2022]
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Transient epileptic amnesia mistaken for mild cognitive impairment? A high-density EEG study. Epilepsy Behav 2014; 36:41-6. [PMID: 24857807 DOI: 10.1016/j.yebeh.2014.04.014] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2013] [Revised: 04/15/2014] [Accepted: 04/18/2014] [Indexed: 02/07/2023]
Abstract
Mild cognitive impairment (MCI) converts to Alzheimer's disease within a few years of diagnosis in up to 80% of patients. The identification among such a population of a rare form of epilepsy (transient epileptic amnesia [TEA]), characterized by mixed anterograde and retrograde amnesia with apparent preservation of other cognitive functions, excessively rapid decay of newly acquired memories, and loss of memories for salient personal events of the remote past, strongly affects prognosis and medical treatment. Our aim was to define the clinical utility of routine high-density electroencephalography (EEG) in patients with MCI for the detection of epilepsy, especially TEA. Using high-density EEG (256 channels), we were able to single out 3 cases of TEA previously misdiagnosed as MCI in this cohort of 76 consecutive patients with MCI diagnosed at our center. Antiepileptic treatment effectively stopped the acute episodes of memory loss. To our knowledge, this is the first report of an incidence of 4% of TEA recorded in such a cohort.
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Poil SS, de Haan W, van der Flier WM, Mansvelder HD, Scheltens P, Linkenkaer-Hansen K. Integrative EEG biomarkers predict progression to Alzheimer's disease at the MCI stage. Front Aging Neurosci 2013; 5:58. [PMID: 24106478 PMCID: PMC3789214 DOI: 10.3389/fnagi.2013.00058] [Citation(s) in RCA: 99] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2013] [Accepted: 09/11/2013] [Indexed: 12/16/2022] Open
Abstract
Alzheimer's disease (AD) is a devastating disorder of increasing prevalence in modern society. Mild cognitive impairment (MCI) is considered a transitional stage between normal aging and AD; however, not all subjects with MCI progress to AD. Prediction of conversion to AD at an early stage would enable an earlier, and potentially more effective, treatment of AD. Electroencephalography (EEG) biomarkers would provide a non-invasive and relatively cheap screening tool to predict conversion to AD; however, traditional EEG biomarkers have not been considered accurate enough to be useful in clinical practice. Here, we aim to combine the information from multiple EEG biomarkers into a diagnostic classification index in order to improve the accuracy of predicting conversion from MCI to AD within a 2-year period. We followed 86 patients initially diagnosed with MCI for 2 years during which 25 patients converted to AD. We show that multiple EEG biomarkers mainly related to activity in the beta-frequency range (13–30 Hz) can predict conversion from MCI to AD. Importantly, by integrating six EEG biomarkers into a diagnostic index using logistic regression the prediction improved compared with the classification using the individual biomarkers, with a sensitivity of 88% and specificity of 82%, compared with a sensitivity of 64% and specificity of 62% of the best individual biomarker in this index. In order to identify this diagnostic index we developed a data mining approach implemented in the Neurophysiological Biomarker Toolbox (http://www.nbtwiki.net/). We suggest that this approach can be used to identify optimal combinations of biomarkers (integrative biomarkers) also in other modalities. Potentially, these integrative biomarkers could be more sensitive to disease progression and response to therapeutic intervention.
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Affiliation(s)
- Simon-Shlomo Poil
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, VU University Amsterdam Amsterdam, Netherlands
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Ward A, Tardiff S, Dye C, Arrighi HM. Rate of conversion from prodromal Alzheimer's disease to Alzheimer's dementia: a systematic review of the literature. Dement Geriatr Cogn Dis Extra 2013; 3:320-32. [PMID: 24174927 PMCID: PMC3808216 DOI: 10.1159/000354370] [Citation(s) in RCA: 252] [Impact Index Per Article: 22.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
Background The purpose of this study was to summarize published estimates for conversion from mild cognitive impairment or amnestic mild cognitive impairment to Alzheimer's dementia. We carried out a systematic review of English language publications to identify cohort studies published since January 2006 that reported the risk or rate of conversion. Summary Thirty-two cohort studies were identified, of which 14 reported annualized conversion rates (ACRs). Conversions over 1 year ranged from 10.2 to 33.6% (5 studies, median: 19.0%), and over 2 years from 9.8 to 36.3% (7 studies, median: 18.6%). ACRs ranged from 7.5 to 16.5% (7 studies, median: 11.0%) per person-year for studies recruiting from clinics, and from 5.4 to 11.5% (7 studies, median: 7.1%) for community samples. Key Message Extensive variation was observed in conversion rates due to the population sampled, diagnostic criteria, and duration, and because many studies did not account for loss to follow-up.
