Alzheimer’s Disease Facts and Figures. Published 2022. Accessed January 25, 2023.https://www.alz.org/media/Documents/alzheimers-facts-and-figures.pdf
Jack CR, Bennett DA, Blennow K, et al. NIA-AA research framework: toward a biological definition of Alzheimer’s disease. Alzheimers Dement. 2018;14(4):535–62. https://doi.org/10.1016/j.jalz.2018.02.018.
Donix M, Small GW, Bookheimer SY. Family history and APOE-4 genetic risk in Alzheimer’s disease. Neuropsychol Rev. 2012;22(3):298–309. https://doi.org/10.1007/s11065-012-9193-2.
Article PubMed PubMed Central Google Scholar
Busche MA, Konnerth A. Impairments of neural circuit function in Alzheimer’s disease. Philos Trans R Soc B Biol Sci. 2016;371(1700):20150429. https://doi.org/10.1098/rstb.2015.0429.
López-Sanz D, Bruña R, Garcés P, et al. Functional connectivity disruption in subjective cognitive decline and mild cognitive impairment: a common pattern of alterations. Front Aging Neurosci. 2017;9:109. https://doi.org/10.3389/fnagi.2017.00109.
Article PubMed PubMed Central Google Scholar
Maestú F, Peña JM, Garcés P, et al. A multicenter study of the early detection of synaptic dysfunction in Mild Cognitive Impairment using Magnetoencephalography-derived functional connectivity. NeuroImage Clin. 2015;9:103–9. https://doi.org/10.1016/j.nicl.2015.07.011.
Article PubMed PubMed Central Google Scholar
Nakamura A, Cuesta P, Kato T, et al. Early functional network alterations in asymptomatic elders at risk for Alzheimer’s disease. Sci Rep. 2017;7(1):6517. https://doi.org/10.1038/s41598-017-06876-8.
Article CAS PubMed PubMed Central Google Scholar
Pusil S, López ME, Cuesta P, Bruña R, Pereda E, Maestú F. Hypersynchronization in mild cognitive impairment: the ‘X’ model. Brain. 2019;142(12):3936–50. https://doi.org/10.1093/brain/awz320.
Quiroz YT, Budson AE, Celone K, et al. Hippocampal hyperactivation in presymptomatic familial Alzheimer’s disease. Ann Neurol. 2010;68(6):865–75. https://doi.org/10.1002/ana.22105.
Article PubMed PubMed Central Google Scholar
Sperling RA, LaViolette PS, O’Keefe K, et al. Amyloid deposition is associated with impaired default network function in older persons without dementia. Neuron. 2009;63(2):178–88. https://doi.org/10.1016/j.neuron.2009.07.003.
Article CAS PubMed PubMed Central Google Scholar
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. https://doi.org/10.1016/j.arr.2021.101372.
Article CAS PubMed Google Scholar
Ramírez-Toraño F, Bruña R, de Frutos-Lucas J, et al. Functional connectivity hypersynchronization in relatives of Alzheimer’s disease patients: an early E/I balance dysfunction? Cereb Cortex. 2021;31(2):1201–10. https://doi.org/10.1093/cercor/bhaa286.
Quevenco FC, van Bergen JM, Treyer V, et al. Functional brain network connectivity patterns associated with normal cognition at old-age, local β-amyloid, tau, and APOE4. Front Aging Neurosci. 2020;12. https://www.frontiersin.org/articles/10.3389/fnagi.2020.00046.
Sepulcre J, Sabuncu MR, Li Q, El Fakhri G, Sperling R, Johnson KA. Tau and amyloid β proteins distinctively associate to functional network changes in the aging brain. Alzheimers Dement. 2017;13(11):1261–9. https://doi.org/10.1016/j.jalz.2017.02.011.
Ren SQ, Yao W, Yan JZ, et al. Amyloid β causes excitation/inhibition imbalance through dopamine receptor 1-dependent disruption of fast-spiking GABAergic input in anterior cingulate cortex. Sci Rep. 2018;8(1):302. https://doi.org/10.1038/s41598-017-18729-5.
Article CAS PubMed PubMed Central Google Scholar
Verret L, Mann EO, Hang GB, et al. Inhibitory interneuron deficit links altered network activity and cognitive dysfunction in Alzheimer model. Cell. 2012;149(3):708–21. https://doi.org/10.1016/j.cell.2012.02.046.
Article CAS PubMed PubMed Central Google Scholar
Limon A, Reyes-Ruiz JM, Miledi R. Loss of functional GABAA receptors in the Alzheimer diseased brain. Proc Natl Acad Sci. 2012;109(25):10071–6. https://doi.org/10.1073/pnas.1204606109.
Article PubMed PubMed Central Google Scholar
Ulrich D. Amyloid-β impairs synaptic inhibition via GABAA receptor endocytosis. J Neurosci. 2015;35(24):9205–10. https://doi.org/10.1523/JNEUROSCI.0950-15.2015.
