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Niknam N, Khaefi S, Heidarpour H, Sadeghi M, Jafari NA, Mohammadi S, Ahmadi Z, Ahangar-Sirous R, Mayeli M, Seyedmirzaei H. Associations between diffusion tensor imaging patterns and cerebrospinal fluid markers in mild cognitive impairment. J Clin Neurosci 2025; 135:111141. [PMID: 40010169 DOI: 10.1016/j.jocn.2025.111141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2024] [Revised: 02/17/2025] [Accepted: 02/17/2025] [Indexed: 02/28/2025]
Abstract
Diffusion tensor imaging (DTI) can be used to detect early signs of increased water diffusivity in white matter tracts in patients with mild cognitive impairment (MCI). This study examined how DTI, alongside cerebrospinal fluid (CSF) biomarkers (like tau proteins and amyloid-β), can help identify early brain changes in MCI. We included 159 individuals (92 with MCI and 67 healthy controls) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and extracted their demographics, CSF biomarkers, and DTI metrics. We compared the biomarkers (CSF biomarkers and DTI markers in 57 white matter tracts) between the two study groups using a general linear model, adjusting for age, sex, and handedness. CSF biomarker levels showed a statistically significant difference between the two study groups. Also, diffusion properties of left Cingulum and left Uncinate fasciculus in both groups were statistically different. Additionally, we explored possible associations between CSF and DTI markers in the MCI group. Our results indicated several statistically significant associations between DTI metrics and CSF biomarkers within specific white matter tracts. These findings underscore the complexity of imaging and molecular markers associated with MCI.
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Affiliation(s)
| | - Sara Khaefi
- Department of Electrical Engineering, Shahed University, Tehran, Iran
| | - Hadise Heidarpour
- Neuroscience Research Center, Golestan University of Medical Sciences, Gorgan, Iran; Gastroenterology and Hepatology Research Center, Golestan University of Medical Sciences, Gorgan, Iran
| | - Mohammad Sadeghi
- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran; School of Rehabilitation, Shiraz University of Medical Sciences, Shiraz, Iran
| | | | - Sheida Mohammadi
- Department of Psychology, South Tehran Branch, Islamic Azad University, Tehran, Iran
| | - Zeinab Ahmadi
- Neuroscience Graduate Program, Medical School, University of Crete, Greece
| | - Ramin Ahangar-Sirous
- Neurosciences Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Mahsa Mayeli
- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran; Department of Radiology and Biomedical Imaging, Yale School of Medicine, CT, USA
| | - Homa Seyedmirzaei
- Occupational Sleep Research Center, Baharloo Hospital, Tehran University of Medical Sciences, Tehran, Iran.
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Dolci G, Ellis CA, Cruciani F, Brusini L, Abrol A, Galazzo IB, Menegaz G, Calhoun VD. Multimodal MRI accurately identifies amyloid status in unbalanced cohorts in Alzheimer's disease continuum. Netw Neurosci 2025; 9:259-279. [PMID: 40161995 PMCID: PMC11949592 DOI: 10.1162/netn_a_00423] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Accepted: 10/21/2024] [Indexed: 04/02/2025] Open
Abstract
Amyloid-β (Aβ) plaques in conjunction with hyperphosphorylated tau proteins in the form of neurofibrillary tangles are the two neuropathological hallmarks of Alzheimer's disease. It is well-known that the identification of individuals with Aβ positivity could enable early diagnosis. In this work, we aim at capturing the Aβ positivity status in an unbalanced cohort enclosing subjects at different disease stages, exploiting the underlying structural and connectivity disease-induced modulations as revealed by structural, functional, and diffusion MRI. Of note, due to the unbalanced cohort, the outcomes may be guided by those factors rather than amyloid accumulation. The partial views provided by each modality are integrated in the model, allowing to take full advantage of their complementarity in encoding the effects of the Aβ accumulation, leading to an accuracy of 0.762 ± 0.04. The specificity of the information brought by each modality is assessed by post hoc explainability analysis (guided backpropagation), highlighting the underlying structural and functional changes. Noteworthy, well-established biomarker key regions related to Aβ deposition could be identified by all modalities, including the hippocampus, thalamus, precuneus, and cingulate gyrus, witnessing in favor of the reliability of the method as well as its potential in shedding light on modality-specific possibly unknown Aβ deposition signatures.
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Affiliation(s)
- Giorgio Dolci
- Department of Computer Science, University of Verona, Verona, Italy
- Department of Engineering for Innovation Medicine, University of Verona, Verona, Italy
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | - Charles A. Ellis
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | - Federica Cruciani
- Department of Engineering for Innovation Medicine, University of Verona, Verona, Italy
| | - Lorenza Brusini
- Department of Engineering for Innovation Medicine, University of Verona, Verona, Italy
| | - Anees Abrol
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | | | - Gloria Menegaz
- Department of Engineering for Innovation Medicine, University of Verona, Verona, Italy
| | - Vince D. Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
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3
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Javed E, Suárez-Méndez I, Susi G, Román JV, Palva JM, Maestú F, Palva S. A Shift Toward Supercritical Brain Dynamics Predicts Alzheimer's Disease Progression. J Neurosci 2025; 45:e0688242024. [PMID: 40011070 PMCID: PMC11867000 DOI: 10.1523/jneurosci.0688-24.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2024] [Revised: 10/29/2024] [Accepted: 11/20/2024] [Indexed: 02/28/2025] Open
Abstract
Alzheimer's disease (AD) is the most common form of dementia with continuum of disease progression of increasing severity from subjective cognitive decline (SCD) to mild cognitive impairment (MCI) and lastly to AD. The transition from MCI to AD has been linked to brain hypersynchronization, but the underlying mechanisms leading to this are unknown. Here, we hypothesized that excessive excitation in AD disease progression would shift brain dynamics toward supercriticality across an extended regime of critical-like dynamics. In this framework, healthy brain activity during aging preserves operation at near the critical phase transition at balanced excitation-inhibition (E/I). To test this hypothesis, we used source-reconstructed resting-state MEG data from a cross-sectional cohort (N = 343) of individuals with SCD, MCI, and healthy controls (HC) as well as from a longitudinal cohort (N = 45) of MCI patients. We then assessed brain criticality by quantifying long-range temporal correlations (LRTCs) and functional EI (fE/I) of neuronal oscillations. LRTCs were attenuated in SCD in spectrally and anatomically constrained regions while this breakdown was progressively more widespread in MC. In parallel, fE/I was increased in the MCI but not in the SC cohort. Both observations also predicted the disease progression in the longitudinal cohort. Finally, using machine learning trained on functional (LRTCs, fE/I) and structural (MTL volumes) features, we show that LRTCs and f/EI are the most informative features for accurate classification of individuals with SCD while structural changes accurate classify the individuals with MCI. These findings establish that a shift toward supercritical brain dynamics reflects early AD disease progression.
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Affiliation(s)
- Ehtasham Javed
- Neuroscience Center, HiLIFE-Helsinki Institute of Life Science, University of Helsinki, Helsinki FI-00014, Finland
| | - Isabel Suárez-Méndez
- Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, Madrid 28015, Spain
- Department of Structure of Matter, Thermal Physics and Electronics, Complutense University of Madrid 28040, Spain
| | - Gianluca Susi
- Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, Madrid 28015, Spain
- Department of Structure of Matter, Thermal Physics and Electronics, Complutense University of Madrid 28040, Spain
| | - Juan Verdejo Román
- Department of Personality, Evaluation and Psychological Treatment, University of Granada 18071, Spain
| | - J Matias Palva
- Neuroscience Center, HiLIFE-Helsinki Institute of Life Science, University of Helsinki, Helsinki FI-00014, Finland
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo 02150, Finland
| | - Fernando Maestú
- Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, Madrid 28015, Spain
- Department of Experimental Psychology, Cognitive Processes and Logopedy, Complutense University of Madrid, Pozuelo de Alarcón 28223, Spain
| | - Satu Palva
- Neuroscience Center, HiLIFE-Helsinki Institute of Life Science, University of Helsinki, Helsinki FI-00014, Finland
- Centre for Cognitive Neuroimaging, School of Psychology and Neuroscience, University of Glasgow, Glasgow G12 8QB
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4
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Del Percio C, Lizio R, Lopez S, Noce G, Carpi M, Jakhar D, Soricelli A, Salvatore M, Yener G, Güntekin B, Massa F, Arnaldi D, Famà F, Pardini M, Ferri R, Carducci F, Lanuzza B, Stocchi F, Vacca L, Coletti C, Marizzoni M, Taylor JP, Hanoğlu L, Yılmaz NH, Kıyı İ, Özbek-İşbitiren Y, D’Anselmo A, Bonanni L, Biundo R, D’Antonio F, Bruno G, Antonini A, Giubilei F, Farotti L, Parnetti L, Frisoni GB, Babiloni C. Resting-State EEG Alpha Rhythms Are Related to CSF Tau Biomarkers in Prodromal Alzheimer's Disease. Int J Mol Sci 2025; 26:356. [PMID: 39796211 PMCID: PMC11720070 DOI: 10.3390/ijms26010356] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2024] [Revised: 12/13/2024] [Accepted: 12/25/2024] [Indexed: 01/13/2025] Open
Abstract
Patients with mild cognitive impairment due to Alzheimer's disease (ADMCI) typically show abnormally high delta (<4 Hz) and low alpha (8-12 Hz) rhythms measured from resting-state eyes-closed electroencephalographic (rsEEG) activity. Here, we hypothesized that the abnormalities in rsEEG activity may be greater in ADMCI patients than in those with MCI not due to AD (noADMCI). Furthermore, they may be associated with the diagnostic cerebrospinal fluid (CSF) amyloid-tau biomarkers in ADMCI patients. An international database provided clinical-demographic-rsEEG datasets for cognitively unimpaired older (Healthy; N = 45), ADMCI (N = 70), and noADMCI (N = 45) participants. The rsEEG rhythms spanned individual delta, theta, and alpha frequency bands. The eLORETA freeware estimated cortical rsEEG sources. Posterior rsEEG alpha source activities were reduced in the ADMCI group compared not only to the Healthy group but also to the noADMCI group (p < 0.001). Negative associations between the CSF phospho-tau and total tau levels and posterior rsEEG alpha source activities were observed in the ADMCI group (p < 0.001), whereas those with CSF amyloid beta 42 levels were marginal. These results suggest that neurophysiological brain neural oscillatory synchronization mechanisms regulating cortical arousal and vigilance through rsEEG alpha rhythms are mainly affected by brain tauopathy in ADMCI patients.
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Affiliation(s)
- Claudio Del Percio
- Department of Physiology and Pharmacology “Vittorio Erspamer”, Sapienza University of Rome, 00185 Rome, Italy; (C.D.P.); (S.L.); (M.C.); (D.J.); (F.C.); (C.B.)
| | - Roberta Lizio
- Department of Physiology and Pharmacology “Vittorio Erspamer”, Sapienza University of Rome, 00185 Rome, Italy; (C.D.P.); (S.L.); (M.C.); (D.J.); (F.C.); (C.B.)
- Oasi Research Institute—IRCCS, 94018 Troina, Italy; (R.F.); (B.L.)
| | - Susanna Lopez
- Department of Physiology and Pharmacology “Vittorio Erspamer”, Sapienza University of Rome, 00185 Rome, Italy; (C.D.P.); (S.L.); (M.C.); (D.J.); (F.C.); (C.B.)
| | - Giuseppe Noce
- IRCCS Synlab SDN, 80143 Naples, Italy; (G.N.); (A.S.); (M.S.)
| | - Matteo Carpi
- Department of Physiology and Pharmacology “Vittorio Erspamer”, Sapienza University of Rome, 00185 Rome, Italy; (C.D.P.); (S.L.); (M.C.); (D.J.); (F.C.); (C.B.)
| | - Dharmendra Jakhar
- Department of Physiology and Pharmacology “Vittorio Erspamer”, Sapienza University of Rome, 00185 Rome, Italy; (C.D.P.); (S.L.); (M.C.); (D.J.); (F.C.); (C.B.)
| | - Andrea Soricelli
- IRCCS Synlab SDN, 80143 Naples, Italy; (G.N.); (A.S.); (M.S.)
- Department of Medical, Movement and Well-Being Sciences, University of Naples Parthenope, 80133 Naples, Italy
| | - Marco Salvatore
- IRCCS Synlab SDN, 80143 Naples, Italy; (G.N.); (A.S.); (M.S.)
| | - Görsev Yener
- Department of Neurology, Faculty of Medicine, Dokuz Eylül University, 35340 İzmir, Turkey;
- IBG: International Biomedicine and Genome Center, 35340 Izmir, Turkey
| | - Bahar Güntekin
- Research Institute for Health Sciences and Technologies (SABITA), Istanbul Medipol University, 34810 Istanbul, Turkey;
- Department of Biophysics, School of Medicine, Istanbul Medipol University, 34810 Istanbul, Turkey
| | - Federico Massa
- Dipartimento di Neuroscienze, Oftalmologia, Genetica, Riabilitazione e Scienze Materno-Infantili (DiNOGMI), Università di Genova, 16132 Genova, Italy; (F.M.); (D.A.); (F.F.); (M.P.)
- Clinica Neurologica, IRCCS Ospedale Policlinico San Martino, 16132 Genova, Italy
| | - Dario Arnaldi
- Dipartimento di Neuroscienze, Oftalmologia, Genetica, Riabilitazione e Scienze Materno-Infantili (DiNOGMI), Università di Genova, 16132 Genova, Italy; (F.M.); (D.A.); (F.F.); (M.P.)
- Neurofisiopatologia, IRCCS Ospedale Policlinico San Martino, 16132 Genova, Italy
| | - Francesco Famà
- Dipartimento di Neuroscienze, Oftalmologia, Genetica, Riabilitazione e Scienze Materno-Infantili (DiNOGMI), Università di Genova, 16132 Genova, Italy; (F.M.); (D.A.); (F.F.); (M.P.)
- Neurofisiopatologia, IRCCS Ospedale Policlinico San Martino, 16132 Genova, Italy
| | - Matteo Pardini
- Dipartimento di Neuroscienze, Oftalmologia, Genetica, Riabilitazione e Scienze Materno-Infantili (DiNOGMI), Università di Genova, 16132 Genova, Italy; (F.M.); (D.A.); (F.F.); (M.P.)
| | - Raffaele Ferri
- Oasi Research Institute—IRCCS, 94018 Troina, Italy; (R.F.); (B.L.)
| | - Filippo Carducci
- Department of Physiology and Pharmacology “Vittorio Erspamer”, Sapienza University of Rome, 00185 Rome, Italy; (C.D.P.); (S.L.); (M.C.); (D.J.); (F.C.); (C.B.)
- Oasi Research Institute—IRCCS, 94018 Troina, Italy; (R.F.); (B.L.)
| | - Bartolo Lanuzza
- Oasi Research Institute—IRCCS, 94018 Troina, Italy; (R.F.); (B.L.)
| | - Fabrizio Stocchi
- IRCCS San Raffaele, 00163 Rome, Italy; (F.S.); (L.V.); (C.C.)
- Department of Neurology, Telematic University San Raffaele, 00166 Rome, Italy
| | - Laura Vacca
- IRCCS San Raffaele, 00163 Rome, Italy; (F.S.); (L.V.); (C.C.)
| | - Chiara Coletti
- IRCCS San Raffaele, 00163 Rome, Italy; (F.S.); (L.V.); (C.C.)
| | - Moira Marizzoni
- Biological Psychiatry Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125 Brescia, Italy;
| | - John Paul Taylor
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne NE2 4AE, UK;
| | - Lutfu Hanoğlu
- Department of Neurology, School of Medicine, Istanbul Medipol University, 34810 Istanbul, Turkey;
| | - Nesrin Helvacı Yılmaz
- Department of Neurology, Medipol University Istanbul Parkinson’s Disease and Movement Disorders Center (PARMER), 34718 Istanbul, Turkey;
| | - İlayda Kıyı
- Health Sciences Institute, Department of Neurosciences, Dokuz Eylül University, 35330 Izmir, Turkey; (İ.K.); (Y.Ö.-İ.)
| | - Yağmur Özbek-İşbitiren
- Health Sciences Institute, Department of Neurosciences, Dokuz Eylül University, 35330 Izmir, Turkey; (İ.K.); (Y.Ö.-İ.)
| | - Anita D’Anselmo
- Department of Aging Medicine and Sciences, University “G. d’Annunzio” of Chieti-Pescara, 66100 Chieti, Italy; (A.D.); (L.B.)
| | - Laura Bonanni
- Department of Aging Medicine and Sciences, University “G. d’Annunzio” of Chieti-Pescara, 66100 Chieti, Italy; (A.D.); (L.B.)
| | - Roberta Biundo
- Department of General Psychology, University of Padua, 35128 Padova, Italy;
- Parkinson and Movement Disorders Unit, Study Center for Neurodegeneration (CESNE), Center for Rare Neurological Diseases (ERN-RND), Department of Neuroscience, University of Padua, 35121 Padua, Italy;
| | - Fabrizia D’Antonio
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy; (F.D.); (G.B.)
| | - Giuseppe Bruno
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy; (F.D.); (G.B.)
| | - Angelo Antonini
- Parkinson and Movement Disorders Unit, Study Center for Neurodegeneration (CESNE), Center for Rare Neurological Diseases (ERN-RND), Department of Neuroscience, University of Padua, 35121 Padua, Italy;
| | - Franco Giubilei
- Department of Neuroscience, Mental Health, and Sensory Organs, Sapienza University of Rome, 00189 Rome, Italy;
| | - Lucia Farotti
- Centre for Memory Disturbances, Lab of Clinical Neurochemistry, Section of Neurology, University of Perugia, 06123 Perugia, Italy;
| | - Lucilla Parnetti
- Department of Medicine and Surgery, University of Perugia, 05100 Perugia, Italy;
| | - Giovanni B. Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, 1205 Geneva, Switzerland
- Geneva Memory Center, Department of Rehabilitation and Geriatrics, Geneva University Hospitals, 1205 Geneva, Switzerland
| | - Claudio Babiloni
- Department of Physiology and Pharmacology “Vittorio Erspamer”, Sapienza University of Rome, 00185 Rome, Italy; (C.D.P.); (S.L.); (M.C.); (D.J.); (F.C.); (C.B.)
