Perfil de conectividad cerebral y el rendimiento cognitivo en consulta neurológica

dc.contributorAllegri, Ricardo Francisco
dc.contributorBarceló, Ernesto
dc.contributorCuesta, Pablo
dc.contributorCochen, Silvia
dc.contributorThomson, Alfredo
dc.contributorFabian Román, Nestor
dc.creatorCamargo, Loida
dc.date2023-07-13T23:43:43Z
dc.date2023-07-13T23:43:43Z
dc.date2023
dc.date.accessioned2023-10-03T19:48:58Z
dc.date.available2023-10-03T19:48:58Z
dc.identifierhttps://hdl.handle.net/11323/10315
dc.identifierCorporación Universidad de la Costa
dc.identifierREDICUC-Repositorio CUC
dc.identifierhttps://repositorio.cuc.edu.co/
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/9172309
dc.descriptionEl abordaje diagnóstico de pacientes con enfermedades que comprometen la cognición es un reto para los sistemas de salud. El electroencefalograma es considerado una técnica útil para evaluar el funcionamiento cerebral, de bajo costo y accesible a la población general. El presente estudio indica que el análisis de la conectividad cerebral y su relación con las pruebas de tamización cognitiva pueden ser un adecuado biomarcador de la función cerebral tanto en las pacientes con enfermedad de Alzheimer como en la población general. Se realizaron análisis tanto en la distribución espectral como en la organización funcional. Se evidenció que el aumento de la potencia Theta se correlacionó negativamente con el desempeño obtenido en las pruebas de tamización cognitiva en toda la población. Por su parte, la conectividad funcional se vio afectada de manera heterogénea. Se demostró una disminución en la sincronización de las oscilaciones Gamma frontotemporales en pacientes con enfermedad de Alzheimer que se correlacionó negativamente con los resultados de las pruebas de tamización. Además, se encontró disminución en la sincronización Theta de similar localización que se correlacionó con la prueba de MOCA. Adicionalmente, se evidenció un aumento en la sincronización Alpha en toda la población que se correlacionó positivamente con los resultados de MOCA.
dc.descriptionThe diagnostic approach to patients with diseases that compromise cognition is a challenge for health systems. The electroencephalogram is considered a useful technique to assess brain function, inexpensive and accessible to the general population. The present study indicates that the analysis of brain connectivity and its relationship with cognitive screening tests may be a suitable biomarker of brain function in both Alzheimer's disease patients and the general population. Analyses were performed on both spectral distribution and functional organization. It was shown that the increase in Theta power was negatively correlated with the performance obtained in the cognitive screening tests in the whole population. Functional connectivity was heterogeneously affected. A decrease in the synchronization of frontotemporal Gamma oscillations was demonstrated in patients with Alzheimer's disease that correlated negatively with the results of the screening tests. In addition, a decrease in Theta synchronization of similar localization was found that correlated with MOCA testing. Additionally, an increase in Alpha synchronization was evidenced in the entire population that correlated positively with MOCA results.
dc.descriptionLista de tablas y figuras 7 -- Introducción 9 -- Planteamiento del problema 11 -- Pregunta problema 17 -- Objetivos 18 -- Objetivo General 18 -- Objetivo Específicos 18 -- Justificación -- 19 -- Marco Teórico 22 -- Una breve revisión histórica de los antecedentes en el estudio de la memoria 22 -- De la memoria a las espinas dendríticas 24 -- Procesos de memoria 26 -- Conectividad neural 26 -- Potenciación a largo plazo 28 -- Bases moleculares de la potenciación a largo plazo 30 -- Consolidación de la memoria 33 -- Cambios celulares en la consolidación 35 -- Consolidación en los sistemas corticales 37 -- Envejecimiento y alteraciones de memoria 39 -- Marco conceptual 41 -- Deterioro cognitivo leve y demencia 41 -- Deterioro cognitivo leve (DCL) 42 -- Enfermedad de Alzheimer 45 -- Criterios diagnósticos de la enfermedad de Alzheimer 46 -- Biomarcadores en enfermedad de Alzheimer 47 –- Biomarcador en imágenes cerebrales 47 -- Biomarcadores en LCR 53 -- Electroencefalograma como biomarcador de alteración cognitiva 57 -- Estado del arte 61 -- Estudios del EEG en DCL y DA 61 -- Metodología 64 -- Tipo y Diseño de Investigación 64 -- Población y muestra 64 -- Población 64 -- Muestra 64 -- Valoración clínica 64 -- Valoración paraclínica 64 -- Valoración neuropsicológica 65 -- Clasificación de los grupos 69 -- Criterios de Inclusión 69 -- Criterios de Exclusión 69 -- Técnicas e instrumentos 70 -- Filtrado 72 -- Análisis del espectro de potencia 75 -- Análisis de sincronización: conectividad funcional 75 -- Procedimiento 77 -- Consideraciones Éticas 78 -- Cuadro de Variables 78 -- Resultados 80 -- Poder espectral: consideraciones metodológicas particulares 84 -- Resultados análisis de potencia 86 -- FOTOTEST 86 -- MOCA 90 -- Resultados análisis de conectividad funcional 93 -- Consideraciones metodológicas especiales 93 -- FOTOTEST 94 -- MOCA 98 -- Discusión 111 -- Conectividad funcional 118 -- Conclusiones 124 -- Limitaciones 125 -- Recomendaciones 126 -- Direcciones futuras 126 -- Referencias 127 --
dc.descriptionDoctor(a) en Neurociencia Cognitiva Aplicada
dc.descriptionDoctorado
dc.format185 páginas
dc.formatapplication/pdf
dc.formatapplication/pdf
dc.languagespa
dc.publisherCorporación Universidad de la Costa
dc.publisherCiencias Humanas y Sociales
dc.publisherBarranquilla, Colombia
dc.publisherDoctorado en Neurociencia Cognitiva Aplicada
dc.relation2021 Alzheimer’s disease facts and figures. (2021). Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 17(3), 327-406. https://doi.org/10.1002/alz.12328
dc.relation280920-boletines-poblacionales-adulto-mayorI-2020.pdf. (s. f.). Recuperado 15 de marzo de 2022, de https://www.minsalud.gov.co/sites/rid/Lists/BibliotecaDigital/RIDE/DE/PS/280920-boletines-poblacionales-adulto-mayorI-2020.pdf
dc.relationAdler, G., Brassen, S., & Jajcevic, A. (2003). EEG coherence in Alzheimer’s dementia. Journal of Neural Transmission (Vienna, Austria: 1996), 110(9), 1051-1058. https://doi.org/10.1007/s00702-003-0024-8
dc.relationAggarwal, N. T. (2005). Mild cognitive impairment in different functional domains and incident Alzheimer’s disease. Journal of Neurology, Neurosurgery & Psychiatry, 76(11), 1479-1484. https://doi.org/10.1136/jnnp.2004.053561
dc.relationAhmed, R. M., Paterson, R. W., Warren, J. D., Zetterberg, H., O’Brien, J. T., Fox, N. C., Halliday, G. M., & Schott, J. M. (2014). Biomarkers in dementia: Clinical utility and new directions. Journal of Neurology, Neurosurgery & Psychiatry, 85(12), 1426-1434. https://doi.org/10.1136/jnnp-2014-307662
dc.relationAlbert, M. S., DeKosky, S. T., Dickson, D., Dubois, B., Feldman, H. H., Fox, N. C., Gamst, A., Holtzman, D. M., Jagust, W. J., Petersen, R. C., Snyder, P. J., Carrillo, M. C., Thies, B., & Phelps, C. H. (2011a). The diagnosis of mild cognitive impairment due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s and Dementia, 7(3), 270-279. Scopus. https://doi.org/10.1016/j.jalz.2011.03.008
dc.relationAlbert, M. S., DeKosky, S. T., Dickson, D., Dubois, B., Feldman, H. H., Fox, N. C., Gamst, A., Holtzman, D. M., Jagust, W. J., Petersen, R. C., Snyder, P. J., Carrillo, M. C., Thies, B., & Phelps, C. H. (2011b). The diagnosis of mild cognitive impairment due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s & Dementia, 7(3), 270-279. https://doi.org/10.1016/j.jalz.2011.03.008
dc.relationAl-Nuaimi, A. H. H., Jammeh, E., Sun, L., & Ifeachor, E. (2018). Complexity Measures for Quantifying Changes in Electroencephalogram in Alzheimer’s Disease. Complexity, 2018, e8915079. https://doi.org/10.1155/2018/8915079
dc.relationAl-Nuaimi, A. H., Jammeh, E., Sun, L., & Ifeachor, E. (2015). Tsallis entropy as a biomarker for detection of Alzheimer’s disease. 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 4166-4169
dc.relationAl-nuaimi, A. H., Jammeh, E., Sun, L., & Ifeachor, E. (2017). Higuchi fractal dimension of the electroencephalogram as a biomarker for early detection of Alzheimer’s disease. 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2320-2324. https://doi.org/10.1109/EMBC.2017.8037320
dc.relationAltomare, D., Caprioglio, C., Assal, F., Allali, G., Mendes, A., Ribaldi, F., Ceyzeriat, K., Martins, M., Tomczyk, S., Stampacchia, S., Dodich, A., Boccardi, M., Chicherio, C., Frisoni, G. B., & Garibotto, V. (2021). Diagnostic value of amyloid-PET and tau-PET: A head-to-head comparison. European Journal of Nuclear Medicine and Molecular Imaging, 48(7), 2200-2211. Scopus. https://doi.org/10.1007/s00259-021-05246-x
dc.relationAlzheimer’s Association. (2014). 2014 Alzheimer’s disease facts and figures. Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 10(2), e47-92.