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Affiliation(s)
- Alex Ward
- United BioSource Corporation, Lexington, Mass., USA
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28
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Babiloni C, Del Percio C, Lizio R, Marzano N, Infarinato F, Soricelli A, Salvatore E, Ferri R, Bonforte C, Tedeschi G, Montella P, Baglieri A, Rodriguez G, Famà F, Nobili F, Vernieri F, Ursini F, Mundi C, Frisoni GB, Rossini PM. Cortical sources of resting state electroencephalographic alpha rhythms deteriorate across time in subjects with amnesic mild cognitive impairment. Neurobiol Aging 2013; 35:130-42. [PMID: 23906617 DOI: 10.1016/j.neurobiolaging.2013.06.019] [Citation(s) in RCA: 52] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2012] [Revised: 06/21/2013] [Accepted: 06/30/2013] [Indexed: 11/13/2022]
Abstract
Cortical sources of resting state electroencephalographic (EEG) rhythms are abnormal in subjects with mild cognitive impairment (MCI). Here, we tested the hypothesis that these sources in amnesic MCI subjects further deteriorate over 1 year. To this aim, the resting state eyes-closed EEG data were recorded in 54 MCI subjects at baseline (Mini Mental State Examination I = 26.9; standard error [SE], 0.2) and at approximately 1-year follow-up (13.8 months; SE, 0.5; Mini Mental State Examination II = 25.8; SE, 0.2). As a control, EEG recordings were also performed in 45 normal elderly and in 50 mild Alzheimer's disease subjects. EEG rhythms of interest were delta (2-4 Hz), theta (4-8 Hz), alpha1 (8-10.5 Hz), alpha2 (10.5-13 Hz), beta1 (13-20 Hz), and beta2 (20-30 Hz). Cortical EEG sources were estimated using low-resolution brain electromagnetic tomography. Compared with the normal elderly and mild Alzheimer's disease subjects, the MCI subjects were characterized by an intermediate power of posterior alpha1 sources. In the MCI subjects, the follow-up EEG recordings showed a decreased power of posterior alpha1 and alpha2 sources. These results suggest that the resting state EEG alpha sources were sensitive-at least at the group level-to the cognitive decline occurring in the amnesic MCI group over 1 year, and might represent cost-effective, noninvasive and widely available markers to follow amnesic MCI populations in large clinical trials.
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Affiliation(s)
- Claudio Babiloni
- Department of Physiology and Pharmacology, University of Rome La Sapienza, Rome, Italy.