- Hospital San Raffaele Cassino, 03043 Cassino, Italy
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Ma L, Pang J, Liu Q, Li P, Huang J, Xu Y, Xie H. A study on cognitive trajectory changes and predictive factors in middle-aged and older adults individuals with dual sensory impairment based on the health social determinants model. Front Public Health 2024; 12:1489429. [PMID: 39741941 PMCID: PMC11685189 DOI: 10.3389/fpubh.2024.1489429] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2024] [Accepted: 12/04/2024] [Indexed: 01/03/2025] Open
Abstract
Aim This study aims to explore the cognitive trajectory changes in middle-aged and older adults individuals with dual sensory impairment (simultaneous visual and hearing impairment) and to identify the predictors of different trajectory changes. Methods Based on the longitudinal data from the China Health and Retirement Longitudinal Study (CHARLS) from 2013 to 2020, data from 2,369 middle-aged and older adults individuals with dual sensory impairment were selected. A latent variable growth mixture model was constructed to analyze the cognitive function development trajectories in this population and to identify their predictive factors. Results The cognitive function development trajectories in the middle-aged and older adults population can be categorized into three types: high cognitive level stable group, low cognitive level slowly declining group, and moderate cognitive level rapidly declining group. Logistic regression analysis showed that age (OR 30.544; 95% CI 9.35-99.754; p < 0.001), sleep duration (OR 0.559; 95% CI 0.343-0.909; p < 0.005), education (OR 0.009; 95% CI 0.003-0.025; p < 0.001), marital status (OR 2.122; 95% CI 1.457-3.090; p < 0.001), social participation (OR 0.499; 95% CI 0.379-0.658; p < 0.001), place of residence (OR 1.471; 95% CI 1.089-1.988; p < 0.001), and medical insurance (OR 0.353; 95% CI 0.169-0.736; p < 0.005) are predictive factors for cognitive function trajectories in this population. Conclusion There is group heterogeneity in the cognitive function development trajectories among middle-aged and older adults individuals with dual sensory impairment. Factors such as less than 4 h of nighttime sleep, low social participation, alcohol consumption, and lack of medical insurance are modifiable risk factors for cognitive decline in this population. Preventive strategies should be formulated accordingly, especially for vulnerable groups, including older rural residents and those with lower educational attainment, to prevent cognitive function deterioration in middle-aged and older adults individuals with dual sensory impairment.
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Affiliation(s)
| | | | | | | | | | | | - Hui Xie
- College of Nursing, Bengbu Medical University, Bengbu, Anhui, China
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Kumar R, Waisberg E, Ong J, Paladugu P, Amiri D, Saintyl J, Yelamanchi J, Nahouraii R, Jagadeesan R, Tavakkoli A. Artificial Intelligence-Based Methodologies for Early Diagnostic Precision and Personalized Therapeutic Strategies in Neuro-Ophthalmic and Neurodegenerative Pathologies. Brain Sci 2024; 14:1266. [PMID: 39766465 PMCID: PMC11674895 DOI: 10.3390/brainsci14121266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2024] [Revised: 12/09/2024] [Accepted: 12/15/2024] [Indexed: 01/11/2025] Open
Abstract
Advancements in neuroimaging, particularly diffusion magnetic resonance imaging (MRI) techniques and molecular imaging with positron emission tomography (PET), have significantly enhanced the early detection of biomarkers in neurodegenerative and neuro-ophthalmic disorders. These include Alzheimer's disease, Parkinson's disease, multiple sclerosis, neuromyelitis optica, and myelin oligodendrocyte glycoprotein antibody disease. This review highlights the transformative role of advanced diffusion MRI techniques-Neurite Orientation Dispersion and Density Imaging and Diffusion Kurtosis Imaging-in identifying subtle microstructural changes in the brain and visual pathways that precede clinical symptoms. When integrated with artificial intelligence (AI) algorithms, these techniques achieve unprecedented diagnostic precision, facilitating early detection of neurodegeneration and inflammation. Additionally, next-generation PET tracers targeting misfolded proteins, such as tau and alpha-synuclein, along with inflammatory markers, enhance the visualization and quantification of pathological processes in vivo. Deep learning models, including convolutional neural networks and multimodal transformers, further improve diagnostic accuracy by integrating multimodal imaging data and predicting disease progression. Despite challenges such as technical variability, data privacy concerns, and regulatory barriers, the potential of AI-enhanced neuroimaging to revolutionize early diagnosis and personalized treatment in neurodegenerative and neuro-ophthalmic disorders is immense. This review underscores the importance of ongoing efforts to validate, standardize, and implement these technologies to maximize their clinical impact.
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Affiliation(s)
- Rahul Kumar
- Department of Biochemistry and Molecular Biology, University of Miami Miller School of Medicine, 1600 NW 10th Ave, Miami, FL 33136, USA; (R.K.); (J.S.)
| | - Ethan Waisberg
- Department of Clinical Neurosciences, University of Cambridge, Downing Street, Cambridge CB2 3EH, UK;
| | - Joshua Ong
- Department of Ophthalmology and Visual Sciences, University of Michigan Kellogg Eye Center, 1000 Wall St, Ann Arbor, MI 48105, USA
| | - Phani Paladugu
- Sidney Kimmel Medical College, Thomas Jefferson University, 1025 Walnut St, Philadelphia, PA 19107, USA;
- Brigham and Women’s Hospital, Harvard Medical School, 75 Francis St, Boston, MA 02115, USA
| | - Dylan Amiri
- Department of Biology, University of Miami, 1301 Memorial Dr, Coral Gables, FL 33146, USA;
- Mecklenburg Neurology Group, 3541 Randolph Rd #301, Charlotte, NC 28211, USA;
| | - Jeremy Saintyl
- Department of Biochemistry and Molecular Biology, University of Miami Miller School of Medicine, 1600 NW 10th Ave, Miami, FL 33136, USA; (R.K.); (J.S.)
| | - Jahnavi Yelamanchi
- Tandon School of Engineering, New York University, 6 MetroTech Center, Brooklyn, NY 11201, USA;
| | - Robert Nahouraii
- Mecklenburg Neurology Group, 3541 Randolph Rd #301, Charlotte, NC 28211, USA;
| | - Ram Jagadeesan
- Whiting School of Engineering, Johns Hopkins University, 3400 N Charles St, Baltimore, MD 21218, USA;
| | - Alireza Tavakkoli
- Human-Machine Perception Laboratory, Department of Computer Science and Engineering, University of Nevada, Reno, 1664 N Virginia St, Reno, NV 89557, USA;
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Liu G, Yang C, Wang X, Chen X, Cai H, Le W. Cerebellum in neurodegenerative diseases: Advances, challenges, and prospects. iScience 2024; 27:111194. [PMID: 39555407 PMCID: PMC11567929 DOI: 10.1016/j.isci.2024.111194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2024] Open
Abstract
Neurodegenerative diseases (NDs) are a group of neurological disorders characterized by the progressive dysfunction of neurons and glial cells, leading to their structural and functional degradation in the central and/or peripheral nervous system. Historically, research on NDs has primarily focused on the brain, brain stem, or spinal cord associated with disease-related symptoms, often overlooking the role of the cerebellum. However, an increasing body of clinical and biological evidence suggests a significant connection between the cerebellum and NDs. In several NDs, cerebellar pathology and biochemical changes may start in the early disease stages. This article provides a comprehensive update on the involvement of the cerebellum in the clinical features and pathogenesis of multiple NDs, suggesting that the cerebellum is involved in the onset and progression of NDs through various mechanisms, including specific neurodegeneration, neuroinflammation, abnormal mitochondrial function, and altered metabolism. Additionally, this review highlights the significant therapeutic potential of cerebellum-related treatments for NDs.
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Affiliation(s)
- Guangdong Liu
- Institute of Neurology, Sichuan Academy of Medical Sciences-Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Cui Yang
- Institute of Neurology, Sichuan Academy of Medical Sciences-Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Xin Wang
- Institute of Neurology, Sichuan Academy of Medical Sciences-Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Xi Chen
- Institute of Neurology, Sichuan Academy of Medical Sciences-Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Huaibin Cai
- Transgenic Section, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA
| | - Weidong Le
- Institute of Neurology, Sichuan Academy of Medical Sciences-Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610054, China
- Shanghai University of Medicine & Health Sciences Affiliated Zhoupu Hospital, Shanghai 200237, China
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Al-Ezzi A, Arechavala RJ, Butler R, Nolty A, Kang JJ, Shimojo S, Wu DA, Fonteh AN, Kleinman MT, Kloner RA, Arakaki X. Disrupted brain functional connectivity as early signature in cognitively healthy individuals with pathological CSF amyloid/tau. Commun Biol 2024; 7:1037. [PMID: 39179782 PMCID: PMC11344156 DOI: 10.1038/s42003-024-06673-w] [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] [Received: 01/16/2024] [Accepted: 08/01/2024] [Indexed: 08/26/2024] Open
Abstract
Alterations in functional connectivity (FC) have been observed in individuals with Alzheimer's disease (AD) with elevated amyloid (Aβ) and tau. However, it is not yet known whether directed FC is already influenced by Aβ and tau load in cognitively healthy (CH) individuals. A 21-channel electroencephalogram (EEG) was used from 46 CHs classified based on cerebrospinal fluid (CSF) Aβ tau ratio: pathological (CH-PAT) or normal (CH-NAT). Directed FC was estimated with Partial Directed Coherence in frontal, temporal, parietal, central, and occipital regions. We also examined the correlations between directed FC and various functional metrics, including neuropsychology, cognitive reserve, MRI volumetrics, and heart rate variability between both groups. Compared to CH-NATs, the CH-PATs showed decreased FC from the temporal regions, indicating a loss of relative functional importance of the temporal regions. In addition, frontal regions showed enhanced FC in the CH-PATs compared to CH-NATs, suggesting neural compensation for the damage caused by the pathology. Moreover, CH-PATs showed greater FC in the frontal and occipital regions than CH-NATs. Our findings provide a useful and non-invasive method for EEG-based analysis to identify alterations in brain connectivity in CHs with a pathological versus normal CSF Aβ/tau.
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Affiliation(s)
- Abdulhakim Al-Ezzi
- Department of Neurosciences, Huntington Medical Research Institutes, Pasadena, CA, USA.
| | - Rebecca J Arechavala
- Department of Environmental and Occupational Health, Center for Occupational and Environmental Health (COEH), University of California, Irvine, CA, USA
| | - Ryan Butler
- Department of Neurosciences, Huntington Medical Research Institutes, Pasadena, CA, USA
| | - Anne Nolty
- Fuller Theological Seminary, Pasadena, CA, USA
| | | | - Shinsuke Shimojo
- The Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Daw-An Wu
- The Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Alfred N Fonteh
- Department of Neurosciences, Huntington Medical Research Institutes, Pasadena, CA, USA
| | - Michael T Kleinman
- Department of Environmental and Occupational Health, Center for Occupational and Environmental Health (COEH), University of California, Irvine, CA, USA
| | - Robert A Kloner
- Department of Neurosciences, Huntington Medical Research Institutes, Pasadena, CA, USA
- Department of Cardiovascular Research, Huntington Medical Research Institutes, Pasadena, CA, USA
| | - Xianghong Arakaki
- Department of Neurosciences, Huntington Medical Research Institutes, Pasadena, CA, USA.
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9
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García-Colomo A, López-Sanz D, Stam CJ, Hillebrand A, Carrasco-Gómez M, Spuch C, Comis-Tuche M, Maestú F. Minimum spanning tree analysis of unimpaired individuals at risk of Alzheimer's disease. Brain Commun 2024; 6:fcae283. [PMID: 39229485 PMCID: PMC11369931 DOI: 10.1093/braincomms/fcae283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Revised: 06/20/2024] [Accepted: 08/16/2024] [Indexed: 09/05/2024] Open
Abstract
Identifying early and non-invasive biomarkers to detect individuals in the earliest stages of the Alzheimer's disease continuum is crucial. As a result, electrophysiology and plasma biomarkers are emerging as great candidates in this pursuit due to their low invasiveness. This is the first magnetoencephalography study to assess the relationship between minimum spanning tree parameters, an alternative to overcome the comparability and thresholding problem issues characteristic of conventional brain network analyses, and plasma phosphorylated tau231 levels in unimpaired individuals, with different risk levels of Alzheimer's disease. Seventy-six individuals with available magnetoencephalography recordings and phosphorylated tau231 plasma determination were included. The minimum spanning tree for the theta, alpha and beta bands for each subject was obtained, and the leaf fraction, tree hierarchy and diameter were calculated. To study the relationship between these topological parameters and phosphorylated tau231, we performed correlation analyses, for the whole sample and considering the two risk sub-groups separately. Increasing concentrations of phosphorylated tau231 were associated with greater leaf fraction and tree hierarchy values, along with lower diameter values, for the alpha and theta frequency bands. These results emerged for the whole sample and the higher risk group, but not for the lower risk group. Our results indicate that the network topology of cognitively unimpaired individuals with elevated plasma phosphorylated tau231 levels, a marker of Alzheimer's disease pathology and amyloid-β accumulation, is already altered, shifting towards a more integrated network increasing its vulnerability and hub-dependency, mostly in the alpha band. This is indicated by increases in leaf fraction and tree hierarchy, along with reductions in diameter. These results match the initial trajectory proposed by theoretical models of disease progression and network disruption and suggest that changes in brain function and organization begin early on.
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Affiliation(s)
- Alejandra García-Colomo
- Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, 28223 Pozuelo de Alarcón, Spain
- Department of Experimental Psychology, Cognitive Psychology and Speech and Language Therapy, Complutense University of Madrid, 28223 Pozuelo de Alarcón, Spain
| | - David López-Sanz
- Department of Experimental Psychology, Cognitive Psychology and Speech and Language Therapy, Complutense University of Madrid, 28223 Pozuelo de Alarcón, Spain
| | - Cornelis J Stam
- Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Systems and Network Neurosciences, 1081 HV Amsterdam, The Netherlands
| | - Arjan Hillebrand
- Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, 1081 HV Amsterdam, The Netherlands
- Amsterdam Neuroscience, Systems and Network Neurosciences, 1081 HV Amsterdam, The Netherlands
| | - Martín Carrasco-Gómez
- Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, 28223 Pozuelo de Alarcón, Spain
- Department of Electronic Engineering, Universidad Politécnica de Madrid, 28040 Madrid, Spain
| | - Carlos Spuch
- Translational Neuroscience Research Group, Galicia Sur Health Research Institute (IIS-Galicia Sur), SERGAS-UVIGO, CIBERSAM, 36312 Vigo, Spain
| | - María Comis-Tuche
- Translational Neuroscience Research Group, Galicia Sur Health Research Institute (IIS-Galicia Sur), SERGAS-UVIGO, CIBERSAM, 36312 Vigo, Spain
| | - Fernando Maestú
- Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, 28223 Pozuelo de Alarcón, Spain
- Department of Experimental Psychology, Cognitive Psychology and Speech and Language Therapy, Complutense University of Madrid, 28223 Pozuelo de Alarcón, Spain
- Health Research Institute of the Hospital Clínico San Carlos (IdISSC), 28040 Madrid, Spain
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10
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Nabizadeh F. Disruption in functional networks mediated tau spreading in Alzheimer's disease. Brain Commun 2024; 6:fcae198. [PMID: 38978728 PMCID: PMC11227975 DOI: 10.1093/braincomms/fcae198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Revised: 04/27/2024] [Accepted: 06/07/2024] [Indexed: 07/10/2024] Open
Abstract
Alzheimer's disease may be conceptualized as a 'disconnection syndrome', characterized by the breakdown of neural connectivity within the brain as a result of amyloid-beta plaques, tau neurofibrillary tangles and other factors leading to progressive degeneration and shrinkage of neurons, along with synaptic dysfunction. It has been suggested that misfolded tau proteins spread through functional connections (known as 'prion-like' properties of tau). However, the local effect of tau spreading on the synaptic function and communication between regions is not well understood. I aimed to investigate how the spreading of tau aggregates through connections can locally influence functional connectivity. In total, the imaging data of 211 participants including 117 amyloid-beta-negative non-demented and 94 amyloid-beta-positive non-demented participants were recruited from the Alzheimer's Disease Neuroimaging Initiative. Furthermore, normative resting-state functional MRI connectomes were used to model tau spreading through functional connections, and functional MRI of the included participants was used to determine the effect of tau spreading on functional connectivity. I found that lower functional connectivity to tau epicentres is associated with tau spreading through functional connections in both amyloid-beta-negative and amyloid-beta-positive participants. Also, amyloid-beta-PET in tau epicentres mediated the association of tau spreading and functional connectivity to epicentres suggesting a partial mediating effect of amyloid-beta deposition in tau epicentres on the local effect of tau spreading on functional connectivity. My findings provide strong support for the notion that tau spreading through connection is locally associated with disrupted functional connectivity between tau epicentre and non-epicentre regions independent of amyloid-beta pathology. Also, I defined several groups based on the relationship between tau spreading and functional disconnection, which provides quantitative assessment to investigate susceptibility or resilience to functional disconnection related to tau spreading. I showed that amyloid-beta, other copathologies and the apolipoprotein E epsilon 4 allele can be a leading factor towards vulnerability to tau relative functional disconnection.
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Affiliation(s)
- Fardin Nabizadeh
- School of Medicine, Iran University of Medical Sciences, Tehran 441265421414, Iran
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11
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Yao Y, Hasan WZW, Jiao W, Dong X, Ramli HR, Norsahperi NMH, Wen D. ChatGPT and BCI-VR: a new integrated diagnostic and therapeutic perspective for the accurate diagnosis and personalized treatment of mild cognitive impairment. Front Hum Neurosci 2024; 18:1426055. [PMID: 38895167 PMCID: PMC11183516 DOI: 10.3389/fnhum.2024.1426055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Accepted: 05/17/2024] [Indexed: 06/21/2024] Open
Affiliation(s)
- Yiduo Yao
- Department of Electrical and Electronic Engineering, Faculty of Engineering, University Putra Malaysia, Selangor, Malaysia
| | - W. Z. W. Hasan
- Department of Electrical and Electronic Engineering, Faculty of Engineering, University Putra Malaysia, Selangor, Malaysia
| | - Wenlong Jiao
- Brain Computer Intelligence and Intelligent Health Institute, School of Intelligence Science and Technology, University of Science and Technology Beijing, Chengde, China
| | - Xianling Dong
- Hebei International Research Center of Medical Engineering, Chengde Medical University, Hebei, China
| | - H. R. Ramli
- Department of Electrical and Electronic Engineering, Faculty of Engineering, University Putra Malaysia, Selangor, Malaysia
| | - N. M. H. Norsahperi
- Department of Electrical and Electronic Engineering, Faculty of Engineering, University Putra Malaysia, Selangor, Malaysia
| | - Dong Wen
- Brain Computer Intelligence and Intelligent Health Institute, School of Intelligence Science and Technology, University of Science and Technology Beijing, Chengde, China
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12
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García-Colomo A, Nebreda A, Carrasco-Gómez M, de Frutos-Lucas J, Ramirez-Toraño F, Spuch C, Comis-Tuche M, Bruña R, Alfonsín S, Maestú F. Longitudinal changes in the functional connectivity of individuals at risk of Alzheimer's disease. GeroScience 2024; 46:2989-3003. [PMID: 38172488 PMCID: PMC11009204 DOI: 10.1007/s11357-023-01036-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 12/01/2023] [Indexed: 01/05/2024] Open
Abstract
First-degree relatives of Alzheimer's disease patients constitute a key population in the search for early markers. Our group identified functional connectivity differences between cognitively unimpaired individuals with and without a family history. In this unprecedented follow-up study, we examine whether family history is associated with a longitudinal increase in the functional connectivity of those regions. Moreover, this is the first work to correlate electrophysiological measures with plasma p-tau231 levels, a known pathology marker, to interpret the nature of the change. We evaluated 69 cognitively unimpaired individuals with a family history of Alzheimer's disease and 28 without, at two different time points, approximately 3 years apart, including resting state magnetoencephalography recordings and plasma p-tau231 determinations. Functional connectivity changes in both precunei and left anterior cingulate cortex in the high-alpha band were studied using non-parametric cluster-based permutation tests. Connectivity values were correlated with p-tau231 levels. Three clusters emerged in individuals with family history, exhibiting a longitudinal increase of connectivity. Notably, the clusters for both precunei bore a striking resemblance to those found in previous cross-sectional studies. The connectivity values at follow-up and the change in connectivity in the left precuneus cluster showed significant positive correlations with p-tau231. This study consolidates the use of electrophysiology, in combination with plasma biomarkers, to monitor healthy individuals at risk of Alzheimer's disease and emphasizes the value of combining noninvasive markers to understand the underlying mechanisms and track disease progression. This could facilitate the design of more effective intervention strategies and accurate progression assessment tools.