dc.relationAndersson, E., Janelidze, S., Lampinen, B., Nilsson, M., Leuzy, A., Stomrud, E., Blennow, K., Zetterberg, H., & Hansson, O. (2020). Blood and cerebrospinal fluid neurofilament light differentially detect neurodegeneration in early Alzheimer’s disease. Neurobiology of Aging, 95, 143-153. https://doi.org/10.1016/j.neurobiolaging.2020.07.018
dc.relationArango-Lasprilla, J. C., Rivera, D., Garza, M. T., Saracho, C. P., Rodríguez, W., Rodríguez-Agudelo, Y., Aguayo, A., Schebela, S., Luna, M., Longoni, M., Martínez, C., Doyle, S., Ocampo-Barba, N., Galarza-del-Angel, J., Aliaga, A., Bringas, M., Esenarro, L., García-Egan, P., & Perrin, P. B. (2015). Hopkins Verbal Learning Test– Revised: Normative data for the Latin American Spanish speaking adult population. NeuroRehabilitation, 37(4), 699-718. https://doi.org/10.3233/NRE-151286
dc.relationAron, L., & Yankner, B. A. (2016). Neural synchronization in Alzheimer’s disease. Nature, 540(7632), Art. 7632. https://doi.org/10.1038/540207a
dc.relationArráez-Aybar, L.-A., Navia-Álvarez, P., Fuentes-Redondo, T., & Bueno-López, J.-L. (2015). Thomas Willis, a pioneer in translational research in anatomy (on the 350th anniversary of Cerebri anatome). Journal of Anatomy, 226(3), 289-300. https://doi.org/10.1111/joa.12273
dc.relationAshburner, J., & Friston, K. J. (2000). Voxel-based morphometry—The methods. NeuroImage, 11(6 Pt 1), 805-821. https://doi.org/10.1006/nimg.2000.0582
dc.relationAssociation, A. P. (2014). Guía de consulta de los criterios diagnósticos del DSM-5®: Spanish Edition of the Desk Reference to the Diagnostic Criteria From DSM-5®. American Psychiatric Pub.
dc.relationÁvila, G. M. R. (2007). Sincronizando con el caos. REBOLDES.
dc.relationAxmacher, N., & Rasch, B. (2017). Cognitive neuroscience of memory consolidation. Springer.
dc.relationBabiloni, C., Arakaki, X., Azami, H., Bennys, K., Blinowska, K., Bonanni, L., Bujan, A., Carrillo, M. C., 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., … Guntekin, B. (2021). Measures of resting state EEG rhythms for clinical trials in Alzheimer’s disease: Recommendations of an expert panel. Alzheimer’s & Dementia, 17(9), 1528-1553. https://doi.org/10.1002/alz.12311
dc.relationBabiloni, C., Barry, R. J., Başar, E., Blinowska, K. J., Cichocki, A., Drinkenburg, W. H. I. M., Klimesch, W., Knight, R. T., Lopes da Silva, F., Nunez, P., Oostenveld, R., Jeong, J., Pascual-Marqui, R., Valdes-Sosa, P., & Hallett, M. (2020). International Federation of Clinical Neurophysiology (IFCN) – EEG research workgroup: Recommendations on frequency and topographic analysis of resting state EEG rhythms. Part 1: Applications in clinical research studies. Clinical Neurophysiology, 131(1), 285-307. https://doi.org/10.1016/j.clinph.2019.06.234
dc.relationBabiloni, C., Binetti, G., Cassarino, A., Dal Forno, G., Del Percio, C., Ferreri, F., Ferri, R., Frisoni, G., Galderisi, S., Hirata, K., Lanuzza, B., Miniussi, C., Mucci, A., Nobili, F., Rodriguez, G., Luca Romani, G., & Rossini, P. M. (2006). Sources of cortical rhythms in adults during physiological aging: A multicentric EEG study. Human Brain Mapping, 27(2), 162-172. https://doi.org/10.1002/hbm.20175
dc.relationBabiloni, C., Del Percio, C., Caroli, A., Salvatore, E., Nicolai, E., Marzano, N., Lizio, R., Cavedo, E., Landau, S., Chen, K., Jagust, W., Reiman, E., Tedeschi, G., Montella, P., De Stefano, M., Gesualdo, L., Frisoni, G. B., & Soricelli, A. (2016). Cortical sources of resting state EEG rhythms are related to brain hypometabolism in subjects with Alzheimer’s disease: An EEG-PET study. Neurobiology of Aging, 48, 122-134. https://doi.org/10.1016/j.neurobiolaging.2016.08.021
dc.relationBabiloni, C., Del Percio, C., Lizio, R., Noce, G., Cordone, S., Lopez, S., Soricelli, A., Ferri, R., Pascarelli, M. T., Nobili, F., Arnaldi, D., Famà, F., Aarsland, D., Orzi, F., Buttinelli, C., Giubilei, F., Onofrj, M., Stocchi, F., Stirpe, P., … De Pandis, M. F. (2017). Abnormalities of Cortical Neural Synchronization Mechanisms in Subjects with Mild Cognitive Impairment due to Alzheimer’s and Parkinson’s Diseases: An EEG Study. Journal of Alzheimer’s Disease, 59(1), 339-358. https://doi.org/10.3233/JAD-160883
dc.relationBabiloni, C., Del Percio, C., Lizio, R., Noce, G., Lopez, S., Soricelli, A., Ferri, R., Pascarelli, M. T., Catania, V., Nobili, F., Arnaldi, D., Famà, F., Orzi, F., Buttinelli, C., Giubilei, F., Bonanni, L., Franciotti, R., Onofrj, M., Stirpe, P., … Stocchi, F. (2018). Functional cortical source connectivity of resting state electroencephalographic alpha rhythms shows similar abnormalities in patients with mild cognitive impairment due to Alzheimer’s and Parkinson’s diseases. Clinical Neurophysiology, 129(4), 766-782. https://doi.org/10.1016/j.clinph.2018.01.009
dc.relationBabiloni, C., Ferri, R., Binetti, G., Vecchio, F., Frisoni, G. B., Lanuzza, B., Miniussi, C., Nobili, F., Rodriguez, G., Rundo, F., Cassarino, A., Infarinato, F., Cassetta, E., Salinari, S., Eusebi, F., & Rossini, P. M. (2009). Directionality of EEG synchronization in Alzheimer’s disease subjects. Neurobiology of Aging, 30(1), 93-102. https://doi.org/10.1016/j.neurobiolaging.2007.05.007
dc.relationBabiloni, C., Frisoni, G. B., Pievani, M., Vecchio, F., Lizio, R., Buttiglione, M., Geroldi, C., Fracassi, C., Eusebi, F., Ferri, R., & Rossini, P. M. (2009). Hippocampal volume and cortical sources of EEG alpha rhythms in mild cognitive impairment and Alzheimer disease. NeuroImage, 44(1), 123-135. https://doi.org/10.1016/j.neuroimage.2008.08.005
dc.relationBajo, R., Castellanos, N. P., Cuesta, P., Aurtenetxe, S., Garcia-Prieto, J., Gil-Gregorio, P., del-Pozo, F., & Maestu, F. (2012). Differential Patterns of Connectivity in Progressive Mild Cognitive Impairment. Brain Connectivity, 2(1), 21-24. https://doi.org/10.1089/brain.2011.0069
dc.relationBalderas, I., Ramírez-Amaya, V., & Bermúdez-Rattoni, F. (2004). [Memory-linked morphological changes]. Revista De Neurologia, 38(10), 944-948.
dc.relationBarco, A., Alarcon, J. M., & Kandel, E. R. (2002). Expression of constitutively active CREB protein facilitates the late phase of long-term potentiation by enhancing synaptic capture. Cell, 108(5), 689-703.
dc.relationBarco, A., & Marie, H. (2011). Genetic approaches to investigate the role of CREB in neuronal plasticity and memory. Molecular neurobiology, 44(3), 330-349.
dc.relationBartus, R. T., Dean, R. L., Beer, B., & Lippa, A. S. (1982). The cholinergic hypothesis of geriatric memory dysfunction. Science (New York, N.Y.), 217(4558), 408-414. https://doi.org/10.1126/science.7046051
dc.relationBateman, R. J., Xiong, C., Benzinger, T. L. S., Fagan, A. M., Goate, A., Fox, N. C., Marcus, D. S., Cairns, N. J., Xie, X., Blazey, T. M., Holtzman, D. M., Santacruz, A., Buckles, V., Oliver, A., Moulder, K., Aisen, P. S., Ghetti, B., Klunk, W. E., McDade, E., … Morris, J. C. (2012). Clinical and Biomarker Changes in Dominantly Inherited Alzheimer’s Disease. New England Journal of Medicine, 367(9), 795-804. https://doi.org/10.1056/NEJMoa1202753
dc.relationBauer, R. M., Grande, L., & Valenstein, E. (2003). Amnesic disorders.
dc.relationBenussi, A., Cantoni, V., Grassi, M., Brechet, L., Michel, C. M., Datta, A., Thomas, C., Gazzina, S., Cotelli, M. S., Bianchi, M., Premi, E., Gadola, Y., Cotelli, M., Pengo, M., Perrone, F., Scolaro, M., Archetti, S., Solje, E., Padovani, A., … Borroni, B. (2022). Increasing Brain Gamma Activity Improves Episodic Memory and Restores Cholinergic Dysfunction in Alzheimer’s Disease. Annals of Neurology, 92(2), 322-334. Scopus. https://doi.org/10.1002/ana.26411
dc.relationBesthorn, C., Sattel, H., Geiger-Kabisch, C., Zerfass, R., & Förstl, H. (1995). Parameters of EEG dimensional complexity in Alzheimer’s disease. Electroencephalography and Clinical Neurophysiology, 95(2), 84-89. https://doi.org/10.1016/0013-4694(95)00050-9
dc.relationBethus, I., Tse, D., & Morris, R. G. (2010). Dopamine and memory: Modulation of the persistence of memory for novel hippocampal NMDA receptor-dependent paired associates. Journal of Neuroscience, 30(5), 1610-1618.