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Babiloni C, Del Percio C, Bordet R, Bourriez JL, Bentivoglio M, Payoux P, Derambure P, Dix S, Infarinato F, Lizio R, Triggiani AI, Richardson JC, Rossini PM. Effects of acetylcholinesterase inhibitors and memantine on resting-state electroencephalographic rhythms in Alzheimer’s disease patients. Clin Neurophysiol 2013; 124:837-50. [DOI: 10.1016/j.clinph.2012.09.017] [Citation(s) in RCA: 54] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2011] [Revised: 09/21/2012] [Accepted: 09/24/2012] [Indexed: 10/27/2022]
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Vecchio F, Babiloni C, Lizio R, Fallani FDV, Blinowska K, Verrienti G, Frisoni G, Rossini PM. Resting state cortical EEG rhythms in Alzheimer's disease: toward EEG markers for clinical applications: a review. SUPPLEMENTS TO CLINICAL NEUROPHYSIOLOGY 2013; 62:223-36. [PMID: 24053043 DOI: 10.1016/b978-0-7020-5307-8.00015-6] [Citation(s) in RCA: 98] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
The human brain contains an intricate network of about 100 billion neurons. Aging of the brain is characterized by a combination of synaptic pruning, loss of cortico-cortical connections, and neuronal apoptosis that provoke an age-dependent decline of cognitive functions. Neural/synaptic redundancy and plastic remodeling of brain networking, also secondary to mental and physical training, promote maintenance of brain activity and cognitive status in healthy elderly subjects for everyday life. However, age is the main risk factor for neurodegenerative disorders such as Alzheimer's disease (AD) that impact on cognition. Growing evidence supports the idea that AD targets specific and functionally connected neuronal networks and that oscillatory electromagnetic brain activity might be a hallmark of the disease. In this line, digital electroencephalography (EEG) allows noninvasive analysis of cortical neuronal synchronization, as revealed by resting state brain rhythms. This review provides an overview of the studies on resting state eyes-closed EEG rhythms recorded in amnesic mild cognitive impairment (MCI) and AD subjects. Several studies support the idea that spectral markers of these EEG rhythms, such as power density, spectral coherence, and other quantitative features, differ among normal elderly, MCI, and AD subjects, at least at group level. Regarding the classification of these subjects at individual level, the most previous studies showed a moderate accuracy (70-80%) in the classification of EEG markers relative to normal and AD subjects. In conclusion, resting state EEG makers are promising for large-scale, low-cost, fully noninvasive screening of elderly subjects at risk of AD.
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Affiliation(s)
- Fabrizio Vecchio
- A.Fa.R., Dipartimento di Neuroscienze, Ospedale Fatebenefratelli, Isola Tiberina, 00186 Rome, Italy
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Hota SK, Sharma VK, Hota K, Das S, Dhar P, Mahapatra BB, Srivastava RB, Singh SB. Multi-domain cognitive screening test for neuropsychological assessment for cognitive decline in acclimatized lowlanders staying at high altitude. Indian J Med Res 2012; 136:411-20. [PMID: 23041734 PMCID: PMC3510887] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022] Open
Abstract
BACKGROUND & OBJECTIVES Ascent to high altitude has been reported to cause hippocampal atrophy and cognitive impairment in mountaineers. We assessed the cognitive performance and probable occurrence of mild cognitive impairment (MCI) in acclimatized lowlanders (ALL) staying at altitudes above 4,300 m for duration above 12 months and validated a multi-domain cognitive screening test (MDCST) for future demographic studies on MCI. METHODS Following evaluation of sensitivity and correlation of the newly developed MDCST battery with Mini Mental State Examination (MMSE) and Clinical Dementia Rating (CDR) scores on a group of 28 individuals, the MDCST battery was validated on a population of 843 ALL staying at high altitude MSL >4,300 m and 862 subjects staying at MSL <230 m. EEG recordings were performed on 840 ALL staying at altitudes above 4,300 m and 743 control subjects staying at MSL <230 m. RESULTS Percentage prevalence of MCI was 4.18 per cent in the ALL population as assessed by MMSE while that of the LL population was <0.42 per cent. The percentage prevalence of MCI based on calculations from the MDCST scores was 12.4 per cent in the ALL population as compared to 1.19 per cent in the LL population. Decrease in alpha wave amplitude at the T3 and T4 sources in MCI subjects was observed in LL group while there was an increase in amplitude for alpha wave in these regions in the ALL groups. Domain specific MDCST showed decline in immediate recall, procedural memory and mind body co-ordination which was negligible in the LL population. INTERPRETATION & CONCLUSIONS MDCST exhibited excellent psychometric properties in terms of sensitivity, and test-retest reliability qualifying it to be used as a more effective cognitive measure for assessment of MCI in demographic studies in comparison to traditional measures. Our findings also showed increased prevalence of MCI in ALL population staying for longer durations at high altitude which is neurophysiologically distinct from MCI leading to Alzheimer's disease.