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Affiliation(s)
- Alejandra García-Colomo
- Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, 28223, Madrid, Spain.
- Department of Experimental Psychology, Cognitive Psychology and Speech & Language Therapy, Complutense University of Madrid, 28223, Madrid, Spain.
| | - Alberto Nebreda
- Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, 28223, Madrid, Spain
- Department of Experimental Psychology, Cognitive Psychology and Speech & Language Therapy, Complutense University of Madrid, 28223, Madrid, Spain
| | - Martín Carrasco-Gómez
- Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, 28223, Madrid, Spain.
- Department of Electronic Engineering, Universidad Politécnica de Madrid, 28040, Madrid, Spain.
| | - Jaisalmer de Frutos-Lucas
- Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, 28223, Madrid, Spain
- Department of Experimental Psychology, Cognitive Psychology and Speech & Language Therapy, Complutense University of Madrid, 28223, Madrid, Spain
| | - Federico Ramirez-Toraño
- Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, 28223, Madrid, Spain
- Department of Experimental Psychology, Cognitive Psychology and Speech & Language Therapy, Complutense University of Madrid, 28223, Madrid, Spain
| | - Carlos Spuch
- Translational Neuroscience Research Group, Galicia Sur Health Research Institute (IIS-Galicia Sur), SERGAS-UVIGO, CIBERSAM, Vigo, Spain
| | - María Comis-Tuche
- Translational Neuroscience Research Group, Galicia Sur Health Research Institute (IIS-Galicia Sur), SERGAS-UVIGO, CIBERSAM, Vigo, Spain
| | - Ricardo Bruña
- Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, 28223, Madrid, Spain
- Health Research Institute of the Hospital Clínico San Carlo.s (IdISSC), 28240, Madrid, Spain
- Department of Radiology, Universidad Complutense de Madrid, 28240, Madrid, Spain
| | - Soraya Alfonsín
- Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, 28223, Madrid, Spain
- Department of Experimental Psychology, Cognitive Psychology and Speech & Language Therapy, Complutense University of Madrid, 28223, Madrid, Spain
| | - Fernando Maestú
- Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, 28223, Madrid, Spain
- Department of Experimental Psychology, Cognitive Psychology and Speech & Language Therapy, Complutense University of Madrid, 28223, Madrid, Spain
- Health Research Institute of the Hospital Clínico San Carlo.s (IdISSC), 28240, Madrid, Spain
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13
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Albeely AM, Williams OOF, Blight CR, Thériault RK, Perreault ML. Sex differences in neuronal oscillatory activity and memory in the methylazoxymethanol acetate model of schizophrenia. Schizophr Res 2024; 267:451-461. [PMID: 38643726 DOI: 10.1016/j.schres.2024.04.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 11/28/2023] [Accepted: 04/01/2024] [Indexed: 04/23/2024]
Abstract
The methylazoxymethanol acetate (MAM) rodent model is used to study aspects of schizophrenia. However, numerous studies that have employed this model have used only males, resulting in a dearth of knowledge on sex differences in brain function and behaviour. The purpose of this study was to determine whether differences exist between male and female MAM rats in neuronal oscillatory function within and between the prefrontal cortex (PFC), ventral hippocampus (vHIP) and thalamus, behaviour, and in proteins linked to schizophrenia neuropathology. We showed that female MAM animals exhibited region-specific alterations in theta power, elevated low and high gamma power in all regions, and elevated PFC-thalamus high gamma coherence. Male MAM rats had elevated beta and low gamma power in PFC, and elevated vHIP-thalamus coherence. MAM females displayed impaired reversal learning whereas MAM males showed impairments in spatial memory. Glycogen synthase kinase-3 (GSK-3) was altered in the thalamus, with female MAM rats displaying elevated GSK-3α phosphorylation. Male MAM rats showed higher expression and phosphorylation GSK-3α, and higher expression of GSK-β. Sex-specific changes in phosphorylated Tau levels were observed in a region-specific manner. These findings demonstrate there are notable sex differences in behaviour, oscillatory network function, and GSK-3 signaling in MAM rats, thus highlighting the importance of inclusion of both sexes when using this model to study schizophrenia.
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Affiliation(s)
- Abdalla M Albeely
- Department of Molecular and Cellular Biology, University of Guelph, Ontario, Canada
| | | | - Colin R Blight
- Department of Molecular and Cellular Biology, University of Guelph, Ontario, Canada
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14
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Prabhu P, Morise H, Kudo K, Beagle A, Mizuiri D, Syed F, Kotegar KA, Findlay A, Miller BL, Kramer JH, Rankin KP, Garcia PA, Kirsch HE, Vossel K, Nagarajan SS, Ranasinghe KG. Abnormal gamma phase-amplitude coupling in the parahippocampal cortex is associated with network hyperexcitability in Alzheimer's disease. Brain Commun 2024; 6:fcae121. [PMID: 38665964 PMCID: PMC11043655 DOI: 10.1093/braincomms/fcae121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Revised: 03/08/2024] [Accepted: 04/07/2024] [Indexed: 04/28/2024] Open
Abstract
While animal models of Alzheimer's disease (AD) have shown altered gamma oscillations (∼40 Hz) in local neural circuits, the low signal-to-noise ratio of gamma in the resting human brain precludes its quantification via conventional spectral estimates. Phase-amplitude coupling (PAC) indicating the dynamic integration between the gamma amplitude and the phase of low-frequency (4-12 Hz) oscillations is a useful alternative to capture local gamma activity. In addition, PAC is also an index of neuronal excitability as the phase of low-frequency oscillations that modulate gamma amplitude, effectively regulates the excitability of local neuronal firing. In this study, we sought to examine the local neuronal activity and excitability using gamma PAC, within brain regions vulnerable to early AD pathophysiology-entorhinal cortex and parahippocampus, in a clinical population of patients with AD and age-matched controls. Our clinical cohorts consisted of a well-characterized cohort of AD patients (n = 50; age, 60 ± 8 years) with positive AD biomarkers, and age-matched, cognitively unimpaired controls (n = 35; age, 63 ± 5.8 years). We identified the presence or the absence of epileptiform activity in AD patients (AD patients with epileptiform activity, AD-EPI+, n = 20; AD patients without epileptiform activity, AD-EPI-, n = 30) using long-term electroencephalography (LTM-EEG) and 1-hour long magnetoencephalography (MEG) with simultaneous EEG. Using the source reconstructed MEG data, we computed gamma PAC as the coupling between amplitude of the gamma frequency (30-40 Hz) with phase of the theta (4-8 Hz) and alpha (8-12 Hz) frequency oscillations, within entorhinal and parahippocampal cortices. We found that patients with AD have reduced gamma PAC in the left parahippocampal cortex, compared to age-matched controls. Furthermore, AD-EPI+ patients showed greater reductions in gamma PAC than AD-EPI- in bilateral parahippocampal cortices. In contrast, entorhinal cortices did not show gamma PAC abnormalities in patients with AD. Our findings demonstrate the spatial patterns of altered gamma oscillations indicating possible region-specific manifestations of network hyperexcitability within medial temporal lobe regions vulnerable to AD pathophysiology. Greater deficits in AD-EPI+ suggests that reduced gamma PAC is a sensitive index of network hyperexcitability in AD patients. Collectively, the current results emphasize the importance of investigating the role of neural circuit hyperexcitability in early AD pathophysiology and explore its potential as a modifiable contributor to AD pathobiology.
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Affiliation(s)
- Pooja Prabhu
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
- Department of Data science and Computer Applications, Manipal Institute of Technology, Manipal 576104, India
| | - Hirofumi Morise
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
- Medical Imaging Business Center, Ricoh Company Ltd., Kanazawa 920-0177, Japan
| | - Kiwamu Kudo
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
- Medical Imaging Business Center, Ricoh Company Ltd., Kanazawa 920-0177, Japan
| | - Alexander Beagle
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA 94158, USA
| | - Danielle Mizuiri
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | - Faatimah Syed
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA 94158, USA
| | - Karunakar A Kotegar
- Department of Data science and Computer Applications, Manipal Institute of Technology, Manipal 576104, India
| | - Anne Findlay
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | - Bruce L Miller
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA 94158, USA
| | - Joel H Kramer
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA 94158, USA
| | - Katherine P Rankin
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA 94158, USA
| | - Paul A Garcia
- Epilepsy Center, Department of Neurology, University of California San Francisco, San Francisco, CA 94158, USA
| | - Heidi E Kirsch
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
- Epilepsy Center, Department of Neurology, University of California San Francisco, San Francisco, CA 94158, USA
| | - Keith Vossel
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA 94158, USA
- Mary S. Easton Center for Alzheimer’s Research and Care, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Srikantan S Nagarajan
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | - Kamalini G Ranasinghe
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA 94158, USA
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15
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Mousa D, Zayed N, Yassine IA. Correlation transfer function analysis as a biomarker for Alzheimer brain plasticity using longitudinal resting-state fMRI data. Sci Rep 2023; 13:21559. [PMID: 38057476 PMCID: PMC10700324 DOI: 10.1038/s41598-023-48693-2] [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] [Received: 03/26/2023] [Accepted: 11/29/2023] [Indexed: 12/08/2023] Open
Abstract
Neural plasticity is the ability of the brain to alter itself functionally and structurally as a result of its experience. However, longitudinal changes in functional connectivity of the brain are still unrevealed in Alzheimer's disease (AD). This study aims to discover the significant connections (SCs) between brain regions for AD stages longitudinally using correlation transfer function (CorrTF) as a new biomarker for the disease progression. The dataset consists of: 29 normal controls (NC), and 23, 24, and 23 for early, late mild cognitive impairments (EMCI, LMCI), and ADs, respectively, along three distant visits. The brain was divided into 116 regions using the automated anatomical labeling atlas, where the intensity time series is calculated, and the CorrTF connections are extracted for each region. Finally, the standard t-test and ANOVA test were employed to investigate the SCs for each subject's visit. No SCs, along three visits, were found For NC subjects. The most SCs were mainly directed from cerebellum in case of EMCI and LMCI. Furthermore, the hippocampus connectivity increased in LMCI compared to EMCI whereas missed in AD. Additionally, the patterns of longitudinal changes among the different AD stages compared to Pearson Correlation were similar, for SMC, VC, DMN, and Cereb networks, while differed for EAN and SN networks. Our findings define how brain changes over time, which could help detect functional changes linked to each AD stage and better understand the disease behavior.
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Affiliation(s)
- Doaa Mousa
- Computers and Systems Department, Electronics Research Institute, Cairo, Egypt.
| | - Nourhan Zayed
- Computers and Systems Department, Electronics Research Institute, Cairo, Egypt
- Mechanical Engineering Department, The British University in Egypt, Cairo, Egypt
| | - Inas A Yassine
- Systems and Biomedical Engineering Department, Cairo University, Giza, Egypt
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16
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Chino B, Torres-Simón L, Żelwetro A, Rodríguez-Rojo IC, Carnes-Vendrell A, Piñol-Ripoll G, Yubero R, Paúl N, Maestú F. Understanding the Episodic Memory and Executive Functioning Axis Impairment in MCI Patients: A Multicenter Study in Comparison with CSF Biomarkers. Biomedicines 2023; 11:3147. [PMID: 38137368 PMCID: PMC10741228 DOI: 10.3390/biomedicines11123147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 11/06/2023] [Accepted: 11/22/2023] [Indexed: 12/24/2023] Open
Abstract
BACKGROUND This study aimed to explore the association between a verbal learning task that evaluates the potential mutual dependency between memory and executive functions (i.e., the Test of Memory Strategies, TMS) and cerebrospinal fluid (CSF) Alzheimer's Disease (AD) biomarkers. METHODS A sample of 47 mild cognitive impairment (MCI) participants from Poland and Spain were classified according to the Erlangen Score Diagnostic Algorithm (ESA) into CSF- (n = 16) and CSF+ (n = 31) groups. Correlation analyses between TMS word-list conditions and CSF biomarkers were conducted. Additionally, an analysis of covariance was performed to define the effect on ESA classification in the sample, using as a covariable the country of origin of the participants. RESULTS Significant associations between the TMS-3 condition and Aβ42, t-tau, and p-tau were observed for the whole sample. In addition, the CSF- participants obtained higher cognitive performance in TMS-3 compared to the CSF+ group. This outcome persisted if the groups were based on Aβ42 scores, but not t-tau or p-tau values. CONCLUSIONS These findings could indicate that poor performance on verbal learning tests may be affected by executive dysfunctions. Therefore, future intervention plans focused on training executive functions would be of interest to improve the ability of MCI patients to encode and organize information.
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Affiliation(s)
- Brenda Chino
- Institute of Neuroscience, Autonomous University of Barcelona (UAB), 08193 Barcelona, Spain;
- Center for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, 28040 Madrid, Spain; (L.T.-S.); (F.M.)
| | - Lucía Torres-Simón
- Center for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, 28040 Madrid, Spain; (L.T.-S.); (F.M.)
- Department of Experimental Psychology, Cognitive Processes and Speech Therapy, Universidad Complutense de Madrid, 28040 Madrid, Spain;
| | - Agnieszka Żelwetro
- Interdisciplinary Doctoral School, SWPS University of Social Sciences and Humanities, 53-238 Wrocław, Poland;
- Alzheimer’s Disease Research, Center in Ścinawa, 59-330 Ścinawa, Poland
| | - Inmaculada Concepción Rodríguez-Rojo
- Center for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, 28040 Madrid, Spain; (L.T.-S.); (F.M.)
- Department of Nursing and Physiotherapy, Faculty of Medicine and Health Sciences, Universidad de Alcalá, 28801 Madrid, Spain
| | - Anna Carnes-Vendrell
- Unitat de Trastorns Cognitius, Cognition and Behavior Study Group, Universitat de Lleida, IRBLleida, 25198 Lleida, Spain; (A.C.-V.); (G.P.-R.)
| | - Gerard Piñol-Ripoll
- Unitat de Trastorns Cognitius, Cognition and Behavior Study Group, Universitat de Lleida, IRBLleida, 25198 Lleida, Spain; (A.C.-V.); (G.P.-R.)
| | - Raquel Yubero
- Neurology Department, Hospital Quirónsalud Madrid, 28223 Madrid, Spain;
| | - Nuria Paúl
- Department of Experimental Psychology, Cognitive Processes and Speech Therapy, Universidad Complutense de Madrid, 28040 Madrid, Spain;
| | - Fernando Maestú
- Center for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, 28040 Madrid, Spain; (L.T.-S.); (F.M.)
- Department of Experimental Psychology, Cognitive Processes and Speech Therapy, Universidad Complutense de Madrid, 28040 Madrid, Spain;
- Instituto de Investigación del Hospital Clínico San Carlos, 28040 Madrid, Spain
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17
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Bitra VR, Challa SR, Adiukwu PC, Rapaka D. Tau trajectory in Alzheimer's disease: Evidence from the connectome-based computational models. Brain Res Bull 2023; 203:110777. [PMID: 37813312 DOI: 10.1016/j.brainresbull.2023.110777] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 07/08/2023] [Accepted: 10/06/2023] [Indexed: 10/11/2023]
Abstract
Alzheimer's disease (AD) is a progressive neurodegenerative disorder with an impairment of cognition and memory. Current research on connectomics have now related changes in the network organization in AD to the patterns of accumulation and spread of amyloid and tau, providing insights into the neurobiological mechanisms of the disease. In addition, network analysis and modeling focus on particular use of graphs to provide intuition into key organizational principles of brain structure, that stipulate how neural activity propagates along structural connections. The utility of connectome-based computational models aids in early predicting, tracking the progression of biomarker-directed AD neuropathology. In this article, we present a short review of tau trajectory, the connectome changes in tau pathology, and the dependent recent connectome-based computational modelling approaches for tau spreading, reproducing pragmatic findings, and developing significant novel tau targeted therapies.
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Affiliation(s)
- Veera Raghavulu Bitra
- School of Pharmacy, Faculty of Health Sciences, University of Botswana, P/Bag-0022, Gaborone, Botswana.
| | - Siva Reddy Challa
- Department of Cancer Biology and Pharmacology, University of Illinois College of Medicine, Peoria, IL 61614, USA; KVSR Siddartha College of Pharmaceutical Sciences, Vijayawada, Andhra Pradesh, India
| | - Paul C Adiukwu
- School of Pharmacy, Faculty of Health Sciences, University of Botswana, P/Bag-0022, Gaborone, Botswana
| | - Deepthi Rapaka
- Pharmacology Division, D.D.T. College of Medicine, Gaborone, Botswana.