dc.relationBiomarkers Definitions Working Group. (2001). Biomarkers and surrogate endpoints: Preferred definitions and conceptual framework. Clinical Pharmacology and Therapeutics, 69(3), 89-95. https://doi.org/10.1067/mcp.2001.113989
dc.relationBlack, M. M., & Baas, P. W. (1989). The basis of polarity in neurons. Trends in Neurosciences, 12(6), 211-214. https://doi.org/10.1016/0166-2236(89)90124-0
dc.relationBlennow, K., Dubois, B., Fagan, A. M., Lewczuk, P., de Leon, M. J., & Hampel, H. (2015). Clinical utility of cerebrospinal fluid biomarkers in the diagnosis of early Alzheimer’s disease. Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 11(1), 58-69. https://doi.org/10.1016/j.jalz.2014.02.004
dc.relationBlennow, K., Vanmechelen, E., & Hampel, H. (2001). CSF total tau, Abeta42 and phosphorylated tau protein as biomarkers for Alzheimer’s disease. Molecular Neurobiology, 24(1-3), 87-97. https://doi.org/10.1385/MN:24:1-3:087
dc.relationBlennow, K., Wallin, A., Agren, H., Spenger, C., Siegfried, J., & Vanmechelen, E. (1995). Tau protein in cerebrospinal fluid: A biochemical marker for axonal degeneration in Alzheimer disease? Molecular and Chemical Neuropathology, 26(3), 231-245. https://doi.org/10.1007/BF02815140
dc.relationBlennow, K., & Zetterberg, H. (2015). Understanding biomarkers of neurodegeneration: Ultrasensitive detection techniques pave the way for mechanistic understanding. Nature Medicine, 21(3), 217-219. https://doi.org/10.1038/nm.3810
dc.relationBliss, T. V., & Collingridge, G. L. (1993). A synaptic model of memory: Long-term potentiation in the hippocampus. Nature, 361(6407), 31-39. https://doi.org/10.1038/361031a0
dc.relationBliss, T. V. P., & Cooke, S. F. (2011). Long-term potentiation and long-term depression: A clinical perspective. Clinics, 66(Suppl 1), 3-17. https://doi.org/10.1590/S1807-59322011001300002
dc.relationBlom, E. S., Giedraitis, V., Zetterberg, H., Fukumoto, H., Blennow, K., Hyman, B. T., Irizarry, M. C., Wahlund, L.-O., Lannfelt, L., & Ingelsson, M. (2009). Rapid progression from mild cognitive impairment to Alzheimer’s disease in subjects with elevated levels of tau in cerebrospinal fluid and the APOE epsilon4/epsilon4 genotype. Dementia and Geriatric Cognitive Disorders, 27(5), 458-464. https://doi.org/10.1159/000216841
dc.relationBoada, M., Cejudo, J. C., Tàrraga, L., López, O. L., & Kaufer, D. (2002). Neuropsychiatric Inventory Questionnaire (NPI-Q): Spanish validation of a brief clinical form of the Neuropsychiatric Inventory (NPI). Neurologia, 17(6), 317-323. Scopus.
dc.relationBozzali, M., Filippi, M., Magnani, G., Cercignani, M., Franceschi, M., Schiatti, E., Castiglioni, S., Mossini, R., Falautano, M., Scotti, G., Comi, G., & Falini, A. (2006). The contribution of voxel-based morphometry in staging patients with mild cognitive impairment. Neurology, 67(3), 453-460. https://doi.org/10.1212/01.wnl.0000228243.56665.c2
dc.relationBraak, H., & Braak, E. (1991). Neuropathological stageing of Alzheimer-related changes. Acta Neuropathologica, 82(4), 239-259. https://doi.org/10.1007/BF00308809
dc.relationBrandt, J. (1991). The Hopkins Verbal Learning Test: Development of a new memory test with six equivalent forms. The clinical neuropsychologist, 5(2), 125-142.
dc.relationBrandt, J., & Benedict, R. H. (2001). Hopkins verbal learning test—Revised: Professional manual. Psychological Assessment Resources.
dc.relationBrenner, R. P., Ulrich, R. F., Spiker, D. G., Sclabassi, R. J., Reynolds, C. F., Marin, R. S., & Boller, F. (1986). Computerized EEG spectral analysis in elderly normal, demented and depressed subjects. Electroencephalography and Clinical Neurophysiology, 64(6), 483-492. https://doi.org/10.1016/0013-4694(86)90184-7
dc.relationBrier, M. R., Thomas, J. B., Snyder, A. Z., Benzinger, T. L., Zhang, D., Raichle, M. E., Holtzman, D. M., Morris, J. C., & Ances, B. M. (2012). Loss of intranetwork and internetwork resting state functional connections with Alzheimer’s disease progression. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience, 32(26), 8890-8899. https://doi.org/10.1523/JNEUROSCI.5698-11.2012
dc.relationBuckner, R. L. (2012). The serendipitous discovery of the brain’s default network. NeuroImage, 62(2), 1137-1145. https://doi.org/10.1016/j.neuroimage.2011.10.035
dc.relationBusse, A., Angermeyer, M. C., & Riedel-Heller, S. G. (2006). Progression of mild cognitive impairment to dementia: A challenge to current thinking. The British Journal of Psychiatry: The Journal of Mental Science, 189, 399-404. https://doi.org/10.1192/bjp.bp.105.014779
dc.relationBuzsáki, G. (2002). Theta Oscillations in the Hippocampus. Neuron, 33(3), 325-340. https://doi.org/10.1016/S0896-6273(02)00586-X
dc.relationCabeza, R., & Nyberg, L. (2000). Imaging cognition II: An empirical review of 275 PET and fMRI studies. Journal of Cognitive Neuroscience, 12(1), 1-47. Scopus. https://doi.org/10.1162/08989290051137585
dc.relationCacho, J., García-García, R., Arcaya, J., Vicente, J. L., & Lantada, N. (1999). Una propuesta de aplicación y puntuación del test del reloj en la enfermedad de Alzheimer. Rev Neurol, 28(7), 648-655.
dc.relationCajal, S. R. (1890). Textura de las circunvolutiones cerebrales de los mamíferos inferiores: Nota preventiva.
dc.relationCajal, S. R. Y. (1894). The Croonian Lecture: La Fine Structure des Centres Nerveux. Proceedings of the Royal Society of London, 55(331-335), 444-468. https://doi.org/10.1098/rspl.1894.0063
dc.relationCajal, S. R. y. (1899). Textura del sistema nervioso del hombre y de los vertebrados: Estudios sobre el plan estructural y composición histológica de los centros nerviosos adicionados de consideraciones fisiológicas fundadas en los nuevos descubrimentos. N. Moya.
dc.relationCajal, S. R. y. (2012). Texture of the Nervous System of Man and the Vertebrates. Springer Science & Business Media.
dc.relationCajal, S. R. y, & Cajal, C. S. de I. C. (Spain) I. R. y. (1952). Neuronismo o reticularismo?: Las pruebas objetivas de la unidad anatomica de las celulas nerviosas. Edicion preparada por el Instituto Cajal con motivo del primer centenario de su fundador y maestro.
dc.relationCamozzato, A. L., Godinho, C., Kochhann, R., Massochini, G., & Chaves, M. L. (2015). Validity of the Brazilian version of the Neuropsychiatric Inventory Questionnaire (NPI-Q). Arquivos de Neuro-Psiquiatria, 73(1), 41-45. Scopus. https://doi.org/10.1590/0004-282X20140177
dc.relationCan, S. S., Gencay-Can, A., & Gunendi, Z. (2012). Validity and reliability of the clock drawing test as a screening tool for cognitive impairment in patients with fibromyalgia. Comprehensive psychiatry, 53(1), 81-86.
dc.relationCarnero Pardo, C. (2011). El FOTOTEST en el cribado de demencia en atención primaria. Revista de Neurología, 52(10), 639. https://doi.org/10.33588/rn.5210.2010808
dc.relationCarnero Pardo, C., Sáez-Zea, C., Montiel Navarro, L., Del Saz, P., Feria Vilar, I., Pérez-Navarro, M. J., Ruiz-Giménez, J., Vilchez-Carrillo, R., & Montoro-Rios, M. T. (2007). Diagnostic accuracy of the Phototest for cognitive impairment and dementia. Neurologia, 22(10), 860-869. Scopus.
dc.relationCarnero-Pardo, C., Sáez-Zea, C., Montiel-Navarro, L., Feria-Vilar, I., & Gurpegui, M. (2011). Estudio normativo y de fiabilidad del FOTOTEST. Neurología, 26(1), 20-25. https://doi.org/10.1016/j.nrl.2010.09.021
dc.relationCasadio, A., Martin, K. C., Giustetto, M., Zhu, H., Chen, M., Bartsch, D., Bailey, C. H., & Kandel, E. R. (1999). A transient, neuron-wide form of CREB-mediated long-term facilitation can be stabilized at specific synapses by local protein synthesis. Cell, 99(2), 221-237.