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Affiliation(s)
- Sunil Kumar Hota
- Defence Institute of High Altitude Research, Leh, Jammu & Kashmir, India
| | - Vijay Kumar Sharma
- Defence Institute of High Altitude Research, Leh, Jammu & Kashmir, India
| | - Kalpana Hota
- Defence Institute of High Altitude Research, Leh, Jammu & Kashmir, India
| | - Saroj Das
- Defence Institute of High Altitude Research, Leh, Jammu & Kashmir, India
| | - Priyanka Dhar
- Defence Institute of High Altitude Research, Leh, Jammu & Kashmir, India
| | | | | | - Shashi Bala Singh
- Defence Institute of Physiology & Allied Sciences, Delhi, India,Reprint requests: Dr Shashi Bala Singh, Scientist G & Director, Defence Institute of Physiology & Allied Sciences, Lucknow Road, Timarpur, Delhi 110 054, India e-mail:
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Buchman AS, Bennett DA. Loss of motor function in preclinical Alzheimer's disease. Expert Rev Neurother 2011; 11:665-76. [PMID: 21539487 DOI: 10.1586/ern.11.57] [Citation(s) in RCA: 173] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
Accumulating evidence suggests that Alzheimer's disease (AD) has a long preclinical phase, during which time its characteristic pathology accumulates and patient function declines, but symptoms are insufficient to warrant a clinical diagnosis of dementia. There have been increasing reports of noncognitive symptoms, including loss of motor function, reported to be associated with incident AD. To understand the link between motor function and preclinical AD, this article examines: our understanding of motor function and its clinical assessment in cohort studies; the relationship of motor function and loss of cognition in older persons; risk factors for cognitive and motor decline; and the relation of post-mortem indices of AD and motor function prior to death. Together, these data suggest that age-related cognitive and motor decline may share a common causation. Furthermore, individuals with a clinical diagnosis of AD may represent the 'tip of the iceberg', since AD pathology may also account for a substantial proportion of cognitive and motor dysfunction currently considered 'normal aging' in older persons without dementia. Thus, AD may have a much larger impact on the health and wellbeing of our aging population.
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Affiliation(s)
- Aron S Buchman
- Rush Alzheimer's Disease Center, Rush University Medical Center, 600 S. Paulina, Suite 1028, Chicago, IL 60612, USA.
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Lizio R, Vecchio F, Frisoni GB, Ferri R, Rodriguez G, Babiloni C. Electroencephalographic rhythms in Alzheimer's disease. Int J Alzheimers Dis 2011; 2011:927573. [PMID: 21629714 PMCID: PMC3100729 DOI: 10.4061/2011/927573] [Citation(s) in RCA: 50] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2010] [Accepted: 03/13/2011] [Indexed: 11/20/2022] Open
Abstract
Physiological brain aging is characterized by synapses loss and neurodegeneration that slowly lead to an age-related decline of cognition. Neural/synaptic redundancy and plastic remodelling of brain networking, also due to mental and physical training, promotes maintenance of brain activity in healthy elderly subjects for everyday life and good social behaviour and intellectual capabilities. However, age is the major risk factor for most common neurodegenerative disorders that impact on cognition, like Alzheimer's disease (AD). Brain electromagnetic activity is a feature of neuronal network function in various brain regions. Modern neurophysiological techniques, such as electroencephalography (EEG) and event-related potentials (ERPs), are useful tools in the investigation of brain cognitive function in normal and pathological aging with an excellent time resolution. These techniques can index normal and abnormal brain aging analysis of corticocortical connectivity and neuronal synchronization of rhythmic oscillations at various frequencies. The present review suggests that discrimination between physiological and pathological brain aging clearly emerges at the group level, with suggested applications also at the level of single individual. The possibility of combining the use of EEG together with biological/neuropsychological markers and structural/functional imaging is promising for a low-cost, non-invasive, and widely available assessment of groups of individuals at-risk.
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