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18
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Hirota Y, Sakakibara Y, Takei K, Nishijima R, Sekiya M, Iijima KM. Alzheimer's Disease-Related Phospho-Tau181 Signals Are Localized to Demyelinated Axons of Parvalbumin-Positive GABAergic Interneurons in an App Knock-In Mouse Model of Amyloid-β Pathology. J Alzheimers Dis 2023:JAD230121. [PMID: 37212118 DOI: 10.3233/jad-230121] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/23/2023]
Abstract
BACKGROUND The tau protein phosphorylated at Thr181 (p-tau181) in cerebrospinal fluid and blood is a sensitive biomarker for Alzheimer's disease (AD). Increased p-tau181 levels correlate well with amyloid-β (Aβ) pathology and precede neurofibrillary tangle formation in the early stage of AD; however, the relationship between p-tau181 and Aβ-mediated pathology is less well understood. We recently reported that p-tau181 represents axonal abnormalities in mice with Aβ pathology (AppNLGF). However, from which neuronal subtype(s) these p-tau181-positive axons originate remains elusive. OBJECTIVE The main purpose of this study is to differentiate neuronal subtype(s) and elucidate damage associated with p-tau181-positive axons by immunohistochemical analysis of AppNLGF mice brains. METHODS Colocalization between p-tau181 and (1) unmyelinated axons positive for vesicular acetylcholine transporter or norepinephrine transporter and (2) myelinated axons positive for vesicular glutamate transporter, vesicular GABA transporter, or parvalbumin in the brains of 24-month-old AppNLGF and control mice without Aβ pathology were analyzed. The density of these axons was also compared. RESULTS Unmyelinated axons of cholinergic or noradrenergic neurons did not overlap with p-tau181. By contrast, p-tau181 signals colocalized with myelinated axons of parvalbumin-positive GABAergic interneurons but not of glutamatergic neurons. Interestingly, the density of unmyelinated axons was significantly decreased in AppNLGF mice, whereas that of glutamatergic, GABAergic, or p-tau181-positive axons was less affected. Instead, myelin sheaths surrounding p-tau181-positive axons were significantly reduced in AppNLGF mice. CONCLUSION This study demonstrates that p-tau181 signals colocalize with axons of parvalbumin-positive GABAergic interneurons with disrupted myelin sheaths in the brains of a mouse model of Aβ pathology.
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Affiliation(s)
- Yu Hirota
- Department of Neurogenetics, Center for Development of Advanced Medicine for Dementia, National Center for Geriatrics and Gerontology, Obu, Aichi, Japan
- Japan Society for the Promotion of Science, Chiyoda-ku, Tokyo, Japan
| | - Yasufumi Sakakibara
- Department of Neurogenetics, Center for Development of Advanced Medicine for Dementia, National Center for Geriatrics and Gerontology, Obu, Aichi, Japan
| | - Kimi Takei
- Department of Neurogenetics, Center for Development of Advanced Medicine for Dementia, National Center for Geriatrics and Gerontology, Obu, Aichi, Japan
| | - Risa Nishijima
- Department of Neurogenetics, Center for Development of Advanced Medicine for Dementia, National Center for Geriatrics and Gerontology, Obu, Aichi, Japan
| | - Michiko Sekiya
- Department of Neurogenetics, Center for Development of Advanced Medicine for Dementia, National Center for Geriatrics and Gerontology, Obu, Aichi, Japan
- Department of Experimental Gerontology, Graduate School of Pharmaceutical Sciences, Nagoya City University, Nagoya, Japan
| | - Koichi M Iijima
- Department of Neurogenetics, Center for Development of Advanced Medicine for Dementia, National Center for Geriatrics and Gerontology, Obu, Aichi, Japan
- Department of Experimental Gerontology, Graduate School of Pharmaceutical Sciences, Nagoya City University, Nagoya, Japan
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19
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Gowik JK, Goelz C, Vieluf S, van den Bongard F, Reinsberger C. Source connectivity patterns in the default mode network differ between elderly golf-novices and non-golfers. Sci Rep 2023; 13:6215. [PMID: 37069191 PMCID: PMC10110620 DOI: 10.1038/s41598-023-31893-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Accepted: 03/20/2023] [Indexed: 04/19/2023] Open
Abstract
Learning to play golf has high demands on attention and therefore may counteract age-related changes of functional brain networks. This cross-sectional study compared source connectivity in the Default Mode Network (DMN) between elderly golf novices and non-golfers. Four-minute resting-state electroencephalography (128 channels) from 22 elderly people (mean age 67 ± 4.3 years, 55% females) were recorded after completing a 22-week golf learning program or after having continued with normal life. Source connectivity was assessed after co-registration of EEG data with native MRI within pre-defined portions of the DMN in the beta band (14-25 Hz). Non-golfers had significantly higher source connectivity values in the anterior DMN compared to non-golfers. Exploratory correlation analyses did not indicate an association to cognitive performance in either group. Inverse correlations between a marker of external attention with source connectivity of the anterior DMN may suggest a trend in the golf group only, but have to be replicated in future studies. Clinical relevance of these findings remains to be elucidated, but the observed difference in the anterior DMN may provide a starting point to further investigate if and how learning golf may have an impact on physiological age-related cognitive changes.
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Affiliation(s)
- J K Gowik
- Department of Exercise and Health, Institute of Sports Medicine, Paderborn University, Warburger Straße 100, 33098, Paderborn, Germany
| | - C Goelz
- Department of Exercise and Health, Institute of Sports Medicine, Paderborn University, Warburger Straße 100, 33098, Paderborn, Germany
| | - S Vieluf
- Department of Exercise and Health, Institute of Sports Medicine, Paderborn University, Warburger Straße 100, 33098, Paderborn, Germany
| | - F van den Bongard
- Department of Exercise and Health, Institute of Sports Medicine, Paderborn University, Warburger Straße 100, 33098, Paderborn, Germany
| | - C Reinsberger
- Department of Exercise and Health, Institute of Sports Medicine, Paderborn University, Warburger Straße 100, 33098, Paderborn, Germany.
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20
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Chow TE, Veziris CR, Mundada N, Martinez-Arroyo AI, Kramer JH, Miller BL, Rosen HJ, Gorno-Tempini ML, Rankin KP, Seeley WW, Rabinovici GD, La Joie R, Sturm VE. Medial Temporal Lobe Tau Aggregation Relates to Divergent Cognitive and Emotional Empathy Abilities in Alzheimer's Disease. J Alzheimers Dis 2023; 96:313-328. [PMID: 37742643 PMCID: PMC10894587 DOI: 10.3233/jad-230367] [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] [Accepted: 08/22/2023] [Indexed: 09/26/2023]
Abstract
BACKGROUND In Alzheimer's disease (AD), the gradual accumulation of amyloid-β (Aβ) and tau proteins may underlie alterations in empathy. OBJECTIVE To assess whether tau aggregation in the medial temporal lobes related to differences in cognitive empathy (the ability to take others' perspectives) and emotional empathy (the ability to experience others' feelings) in AD. METHODS Older adults (n = 105) completed molecular Aβ positron emission tomography (PET) scans. Sixty-eight of the participants (35 women) were Aβ positive and symptomatic with diagnoses of mild cognitive impairment, dementia of the Alzheimer's type, logopenic variant primary progressive aphasia, or posterior cortical atrophy. The remaining 37 (22 women) were asymptomatic Aβ negative healthy older controls. Using the Interpersonal Reactivity Index, we compared current levels of informant-rated cognitive empathy (Perspective-Taking subscale) and emotional empathy (Empathic Concern subscale) in the Aβ positive and negative participants. The Aβ positive participants also underwent molecular tau-PET scans, which were used to investigate whether regional tau burden in the bilateral medial temporal lobes related to empathy. RESULTS Aβ positive participants had lower perspective-taking and higher empathic concern than Aβ negative healthy controls. Medial temporal tau aggregation in the Aβ positive participants had divergent associations with cognitive and emotional empathy. Whereas greater tau burden in the amygdala predicted lower perspective-taking, greater tau burden in the entorhinal cortex predicted greater empathic concern. Tau burden in the parahippocampal cortex did not predict either form of empathy. CONCLUSIONS Across AD clinical syndromes, medial temporal lobe tau aggregation is associated with lower perspective-taking yet higher empathic concern.
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Affiliation(s)
- Tiffany E. Chow
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Christina R. Veziris
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Nidhi Mundada
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Alexis I. Martinez-Arroyo
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Joel H. Kramer
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Bruce L. Miller
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Howard J. Rosen
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Maria Luisa Gorno-Tempini
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Katherine P. Rankin
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - William W. Seeley
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
- Department of Pathology, University of California, San Francisco, CA, USA
| | - Gil D. Rabinovici
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Virginia E. Sturm
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
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21
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Caravaglios G, Muscoso EG, Blandino V, Di Maria G, Gangitano M, Graziano F, Guajana F, Piccoli T. EEG Resting-State Functional Networks in Amnestic Mild Cognitive Impairment. Clin EEG Neurosci 2023; 54:36-50. [PMID: 35758261 DOI: 10.1177/15500594221110036] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Background. Alzheimer's cognitive-behavioral syndrome is the result of impaired connectivity between nerve cells, due to misfolded proteins, which accumulate and disrupt specific brain networks. Electroencephalography, because of its excellent temporal resolution, is an optimal approach for assessing the communication between functionally related brain regions. Objective. To detect and compare EEG resting-state networks (RSNs) in patients with amnesic mild cognitive impairment (aMCI), and healthy elderly (HE). Methods. We recruited 125 aMCI patients and 70 healthy elderly subjects. One hundred and twenty seconds of artifact-free EEG data were selected and compared between patients with aMCI and HE. We applied standard low-resolution brain electromagnetic tomography (sLORETA)-independent component analysis (ICA) to assess resting-state networks. Each network consisted of a set of images, one for each frequency (delta, theta, alpha1/2, beta1/2). Results. The functional ICA analysis revealed 17 networks common to groups. The statistical procedure demonstrated that aMCI used some networks differently than HE. The most relevant findings were as follows. Amnesic-MCI had: i) increased delta/beta activity in the superior frontal gyrus and decreased alpha1 activity in the paracentral lobule (ie, default mode network); ii) greater delta/theta/alpha/beta in the superior frontal gyrus (i.e, attention network); iii) lower alpha in the left superior parietal lobe, as well as a lower delta/theta and beta, respectively in post-central, and in superior frontal gyrus(ie, attention network). Conclusions. Our study confirms sLORETA-ICA method is effective in detecting functional resting-state networks, as well as between-groups connectivity differences. The findings provide support to the Alzheimer's network disconnection hypothesis.
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Affiliation(s)
- G Caravaglios
- U.O.C. Neurologia, A.O. Cannizzaro per l'emergenza, Catania, Italy
| | - E G Muscoso
- U.O.C. Neurologia, A.O. Cannizzaro per l'emergenza, Catania, Italy
| | - V Blandino
- Department of Biomedicine, Neuroscience and Advanced Diagnostics (Bi.N.D.), 18998University of Palermo, Palermo, Italy
| | - G Di Maria
- U.O.C. Neurologia, A.O. Cannizzaro per l'emergenza, Catania, Italy
| | - M Gangitano
- Department of Biomedicine, Neuroscience and Advanced Diagnostics (Bi.N.D.), 18998University of Palermo, Palermo, Italy
| | - F Graziano
- U.O.C. Neurologia, A.O. Cannizzaro per l'emergenza, Catania, Italy
| | - F Guajana
- U.O.C. Neurologia, A.O. Cannizzaro per l'emergenza, Catania, Italy
| | - T Piccoli
- Department of Biomedicine, Neuroscience and Advanced Diagnostics (Bi.N.D.), 18998University of Palermo, Palermo, Italy
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22
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Maldjian JA, Lee R, Jordan J, Davenport EM, Proskovec AL, Wintermark M, Stufflebeam S, Anderson J, Mukherjee P, Nagarajan SS, Ferrari P, Gaetz W, Schwartz E, Roberts TPL. ACR White Paper on Magnetoencephalography and Magnetic Source Imaging: A Report from the ACR Commission on Neuroradiology. AJNR Am J Neuroradiol 2022; 43:E46-E53. [PMID: 36456085 DOI: 10.3174/ajnr.a7714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Accepted: 10/04/2022] [Indexed: 12/04/2022]
Abstract
Magnetoencephalography, the extracranial detection of tiny magnetic fields emanating from intracranial electrical activity of neurons, and its source modeling relation, magnetic source imaging, represent a powerful functional neuroimaging technique, able to detect and localize both spontaneous and evoked activity of the brain in health and disease. Recent years have seen an increased utilization of this technique for both clinical practice and research, in the United States and worldwide. This report summarizes current thinking, presents recommendations for clinical implementation, and offers an outlook for emerging new clinical indications.
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Affiliation(s)
- J A Maldjian
- From the Advanced Neuroscience Imaging Research Laboratory (J.A.M., E.M.D., A.L.P.) .,MEG Center of Excellence (J.A.M., E.M.D., A.L.P.).,Department of Radiology (J.A.M., E.M.D., A.L.P.), University of Texas Southwestern Medical Center, Dallas, Texas
| | - R Lee
- Department of Neuroradiology (R.L.), University of California San Diego, San Diego, California
| | - J Jordan
- ACR Commission on Neuroradiology (J.J.), American College of Radiology, Reston, Virginia.,Stanford University School of Medicine (J.J.), Stanford, California
| | - E M Davenport
- From the Advanced Neuroscience Imaging Research Laboratory (J.A.M., E.M.D., A.L.P.).,MEG Center of Excellence (J.A.M., E.M.D., A.L.P.).,Department of Radiology (J.A.M., E.M.D., A.L.P.), University of Texas Southwestern Medical Center, Dallas, Texas
| | - A L Proskovec
- From the Advanced Neuroscience Imaging Research Laboratory (J.A.M., E.M.D., A.L.P.).,MEG Center of Excellence (J.A.M., E.M.D., A.L.P.).,Department of Radiology (J.A.M., E.M.D., A.L.P.), University of Texas Southwestern Medical Center, Dallas, Texas
| | - M Wintermark
- Department of Neuroradiology (M.W.), University of Texas MD Anderson Center, Houston, Texas
| | - S Stufflebeam
- Athinoula A. Martinos Center for Biomedical Imaging (S.S.), Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts
| | - J Anderson
- Department of Radiology and Imaging Sciences (J.A.), University of Utah School of Medicine, Salt Lake City, Utah
| | - P Mukherjee
- Department of Radiology and Biomedical Imaging (P.M., S.S.N.), University of California, San Francisco, San Francisco, California
| | - S S Nagarajan
- Department of Radiology and Biomedical Imaging (P.M., S.S.N.), University of California, San Francisco, San Francisco, California
| | - P Ferrari
- Pediatric Neurosciences (P.F.), Helen DeVos Children's Hospital, Grand Rapids, Michigan.,Department of Pediatrics and Human Development (P.F.), College of Human Medicine, Michigan State University, Grand Rapids, Michigan
| | - W Gaetz
- Department of Radiology (W.G., E.S., T.P.L.R.), Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
| | - E Schwartz
- Department of Radiology (W.G., E.S., T.P.L.R.), Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
| | - T P L Roberts
- Department of Radiology (W.G., E.S., T.P.L.R.), Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
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23
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Xiong Y, Ye C, Chen Y, Zhong X, Chen H, Sun R, Zhang J, Zhong Z, Huang M. Altered Functional Connectivity of Basal Ganglia in Mild Cognitive Impairment and Alzheimer's Disease. Brain Sci 2022; 12:1555. [PMID: 36421879 PMCID: PMC9688931 DOI: 10.3390/brainsci12111555] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Revised: 11/04/2022] [Accepted: 11/12/2022] [Indexed: 06/28/2024] Open
Abstract
(1) Background: Alzheimer's disease (AD), an age-progressive neurodegenerative disease that affects cognitive function, causes changes in the functional connectivity of the default-mode network (DMN). However, the question of whether AD-related changes occur in the functional connectivity of the basal ganglia has rarely been specifically analyzed. This study aimed to measure the changes in basal ganglia functional connectivity among patients with AD and mild cognitive impairment (MCI) in their resting state using the functional connectivity density (FCD) value, the functional connectivity (FC) intensity, and the graph theory index, and to confirm their influence on clinical manifestations. (2) Methods: Resting-state functional MRI (rs-fMRI) and neuropsychological data from 48 participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) were used for analyses. The 48 ADNI participants comprised 16 patients with AD, 16 patients with MCI, and 16 normal controls (NCs). The functional connectivity of basal ganglia was evaluated by FCDs, FC strength, and graph theory index. We compared voxel-based FCD values between groups to show specific regions with significant variation and significant connectivity from ROI conduction to ROI analysis. Pearson's correlation analyses between functional connectivity and several simultaneous clinical variables were also conducted. Additionally, receiver operating characteristic (ROC) analyses associated with classification were conducted for both FCD values and graph theory indices. (3) Results: The level of FCD in patients with cognitive impairment showed obvious abnormalities (including short-range and long-range FCD). In addition to DMN-related regions, aberrant functional connectivity was also found to be present in the basal ganglia, especially in the caudate and amygdala. The FCD values of the basal ganglia (involving the caudate and amygdala) were closely related to scores from the Mini-Mental State Examination (MMSE) and the Functional Activities Questionnaire (FAQ); meanwhile, the graph theory indices (involving global efficiency and degree) of the basal ganglia (involving the caudate, amygdala, and putamen) were also found to be closely correlated with MMSE scores. In ROC analyses of both FCD and graph theory, the amygdala was of the utmost importance in the early-stage detection of MCI; additionally, the caudate nucleus was found to be crucial in the progression of cognitive decline and AD diagnosis. (4) Conclusions: It was systematically confirmed that there is a phenomenon of change in the functional connections in the basal ganglia during cognitive decline. The findings of this study could improve our understanding of AD and MCI pathology in the basal ganglia and make it possible to propose new targets for AD treatment in further studies.
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Affiliation(s)
- Yu Xiong
- Department of Neurology, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen 518107, China
| | - Chenghui Ye
- Department of Neurology, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen 518107, China
| | - Ying Chen
- Department of Neurology, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen 518107, China
| | - Xiaochun Zhong
- Department of Neurology, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen 518107, China
| | - Hongda Chen
- Department of Traditional Chinese Medicine, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen 518107, China
| | - Ruxin Sun
- Department of Neurology, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen 518107, China
| | - Jiaqi Zhang
- Department of Neurology, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen 518107, China
| | - Zhanhua Zhong
- Department of Neurology, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen 518107, China
| | - Min Huang
- Department of Neurology, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen 518107, China
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24
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Cheron G, Ristori D, Marquez-Ruiz J, Cebolla AM, Ris L. Electrophysiological alterations of the Purkinje cells and deep cerebellar neurons in a mouse model of Alzheimer disease (electrophysiology on cerebellum of AD mice). Eur J Neurosci 2022; 56:5547-5563. [PMID: 35141975 DOI: 10.1111/ejn.15621] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Revised: 12/16/2021] [Accepted: 12/19/2021] [Indexed: 12/14/2022]
Abstract
Alzheimer's disease is histopathologically well defined by the presence of amyloid deposits and tau-related neurofibrillary tangles in crucial regions of the brain. Interest is growing in revealing and determining possible pathological markers also in the cerebellum as its involvement in cognitive functions is now well supported. Despite the central position of the Purkinje cell in the cerebellum, its electrophysiological behaviour in mouse models of Alzheimer's disease is scarce in the literature. Our first aim was here to focus on the electrophysiological behaviour of the cerebellum in awake mouse model of Alzheimer's disease (APPswe/PSEN1dE9) and the related performance on the water-maze test classically used in behavioural studies. We found prevalent signs of electrophysiological alterations in both Purkinje cells and deep cerebellar nuclei neurons which might explain the behavioural deficits reported during the water-maze test. The alterations of neurons firing were accompanied by a dual (~16 and ~228 Hz) local field potential's oscillation in the Purkinje cell layer of Alzheimer's disease mice which was concomitant to an important increase of both the simple and the complex spikes. In addition, β-amyloid deposits were present in the molecular layer of the cerebellum. These results highlight the importance of the output firing modification of the AD cerebellum that may indirectly impact the activity of its subcortical and cortical targets.