dc.relationCassani, R., Estarellas, M., San-Martin, R., Fraga, F. J., & Falk, T. H. (2018). Systematic Review on Resting-State EEG for Alzheimer’s Disease Diagnosis and Progression Assessment. Disease Markers, 2018, e5174815. https://doi.org/10.1155/2018/5174815
dc.relationCasula, E. P., Pellicciari, M. C., Bonnì, S., Borghi, I., Maiella, M., Assogna, M., Minei, M., Motta, C., D’Acunto, A., Porrazzini, F., Pezzopane, V., Mencarelli, L., Roncaioli, A., Rocchi, L., Spampinato, D. A., Caltagirone, C., Santarnecchi, E., Martorana, A., & Koch, G. (2022). Decreased Frontal Gamma Activity in Alzheimer Disease Patients. Annals of Neurology, 92(3), 464-475. Scopus. https://doi.org/10.1002/ana.26444
dc.relationCavedo, E., Boccardi, M., Ganzola, R., Canu, E., Beltramello, A., Caltagirone, C., Thompson, P. M., & Frisoni, G. B. (2011). Local amygdala structural differences with 3T MRI in patients with Alzheimer disease. Neurology, 76(8), 727-733. https://doi.org/10.1212/WNL.0b013e31820d62d9
dc.relationCecchetti, G., Agosta, F., Basaia, S., Cividini, C., Cursi, M., Santangelo, R., Caso, F., Minicucci, F., Magnani, G., & Filippi, M. (2021). Resting-state electroencephalographic biomarkers of Alzheimer’s disease. NeuroImage: Clinical, 31. Scopus. https://doi.org/10.1016/j.nicl.2021.102711
dc.relationCerebri anatome: Cui accessit Nervorum descriptio & usus. (1676). apud Joannem Maximilianum Lucas.
dc.relationChandra, A., Dervenoulas, G., Politis, M., & for, the A. D. N. I. (2019). Magnetic resonance imaging in Alzheimer’s disease and mild cognitive impairment. Journal of Neurology, 266(6), 1293-1302. Scopus. https://doi.org/10.1007/s00415-018-9016-3
dc.relationChen, A. C., Feng, W., Zhao, H., Yin, Y., & Wang, P. (2008). EEG default mode network in the human brain: Spectral regional field powers. Neuroimage, 41(2), 561-574.
dc.relationChoi, J., Ku, B., You, Y. G., Jo, M., Kwon, M., Choi, Y., Jung, S., Ryu, S., Park, E., Go, H., Kim, G., Cha, W., & Kim, J. U. (2019). Resting-state prefrontal EEG biomarkers in correlation with MMSE scores in elderly individuals. Scientific Reports, 9(1). Scopus. https://doi.org/10.1038/s41598-019-46789-2
dc.relationCieslak, A., Smith, E. E., Lysack, J., & Ismail, Z. (2017). Case series of mild behavioral impairment: Toward an understanding of the early stages of neurodegenerative diseases affecting behavior and cognition. International Psychogeriatrics, 1-8. https://doi.org/10.1017/S1041610217001855
dc.relationClute-Reinig, N., Jayadev, S., Rhoads, K., & Le Ny, A.-L. (2021). Alzheimer’s Disease Diagnostics Must Be Globally Accessible. Journal of Alzheimer’s Disease: JAD, 84(4), 1453-1455. https://doi.org/10.3233/JAD-210663
dc.relationConstitución de Colombia. (1991). ConstitucionColombia.com. https://www.constitucioncolombia.com/titulo-2/capitulo-2/articulo-46
dc.relationCounter, S. A., Buchanan, L. H., & Ortega, F. (2009). Neurophysiologic and neurocognitive case profiles of andean patients with chronic environmental lead poisoning. Journal of Toxicology and Environmental Health - Part A: Current Issues, 72(19), 1150-1159. Scopus. https://doi.org/10.1080/15287390903091772
dc.relationCoutanche, M. N., & Thompson-Schill, S. L. (2015). Rapid consolidation of new knowledge in adulthood via fast mapping. Trends in cognitive sciences, 19(9), 486-488.
dc.relationCowansage, K. K., Shuman, T., Dillingham, B. C., Chang, A., Golshani, P., & Mayford, M. (2014). Direct reactivation of a coherent neocortical memory of context. Neuron, 84(2), 432-441.
dc.relationCuesta, P., Ochoa-Urrea, M., Funke, M., Hasan, O., Zhu, P., Marcos, A., López, M. E., Schulz, P. E., Lhatoo, S., Pantazis, D., Mosher, J. C., & Maestu, F. (2022). Gamma band functional connectivity reduction in patients with amnestic mild cognitive impairment and epileptiform activity. Brain Communications, 4(2). Scopus. https://doi.org/10.1093/braincomms/fcac012
dc.relationCuesta Prieto, P. (2015). Perfiles biomagnéticos de la actividad en reposo cerebral en las fases preclínica y prodrómica de la Enfermedad de Alzheimer: Influencia del alelo APOE-ε4 y de la acumulación de β-amiloide [Http://purl.org/dc/dcmitype/Text, Universidad Complutense de Madrid]. https://dialnet.unirioja.es/servlet/tesis?codigo=100398
dc.relationDauwels, J., Srinivasan, K., Ramasubba Reddy, M., Musha, T., Vialatte, F.-B., Latchoumane, C., Jeong, J., & Cichocki, A. (2011). Slowing and Loss of Complexity in Alzheimer’s EEG: Two Sides of the Same Coin? International Journal of Alzheimer’s Disease, 2011, e539621. https://doi.org/10.4061/2011/539621
dc.relationDavachi, L., & DuBrow, S. (2015). How the hippocampus preserves order: The role of prediction and context. Trends in cognitive sciences, 19(2), 92-99.
dc.relationDavis, D. H. J., Creavin, S. T., Yip, J. L. Y., Noel-Storr, A. H., Brayne, C., & Cullum, S. (2021). Montreal Cognitive Assessment for the detection of dementia. Cochrane Database of Systematic Reviews, 2021(7). Scopus. https://doi.org/10.1002/14651858.CD010775.pub3
dc.relationDavis, H. P., & Squire, L. R. (1984). Protein synthesis and memory: A review. Psychological bulletin, 96(3), 518.
dc.relationDe Carlos, J. A., & Borrell, J. (2007). A historical reflection of the contributions of Cajal and Golgi to the foundations of neuroscience. Brain Research Reviews, 55(1), 8-16. https://doi.org/10.1016/j.brainresrev.2007.03.010
dc.relationde Frutos-Lucas, J., Cuesta, P., Ramírez-Toraño, F., Nebreda, A., Cuadrado-Soto, E., Peral-Suárez, Á., Lopez-Sanz, D., Bruña, R., Marcos-de Pedro, S., Delgado-Losada, M. L., López-Sobaler, A. M., Concepción Rodríguez-Rojo, I., Barabash, A., Serrano Rodriguez, J. M., Laws, S. M., Dolado, A. M., López-Higes, R., Brown, B. M., & Maestú, F. (2020). Age and APOE genotype affect the relationship between objectively measured physical activity and power in the alpha band, a marker of brain disease. Alzheimer’s Research & Therapy, 12, 113. https://doi.org/10.1186/s13195-020-00681-8
dc.relationde Jong, L. W., van der Hiele, K., Veer, I. M., Houwing, J. J., Westendorp, R. G. J., Bollen, E. L. E. M., de Bruin, P. W., Middelkoop, H. A. M., van Buchem, M. A., & van der Grond, J. (2008). Strongly reduced volumes of putamen and thalamus in Alzheimer’s disease: An MRI study. Brain, 131(12), 3277-3285. https://doi.org/10.1093/brain/awn278
dc.relationDe La Torre, J. C. (2012). Cardiovascular risk factors promote brain hypoperfusion leading to cognitive decline and dementia. Cardiovascular Psychiatry and Neurology. Scopus. https://doi.org/10.1155/2012/367516
dc.relationde Sánchez, C. R., Nariño, D., & Cerón, J. F. M. (2010). Epidemiología y carga de la Enfermedad de Alzheimer. Acta Neurol Colomb, 26(3), 1.
dc.relationDeFelipe, J. (2015a). The dendritic spine story: An intriguing process of discovery. Frontiers in Neuroanatomy, 9, 14. https://doi.org/10.3389/fnana.2015.00014
dc.relationDeFelipe, J. (2015b). The dendritic spine story: An intriguing process of discovery. Frontiers in Neuroanatomy, 9, 14. https://doi.org/10.3389/fnana.2015.00014
dc.relationDelbeuck, X., Van der Linden, M., & Collette, F. (2003). Alzheimer’ Disease as a Disconnection Syndrome? Neuropsychology Review, 13(2), 79-92. https://doi.org/10.1023/A:1023832305702
dc.relationDelgado Derio, C., Guerrero Bonnet, S., Troncoso Ponce, M., Araneda Yañez, A., Slachevsky Chonchol, A., & Behrens Pellegrino, M. I. (2013). Memoria, fluidez y orientación: Prueba de cribado de deterioro cognitivo en 5 minutos. Neurología, 28(7), 400-407. https://doi.org/10.1016/j.nrl.2012.10.001
dc.relationDemencia. (2020, septiembre 21). https://www.who.int/es/news-room/fact-sheets/detail/dementia
dc.relationDevos, H., Gustafson, K., Liao, K., Ahmadnezhad, P., Estes, B., Martin, L. E., Mahnken, J. D., Brooks, W. M., & Burns, J. M. (2022). EEG/ERP evidence of possible hyperexcitability in older adults with elevated beta-amyloid. Translational Neurodegeneration, 11(1). Scopus. https://doi.org/10.1186/s40035-022-00282-5
dc.relationDíaz Cabezas, R., Marulanda Mejía, F., Arias, M., & Helena, M. (2013). Prevalence of cognitive impairment and dementia in people older 65 years in a Colombian urban population. Acta Neurológica Colombiana, 29(3), 141-151.