Article CAS PubMed PubMed Central Google Scholar
Zott B, Simon MM, Hong W, et al. A vicious cycle of β amyloid–dependent neuronal hyperactivation. Science. 2019;365(6453):559–65. https://doi.org/10.1126/science.aay0198.
Article CAS PubMed PubMed Central Google Scholar
Tombini M, Assenza G, Ricci L, et al. Temporal lobe epilepsy and Alzheimer’s disease: from preclinical to clinical evidence of a strong association. J Alzheimers Dis Rep. 2021;5(1):243–61. https://doi.org/10.3233/ADR-200286.
Article PubMed PubMed Central Google Scholar
Vossel KA, Tartaglia MC, Nygaard HB, Zeman AZ, Miller BL. Epileptic activity in Alzheimer’s disease: causes and clinical relevance. Lancet Neurol. 2017;16(4):311–22. https://doi.org/10.1016/S1474-4422(17)30044-3.
Article PubMed PubMed Central Google Scholar
Ashton NJ, Pascoal TA, Karikari TK, et al. Plasma p-tau231: a new biomarker for incipient Alzheimer’s disease pathology. Acta Neuropathol (Berl). 2021;141(5):709–24. https://doi.org/10.1007/s00401-021-02275-6.
Article CAS PubMed Google Scholar
Suárez-Calvet M, Karikari TK, Ashton NJ, et al. Novel tau biomarkers phosphorylated at T181, T217 or T231 rise in the initial stages of the preclinical Alzheimer’s continuum when only subtle changes in Aβ pathology are detected. EMBO Mol Med. 2020;12(12):e12921. https://doi.org/10.15252/emmm.202012921.
Ashton NJ, Benedet AL, Pascoal TA, et al. Cerebrospinal fluid p-tau231 as an early indicator of emerging pathology in Alzheimer’s disease. eBioMedicine. 2022;76:103836. https://doi.org/10.1016/j.ebiom.2022.103836.
Article CAS PubMed PubMed Central Google Scholar
Milà-Alomà M, Ashton NJ, Shekari M, et al. Plasma p-tau231 and p-tau217 as state markers of amyloid-β pathology in preclinical Alzheimer’s disease. Nat Med. 2022;28(9): 1797–1801. https://doi.org/10.1038/s41591-022-01925-w.
McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM. Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA Work Group* under the auspices of Department of Health and Human Services Task Force on Alzheimer’s Disease. Neurology. 1984;34(7):939–939. https://doi.org/10.1212/WNL.34.7.939.
Article CAS PubMed Google Scholar
Taulu S, Simola J. Spatiotemporal signal space separation method for rejecting nearby interference in MEG measurements. Phys Med Biol. 2006;51(7):1759–68. https://doi.org/10.1088/0031-9155/51/7/008.
Article CAS PubMed Google Scholar
Oostenveld R, Fries P, Maris E, Schoffelen JM. FieldTrip: open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data. Comput Intell Neurosci. 2011;2011:1–9. https://doi.org/10.1155/2011/156869.
Garcés P, López-Sanz D, Maestú F, Pereda E. Choice of magnetometers and gradiometers after signal space separation. Sensors. 2017;17(12):2926. https://doi.org/10.3390/s17122926.
Article PubMed PubMed Central Google Scholar
Tzourio-Mazoyer N, Landeau B, Papathanassiou D, et al. Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage. 2002;15(1):273–89. https://doi.org/10.1006/nimg.2001.0978.
Article CAS PubMed Google Scholar
Statistical Parametric Mapping. Elsevier. 2007. https://doi.org/10.1016/B978-0-12-372560-8.X5000-1.
Nolte G. The magnetic lead field theorem in the quasi-static approximation and its use for magnetoencephalography forward calculation in realistic volume conductors. Phys Med Biol. 2003;48(22):3637–52. https://doi.org/10.1088/0031-9155/48/22/002.
Van Veen BD, Van Drongelen W, Yuchtman M, Suzuki A. Localization of brain electrical activity via linearly constrained minimum variance spatial filtering. IEEE Trans Biomed Eng. 1997;44(9):867–80. https://doi.org/10.1109/10.623056.
Lachaux JP, Rodriguez E, Martinerie J, Varela FJ. Measuring phase synchrony in brain signals. Hum Brain Mapp. 1999;8(4):194–208. https://doi.org/10.1002/(SICI)1097-0193(1999)8:4%3c194::AID-HBM4%3e3.0.CO;2-C.
Article CAS PubMed PubMed Central Google Scholar
Garcés P, Martín-Buro MC, Maestú F. Quantifying the test-retest reliability of magnetoencephalography resting-state functional connectivity. Brain Connect. 2016;6(6):448–60. https://doi.org/10.1089/brain.2015.0416.
Mattsson N, Palmqvist S, Stomrud E, Vogel J, Hansson O. Staging β-amyloid pathology with amyloid positron emission tomography. JAMA Neurol. 2019;76(11):1319–29.
Bullmore ET, Suckling J, Overmeyer S, Rabe-Hesketh S, Taylor E, Brammer MJ. Global, voxel, and cluster tests, by
留言 (0)