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Affiliation(s)
- Guy Cheron
- Laboratory of Neurophysiology and Movement Biomechanics, Université Libre de Bruxelles, Brussels, Belgium.,ULB Neuroscience Institut, Université Libre de Bruxelles, Brussels, Belgium.,Laboratory of Neuroscience, Université de Mons, Mons, Belgium
| | - Dominique Ristori
- Laboratory of Neurophysiology and Movement Biomechanics, Université Libre de Bruxelles, Brussels, Belgium
| | - Javier Marquez-Ruiz
- Department of Physiology, Anatomy and Cell Biology, Pablo de Olavide University, Seville, Spain
| | - Anna-Maria Cebolla
- Laboratory of Neurophysiology and Movement Biomechanics, Université Libre de Bruxelles, Brussels, Belgium
| | - Laurence Ris
- Laboratory of Neuroscience, Université de Mons, Mons, Belgium.,UMONS Research Institut for health and technology, Université de Mons, Mons, Belgium
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25
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Chino B, Cuesta P, Pacios J, de Frutos-Lucas J, Torres-Simón L, Doval S, Marcos A, Bruña R, Maestú F. Episodic memory dysfunction and hypersynchrony in brain functional networks in cognitively intact subjects and MCI: a study of 379 individuals. GeroScience 2022; 45:477-489. [PMID: 36109436 PMCID: PMC9886758 DOI: 10.1007/s11357-022-00656-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Accepted: 09/01/2022] [Indexed: 02/03/2023] Open
Abstract
Delayed recall (DR) impairment is one of the most significant predictive factors in defining the progression to Alzheimer's disease (AD). Changes in brain functional connectivity (FC) could accompany this decline in the DR performance even in a resting state condition from the preclinical stages to the diagnosis of AD itself, so the characterization of the relationship between the two phenomena has attracted increasing interest. Another aspect to contemplate is the potential moderator role of the APOE genotype in this association, considering the evidence about their implication for the disease. 379 subjects (118 mild cognitive impairment (MCI) and 261 cognitively intact (CI) individuals) underwent an extensive evaluation, including MEG recording. Applying cluster-based permutation test, we identified a cluster of differences in FC and studied which connections drove such an effect in DR. The moderation effect of APOE genotype between FC results and delayed recall was evaluated too. Higher FC in beta band in the right occipital region is associated with lower DR scores in both groups. A significant anteroposterior link emerged in the seed-based analysis with higher values in MCI. Moreover, APOE genotype appeared as a moderator between beta FC and DR performance only in the CI group. An increased beta FC in the anteroposterior brain region appears to be associated with lower memory performance in MCI. This finding could help discriminate the pattern of the progression of healthy aging to MCI and the relation between resting state and memory performance.
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Affiliation(s)
- Brenda Chino
- Institute of Neuroscience, Autonomous University of Barcelona, Barcelona, Spain. .,Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, Madrid, Spain.
| | - Pablo Cuesta
- Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, Madrid, Spain ,Department of Radiology, Rehabilitation, and Physiotherapy, Complutense University of Madrid, Madrid, Spain ,Instituto de Investigación Sanitaria San Carlos (IdISSC), Madrid, Spain
| | - Javier Pacios
- Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, Madrid, Spain ,Instituto de Investigación Sanitaria San Carlos (IdISSC), Madrid, Spain ,Department of Experimental Psychology, Complutense University of Madrid, Madrid, Spain
| | - Jaisalmer de Frutos-Lucas
- Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, Madrid, Spain ,Department of Experimental Psychology, Complutense University of Madrid, Madrid, Spain ,Centre for Precision Health, Edith Cowan University, Joondalup, WA 6027 Australia ,Centro de Investigación Nebrija en Cognición (CINC), Universidad de Nebrija, Madrid, Spain
| | - Lucía Torres-Simón
- Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, Madrid, Spain ,Department of Experimental Psychology, Complutense University of Madrid, Madrid, Spain
| | - Sandra Doval
- Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, Madrid, Spain ,Department of Experimental Psychology, Complutense University of Madrid, Madrid, Spain
| | - Alberto Marcos
- Instituto de Investigación Sanitaria San Carlos (IdISSC), Madrid, Spain ,Neurology Department, Hospital Clinico San Carlos, Madrid, Spain
| | - Ricardo Bruña
- Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, Madrid, Spain ,Department of Radiology, Rehabilitation, and Physiotherapy, Complutense University of Madrid, Madrid, Spain ,Instituto de Investigación Sanitaria San Carlos (IdISSC), Madrid, Spain
| | - Fernando Maestú
- Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, Madrid, Spain ,Instituto de Investigación Sanitaria San Carlos (IdISSC), Madrid, Spain ,Department of Experimental Psychology, Complutense University of Madrid, Madrid, Spain
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26
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Wiesman AI, Murman DL, Losh RA, Schantell M, Christopher-Hayes NJ, Johnson HJ, Willett MP, Wolfson SL, Losh KL, Johnson CM, May PE, Wilson TW. Spatially resolved neural slowing predicts impairment and amyloid burden in Alzheimer's disease. Brain 2022; 145:2177-2189. [PMID: 35088842 PMCID: PMC9246709 DOI: 10.1093/brain/awab430] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 10/05/2021] [Accepted: 10/24/2021] [Indexed: 11/28/2022] Open
Abstract
An extensive electrophysiological literature has proposed a pathological 'slowing' of neuronal activity in patients on the Alzheimer's disease spectrum. Supported by numerous studies reporting increases in low-frequency and decreases in high-frequency neural oscillations, this pattern has been suggested as a stable biomarker with potential clinical utility. However, no spatially resolved metric of such slowing exists, stymieing efforts to understand its relation to proteinopathy and clinical outcomes. Further, the assumption that this slowing is occurring in spatially overlapping populations of neurons has not been empirically validated. In the current study, we collected cross-sectional resting state measures of neuronal activity using magnetoencephalography from 38 biomarker-confirmed patients on the Alzheimer's disease spectrum and 20 cognitively normal biomarker-negative older adults. From these data, we compute and validate a new metric of spatially resolved oscillatory deviations from healthy ageing for each patient on the Alzheimer's disease spectrum. Using this Pathological Oscillatory Slowing Index, we show that patients on the Alzheimer's disease spectrum exhibit robust neuronal slowing across a network of temporal, parietal, cerebellar and prefrontal cortices. This slowing effect is shown to be directly relevant to clinical outcomes, as oscillatory slowing in temporal and parietal cortices significantly predicted both general (i.e. Montreal Cognitive Assessment scores) and domain-specific (i.e. attention, language and processing speed) cognitive function. Further, regional amyloid-β accumulation, as measured by quantitative 18F florbetapir PET, robustly predicted the magnitude of this pathological neural slowing effect, and the strength of this relationship between amyloid-β burden and neural slowing also predicted attentional impairments across patients. These findings provide empirical support for a spatially overlapping effect of oscillatory neural slowing in biomarker-confirmed patients on the Alzheimer's disease spectrum, and link this effect to both regional proteinopathy and cognitive outcomes in a spatially resolved manner. The Pathological Oscillatory Slowing Index also represents a novel metric that is of potentially high utility across a number of clinical neuroimaging applications, as oscillatory slowing has also been extensively documented in other patient populations, most notably Parkinson's disease, with divergent spectral and spatial features.
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Affiliation(s)
- Alex I Wiesman
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
- Department of Neurological Sciences, University of Nebraska Medical Center (UNMC), Omaha, NE, USA
| | - Daniel L Murman
- Department of Neurological Sciences, University of Nebraska Medical Center (UNMC), Omaha, NE, USA
- Memory Disorders & Behavioral Neurology Program, UNMC, Omaha, NE, USA
| | - Rebecca A Losh
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
| | - Mikki Schantell
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
| | | | - Hallie J Johnson
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
| | - Madelyn P Willett
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
| | | | - Kathryn L Losh
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
| | | | - Pamela E May
- Department of Neurological Sciences, University of Nebraska Medical Center (UNMC), Omaha, NE, USA
| | - Tony W Wilson
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
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27
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Ranasinghe KG, Verma P, Cai C, Xie X, Kudo K, Gao X, Lerner H, Mizuiri D, Strom A, Iaccarino L, La Joie R, Miller BL, Gorno-Tempini ML, Rankin KP, Jagust WJ, Vossel K, Rabinovici GD, Raj A, Nagarajan SS. Altered excitatory and inhibitory neuronal subpopulation parameters are distinctly associated with tau and amyloid in Alzheimer's disease. eLife 2022; 11:e77850. [PMID: 35616532 PMCID: PMC9217132 DOI: 10.7554/elife.77850] [Citation(s) in RCA: 64] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2022] [Accepted: 05/19/2022] [Indexed: 11/13/2022] Open
Abstract
Background Neuronal- and circuit-level abnormalities of excitation and inhibition are shown to be associated with tau and amyloid-beta (Aβ) in preclinical models of Alzheimer's disease (AD). These relationships remain poorly understood in patients with AD. Methods Using empirical spectra from magnetoencephalography and computational modeling (neural mass model), we examined excitatory and inhibitory parameters of neuronal subpopulations and investigated their specific associations to regional tau and Aβ, measured by positron emission tomography, in patients with AD. Results Patients with AD showed abnormal excitatory and inhibitory time-constants and neural gains compared to age-matched controls. Increased excitatory time-constants distinctly correlated with higher tau depositions while increased inhibitory time-constants distinctly correlated with higher Aβ depositions. Conclusions Our results provide critical insights about potential mechanistic links between abnormal neural oscillations and cellular correlates of impaired excitatory and inhibitory synaptic functions associated with tau and Aβ in patients with AD. Funding This study was supported by the National Institutes of Health grants: K08AG058749 (KGR), F32AG050434-01A1 (KGR), K23 AG038357 (KAV), P50 AG023501, P01 AG19724 (BLM), P50-AG023501 (BLM and GDR), R01 AG045611 (GDR); AG034570, AG062542 (WJ); NS100440 (SSN), DC176960 (SSN), DC017091 (SSN), AG062196 (SSN); a grant from John Douglas French Alzheimer's Foundation (KAV); grants from Larry L. Hillblom Foundation: 2015-A-034-FEL (KGR), 2019-A-013-SUP (KGR); grants from the Alzheimer's Association: AARG-21-849773 (KGR); PCTRB-13-288476 (KAV), and made possible by Part the CloudTM (ETAC-09-133596); a grant from Tau Consortium (GDR and WJJ), and a gift from the S. D. Bechtel Jr. Foundation.
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Affiliation(s)
- Kamalini G Ranasinghe
- Memory and Aging Center, Department of Neurology, University of California, San FranciscoSan FranciscoUnited States
| | - Parul Verma
- Department of Radiology and Biomedical Imaging, University of California, San FranciscoSan FranciscoUnited States
| | - Chang Cai
- Department of Radiology and Biomedical Imaging, University of California, San FranciscoSan FranciscoUnited States
| | - Xihe Xie
- Department of Radiology and Biomedical Imaging, University of California, San FranciscoSan FranciscoUnited States
| | - Kiwamu Kudo
- Department of Radiology and Biomedical Imaging, University of California, San FranciscoSan FranciscoUnited States
- Medical Imaging Business Center, Ricoh CompanyKanazawaJapan
| | - Xiao Gao
- Department of Radiology and Biomedical Imaging, University of California, San FranciscoSan FranciscoUnited States
| | - Hannah Lerner
- Memory and Aging Center, Department of Neurology, University of California, San FranciscoSan FranciscoUnited States
| | - Danielle Mizuiri
- Department of Radiology and Biomedical Imaging, University of California, San FranciscoSan FranciscoUnited States
| | - Amelia Strom
- Memory and Aging Center, Department of Neurology, University of California, San FranciscoSan FranciscoUnited States
| | - Leonardo Iaccarino
- Memory and Aging Center, Department of Neurology, University of California, San FranciscoSan FranciscoUnited States
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, University of California, San FranciscoSan FranciscoUnited States
| | - Bruce L Miller
- Memory and Aging Center, Department of Neurology, University of California, San FranciscoSan FranciscoUnited States
| | - Maria Luisa Gorno-Tempini
- Memory and Aging Center, Department of Neurology, University of California, San FranciscoSan FranciscoUnited States
| | - Katherine P Rankin
- Memory and Aging Center, Department of Neurology, University of California, San FranciscoSan FranciscoUnited States
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California, BerkeleyBerkeleyUnited States
| | - Keith Vossel
- Memory and Aging Center, Department of Neurology, University of California, San FranciscoSan FranciscoUnited States
- Mary S. Easton Center for Alzheimer’s Disease Research, Department of Neurology, David Geffen School of Medicine, University of California, Los AngelesLos AngelesUnited States
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, University of California, San FranciscoSan FranciscoUnited States
- Department of Radiology and Biomedical Imaging, University of California, San FranciscoSan FranciscoUnited States
| | - Ashish Raj
- Department of Radiology and Biomedical Imaging, University of California, San FranciscoSan FranciscoUnited States
| | - Srikantan S Nagarajan
- Department of Radiology and Biomedical Imaging, University of California, San FranciscoSan FranciscoUnited States
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28
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Treatment effects on event-related EEG potentials and oscillations in Alzheimer's disease. Int J Psychophysiol 2022; 177:179-201. [PMID: 35588964 DOI: 10.1016/j.ijpsycho.2022.05.008] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 05/11/2022] [Accepted: 05/12/2022] [Indexed: 11/23/2022]
Abstract
Alzheimer's disease dementia (ADD) is the most diffuse neurodegenerative disorder belonging to mild cognitive impairment (MCI) and dementia in old persons. This disease is provoked by an abnormal accumulation of amyloid-beta and tauopathy proteins in the brain. Very recently, the first disease-modifying drug has been licensed with reserve (i.e., Aducanumab). Therefore, there is a need to identify and use biomarkers probing the neurophysiological underpinnings of human cognitive functions to test the clinical efficacy of that drug. In this regard, event-related electroencephalographic potentials (ERPs) and oscillations (EROs) are promising candidates. Here, an Expert Panel from the Electrophysiology Professional Interest Area of the Alzheimer's Association and Global Brain Consortium reviewed the field literature on the effects of the most used symptomatic drug against ADD (i.e., Acetylcholinesterase inhibitors) on ERPs and EROs in ADD patients with MCI and dementia at the group level. The most convincing results were found in ADD patients. In those patients, Acetylcholinesterase inhibitors partially normalized ERP P300 peak latency and amplitude in oddball paradigms using visual stimuli. In these same paradigms, those drugs partially normalize ERO phase-locking at the theta band (4-7 Hz) and spectral coherence between electrode pairs at the gamma (around 40 Hz) band. These results are of great interest and may motivate multicentric, double-blind, randomized, and placebo-controlled clinical trials in MCI and ADD patients for final cross-validation.
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29
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Phillips NS, Rao V, Kmetz L, Vela R, Medick S, Krull K, Kesler SR. Changes in Brain Functional and Effective Connectivity After Treatment for Breast Cancer and Implications for Intervention Targets. Brain Connect 2022; 12:385-397. [PMID: 34210168 PMCID: PMC9131353 DOI: 10.1089/brain.2021.0049] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Background: Patients with breast cancer frequently report cognitive impairment both during and after completion of therapy. Evidence suggests that cancer-related cognitive impairments are related to widespread neural network dysfunction. The default mode network (DMN) is a large conserved network that plays a critical role in integrating the functions of various neural systems. Disruption of the network may play a key role in the development of cognitive impairment. Methods: We compared neuroimaging and neurocognitive data from 43 newly diagnosed primary breast cancer patients (mean age = 48, standard deviation [SD] = 8.9 years) and 50 frequency-matched healthy female controls (mean age = 50, SD = 10 years) before treatment and 1 year after treatment completion. Functional and effective connectivity measures of the DMN were obtained using graph theory and Bayesian network analysis methods, respectively. Results: Compared with healthy females, the breast cancer group displayed higher global efficiency and path length post-treatment (p < 0.03, corrected). Breast cancer survivors showed significantly lower performance on measures of verbal memory, attention, and verbal fluency (p < 0.05) at both time points. Within the DMN, local brain network organization, as measured by edge-betweenness centralities, was significantly altered in the breast cancer group compared with controls at both time points (p < 0.0001, corrected), with several connections showing a significant group-by-time effect (p < 0.003, corrected). Effective connectivity demonstrated significantly altered patterns of neuronal coupling in patients with breast cancer (p < 0.05). Significant correlations were seen between hormone blockade therapy, radiation therapy, chemotherapy cycles, memory, and verbal fluency test and edge-betweenness centralities. Discussion: This pattern of altered network organization in the default mode is believed to result in reduced network efficiency and disrupted communication. Subregions of the DMN, the orbital prefrontal cortex and posterior memory network, appear to be at the center of this disruption and this could inform future interventions. Impact statement This prospective study is the first to investigate how post-treatment changes in functional and effective connectivity in the regions of default mode network are related to cancer therapy and measures of memory and verbal learning in breast cancer patients. We demonstrate that the interactions between treatment, brain connectivity, and neurocognitive outcomes coalesce around a subgroup of brain structures in the orbital frontal and parietal lobe. This would suggest that interventions that target these regions may improve neurocognitive outcomes in breast cancer survivors.