dc.relationDierks, T., Jelic, V., Pascual-Marqui, R. D., Wahlund, L.-O., Julin, P., Linden, D. E. J., Maurer, K., Winblad, B., & Nordberg, A. (2000). Spatial pattern of cerebral glucose metabolism (PET) correlates with localization of intracerebral EEG-generators in Alzheimer’s disease. Clinical Neurophysiology, 111(10), 1817-1824. Scopus. https://doi.org/10.1016/S1388-2457(00)00427-2
dc.relationDong, Y., Sharma, V. K., Chan, B. P.-L., Venketasubramanian, N., Teoh, H. L., Seet, R. C. S., Tanicala, S., Chan, Y. H., & Chen, C. (2010). The Montreal Cognitive Assessment (MoCA) is superior to the Mini-Mental State Examination (MMSE) for the detection of vascular cognitive impairment after acute stroke. Journal of the Neurological Sciences, 299(1-2), 15-18. https://doi.org/10.1016/j.jns.2010.08.051
dc.relationDringenberg, H. C. (2000). Alzheimer’s disease: More than a ‘cholinergic disorder’ — evidence that cholinergic–monoaminergic interactions contribute to EEG slowing and dementia. Behavioural Brain Research, 115(2), 235-249. https://doi.org/10.1016/S0166-4328(00)00261-8
dc.relationDu, A. T., Schuff, N., Kramer, J. H., Ganzer, S., Zhu, X. P., Jagust, W. J., Miller, B. L., Reed, B. R., Mungas, D., Yaffe, K., Chui, H. C., & Weiner, M. W. (2004). Higher atrophy rate of entorhinal cortex than hippocampus in AD. Neurology, 62(3), 422-427. https://doi.org/10.1212/01.wnl.0000106462.72282.90
dc.relationEichenbaum, H. (2011). The Cognitive Neuroscience of Memory: An Introduction. Oxford University Press, USA.
dc.relationElwood, R. W. (1991). The Wechsler Memory Scale—Revised: Psychometric characteristics and clinical application. Neuropsychology review, 2(2), 179-201.
dc.relationEmsell, L., Vanhaute, H., Vansteelandt, K., De Winter, F.-L., Christiaens, D., Van den Stock, J., Vandenberghe, R., Van Laere, K., Sunaert, S., Bouckaert, F., & Vandenbulcke, M. (2022). An optimized MRI and PET based clinical protocol for improving the differential diagnosis of geriatric depression and Alzheimer’s disease. Psychiatry Research - Neuroimaging, 320. Scopus. https://doi.org/10.1016/j.pscychresns.2022.111443
dc.relationEnvejecimiento y salud. (2022, octubre 1). https://www.who.int/es/news-room/fact-sheets/detail/ageing-and-health
dc.relationEstudio FOTOTRANS: estudio multicéntrico sobre la validez del FOTOTEST en condiciones de práctica clínica | Neurología. (s. f.). Recuperado 10 de marzo de 2022, de https://www.elsevier.es/es-revista-neurologia-295-articulo-estudio-fototrans-estudio-multicentrico-sobre-S021348531100260X
dc.relationFazekas, F. (1989). Magnetic resonance signal abnormalities in asymptomatic individuals: Their incidence and functional correlates. European Neurology, 29(3), 164-168. https://doi.org/10.1159/000116401
dc.relationFonseca, L. C., Tedrus, G. M., Prandi, L. R., Almeida, A. M., & Furlanetto, D. S. (2011). Alzheimer’s disease: Relationship between cognitive aspects and power and coherence EEG measures. Arquivos de Neuro-Psiquiatria, 69(6), 875-881. Scopus. https://doi.org/10.1590/s0004-282x2011000700005
dc.relationFOTOTEST online. (s. f.). Recuperado 25 de julio de 2022, de https://www.hipocampo.org/FOTOTESTOnline/FOTOTEST-enlinea.asp
dc.relationFox, C. A., & Barnard, J. W. (1957). A quantitative study of the Purkinje cell dendritic branchlets and their relationship to afferent fibres. Journal of Anatomy, 91(3), 299-313.
dc.relationFrank, D. A., & Greenberg, M. E. (1994). CREB: a mediator of long-term memory from mollusks to mammals. Cell, 79(1), 5-8.
dc.relationFrey, U., & Morris, R. G. (1998). Synaptic tagging: Implications for late maintenance of hippocampal long-term potentiation. Trends in neurosciences, 21(5), 181-188.
dc.relationFriston, K. J. (1994). Functional and effective connectivity in neuroimaging: A synthesis. Human Brain Mapping, 2(1-2), 56-78. https://doi.org/10.1002/hbm.460020107
dc.relationFuchs, M., Kastner, J., Wagner, M., Hawes, S., & Ebersole, J. S. (2002). A standardized boundary element method volume conductor model. Clinical Neurophysiology: Official Journal of the International Federation of Clinical Neurophysiology, 113(5), 702-712. https://doi.org/10.1016/s1388-2457(02)00030-5
dc.relationGallistel, C. R., & Matzel, L. D. (2013). The neuroscience of learning: Beyond the Hebbian synapse. Annual Review of Psychology, 64, 169-200. https://doi.org/10.1146/annurev-psych-113011-143807
dc.relationGanguli, M., Dodge, H. H., Shen, C., & DeKosky, S. T. (2004). Mild cognitive impairment, amnestic type: An epidemiologic study. Neurology, 63(1), 115-121.
dc.relationGarcía-Morales, P., Gich-Fullà, J., Guardia-Olmos, J., & Casanova, J. P. (1998). Series de dígitos, series automáticas y orientación: Normas ampliadas del Test Barcelona. Neurología (Barc., Ed. impr.), 13(S-6), 277-286.
dc.relationGarcía-Sánchez, J. E., García, E., & Lucila Merino, M. (2010). Cien años de la bala mágica del Dr. Ehrlich (1909–2009). Enfermedades Infecciosas y Microbiología Clínica, 28(8), 521-533. https://doi.org/10.1016/j.eimc.2009.07.009
dc.relationGasser, T., & Molinari, L. (1996). The analysis of the EEG. Statistical Methods in Medical Research, 5(1), 67-99. https://doi.org/10.1177/096228029600500105
dc.relationGe, Q., Lin, Z.-C., Gao, Y.-X., & Zhang, J.-X. (2020). A Robust Discriminant Framework Based on Functional Biomarkers of EEG and Its Potential for Diagnosis of Alzheimer’s Disease. Healthcare, 8(4), Art. 4. https://doi.org/10.3390/healthcare8040476
dc.relationGianotti, L. R. R., Künig, G., Lehmann, D., Faber, P. L., Pascual-Marqui, R. D., Kochi, K., & Schreiter-Gasser, U. (2007). Correlation between disease severity and brain electric LORETA tomography in Alzheimer’s disease. Clinical Neurophysiology: Official Journal of the International Federation of Clinical Neurophysiology, 118(1), 186-196. https://doi.org/10.1016/j.clinph.2006.09.007
dc.relationGili, T., Cercignani, M., Serra, L., Perri, R., Giove, F., Maraviglia, B., Caltagirone, C., & Bozzali, M. (2011). Regional brain atrophy and functional disconnection across Alzheimer’s disease evolution. Journal of Neurology, Neurosurgery, and Psychiatry, 82(1), 58-66. https://doi.org/10.1136/jnnp.2009.199935
dc.relationGolby, A., Silverberg, G., Race, E., Gabrieli, S., O’Shea, J., Knierim, K., Stebbins, G., & Gabrieli, J. (2005). Memory encoding in Alzheimer’s disease: An fMRI study of explicit and implicit memory. Brain: A Journal of Neurology, 128(Pt 4), 773-787. https://doi.org/10.1093/brain/awh400
dc.relationGómez, F. R., Guerrero, C. E. D., Bernal, G. B., Pongutá, J. P. C., & Olarte, J. L. R. (s. f.). Politica colombiana de envejecimiento humano y vejez 2015—2024. 54.
dc.relationGonzalez-Escamilla, G., Atienza, M., & Cantero, J. L. (2015). Impaired cortical oscillatory coupling in mild cognitive impairment: Anatomical substrate and ApoE4 effects. Brain Structure & Function, 220(3), 1721-1737. https://doi.org/10.1007/s00429-014-0757-1
dc.relationGordon, B. A., Najmi, S., Hsu, P., Roe, C. M., Morris, J. C., & Benzinger, T. L. (2015). The effects of white matter hyperintensities and amyloid deposition on Alzheimer dementia. NeuroImage: Clinical, 8, 246-252.
dc.relationGouveia, P. A. R., Brucki, S. M. D., Malheiros, S. M. F., & Bueno, O. F. A. (2007). Disorders in planning and strategy application in frontal lobe lesion patients. Brain and cognition, 63(3), 240-246.
dc.relationGray, E. G. (1959). Electron Microscopy of Synaptic Contacts on Dendrite Spines of the Cerebral Cortex. Nature, 183(4675), 1592-1593. https://doi.org/10.1038/1831592a0
dc.relationGreicius, M. D., Krasnow, B., Reiss, A. L., & Menon, V. (2003). Functional connectivity in the resting brain: A network analysis of the default mode hypothesis. Proceedings of the National Academy of Sciences, 100(1), 253-258. https://doi.org/10.1073/pnas.0135058100
dc.relationGreicius, M. D., Srivastava, G., Reiss, A. L., & Menon, V. (2004). Default-mode network activity distinguishes Alzheimer’s disease from healthy aging: Evidence from functional MRI. Proceedings of the National Academy of Sciences of the United States of America, 101(13), 4637-4642. https://doi.org/10.1073/pnas.0308627101
dc.relationGu, F., Meng, X., Shen, E., & Cai, Z. (2003). Can we measure consciousness with eeg complexities? International Journal of Bifurcation and Chaos, 13(03), 733-742. https://doi.org/10.1142/S0218127403006893
dc.relationHall, B., Mak, E., Cervenka, S., Aigbirhio, F. I., Rowe, J. B., & O’Brien, J. T. (2017). In vivo tau PET imaging in dementia: Pathophysiology, radiotracer quantification, and a systematic review of clinical findings. Ageing Research Reviews, 36, 50-63. Scopus. https://doi.org/10.1016/j.arr.2017.03.002
dc.relationHandayani, N., Haryanto, F., Khotimah, S. N., Arif, I., & Taruno, W. P. (2018). Coherence and phase synchrony analyses of EEG signals in Mild Cognitive Impairment (MCI): A study of functional brain connectivity. Polish Journal of Medical Physics and Engineering, 24(1), 1-9. Scopus. https://doi.org/10.2478/pjmpe-2018-0001
dc.relationHanslmayr, S., & Staudigl, T. (2014). How brain oscillations form memories—A processing based perspective on oscillatory subsequent memory effects. NeuroImage, 85, 648-655. https://doi.org/10.1016/j.neuroimage.2013.05.121
dc.relationHebb, D. O. (1949). The organization of behavior: A neuropsychological approach. John Wiley & Sons.