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Affiliation(s)
- Nicholas S. Phillips
- Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
- Department of Oncology, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - Vikram Rao
- School of Nursing, University of Texas at Austin, Austin, Texas, USA
| | - Lorie Kmetz
- School of Nursing, University of Texas at Austin, Austin, Texas, USA
| | - Ruben Vela
- School of Nursing, University of Texas at Austin, Austin, Texas, USA
- Department of Diagnostic Medicine, Dell School of Medicine, University of Texas at Austin, Austin, Texas, USA
| | - Sarah Medick
- School of Nursing, University of Texas at Austin, Austin, Texas, USA
| | - Kevin Krull
- Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
- Department of Oncology, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - Shelli R. Kesler
- School of Nursing, University of Texas at Austin, Austin, Texas, USA
- Department of Diagnostic Medicine, Dell School of Medicine, University of Texas at Austin, Austin, Texas, USA
- Center for Computational Oncology, Oden Institute for Computational Engineering and Sciences, University of Texas at Austin, Austin, Texas, USA
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30
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Ranasinghe KG, Kudo K, Hinkley L, Beagle A, Lerner H, Mizuiri D, Findlay A, Miller BL, Kramer JH, Gorno-Tempini ML, Rabinovici GD, Rankin KP, Garcia PA, Kirsch HE, Vossel K, Nagarajan SS. Neuronal synchrony abnormalities associated with subclinical epileptiform activity in early-onset Alzheimer's disease. Brain 2022; 145:744-753. [PMID: 34919638 PMCID: PMC9630715 DOI: 10.1093/brain/awab442] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 09/27/2021] [Accepted: 11/09/2021] [Indexed: 11/12/2022] Open
Abstract
Since the first demonstrations of network hyperexcitability in scientific models of Alzheimer's disease, a growing body of clinical studies have identified subclinical epileptiform activity and associated cognitive decline in patients with Alzheimer's disease. An obvious problem presented in these studies is lack of sensitive measures to detect and quantify network hyperexcitability in human subjects. In this study we examined whether altered neuronal synchrony can be a surrogate marker to quantify network hyperexcitability in patients with Alzheimer's disease. Using magnetoencephalography (MEG) at rest, we studied 30 Alzheimer's disease patients without subclinical epileptiform activity, 20 Alzheimer's disease patients with subclinical epileptiform activity and 35 age-matched controls. Presence of subclinical epileptiform activity was assessed in patients with Alzheimer's disease by long-term video-EEG and a 1-h resting MEG with simultaneous EEG. Using the resting-state source-space reconstructed MEG signal, in patients and controls we computed the global imaginary coherence in alpha (8-12 Hz) and delta-theta (2-8 Hz) oscillatory frequencies. We found that Alzheimer's disease patients with subclinical epileptiform activity have greater reductions in alpha imaginary coherence and greater enhancements in delta-theta imaginary coherence than Alzheimer's disease patients without subclinical epileptiform activity, and that these changes can distinguish between Alzheimer's disease patients with subclinical epileptiform activity and Alzheimer's disease patients without subclinical epileptiform activity with high accuracy. Finally, a principal component regression analysis showed that the variance of frequency-specific neuronal synchrony predicts longitudinal changes in Mini-Mental State Examination in patients and controls. Our results demonstrate that quantitative neurophysiological measures are sensitive biomarkers of network hyperexcitability and can be used to improve diagnosis and to select appropriate patients for the right therapy in the next-generation clinical trials. The current results provide an integrative framework for investigating network hyperexcitability and network dysfunction together with cognitive and clinical correlates in patients with Alzheimer's disease.
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Affiliation(s)
- Kamalini G Ranasinghe
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Kiwamu Kudo
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
- Medical Imaging Business Center, Ricoh Company, Ltd, Kanazawa 920-0177, Japan
| | - Leighton Hinkley
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Alexander Beagle
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Hannah Lerner
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Danielle Mizuiri
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Anne Findlay
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Bruce L Miller
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Joel H Kramer
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Maria Luisa Gorno-Tempini
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
- Epilepsy Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Katherine P Rankin
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Paul A Garcia
- Epilepsy Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Heidi E Kirsch
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
- Epilepsy Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Keith Vossel
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
- Mary S. Easton Center for Alzheimer’s Disease Research, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Srikantan S Nagarajan
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
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31
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Barcia JA, Viloria MA, Yubero R, Sanchez-Sanchez-Rojas L, López A, Strange BA, Cabrera M, Canuet L, Gil P, Nombela C. Directional DBS of the Fornix in Alzheimer’s Disease Achieves Long-Term Benefits: A Case Report. Front Aging Neurosci 2022; 14:809972. [PMID: 35431895 PMCID: PMC9011335 DOI: 10.3389/fnagi.2022.809972] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Accepted: 01/17/2022] [Indexed: 11/14/2022] Open
Abstract
Background Current treatments for Alzheimer’s disease (AD) modulate global neurotransmission but are neither specific nor anatomically directed. Tailored stimulation of target nuclei will increase treatment efficacy while reducing side effects. We report the results of the first directional deep brain stimulation (dDBS) surgery and treatment of a patient with AD in an attempt to slow the progression of the disease in a woman with multi-domain, amnestic cognitive status. Methods We aimed to assess the safety of dDBS in patients with AD using the fornix as stimulation target (primary objective) and the clinical impact of the stimulation (secondary objective). In a registered clinical trial, a female patient aged 81 years with a 2-year history of cognitive decline and diagnoses of AD underwent a bilateral dDBS surgery targeting the fornix. Stimulation parameters were set between 3.9 and 7.5 mA, 90 μs, 130 Hz for 24 months, controlling stimulation effects by 18F-fluoro-2-deoxy-D-glucose (18F-FDG) scans (baseline, 12 and 24 months), magnetoencephalography (MEG) and clinical/neuropsychological assessment (baseline, 6, 12, 18, and 24 months). Results There were no important complications related to the procedure. In general terms, the patient showed cognitive fluctuations over the period, related to attention and executive function patterns, with no meaningful changes in any other cognitive functions, as is shown in the clinical dementia rating scale (CDR = 1) scores over the 24 months. Such stability in neuropsychological scores corresponds to the stability of the brain metabolic function, seen in PET scans. The MEG studies described low functional connectivity at baseline and a subsequent increase in the number of significant connections, mainly in the theta band, at 12 months. Conclusion The dDBS stimulation in the fornix seems to be a safe treatment for patients in the first stage of AD. Effects on cognition seem to be mild to moderate during the first months of stimulation and return to baseline levels after 24 months, except for verbal fluency. Clinical Trial Registration [https://clinicaltrials.gov/ct2/show/NCT03290274], identifier [NCT03290274].
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Affiliation(s)
- Juan A. Barcia
- Departamento de Cirugía, Facultad de Medicina, Servicio de Neurocirugía, Hospital Clínico San Carlos, Universidad Complutense de Madrid, IdISSC, Madrid, Spain
| | - María Aurora Viloria
- Departamento de Medicina, Facultad de Medicina, Servicio de Geriatría, Hospital Clínico San Carlos, Universidad Complutense de Madrid, IdISSC, Madrid, Spain
| | - Raquel Yubero
- Departamento de Neurología, Hospital Quirón Salud, Madrid, Spain
- Universidad Pontificia de Comillas, Madrid, Spain
| | - Leyre Sanchez-Sanchez-Rojas
- Grupo de Investigación en Neurociencias Aplicadas, Hospital Clínico San Carlos, IdISSC, Madrid, Spain
- Departamento de Medicamentos Veterinarios, Agencia Española del Medicamento y Producto Sanitario, Madrid, Spain
| | - Amanda López
- Unidad de Investigación y Ensayos Clínicos, Instituto de Investigación Sanitaria Hospital Clínico San Carlos, Madrid, Spain
- Facultad de Salud, Universidad Internacional de la Rioja, Logroño, Spain
| | - Bryan Andrew Strange
- Laboratory for Clinical Neuroscience, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Campus de Montegancedo, Madrid, Spain
| | - María Cabrera
- Servicio de Medicina Nuclear, Hospital Clínico San Carlos, IdISSC, Madrid, Spain
| | - Leonides Canuet
- Departamento de Neurología, Hospital Nuestra Señora del Rosario, Madrid, Spain
| | - Pedro Gil
- Departamento de Medicina, Facultad de Medicina, Servicio de Geriatría, Hospital Clínico San Carlos, Universidad Complutense de Madrid, IdISSC, Madrid, Spain
| | - Cristina Nombela
- Grupo de Investigación en Neurociencias Aplicadas, Hospital Clínico San Carlos, IdISSC, Madrid, Spain
- Departamento de Psicología Biológica y de la Salud, Facultad de Psicología, Universidad Autónoma de Madrid, Madrid, Spain
- *Correspondence: Cristina Nombela,
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32
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Ranasinghe KG, Petersen C, Kudo K, Mizuiri D, Rankin KP, Rabinovici GD, Gorno-Tempini ML, Seeley WW, Spina S, Miller BL, Vossel K, Grinberg LT, Nagarajan SS. Reduced synchrony in alpha oscillations during life predicts post mortem neurofibrillary tangle density in early-onset and atypical Alzheimer's disease. Alzheimers Dement 2021; 17:2009-2019. [PMID: 33884753 PMCID: PMC8528895 DOI: 10.1002/alz.12349] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Revised: 03/04/2021] [Accepted: 03/19/2021] [Indexed: 12/13/2022]
Abstract
INTRODUCTION Neurophysiological manifestations selectively associated with amyloid beta and tau depositions in Alzheimer's disease (AD) are useful network biomarkers to identify peptide specific pathological processes. The objective of this study was to validate the associations between reduced neuronal synchrony within alpha oscillations and neurofibrillary tangle (NFT) density in autopsy examination, in patients with AD. METHODS In a well-characterized clinicopathological cohort of AD patients (n = 13), we quantified neuronal synchrony within alpha (8-12 Hz) and delta-theta (2-8 Hz) oscillations, using magnetoencephalography during the disease course, within six selected neocortical and hippocampal regions, including angular gyrus, superior temporal gurus, middle frontal gyrus, primary motor cortex, CA1, and subiculum, and correlated these with regional NFT density quantified at histopathological examination. RESULTS Abnormal synchrony in alpha, but not in delta-theta, significantly predicted the NFT density at post mortem neuropathological examination. DISCUSSION Reduced alpha synchrony is a sensitive neurophysiological index associated with pathological tau, and a potential network biomarker for clinical trials, to gauge the extent of network dysfunction and the degree of rescue in treatments targeting tau pathways in AD.
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Affiliation(s)
- Kamalini G. Ranasinghe
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, California, USA
| | - Cathrine Petersen
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, California, USA
| | - Kiwamu Kudo
- Department Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA,Medical Imaging Business Center, Ricoh Company, Ltd., Kanazawa, Japan
| | - Danielle Mizuiri
- Department Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Katherine P. Rankin
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, California, USA
| | - Gil D. Rabinovici
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, California, USA,Department Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Maria Luisa Gorno-Tempini
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, California, USA
| | - William W. Seeley
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, California, USA,Department of Pathology, University of California, San Francisco, San Francisco, California, USA
| | - Salvatore Spina
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, California, USA
| | - Bruce L. Miller
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, California, USA
| | - Keith Vossel
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, California, USA,Mary S. Easton Center for Alzheimer’s Disease Research, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Lea T. Grinberg
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, California, USA,Department of Pathology, University of California, San Francisco, San Francisco, California, USA,Department of Pathology, LIM22, University of Sao Paulo, Sao Paulo, Brazil
| | - Srikantan S. Nagarajan
- Department Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
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Bruña R, Maestú F, López-Sanz D, Bagic A, Cohen AD, Chang YF, Cheng Y, Doman J, Huppert T, Kim T, Roush RE, Snitz BE, Becker JT. Sex Differences in Magnetoencephalography-Identified Functional Connectivity in the Human Connectome Project Connectomics of Brain Aging and Dementia Cohort. Brain Connect 2021; 12:561-570. [PMID: 34726478 PMCID: PMC9419974 DOI: 10.1089/brain.2021.0059] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Introduction: The human brain shows modest traits of sexual dimorphism, with the female brain, on average, 10% smaller than the male brain. These differences do not imply a lowered cognitive performance, but suggest a more optimal brain organization in women. Here we evaluate the patterns of functional connectivity (FC) in women and men from the Connectomics of Brain Aging and Dementia sample. Methods: We used phase locking values to calculate FC from the magnetoencephalography time series in a sample of 138 old adults (87 females and 51 males). We compared the FC patterns between sexes, with the intention of detecting regions with different levels of connectivity. Results: We found a frontal cluster, involving anterior cingulate and the medial frontal lobe, where women showed higher FC values than men. Involved connections included the following: (1) medial parietal areas, such as posterior cingulate cortices and precunei; (2) right insula; and (3) medium cingulate and paracingulate cortices. Moreover, these differences persisted when considering only cognitively intact individuals, but not when considering only cognitively impaired individuals. Discussion: Increased anteroposterior FC has been identified as a biomarker for increased risk of developing cognitive impairment or dementia. In our study, cognitively intact women showed higher levels of FC than their male counterparts. This result suggests that neurodegenerative processes could be taking place in these women, but the changes are undetected by current diagnosis tools. FC, as measured here, might be valuable for early identification of this neurodegeneration.
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Affiliation(s)
- Ricardo Bruña
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology, Universidad Politécnica de Madrid, Madrid, Spain.,Department of Experimental Psychology, Universidad Complutense de Madrid, Pozuelo de Alarcón, Madrid, Spain.,Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain
| | - Fernando Maestú
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology, Universidad Politécnica de Madrid, Madrid, Spain.,Department of Experimental Psychology, Universidad Complutense de Madrid, Pozuelo de Alarcón, Madrid, Spain.,Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain
| | - David López-Sanz
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology, Universidad Politécnica de Madrid, Madrid, Spain.,Department of Psychobiology, Universidad Complutense de Madrid, Madrid, Spain
| | - Anto Bagic
- Department of Psychiatry, The University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,Department of Statistics, The University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Ann D Cohen
- Department of Neurosurgery, The University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Yue-Fang Chang
- Department of Neurosurgery, The University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Yu Cheng
- Department of Statistics, The University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,Department of Biostatistics, The University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Jack Doman
- Department of Neurosurgery, The University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Ted Huppert
- Department of Electrical Engineering, The University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Tae Kim
- Department of Radiology, The University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Rebecca E Roush
- Department of Psychiatry, The University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Beth E Snitz
- Department of Psychiatry, The University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - James T Becker
- Department of Psychiatry, The University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,Department of Neurology, and The University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,Department of Psychology, The University of Pittsburgh, Pittsburgh, Pennsylvania, USA
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34
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Yu M, Sporns O, Saykin AJ. The human connectome in Alzheimer disease - relationship to biomarkers and genetics. Nat Rev Neurol 2021; 17:545-563. [PMID: 34285392 PMCID: PMC8403643 DOI: 10.1038/s41582-021-00529-1] [Citation(s) in RCA: 131] [Impact Index Per Article: 32.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/10/2021] [Indexed: 02/06/2023]
Abstract
The pathology of Alzheimer disease (AD) damages structural and functional brain networks, resulting in cognitive impairment. The results of recent connectomics studies have now linked changes in structural and functional network organization in AD to the patterns of amyloid-β and tau accumulation and spread, providing insights into the neurobiological mechanisms of the disease. In addition, the detection of gene-related connectome changes might aid in the early diagnosis of AD and facilitate the development of personalized therapeutic strategies that are effective at earlier stages of the disease spectrum. In this article, we review studies of the associations between connectome changes and amyloid-β and tau pathologies as well as molecular genetics in different subtypes and stages of AD. We also highlight the utility of connectome-derived computational models for replicating empirical findings and for tracking and predicting the progression of biomarker-indicated AD pathophysiology.
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Affiliation(s)
- Meichen Yu
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana University Network Science Institute, Bloomington, IN, USA
| | - Olaf Sporns
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana University Network Science Institute, Bloomington, IN, USA
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Andrew J Saykin
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA.
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA.
- Indiana University Network Science Institute, Bloomington, IN, USA.
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35
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Maestú F, de Haan W, Busche MA, DeFelipe J. Neuronal excitation/inhibition imbalance: core element of a translational perspective on Alzheimer pathophysiology. Ageing Res Rev 2021; 69:101372. [PMID: 34029743 DOI: 10.1016/j.arr.2021.101372] [Citation(s) in RCA: 105] [Impact Index Per Article: 26.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Revised: 04/16/2021] [Accepted: 05/19/2021] [Indexed: 02/08/2023]
Abstract
Our incomplete understanding of the link between Alzheimer's Disease pathology and symptomatology is a crucial obstacle for therapeutic success. Recently, translational studies have begun to connect the dots between protein alterations and deposition, brain network dysfunction and cognitive deficits. Disturbance of neuronal activity, and in particular an imbalance in underlying excitation/inhibition (E/I), appears early in AD, and can be regarded as forming a central link between structural brain pathology and cognitive dysfunction. While there are emerging (non-)pharmacological options to influence this imbalance, the complexity of human brain dynamics has hindered identification of an optimal approach. We suggest that focusing on the integration of neurophysiological aspects of AD at the micro-, meso- and macroscale, with the support of computational network modeling, can unite fundamental and clinical knowledge, provide a general framework, and suggest rational therapeutic targets.
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36
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Wu N, Liu W, Wang J, Han Y, Ye Y, Liu X, Yu Y, Chen Q, Bao Y, Liu C. Berberine ameliorates neuronal AD-like change via activating Pi3k/PGCε pathway. Biofactors 2021; 47:587-599. [PMID: 33740285 DOI: 10.1002/biof.1725] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Accepted: 02/24/2021] [Indexed: 12/11/2022]
Abstract
IR (insulin resistance) in diabetic brain gave rise to the generation of toxic factor Aβ42 and axon collapse which were the marker of AD (Alzheimer's disease)-like lesions in the circumstance of diabetes mellitus. But the underling molecular mechanism was not clear. Chronic HGHI (high glucose and high insulin) exposure accelerates IR has been reported in type II diabetes models. Berberine has been shown to promising effect for IR in vitro and in vivo. This study demonstrates the protective effect and the underlying mechanism of berberine on HGHI-induced IR. HGHI-induced cells were used to mimic the hyperinsulinemia resulting in IR. Berberine was used to uncover the mechanisms for the treatment of hyperinsulinemia in IR model. Morris water maze (MWM), PET imaging, CCK8 assay, ELISA assay, glucose kits, microscopy, and western blot analysis were performed to evaluate the protective effects of berberine. Berberine-improved HGHI-induced IR was correlated with the increase of glucose application in neurons. Meanwhile, the expressions of Pi3K, as well as GLUT3, PKCε, and APP were downregulated in the model, while p-IRS Ser307 was upregulated compared with Normal group. Fortunately, these scenes were reversed by berberine administration. Furthermore, berberine decreased GSK3β Y216 expressions, inhibited the production of oligomer Aβ42 and extended neuronal axon. The monomeric berberine treatment improves IR that may be involved in glucose effective application, rectifying the related proteins of the aberrant insulin pathway. Additionally, it suppressed the generation of Aβ42 and ameliorated neuron axon damage. Finally, berberine improves DM (diabetes mellitus)-induced cognitive impairment.