dc.relationHemmy, L. S., Linskens, E. J., Silverman, P. C., Miller, M. A., Talley, K. M. C., Taylor, B. C., Ouellette, J. M., Greer, N. L., Wilt, T. J., Butler, M., & Fink, H. A. (2020). Brief cognitive tests for distinguishing clinical Alzheimer-type dementia from mild cognitive impairment or normal cognition in older adults with suspected cognitive impairment: A systematic review. Annals of Internal Medicine, 172(10), 678-687. Scopus. https://doi.org/10.7326/M19-3889
dc.relationHenry, J. D., & Crawford, J. R. (2004). A meta-analytic review of verbal fluency performance in patients with traumatic brain injury. Neuropsychology, 18(4), 621.
dc.relationHorvath, A. (2018). EEG and ERP biomarkers of Alzheimer rsquo s disease a critical review. Frontiers in Bioscience, 23(1), 183-220. https://doi.org/10.2741/4587
dc.relationHsu, Y.-H., Huang, S.-M., Lin, S.-Y., Yang, J.-J., Tu, M.-C., & Kuo, L.-W. (2022). Prospective Memory and Default Mode Network Functional Connectivity in Normal and Pathological Aging. Journal of Alzheimer’s Disease, 86(2), 753-762. Scopus. https://doi.org/10.3233/JAD-215293
dc.relationHuang, Y. Y., & Kandel, E. R. (1994). Recruitment of long-lasting and protein kinase A-dependent long-term potentiation in the CA1 region of hippocampus requires repeated tetanization. Learning & Memory, 1(1), 74-82. https://doi.org/10.1101/lm.1.1.74
dc.relationHuey, E. D., Manly, J. J., Tang, M.-X., Schupf, N., Brickman, A. M., Manoochehri, M., Mez, J., DeCarli, C., Devanand, D. P., & Mayeux, R. (2013). Course and etiology of dysexecutive MCI in a community sample. Alzheimer’s & dementia : the journal of the Alzheimer’s Association, 9(6), 632-639. https://doi.org/10.1016/j.jalz.2012.10.014
dc.relationHunt, K., Adamson, J., Hewitt, C., & Nazareth, I. (2011). Do women consult more than men? A review of gender and consultation for back pain and headache. Journal of Health Services Research and Policy, 16(2), 108-117. Scopus. https://doi.org/10.1258/jhsrp.2010.009131
dc.relationHuygens, C. (1673). Horologium Oscillatorium.
dc.relationIaccarino, H. F., Singer, A. C., Martorell, A. J., Rudenko, A., Gao, F., Gillingham, T. Z., Mathys, H., Seo, J., Kritskiy, O., Abdurrob, F., Adaikkan, C., Canter, R. G., Rueda, R., Brown, E. N., Boyden, E. S., & Tsai, L.-H. (2016). Gamma frequency entrainment attenuates amyloid load and modifies microglia. Nature, 540(7632), Art. 7632. https://doi.org/10.1038/nature20587
dc.relationIbanez, A., Parra, M. A., Butler, C., & Latin America and the Caribbean Consortium on Dementia (LAC-CD). (2021). The Latin America and the Caribbean Consortium on Dementia (LAC-CD): From Networking to Research to Implementation Science. Journal of Alzheimer’s Disease: JAD, 82(s1), S379-S394. https://doi.org/10.3233/JAD-201384
dc.relationIsaac, J. T., Nicoll, R. A., & Malenka, R. C. (1995). Evidence for silent synapses: Implications for the expression of LTP. Neuron, 15(2), 427-434.
dc.relationIvan Pavlov—Biographical. (s. f.). Recuperado 4 de noviembre de 2017, de https://www.nobelprize.org/nobel_prizes/medicine/laureates/1904/pavlov-bio.html
dc.relationJack, C. R., Bennett, D. A., Blennow, K., Carrillo, M. C., Dunn, B., Haeberlein, S. B., Holtzman, D. M., Jagust, W., Jessen, F., Karlawish, J., Liu, E., Molinuevo, J. L., Montine, T., Phelps, C., Rankin, K. P., Rowe, C. C., Scheltens, P., Siemers, E., Snyder, H. M., … Contributors. (2018). NIA-AA Research Framework: Toward a biological definition of Alzheimer’s disease. Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 14(4), 535-562. https://doi.org/10.1016/j.jalz.2018.02.018
dc.relationJanelidze, S., Stomrud, E., Smith, R., Palmqvist, S., Mattsson, N., Airey, D. C., Proctor, N. K., Chai, X., Shcherbinin, S., Sims, J. R., Triana-Baltzer, G., Theunis, C., Slemmon, R., Mercken, M., Kolb, H., Dage, J. L., & Hansson, O. (2020). Cerebrospinal fluid p-tau217 performs better than p-tau181 as a biomarker of Alzheimer’s disease. Nature Communications, 11(1), 1683. https://doi.org/10.1038/s41467-020-15436-0
dc.relationJarrett, J. T., Berger, E. P., & Lansbury, P. T. (1993). The carboxy terminus of the beta amyloid protein is critical for the seeding of amyloid formation: Implications for the pathogenesis of Alzheimer’s disease. Biochemistry, 32(18), 4693-4697. https://doi.org/10.1021/bi00069a001
dc.relationJelic, V., Johansson, S.-E., Almkvist, O., Shigeta, M., Julin, P., Nordberg, A., Winblad, B., & Wahlund, L.-O. (2000). Quantitative electroencephalography in mild cognitive impairment: Longitudinal changes and possible prediction of Alzheimer’s disease. Neurobiology of Aging, 21(4), 533-540. https://doi.org/10.1016/S0197-4580(00)00153-6
dc.relationJeong, J., Gore, J. C., & Peterson, B. S. (2001). Mutual information analysis of the EEG in patients with Alzheimer’s disease. Clinical Neurophysiology, 112(5), 827-835. https://doi.org/10.1016/S1388-2457(01)00513-2
dc.relationJohnson, N., Barion, A., Rademaker, A., Rehkemper, G., & Weintraub, S. (2004). The Activities of Daily Living Questionnaire: A validation study in patients with dementia. Alzheimer disease & associated disorders, 18(4), 223-230.
dc.relationJongsiriyanyong, S., & Limpawattana, P. (2018). Mild Cognitive Impairment in Clinical Practice: A Review Article. American Journal of Alzheimer’s Disease and Other Dementias, 33(8), 500-507. Scopus. https://doi.org/10.1177/1533317518791401
dc.relationJosselyn, S. A., Köhler, S., & Frankland, P. W. (2015). Finding the engram. Nature Reviews Neuroscience, 16(9), 521-534. https://doi.org/10.1038/nrn4000
dc.relationKandel, E. R. (2007). En busca de la memoria: El nacimiento de una nueva ciencia de la mente. Katz Editores.
dc.relationKandel, E. R., Schwartz, J. H., & Jessell, T. M. (2000). Principios de neurociencia. McGraw-Hill Interamericana.
dc.relationKandel, E. R., & Spencer, W. A. (1968). Cellular neurophysiological approaches in the study of learning. Physiological Reviews, 48(1), 65-134.
dc.relationKapasi, A., DeCarli, C., & Schneider, J. A. (2017). Impact of multiple pathologies on the threshold for clinically overt dementia. Acta Neuropathologica, 134(2), 171-186. https://doi.org/10.1007/s00401-017-1717-7
dc.relationKarikari, T. K., Benedet, A. L., Ashton, N. J., Lantero Rodriguez, J., Snellman, A., Suárez-Calvet, M., Saha-Chaudhuri, P., Lussier, F., Kvartsberg, H., Rial, A. M., Pascoal, T. A., Andreasson, U., Schöll, M., Weiner, M. W., Rosa-Neto, P., Trojanowski, J. Q., Shaw, L. M., Blennow, K., Zetterberg, H., & Alzheimer’s Disease Neuroimaging Initiative. (2021). Diagnostic performance and prediction of clinical progression of plasma phospho-tau181 in the Alzheimer’s Disease Neuroimaging Initiative. Molecular Psychiatry, 26(2), 429-442. https://doi.org/10.1038/s41380-020-00923-z
dc.relationKarikari, T. K., Pascoal, T. A., Ashton, N. J., Janelidze, S., Benedet, A. L., Rodriguez, J. L., Chamoun, M., Savard, M., Kang, M. S., Therriault, J., Schöll, M., Massarweh, G., Soucy, J.-P., Höglund, K., Brinkmalm, G., Mattsson, N., Palmqvist, S., Gauthier, S., Stomrud, E., … Blennow, K. (2020). Blood phosphorylated tau 181 as a biomarker for Alzheimer’s disease: A diagnostic performance and prediction modelling study using data from four prospective cohorts. The Lancet. Neurology, 19(5), 422-433. https://doi.org/10.1016/S1474-4422(20)30071-5
dc.relationKauer, J. A., Malenka, R. C., & Nicoll, R. A. (1988). NMDA application potentiates synaptic transmission in the hippocampus. Nature, 334(6179), 250-252. https://doi.org/10.1038/334250a0
dc.relationKichigina, V. F. (2019). Disturbances of theta and gamma oscillations in the brains with pathologies pecular to Alzheimer’s disease and temporal lobe epilepsy. Zhurnal Vysshei Nervnoi Deyatelnosti Imeni I.P. Pavlova, 69(4), 395-412. Scopus. https://doi.org/10.1134/S0044467719040075
dc.relationKlyucherev, T. O., Olszewski, P., Shalimova, A. A., Chubarev, V. N., Tarasov, V. V., Attwood, M. M., Syvänen, S., & Schiöth, H. B. (2022). Advances in the development of new biomarkers for Alzheimer’s disease. Translational Neurodegeneration, 11(1). Scopus. https://doi.org/10.1186/s40035-022-00296-z
dc.relationKoenig, T., Prichep, L., Dierks, T., Hubl, D., Wahlund, L. O., John, E. R., & Jelic, V. (2005). Decreased EEG synchronization in Alzheimer’s disease and mild cognitive impairment. Neurobiology of Aging, 26(2), 165-171. https://doi.org/10.1016/j.neurobiolaging.2004.03.008
dc.relationKölliker, A., & Kölliker, A. von. (1863). Handbuch der Gewebelehre des Menschen: Für Aerzte und Studirende. Wilhelm Engelmann.