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Affiliation(s)
- Ninghua Wu
- Hubei Key Laboratory of Diabetes and Angiopathy, Hubei University of Science and Technology, Xianning, China
- Basic Medical College, Hubei University of Science and Technology, Xianning, China
| | - Wu Liu
- Hubei Key Laboratory of Diabetes and Angiopathy, Hubei University of Science and Technology, Xianning, China
| | - Jiawen Wang
- Hubei Key Laboratory of Diabetes and Angiopathy, Hubei University of Science and Technology, Xianning, China
| | - Yanqi Han
- Hubei Key Laboratory of Diabetes and Angiopathy, Hubei University of Science and Technology, Xianning, China
| | - Yu Ye
- Hubei Key Laboratory of Diabetes and Angiopathy, Hubei University of Science and Technology, Xianning, China
| | - Xiufen Liu
- Hubei Key Laboratory of Diabetes and Angiopathy, Hubei University of Science and Technology, Xianning, China
| | - Yuandong Yu
- Department of Oncology, Renmin Hospital, Hubei University of Medicine, Shiyan, China
| | - Qingjie Chen
- Hubei Key Laboratory of Diabetes and Angiopathy, Hubei University of Science and Technology, Xianning, China
| | - Yongfen Bao
- Basic Medical College, Hubei University of Science and Technology, Xianning, China
| | - Chao Liu
- Hubei Key Laboratory of Diabetes and Angiopathy, Hubei University of Science and Technology, Xianning, China
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37
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Kang DW, Wang SM, Um YH, Na HR, Kim NY, Lee CU, Lim HK. Distinctive Association of the Functional Connectivity of the Posterior Cingulate Cortex on Memory Performances in Early and Late Amnestic Mild Cognitive Impairment Patients. Front Aging Neurosci 2021; 13:696735. [PMID: 34276347 PMCID: PMC8281268 DOI: 10.3389/fnagi.2021.696735] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2021] [Accepted: 05/31/2021] [Indexed: 11/16/2022] Open
Abstract
Background Attempts have been made to explore the biological basis of neurodegeneration in the amnestic mild cognitive impairment (MCI) stage, subdivided by memory performance. However, few studies have evaluated the differential impact of functional connectivity (FC) on memory performances in early- and late-MCI patients. Objective This study aims to explore the difference in FC of the posterior cingulate cortex (PCC) among healthy controls (HC) (n = 37), early-MCI patients (n = 30), and late-MCI patients (n = 35) and to evaluate a group-memory performance interaction against the FC of PCC. Methods The subjects underwent resting-state functional MRI scanning and a battery of neuropsychological tests. Results A significant difference among the three groups was found in FC between the PCC (seed region) and bilateral crus cerebellum, right superior medial frontal gyrus, superior temporal gyrus, and left middle cingulate gyrus (Monte Carlo simulation-corrected p < 0.01; cluster p < 0.05). Additionally, the early-MCI patients displayed higher FC values than the HC and late-MCI patients in the right superior medial frontal gyrus, cerebellum crus 1, and left cerebellum crus 2 (Bonferroni-corrected p < 0.05). Furthermore, there was a significant group-memory performance interaction (HC vs. early MCI vs. late MCI) for the FC between PCC and bilateral crus cerebellum, right superior medial frontal gyrus, superior temporal gyrus, and left middle cingulate gyrus (Bonferroni-corrected p < 0.05). Conclusion These findings contribute to the biological implications of early- and late-MCI stages, categorized by evaluating the impairment of memory performance. Additionally, comprehensively analyzing the structural differences in the subdivided amnestic MCI (aMCI) stages could deepen our understanding of these biological meanings.
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Affiliation(s)
- Dong Woo Kang
- Department of Psychiatry, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea
| | - Sheng-Min Wang
- Department of Psychiatry, Yeouido St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea
| | - Yoo Hyun Um
- Department of Psychiatry, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Suwon, South Korea
| | - Hae-Ran Na
- Department of Psychiatry, Yeouido St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea
| | - Nak-Young Kim
- Department of Psychiatry, Keyo Hospital, Uiwang, South Korea
| | - Chang Uk Lee
- Department of Psychiatry, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea
| | - Hyun Kook Lim
- Department of Psychiatry, Yeouido St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea
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38
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Ramírez-Toraño F, García-Alba J, Bruña R, Esteba-Castillo S, Vaquero L, Pereda E, Maestú F, Fernández A. Hypersynchronized Magnetoencephalography Brain Networks in Patients with Mild Cognitive Impairment and Alzheimer's Disease in Down Syndrome. Brain Connect 2021; 11:725-733. [PMID: 33858203 DOI: 10.1089/brain.2020.0897] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
Introduction: The majority of individuals with Down syndrome (DS) show signs of Alzheimer's disease (AD) neuropathology in their fourth decade. However, there is a lack of specific markers for characterizing the disease stages while considering this population's differential features. Methods: Forty-one DS individuals participated in the study, and were classified into three groups according to their clinical status: Alzheimer's disease (AD-DS), mild cognitive impairment (MCI-DS), and controls (CN-DS). We performed an exhaustive neuropsychological evaluation and assessed brain functional connectivity (FC) from magnetoencephalographic recordings. Results: Compared with CN-DS, both MCI-DS and AD-DS showed a pattern of increased FC within the high alpha band. The neuropsychological assessment showed a generalized cognitive impairment, especially affecting mnestic functions, in MCI-DS and, more pronouncedly, in AD-DS. Discussion: These findings might help to characterize the AD-continuum in DS. In addition, they support the role of the excitatory/inhibitory imbalance as a key pathophysiological factor in AD. Impact statement The pattern of functional connectivity (FC) hypersynchronization found in this study resembles the largely reported Alzheimer's disease (AD) FC evolution pattern in population with typical development. This study supports the hypothesis of the excitatory/inhibitory imbalance as a key pathophysiological factor in AD, and its conclusions could help in the characterization and prediction of Down syndrome individuals with a greater likelihood of converting to dementia.
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Affiliation(s)
- Federico Ramírez-Toraño
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology, Technical University of Madrid, Madrid, Spain.,Department of Experimental Psychology, Universidad Complutense de Madrid, Madrid, Spain
| | - Javier García-Alba
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology, Technical University of Madrid, Madrid, Spain.,Research and Psychology in Education Department, Complutense University of Madrid, Madrid, Spain
| | - Ricardo Bruña
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology, Technical University of Madrid, Madrid, Spain.,Department of Experimental Psychology, Universidad Complutense de Madrid, Madrid, Spain.,Networking Research Center on Bioengineering, Biomaterials, and Nanomedicine (CIBER-BBN), Madrid, Spain
| | - Susanna Esteba-Castillo
- Specialized Department in Mental Health and Intellectual Disability, Parc Hospitalari Martí i Julià-Institut 'd'Assistència Sanitària, Institut 'd'Assistència Sanitària (IAS), Girona, Spain
| | - Lucía Vaquero
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology, Technical University of Madrid, Madrid, Spain.,Department of Legal Medicine, Psychiatry and Pathology, Complutense University of Madrid, Spain
| | - Ernesto Pereda
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology, Technical University of Madrid, Madrid, Spain.,Electrical Engineering and Bioengineering Group, Department of Industrial Engineering and IUNE and ITB Universidad de La Laguna, Santa Cruz de Tenerife, Spain
| | - Fernando Maestú
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology, Technical University of Madrid, Madrid, Spain.,Department of Experimental Psychology, Universidad Complutense de Madrid, Madrid, Spain.,Networking Research Center on Bioengineering, Biomaterials, and Nanomedicine (CIBER-BBN), Madrid, Spain
| | - Alberto Fernández
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology, Technical University of Madrid, Madrid, Spain.,Department of Legal Medicine, Psychiatry and Pathology, Complutense University of Madrid, Spain.,Institute of Sanitary Investigation (IdISSC), San Carlos University Hospital, Madrid, Spain
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39
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Xu M, Sanz DL, Garces P, Maestu F, Li Q, Pantazis D. A Graph Gaussian Embedding Method for Predicting Alzheimer's Disease Progression With MEG Brain Networks. IEEE Trans Biomed Eng 2021; 68:1579-1588. [PMID: 33400645 PMCID: PMC8162933 DOI: 10.1109/tbme.2021.3049199] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Characterizing the subtle changes of functional brain networks associated with the pathological cascade of Alzheimer's disease (AD) is important for early diagnosis and prediction of disease progression prior to clinical symptoms. We developed a new deep learning method, termed multiple graph Gaussian embedding model (MG2G), which can learn highly informative network features by mapping high-dimensional resting-state brain networks into a low-dimensional latent space. These latent distribution-based embeddings enable a quantitative characterization of subtle and heterogeneous brain connectivity patterns at different regions, and can be used as input to traditional classifiers for various downstream graph analytic tasks, such as AD early stage prediction, and statistical evaluation of between-group significant alterations across brain regions. We used MG2G to detect the intrinsic latent dimensionality of MEG brain networks, predict the progression of patients with mild cognitive impairment (MCI) to AD, and identify brain regions with network alterations related to MCI.
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40
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Babiloni C, Arakaki X, Azami H, Bennys K, Blinowska K, Bonanni L, Bujan A, Carrillo MC, Cichocki A, de Frutos-Lucas J, Del Percio C, Dubois B, Edelmayer R, Egan G, Epelbaum S, Escudero J, Evans A, Farina F, Fargo K, Fernández A, Ferri R, Frisoni G, Hampel H, Harrington MG, Jelic V, Jeong J, Jiang Y, Kaminski M, Kavcic V, Kilborn K, Kumar S, Lam A, Lim L, Lizio R, Lopez D, Lopez S, Lucey B, Maestú F, McGeown WJ, McKeith I, Moretti DV, Nobili F, Noce G, Olichney J, Onofrj M, Osorio R, Parra-Rodriguez M, Rajji T, Ritter P, Soricelli A, Stocchi F, Tarnanas I, Taylor JP, Teipel S, Tucci F, Valdes-Sosa M, Valdes-Sosa P, Weiergräber M, Yener G, Guntekin B. Measures of resting state EEG rhythms for clinical trials in Alzheimer's disease: Recommendations of an expert panel. Alzheimers Dement 2021; 17:1528-1553. [PMID: 33860614 DOI: 10.1002/alz.12311] [Citation(s) in RCA: 100] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Revised: 12/28/2020] [Accepted: 01/01/2021] [Indexed: 12/25/2022]
Abstract
The Electrophysiology Professional Interest Area (EPIA) and Global Brain Consortium endorsed recommendations on candidate electroencephalography (EEG) measures for Alzheimer's disease (AD) clinical trials. The Panel reviewed the field literature. As most consistent findings, AD patients with mild cognitive impairment and dementia showed abnormalities in peak frequency, power, and "interrelatedness" at posterior alpha (8-12 Hz) and widespread delta (< 4 Hz) and theta (4-8 Hz) rhythms in relation to disease progression and interventions. The following consensus statements were subscribed: (1) Standardization of instructions to patients, resting state EEG (rsEEG) recording methods, and selection of artifact-free rsEEG periods are needed; (2) power density and "interrelatedness" rsEEG measures (e.g., directed transfer function, phase lag index, linear lagged connectivity, etc.) at delta, theta, and alpha frequency bands may be use for stratification of AD patients and monitoring of disease progression and intervention; and (3) international multisectoral initiatives are mandatory for regulatory purposes.
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Affiliation(s)
- Claudio Babiloni
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy.,San Raffaele of Cassino, Cassino (FR), Italy
| | | | - Hamed Azami
- Department of Neurology and Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts, USA
| | - Karim Bennys
- Centre Mémoire de Ressources et de Recherche (CMRR), Centre Hospitalier, Universitaire de Montpellier, Montpellier, France
| | - Katarzyna Blinowska
- Institute of Biocybernetics, Warsaw, Poland.,Faculty of Physics University of Warsaw and Nalecz, Warsaw, Poland
| | - Laura Bonanni
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University "G. D'Annunzio" of Chieti-Pescara, Chieti, Italy
| | - Ana Bujan
- Psychological Neuroscience Lab, School of Psychology, University of Minho, Minho, Portugal
| | - Maria C Carrillo
- Division of Medical & Scientific Relations, Alzheimer's Association, Chicago, Illinois, USA
| | - Andrzej Cichocki
- Skolkowo Institute of Science and Technology (SKOLTECH), Moscow, Russia.,Systems Research Institute PAS, Warsaw, Poland.,Nicolaus Copernicus University (UMK), Torun, Poland
| | - Jaisalmer de Frutos-Lucas
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain
| | - Claudio Del Percio
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | - Bruno Dubois
- Department of Neurology, Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l'hôpital, Institute of Memory and Alzheimer's Disease (IM2A), Paris, France.,ICM, INSERM U1127, CNRS UMR 7225, Sorbonne Université, Institut du Cerveau et de la Moelle épinière, Paris, France
| | - Rebecca Edelmayer
- Division of Medical & Scientific Relations, Alzheimer's Association, Chicago, Illinois, USA
| | - Gary Egan
- Foundation Director of the Monash Biomedical Imaging (MBI) Research Facilities, Monash University, Clayton, Australia
| | - Stephane Epelbaum
- Department of Neurology, Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l'hôpital, Institute of Memory and Alzheimer's Disease (IM2A), Paris, France.,ICM, INSERM U1127, CNRS UMR 7225, Sorbonne Université, Institut du Cerveau et de la Moelle épinière, Paris, France
| | - Javier Escudero
- School of Engineering, Institute for Digital Communications, The University of Edinburgh, Edinburgh, UK
| | - Alan Evans
- Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
| | - Francesca Farina
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Keith Fargo
- Division of Medical & Scientific Relations, Alzheimer's Association, Chicago, Illinois, USA
| | - Alberto Fernández
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain
| | | | - Giovanni Frisoni
- IRCCS San Giovanni di Dio Fatebenefratelli, Brescia, Italy.,Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Harald Hampel
- GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l'hôpital, Sorbonne University, Paris, France
| | | | - Vesna Jelic
- Division of Clinical Geriatrics, NVS Department, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
| | - Jaeseung Jeong
- Department of Bio and Brain Engineering/Program of Brain and Cognitive Engineering Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea
| | - Yang Jiang
- Department of Behavioral Science, College of Medicine, University of Kentucky, Lexington, Kentucky, USA
| | - Maciej Kaminski
- Faculty of Physics University of Warsaw and Nalecz, Warsaw, Poland
| | - Voyko Kavcic
- Institute of Gerontology, Wayne State University, Detroit, Michigan, USA
| | - Kerry Kilborn
- School of Psychology, University of Glasgow, Glasgow, UK
| | - Sanjeev Kumar
- Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Alice Lam
- MGH Epilepsy Service, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Lew Lim
- Vielight Inc., Toronto, Ontario, Canada
| | | | - David Lopez
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain
| | - Susanna Lopez
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | - Brendan Lucey
- Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA
| | - Fernando Maestú
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain
| | - William J McGeown
- School of Psychological Sciences and Health, University of Strathclyde, Glasgow, UK
| | - Ian McKeith
- Newcastle upon Tyne, Translational and Clinical Research Institute, Newcastle University, UK
| | | | - Flavio Nobili
- Department of Neuroscience (DINOGMI), University of Genoa, Genoa, Italy.,Clinica Neurologica, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | | | - John Olichney
- UC Davis Department of Neurology and Center for Mind and Brain, Davis, California, USA
| | - Marco Onofrj
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University "G. D'Annunzio" of Chieti-Pescara, Chieti, Italy
| | - Ricardo Osorio
- Center for Brain Health, Department of Psychiatry, NYU Langone Medical Center, New York, New York, USA
| | | | - Tarek Rajji
- Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Petra Ritter
- Brain Simulation Section, Department of Neurology, Charité Universitätsmedizin and Berlin Institute of Health, Berlin, Germany.,Bernstein Center for Computational Neuroscience, Berlin, Germany
| | - Andrea Soricelli
- IRCCS SDN, Napoli, Italy.,Department of Motor Sciences and Healthiness, University of Naples Parthenope, Naples, Italy
| | | | - Ioannis Tarnanas
- Global Brain Health Institute, University of California San Francisco, San Francisco, USA.,Global Brain Health Institute, Trinity College Dublin, Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - John Paul Taylor
- Newcastle upon Tyne, Translational and Clinical Research Institute, Newcastle University, UK
| | - Stefan Teipel
- Department of Psychosomatic Medicine, University of Rostock, Rostock, Germany.,German Center for Neurodegenerative Diseases (DZNE) - Rostock/Greifswald, Rostock, Germany
| | - Federico Tucci
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | | | - Pedro Valdes-Sosa
- Cuban Neuroscience Center, Havana, Cuba.,Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Marco Weiergräber
- Experimental Neuropsychopharmacology, BfArM), Federal Institute for Drugs and Medical Devices (Bundesinstitut für Arzneimittel und Medizinprodukte, Bonn, Germany
| | - Gorsev Yener
- Departments of Neurosciences and Department of Neurology, Dokuz Eylül University Medical School, Izmir, Turkey
| | - Bahar Guntekin
- Department of Biophysics, School of Medicine, Istanbul Medipol University, Istanbul, Turkey.,REMER, Clinical Electrophysiology, Neuroimaging and Neuromodulation Lab, Istanbul Medipol University, Istanbul, Turkey
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41
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Maestú F, Fernández A. Role of Magnetoencephalography in the Early Stages of Alzheimer Disease. Neuroimaging Clin N Am 2021; 30:217-227. [PMID: 32336408 DOI: 10.1016/j.nic.2020.01.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
As synaptic dysfunction is an early manifestation of Alzheimer disease (AD) pathology, magnetoencephalography (MEG) is capable of detecting disruptions by assessing the synchronized oscillatory activity of thousands of neurons that rely on the integrity of neural connections. MEG findings include slowness of the oscillatory activity, accompanied by a reduction of the alpha band power, and dysfunction of the functional networks. These findings are associated with the neuropathology of the disease and cognitive impairment. These neurophysiological biomarkers predict which patients with mild cognitive impairment will develop dementia. MEG has demonstrated its utility as a noninvasive biomarker for early detection of AD.