dc.relationKowalski, J. W., Gawel, M., Pfeffer, A., & Barcikowska, M. (2001). The Diagnostic Value of EEG in Alzheimer Disease: Correlation With the Severity of Mental Impairment. Journal of Clinical Neurophysiology, 18(6), 570-575.
dc.relationKulkarni, N., & Bairagi, V. (2018). Chapter Two—Electroencephalogram and Its Use in Clinical Neuroscience. En N. Kulkarni & V. Bairagi (Eds.), EEG-Based Diagnosis of Alzheimer Disease (pp. 25-35). Academic Press. https://doi.org/10.1016/B978-0-12-815392-5.00002-2
dc.relationKwak, Y. T. (2006). Quantitative EEG findings in different stages of Alzheimer’s disease. Journal of Clinical Neurophysiology: Official Publication of the American Electroencephalographic Society, 23(5), 456-461. https://doi.org/10.1097/01.wnp.0000223453.47663.63
dc.relationLamar, M., Boots, E. A., Arfanakis, K., Barnes, L. L., & Schneider, J. A. (2020). Common Brain Structural Alterations Associated with Cardiovascular Disease Risk Factors and Alzheimer’s Dementia: Future Directions and Implications. Neuropsychology Review, 30(4), 546-557. Scopus. https://doi.org/10.1007/s11065-020-09460-6
dc.relationLarson, J., & Munkácsy, E. (2015). Theta-Burst LTP. Brain research, 1621, 38-50. https://doi.org/10.1016/j.brainres.2014.10.034
dc.relationLashley, K. S. (1950). In search of the engram.
dc.relationLaufs, H. (2008). Endogenous brain oscillations and related networks detected by surface EEG‐combined fMRI. Human brain mapping, 29(7), 762-769.
dc.relationLee, S.-H., Park, Y.-M., Kim, D.-W., & Im, C.-H. (2010). Global synchronization index as a biological correlate of cognitive decline in Alzheimer’s disease. Neuroscience Research, 66(4), 333-339. Scopus. https://doi.org/10.1016/j.neures.2009.12.004
dc.relationLempel, A., & Ziv, J. (1976). On the Complexity of Finite Sequences. IEEE Transactions on Information Theory, 22(1), 75-81. https://doi.org/10.1109/TIT.1976.1055501
dc.relationLenzi, D., Serra, L., Perri, R., Pantano, P., Lenzi, G. L., Paulesu, E., Caltagirone, C., Bozzali, M., & Macaluso, E. (2011). Single domain amnestic MCI: A multiple cognitive domains fMRI investigation. Neurobiology of Aging, 32(9), 1542-1557. https://doi.org/10.1016/j.neurobiolaging.2009.09.006
dc.relationLeuzy, A., Cullen, N. C., Mattsson-Carlgren, N., & Hansson, O. (2021). Current advances in plasma and cerebrospinal fluid biomarkers in Alzheimer’s disease. Current Opinion in Neurology, 34(2), 266-274. https://doi.org/10.1097/WCO.0000000000000904
dc.relationLey 1850 de 2017—Medidas de protección al adulto mayor en Colombia. (2018, mayo 10). Así Vamos en Salud - indicadores en salud normatividad derechos. https://www.asivamosensalud.org/politicas-publicas/normatividad-leyes/promocion-social/ley-1850-de-2017-medidas-de-proteccion-al
dc.relationLi, C., Zheng, J., Wang, J., Gui, L., & Li, C. (2009). An fMRI stroop task study of prefrontal cortical function in normal aging, mild cognitive impairment, and Alzheimer’s disease. Current Alzheimer Research, 6(6), 525-530. https://doi.org/10.2174/156720509790147142
dc.relationLizio, R., Del Percio, C., Marzano, N., Soricelli, A., Yener, G. G., Başar, E., Mundi, C., De Rosa, S., Triggiani, A. I., Ferri, R., Arnaldi, D., Nobili, F. M., Cordone, S., Lopez, S., Carducci, F., Santi, G., Gesualdo, L., Rossini, P. M., Cavedo, E., … Babiloni, C. (2016). Neurophysiological assessment of Alzheimer’s disease individuals by a single electroencephalographic marker. Journal of Alzheimer’s Disease: JAD, 49(1), 159-177. https://doi.org/10.3233/JAD-143042
dc.relationLizio, R., Vecchio, F., Frisoni, G. B., Ferri, R., Rodriguez, G., & Babiloni, C. (2011). Electroencephalographic rhythms in Alzheimer’s disease. International Journal of Alzheimer’s Disease, 2011, 927573. https://doi.org/10.4061/2011/927573
dc.relationLleó, A., Alcolea, D., Martínez-Lage, P., Scheltens, P., Parnetti, L., Poirier, J., Simonsen, A. H., Verbeek, M. M., Rosa-Neto, P., Slot, R. E. R., Tainta, M., Izaguirre, A., Reijs, B. L. R., Farotti, L., Tsolaki, M., Vandenbergue, R., Freund-Levi, Y., Verhey, F. R. J., Clarimón, J., … Blennow, K. (2019). Longitudinal cerebrospinal fluid biomarker trajectories along the Alzheimer’s disease continuum in the BIOMARKAPD study. Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 15(6), 742-753. https://doi.org/10.1016/j.jalz.2019.01.015
dc.relationLocatelli, T., Cursi, M., Liberati, D., Franceschi, M., & Comi, G. (1998). EEG coherence in Alzheimer’s disease. Electroencephalography and Clinical Neurophysiology, 106(3), 229-237. https://doi.org/10.1016/S0013-4694(97)00129-6
dc.relationLomo, T. (1966). Frequency potentiation of excitatory synaptic activity in dentate area of hippocampal formation. Acta Physiologica Scandinavica, 128-.
dc.relationLomo, T. (1971). Patterns of activation in a monosynaptic cortical pathway: The perforant path input to the dentate area of the hippocampal formation. Experimental Brain Research, 12(1), 18-45.
dc.relationLømo, T. (2003). The discovery of long-term potentiation. Philosophical Transactions of the Royal Society B: Biological Sciences, 358(1432), 617-620. https://doi.org/10.1098/rstb.2002.1226
dc.relationLópez, N., Allegri, R., & Soto-Añari, M. (2014). Capacidad diagnóstica y validación preliminar del Test del Reloj, versión de Cacho a la Orden, para enfermedad de Alzheimer de grado leve en población chilena. Revista Ecuatoriana de Neurología, 23(1-3), 18-23.
dc.relationLoureiro, C. C. de S., García, C., Adana, L., Yacelga, T., Rodríguez Lorenzana, A., & Maruta, C. (2018). Uso del test de evaluación cognitiva de Montreal (MoCA) en América Latina: Revisión sistemática. Revista de Neurología, 66(12), 397. https://doi.org/10.33588/rn.6612.2017508
dc.relationLu, W., Man, H., Ju, W., Trimble, W. S., MacDonald, J. F., & Wang, Y. T. (2001). Activation of synaptic NMDA receptors induces membrane insertion of new AMPA receptors and LTP in cultured hippocampal neurons. Neuron, 29(1), 243-254.
dc.relationLüscher, C., & Frerking, M. (2001). Restless AMPA receptors: Implications for synaptic transmission and plasticity. Trends in Neurosciences, 24(11), 665-670.
dc.relationLynch, M. A. (2004). Long-term potentiation and memory. Physiological Reviews, 84(1), 87-136. https://doi.org/10.1152/physrev.00014.2003
dc.relationMaestú, F., Cuesta, P., Hasan, O., Fernandéz, A., Funke, M., & Schulz, P. E. (2019). The Importance of the Validation of M/Eeg with Current Biomarkers in Alzheimer’s Disease. Frontiers in Human Neuroscience, 13. https://www.frontiersin.org/article/10.3389/fnhum.2019.00017
dc.relationMalenka, R. C., Kauer, J. A., Zucker, R. S., & Nicoll, R. A. (1988). Postsynaptic calcium is sufficient for potentiation of hippocampal synaptic transmission. Science, 242(4875), 81-84. https://doi.org/10.1126/science.2845577
dc.relationMalinow, R., & Malenka, R. C. (2002). AMPA receptor trafficking and synaptic plasticity. Annual Review of Neuroscience, 25, 103-126. https://doi.org/10.1146/annurev.neuro.25.112701.142758
dc.relationMallo, S. C., Patten, S. B., Ismail, Z., Pereiro, A. X., Facal, D., Otero, C., & Juncos-Rabadán, O. (2020). Does the neuropsychiatric inventory predict progression from mild cognitive impairment to dementia? A systematic review and meta-analysis. Ageing Research Reviews, 58. Scopus. https://doi.org/10.1016/j.arr.2019.101004
dc.relationManning, J. R., Polyn, S. M., Baltuch, G. H., Litt, B., & Kahana, M. J. (2011). Oscillatory patterns in temporal lobe reveal context reinstatement during memory search. Proceedings of the National Academy of Sciences, 108(31), 12893-12897.