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Affiliation(s)
- Fernando Maestú
- Department of Experimental Psychology, Complutense University of Madrid, Madrid, Spain; Centro de Tecnología Biomédica, Campus de Montegancedo de la UPM, Pozuelo de Alarcón, Madrid 28223, Spain.
| | - Alberto Fernández
- Centro de Tecnología Biomédica, Campus de Montegancedo de la UPM, Pozuelo de Alarcón, Madrid 28223, Spain; Department of Legal Medicine, Psychiatry and Pathology, Complutense University of Madrid, Madrid, Spain
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42
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Alvares Pereira G, Silva Nunes MV, Alzola P, Contador I. Cognitive reserve and brain maintenance in aging and dementia: An integrative review. APPLIED NEUROPSYCHOLOGY-ADULT 2021; 29:1615-1625. [PMID: 33492168 DOI: 10.1080/23279095.2021.1872079] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
This research is an integrative review of scientific evidence differentiating between cognitive reserve (CR) and brain maintenance concepts. Thus, we have examined how CR socio-behavioral proxies (i.e. education, occupational attainment, and leisure activities) may help to cope with age-related cognitive decline and negative consequences of brain pathology. We also analyze lifestyle factors associated with brain maintenance or the relative absence of change in neural resources over time. Medline and Web of Science databases were used for the bibliographic search in the last 20 years. Observational cohort studies were selected to analyze the effect of different CR proxies on cognitive decline, including dementia incidence, whereas studies employing functional neuroimaging (fMRI) were used to display the existence of compensation mechanisms. Besides, structural MRI studies were used to test the association between lifestyle factors and neural changes. Our findings suggest that education, leisure activities, and occupational activity are protective factors against cognitive decline and dementia. Moreover, functional neuroimaging studies have verified the existence of brain networks that may underlie CR. Therefore, CR may be expressed either through a more efficient utilization (neural reserve) of brain networks or the recruitment of additional brain regions (compensation). Finally, lifestyle factors such as abstaining from smoking, lower alcohol consumption, and physical activity contributed to brain maintenance and were associated with the preservation of cognitive function. Advances in multimodal neuroimaging studies, preferably longitudinal design, will allow a better understanding of the neural mechanisms associated with the prevention of cognitive decline and preservation of neural resources in aging.
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Affiliation(s)
| | - Maria Vânia Silva Nunes
- Health Sciences Institute, Portuguese Catholic University, Lisbon, Portugal.,Interdisciplinary Health Research Center, Lisbon, Portugal
| | - Patricia Alzola
- Department of Basic Psychology, Psychobiology and Methodology, University of Salamanca, Salamanca, Spain
| | - Israel Contador
- Department of Basic Psychology, Psychobiology and Methodology, University of Salamanca, Salamanca, Spain
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43
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Ramírez-Toraño F, Bruña R, de Frutos-Lucas J, Rodríguez-Rojo IC, Marcos de Pedro S, Delgado-Losada ML, Gómez-Ruiz N, Barabash A, Marcos A, López Higes R, Maestú F. Functional Connectivity Hypersynchronization in Relatives of Alzheimer’s Disease Patients: An Early E/I Balance Dysfunction? Cereb Cortex 2020; 31:1201-1210. [DOI: 10.1093/cercor/bhaa286] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2020] [Revised: 08/05/2020] [Accepted: 09/01/2020] [Indexed: 12/13/2022] Open
Abstract
Abstract
Alzheimer’s disease (AD) studies on animal models, and humans showed a tendency of the brain tissue to become hyperexcitable and hypersynchronized, causing neurodegeneration. However, we know little about either the onset of this phenomenon or its early effects on functional brain networks. We studied functional connectivity (FC) on 127 participants (92 middle-age relatives of AD patients and 35 age-matched nonrelatives) using magnetoencephalography. FC was estimated in the alpha band in areas known both for early amyloid accumulation and disrupted FC in MCI converters to AD. We found a frontoparietal network (anterior cingulate cortex, dorsal frontal, and precuneus) where relatives of AD patients showed hypersynchronization in high alpha (not modulated by APOE-ε4 genotype) in comparison to age-matched nonrelatives. These results represent the first evidence of neurophysiological events causing early network disruption in humans, opening a new perspective for intervention on the excitation/inhibition unbalance.
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Affiliation(s)
- F Ramírez-Toraño
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Technical University of Madrid, Madrid, Comunidad de Madrid 28223, Spain
- Department of Experimental Psychology, Universidad Complutense de Madrid, Madrid, Comunidad de Madrid 28223, Spain
| | - R Bruña
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Technical University of Madrid, Madrid, Comunidad de Madrid 28223, Spain
- Department of Experimental Psychology, Universidad Complutense de Madrid, Madrid, Comunidad de Madrid 28223, Spain
- Networking Research Center on Bioengineering, Biomaterials, and Nanomedicine (CIBER-BBN), Madrid, Comunidad de Madrid 28029, Spain
| | - J de Frutos-Lucas
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Technical University of Madrid, Madrid, Comunidad de Madrid 28223, Spain
- Biological and Health Psychology Department, Universidad Autonoma de Madrid, Madrid, Comunidad de Madrid 28049, Spain
| | - I C Rodríguez-Rojo
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Technical University of Madrid, Madrid, Comunidad de Madrid 28223, Spain
- Facultad de Psicología, Centro Universitario Villanueva, Madrid, Comunidad de Madrid 28034, Spain
| | - S Marcos de Pedro
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Technical University of Madrid, Madrid, Comunidad de Madrid 28223, Spain
- Facultad de Educación y Salud, Universidad Camilo José Cela, Madrid, Comunidad de Madrid 28010, Spain
| | - M L Delgado-Losada
- Department of Experimental Psychology, Universidad Complutense de Madrid, Madrid, Comunidad de Madrid 28223, Spain
| | - N Gómez-Ruiz
- Sección Neurorradiología, Servicio de Diagnóstico por Imagen, Hospital Clínico San Carlos, Madrid, Comunidad de Madrid 28040, Spain
| | - A Barabash
- Endocrinology and Nutrition Department, Hospital Clinico San Carlos and Instituto de Investigación Sanitaria del Hospital Clínico San Carlos, Madrid, Comunidad de Madrid 28040, Spain
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas, Madrid, Comunidad de Madrid 28029, Spain
| | - A Marcos
- Neurology Department, Hospital Clinico San Carlos and Instituto de Investigación Sanitaria del Hospital Clínico San Carlos, Madrid, Comunidad de Madrid 28040, Spain
| | - R López Higes
- Department of Experimental Psychology, Universidad Complutense de Madrid, Madrid, Comunidad de Madrid 28223, Spain
| | - F Maestú
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Technical University of Madrid, Madrid, Comunidad de Madrid 28223, Spain
- Department of Experimental Psychology, Universidad Complutense de Madrid, Madrid, Comunidad de Madrid 28223, Spain
- Networking Research Center on Bioengineering, Biomaterials, and Nanomedicine (CIBER-BBN), Madrid, Comunidad de Madrid 28029, Spain
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44
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Kocagoncu E, Quinn A, Firouzian A, Cooper E, Greve A, Gunn R, Green G, Woolrich MW, Henson RN, Lovestone S, Rowe JB. Tau pathology in early Alzheimer's disease is linked to selective disruptions in neurophysiological network dynamics. Neurobiol Aging 2020; 92:141-152. [PMID: 32280029 PMCID: PMC7269692 DOI: 10.1016/j.neurobiolaging.2020.03.009] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2018] [Revised: 02/03/2020] [Accepted: 03/10/2020] [Indexed: 11/29/2022]
Abstract
Understanding the role of Tau protein aggregation in the pathogenesis of Alzheimer's disease is critical for the development of new Tau-based therapeutic strategies to slow or prevent dementia. We tested the hypothesis that Tau pathology is associated with functional organization of widespread neurophysiological networks. We used electro-magnetoencephalography with [18F]AV-1451 PET scanning to quantify Tau-dependent network changes. Using a graph theoretical approach to brain connectivity, we quantified nodal measures of functional segregation, centrality, and the efficiency of information transfer and tested them against levels of [18F]AV-1451. Higher Tau burden in early Alzheimer's disease was associated with a shift away from the optimal small-world organization and a more fragmented network in the beta and gamma bands, whereby parieto-occipital areas were disconnected from the anterior parts of the network. Similarly, higher Tau burden was associated with decreases in both local and global efficiency, especially in the gamma band. The results support the translational development of neurophysiological "signatures" of Alzheimer's disease, to understand disease mechanisms in humans and facilitate experimental medicine studies.
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Affiliation(s)
- Ece Kocagoncu
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK; MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.
| | - Andrew Quinn
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK,Department of Psychiatry, University of Oxford, Oxford, UK
| | | | - Elisa Cooper
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Andrea Greve
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Roger Gunn
- Invicro LLC, London, UK,Department of Medicine, Imperial College London, London, UK,Department of Engineering Science, University of Oxford, Oxford, UK
| | - Gary Green
- Department of Psychology, University of York, York, UK
| | - Mark W. Woolrich
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK,Department of Psychiatry, University of Oxford, Oxford, UK
| | - Richard N. Henson
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK,Department of Psychiatry, University of Cambridge, Cambridge, UK
| | | | | | - James B. Rowe
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK,MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
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45
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Jafari Z, Kolb BE, Mohajerani MH. Neural oscillations and brain stimulation in Alzheimer's disease. Prog Neurobiol 2020; 194:101878. [PMID: 32615147 DOI: 10.1016/j.pneurobio.2020.101878] [Citation(s) in RCA: 111] [Impact Index Per Article: 22.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2019] [Revised: 12/20/2019] [Accepted: 06/25/2020] [Indexed: 12/30/2022]
Abstract
Aging is associated with alterations in cognitive processing and brain neurophysiology. Whereas the primary symptom of amnestic mild cognitive impairment (aMCI) is memory problems greater than normal for age and education, patients with Alzheimer's disease (AD) show impairments in other cognitive domains in addition to memory dysfunction. Resting-state electroencephalography (rsEEG) studies in physiological aging indicate a global increase in low-frequency oscillations' power and the reduction and slowing of alpha activity. The enhancement of slow and the reduction of fast oscillations, and the disruption of brain functional connectivity, however, are characterized as major rsEEG changes in AD. Recent rodent studies also support human evidence of age- and AD-related changes in resting-state brain oscillations, and the neuroprotective effect of brain stimulation techniques through gamma-band stimulations. Cumulatively, current evidence moves toward optimizing rsEEG features as reliable predictors of people with aMCI at risk for conversion to AD and mapping neural alterations subsequent to brain stimulation therapies. The present paper reviews the latest evidence of changes in rsEEG oscillations in physiological aging, aMCI, and AD, as well as findings of various brain stimulation therapies from both human and non-human studies.
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Affiliation(s)
- Zahra Jafari
- Department of Neuroscience, Canadian Centre for Behavioural Neuroscience, University of Lethbridge, Lethbridge, AB, T1K 3M4, Canada
| | - Bryan E Kolb
- Department of Neuroscience, Canadian Centre for Behavioural Neuroscience, University of Lethbridge, Lethbridge, AB, T1K 3M4, Canada.
| | - Majid H Mohajerani
- Department of Neuroscience, Canadian Centre for Behavioural Neuroscience, University of Lethbridge, Lethbridge, AB, T1K 3M4, Canada.
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46
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Ponomareva N, Andreeva T, Protasova M, Konovalov R, Krotenkova M, Malina D, Mitrofanov A, Fokin V, Illarioshkin S, Rogaev E. Genetic Association Between Alzheimer's Disease Risk Variant of the PICALM Gene and EEG Functional Connectivity in Non-demented Adults. Front Neurosci 2020; 14:324. [PMID: 32372909 PMCID: PMC7177435 DOI: 10.3389/fnins.2020.00324] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2019] [Accepted: 03/19/2020] [Indexed: 11/13/2022] Open
Abstract
Genome wide association studies (GWAS) have identified and validated the association of the PICALM genotype with Alzheimer's disease (AD). The PICALM rs3851179 A allele is thought to have a protective effect, whereas the G allele appears to confer risk for AD. The influence of the PICALM genotype on brain functional connectivity in non-demented subjects remains largely unknown. We examined the association of the PICALM rs3851179 genotype with the characteristics of lagged linear connectivity (LLC) of resting EEG sources in 104 non-demented adults younger than 60 years of age. The EEG analysis was performed using exact low-resolution brain electromagnetic tomography (eLORETA) freeware (Pascual-Marqui et al., 2011). We found that the carriers of the A PICALM allele (PICALM AA and AG genotypes) had higher widespread interhemispheric LLC of alpha sources compared to the carriers of the GG PICALM allele. An exploratory correlation analysis showed a moderate positive association between the alpha LLC interhemispheric characteristics and the corpus callosum size and between the alpha interhemispheric LLC characteristics and the Luria word memory scores. These results suggest that the PICALM rs3851179 A allele provides protection against cognitive decline by facilitating neurophysiological reserve capacities in non-demented adults. In contrast, lower functional connectivity in carriers of the AD risk variant, PICALM GG, suggests early functional alterations in alpha rhythm networks.
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Affiliation(s)
- Natalya Ponomareva
- Research Center of Neurology, Russian Academy of Sciences, Moscow, Russia
| | - Tatiana Andreeva
- Laboratory of Evolutionary Genomics, Department of Human Genetics and Genomics, Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, Russia.,Center for Genetics and Genetic Technologies, Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia
| | - Maria Protasova
- Laboratory of Evolutionary Genomics, Department of Human Genetics and Genomics, Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, Russia
| | - Rodion Konovalov
- Research Center of Neurology, Russian Academy of Sciences, Moscow, Russia
| | - Marina Krotenkova
- Research Center of Neurology, Russian Academy of Sciences, Moscow, Russia
| | - Daria Malina
- Research Center of Neurology, Russian Academy of Sciences, Moscow, Russia
| | - Andrey Mitrofanov
- Research Center of Mental Health, Russian Academy of Medical Sciences, Moscow, Russia
| | - Vitaly Fokin
- Research Center of Neurology, Russian Academy of Sciences, Moscow, Russia
| | | | - Evgeny Rogaev
- Laboratory of Evolutionary Genomics, Department of Human Genetics and Genomics, Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, Russia.,Center for Genetics and Genetic Technologies, Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia.,Department of Psychiatry, University of Massachusetts Medical School, Worcester, MA, United States.,Sirius University of Science and Technology, Sochi, Russia
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47
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What electrophysiology tells us about Alzheimer's disease: a window into the synchronization and connectivity of brain neurons. Neurobiol Aging 2020; 85:58-73. [DOI: 10.1016/j.neurobiolaging.2019.09.008] [Citation(s) in RCA: 77] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2019] [Revised: 08/27/2019] [Accepted: 09/14/2019] [Indexed: 01/14/2023]
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48
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Synaptic Plasticity Shapes Brain Connectivity: Implications for Network Topology. Int J Mol Sci 2019; 20:ijms20246193. [PMID: 31817968 PMCID: PMC6940892 DOI: 10.3390/ijms20246193] [Citation(s) in RCA: 93] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Revised: 12/02/2019] [Accepted: 12/06/2019] [Indexed: 12/13/2022] Open
Abstract
Studies of brain network connectivity improved understanding on brain changes and adaptation in response to different pathologies. Synaptic plasticity, the ability of neurons to modify their connections, is involved in brain network remodeling following different types of brain damage (e.g., vascular, neurodegenerative, inflammatory). Although synaptic plasticity mechanisms have been extensively elucidated, how neural plasticity can shape network organization is far from being completely understood. Similarities existing between synaptic plasticity and principles governing brain network organization could be helpful to define brain network properties and reorganization profiles after damage. In this review, we discuss how different forms of synaptic plasticity, including homeostatic and anti-homeostatic mechanisms, could be directly involved in generating specific brain network characteristics. We propose that long-term potentiation could represent the neurophysiological basis for the formation of highly connected nodes (hubs). Conversely, homeostatic plasticity may contribute to stabilize network activity preventing poor and excessive connectivity in the peripheral nodes. In addition, synaptic plasticity dysfunction may drive brain network disruption in neuropsychiatric conditions such as Alzheimer's disease and schizophrenia. Optimal network architecture, characterized by efficient information processing and resilience, and reorganization after damage strictly depend on the balance between these forms of plasticity.
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49
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Qi Z, An Y, Zhang M, Li HJ, Lu J. Altered Cerebro-Cerebellar Limbic Network in AD Spectrum: A Resting-State fMRI Study. Front Neural Circuits 2019; 13:72. [PMID: 31780903 PMCID: PMC6851020 DOI: 10.3389/fncir.2019.00072] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Accepted: 10/17/2019] [Indexed: 12/05/2022] Open
Abstract
Recent evidence suggests that the cerebellum is related to motor and non-motor cognitive functions, and that several coupled cerebro-cerebellar networks exist, including links with the limbic network. Since several limbic structures are affected by Alzheimer pathology, even in the preclinical stages of Alzheimer’s disease (AD), we aimed to investigate the cerebral limbic network activity from the perspective of the cerebellum. Twenty patients with mild cognitive impairment (MCI), 18 patients with AD, and 26 healthy controls (HC) were recruited to acquire Resting-state functional MRI (rs-fMRI). We used seed-based approach to construct the cerebro-cerebellar limbic network. Two-sample t-tests were carried out to explore the differences of the cerebellar limbic network connectivity. The first result, a sub-scale network including the bilateral posterior part of the orbitofrontal cortex (POFC) extending to the anterior insular cortex (AIC) and left inferior parietal lobule (L-IPL), showed greater functional connectivity in MCI than in HC and less functional connectivity in AD than in MCI. The location of this sub-scale network was in accordance with components of the ventral attention network. Second, there was decreased functional connectivity to the right mid-cingulate cortex (MCC) in the AD and MCI patient groups relative to the HC group. As the cerebellum is not compromised by Alzheimer pathology in the prodromal stage of AD, this pattern indicates that the sub-scale ventral attention network may play a pivotal role in functional compensation through the coupled cerebro-cerebellar limbic network in MCI, and the cerebellum may be a key node in the modulation of social cognition.
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Affiliation(s)
- Zhigang Qi
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Yanhong An
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Mo Zhang
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Hui-Jie Li
- Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Jie Lu
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
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50
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Pusil S, López ME, Cuesta P, Bruña R, Pereda E, Maestú F. Hypersynchronization in mild cognitive impairment: the ‘X’ model. Brain 2019; 142:3936-3950. [DOI: 10.1093/brain/awz320] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2019] [Revised: 08/06/2019] [Accepted: 08/13/2019] [Indexed: 12/21/2022] Open
Abstract
Hypersynchronization has been considered as a biomarker of synaptic dysfunction along the Alzheimeŕs disease continuum. In a longitudinal MEG study, Pusil et al. reveal changes in functional connectivity upon progression from MCI to Alzheimer’s disease. They propose the ‘X’ model to explain their findings, and suggest that hypersynchronization predicts conversion.
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Affiliation(s)
- Sandra Pusil
- Laboratory of Neuropsychology, University of the Balearic Islands, Spain
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain
| | - María Eugenia López
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain
- Department of Experimental Psychology, Universidad Complutense de Madrid, Madrid, Spain
- Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain
| | - Pablo Cuesta
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain
- Electrical Engineering and Bioengineering Lab, Department of Industrial Engineering and IUNE Universidad de La Laguna, Tenerife, Spain
| | - Ricardo Bruña
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain
- Department of Experimental Psychology, Universidad Complutense de Madrid, Madrid, Spain
- Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain
| | - Ernesto Pereda
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain
- Electrical Engineering and Bioengineering Lab, Department of Industrial Engineering and IUNE Universidad de La Laguna, Tenerife, Spain
| | - Fernando Maestú
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain
- Department of Experimental Psychology, Universidad Complutense de Madrid, Madrid, Spain
- Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain
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