dc.relationMatsunari, I. (2012). MRI and PET in Alzheimer’s disease. Neurological Surgery, 40(12), 1051-1063. Scopus.
dc.relationMattia, D., Babiloni, F., Romigi, A., Cincotti, F., Bianchi, L., Sperli, F., Placidi, F., Bozzao, A., Giacomini, P., Floris, R., & Marciani, M. G. (2003). Quantitative EEG and dynamic susceptibility contrast MRI in Alzheimer’s disease: A correlative study. Clinical Neurophysiology, 114(7), 1210-1216. Scopus. https://doi.org/10.1016/S1388-2457(03)00085-3
dc.relationMazziotta, J. C., Toga, A. W., Evans, A., Fox, P., & Lancaster, J. (1995). A probabilistic atlas of the human brain: Theory and rationale for its development. The International Consortium for Brain Mapping (ICBM). NeuroImage, 2(2), 89-101. https://doi.org/10.1006/nimg.1995.1012
dc.relationMcGeown, W. J., Shanks, M. F., Forbes-McKay, K. E., & Venneri, A. (2009). Patterns of brain activity during a semantic task differentiate normal aging from early Alzheimer’s disease. Psychiatry Research, 173(3), 218-227. https://doi.org/10.1016/j.pscychresns.2008.10.005
dc.relationMcKhann, G. M., Knopman, D. S., Chertkow, H., Hyman, B. T., Jack, C. R., Kawas, C. H., Klunk, W. E., Koroshetz, W. J., Manly, J. J., Mayeux, R., Mohs, R. C., Morris, J. C., Rossor, M. N., Scheltens, P., Carrillo, M. C., Thies, B., Weintraub, S., & Phelps, C. H. (2011). The diagnosis of dementia due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s & Dementia, 7(3), 263-269. https://doi.org/10.1016/j.jalz.2011.03.005
dc.relationMiledi, R., & Slater, C. R. (1966). The action of calcium on neuronal synapses in the squid. The Journal of Physiology, 184(2), 473-498. https://doi.org/10.1113/jphysiol.1966.sp007927
dc.relationMINISTERIO DE SALUD Y PROTECCIÓN SOCIAL. (2013). Envejecimiento-demografico-Colombia-1951-2020. OFICINA DE PROMOCIÓN SOCIAL. https://www.minsalud.gov.co/sites/rid/Lists/BibliotecaDigital/RIDE/DE/PS/Envejecimiento-demografico-Colombia-1951-2020.pdf
dc.relationMöller, C., Van Der Flier, W. M., Versteeg, A., Benedictus, M. R., Wattjes, M. P., Koedam, E. L. G. M., Scheltens, P., Barkhof, F., & Vrenken, H. (2014). Quantitative regional validation of the visual rating scale for posterior cortical atrophy. European Radiology, 24(2), 397-404. Scopus. https://doi.org/10.1007/s00330-013-3025-5
dc.relationMonllor, P., Cervera-Ferri, A., Lloret, M.-A., Esteve, D., Lopez, B., Leon, J.-L., & Lloret, A. (2021). Electroencephalography as a non-invasive biomarker of alzheimer’s disease: A forgotten candidate to substitute CSF molecules? International Journal of Molecular Sciences, 22(19). Scopus. https://doi.org/10.3390/ijms221910889
dc.relationMontez, T., Linkenkaer-Hansen, K., van Dijk, B. W., & Stam, C. J. (2006). Synchronization likelihood with explicit time-frequency priors. NeuroImage, 33(4), 1117-1125. https://doi.org/10.1016/j.neuroimage.2006.06.066
dc.relationMoretti, D. V. (2015). Theta and alpha eeg frequency interplay in subjects with mild cognitive impairment: Evidence from EEG, MRI and spect brain modifications. Frontiers in Aging Neuroscience, 7(FEB). Scopus. https://doi.org/10.3389/fnagi.2015.00031
dc.relationMorris, J. C. (2006). Mild Cognitive Impairment Is Early-Stage Alzheimer Disease: Time to Revise Diagnostic Criteria. Archives of Neurology, 63(1), 15-16. https://doi.org/10.1001/archneur.63.1.15
dc.relationMorris, R. G., Anderson, E., Lynch, G. S., & Baudry, M. (1986). Selective impairment of learning and blockade of long-term potentiation by an N-methyl-D-aspartate receptor antagonist, AP5. Nature, 319(6056), 774-776. https://doi.org/10.1038/319774a0
dc.relationMorris, R. G. M. (2006). Elements of a neurobiological theory of hippocampal function: The role of synaptic plasticity, synaptic tagging and schemas. European Journal of Neuroscience, 23(11), 2829-2846. https://doi.org/10.1111/j.1460-9568.2006.04888.x
dc.relationMorris, R. G. M. (2013). NMDA receptors and memory encoding. Neuropharmacology, 74, 32-40. https://doi.org/10.1016/j.neuropharm.2013.04.014
dc.relationMullany, P., & Lynch, M. A. (1997). Changes in protein synthesis and synthesis of the synaptic vesicle protein, synaptophysin, in entorhinal cortex following induction of long-term potentiation in dentate gyrus: An age-related study in the rat. Neuropharmacology, 36(7), 973-980.
dc.relationMuñoz-Neira, C., López, O. L., Riveros, R., Núñez-Huasaf, J., Flores, P., & Slachevsky, A. (2012). The Technology – Activities of Daily Living Questionnaire: A Version with a Technology-Related Subscale. Dementia and Geriatric Cognitive Disorders, 33(6), 361-371. https://doi.org/10.1159/000338606
dc.relationMurphy, D. D., & Segal, M. (1997). Morphological plasticity of dendritic spines in central neurons is mediated by activation of cAMP response element binding protein. Proceedings of the National Academy of Sciences, 94(4), 1482-1487.
dc.relationMusa, G., Henríquez, F., Muñoz-Neira, C., Delgado, C., Lillo, P., & Slachevsky, A. (2017). Utility of the Neuropsychiatric Inventory Questionnaire (NPI-Q) in the assessment of a sample of patients with Alzheimer’s disease in Chile. Dementia & Neuropsychologia, 11(2), 129-136. https://doi.org/10.1590/1980-57642016dn11-020005
dc.relationMusaeus, C. S., Engedal, K., Høgh, P., Jelic, V., Mørup, M., Naik, M., Oeksengaard, A.-R., Snaedal, J., Wahlund, L.-O., Waldemar, G., & Andersen, B. B. (2018). EEG Theta Power Is an Early Marker of Cognitive Decline in Dementia due to Alzheimer’s Disease. Journal of Alzheimer’s Disease, 64(4), 1359-1371. https://doi.org/10.3233/JAD-180300
dc.relationMusaeus, C. S., Engedal, K., Høgh, P., Jelic, V., Mørup, M., Naik, M., Oeksengaard, A.-R., Snaedal, J., Wahlund, L.-O., Waldemar, G., & Andersen, B. B. (2019). Oscillatory connectivity as a diagnostic marker of dementia due to Alzheimer’s disease. Clinical Neurophysiology, 130(10), 1889-1899. https://doi.org/10.1016/j.clinph.2019.07.016
dc.relationNakamura, A., Cuesta, P., Fernández, A., Arahata, Y., Iwata, K., Kuratsubo, I., Bundo, M., Hattori, H., Sakurai, T., Fukuda, K., Washimi, Y., Endo, H., Takeda, A., Diers, K., Bajo, R., Maestú, F., Ito, K., & Kato, T. (2018). Electromagnetic signatures of the preclinical and prodromal stages of Alzheimer’s disease. Brain, 141(5), 1470-1485. https://doi.org/10.1093/brain/awy044
dc.relationNakamura, A., Kaneko, N., Villemagne, V. L., Kato, T., Doecke, J., Doré, V., Fowler, C., Li, Q.-X., Martins, R., Rowe, C., Tomita, T., Matsuzaki, K., Ishii, K., Ishii, K., Arahata, Y., Iwamoto, S., Ito, K., Tanaka, K., Masters, C. L., & Yanagisawa, K. (2018). High performance plasma amyloid-β biomarkers for Alzheimer’s disease. Nature, 554(7691), 249-254. https://doi.org/10.1038/nature25456
dc.relationNasreddine, Z. S., Phillips, N. A., Bédirian, V., Charbonneau, S., Whitehead, V., Collin, I., Cummings, J. L., & Chertkow, H. (2005). The Montreal Cognitive Assessment, MoCA: A Brief Screening Tool For Mild Cognitive Impairment. Journal of the American Geriatrics Society, 53(4), 695-699. https://doi.org/10.1111/j.1532-5415.2005.53221.x
dc.relationNatham, R., Amirthalingam, P., & Arunachalam, G. (2018). Comparison of Montreal Cognitive Assessment (MOCA) with Mini Mental State Examination (MMSE) on association between homocysteine and cognitive status in epilepsy patients with phenytoin monotherapy. Asia Pacific Journal of Counselling and Psychotherapy, 9(2), 160-170. https://doi.org/10.1080/21507686.2018.1483411
dc.relationNesteruk, M., Nesteruk, T., Styczyńska, M., Barczak, A., Mandecka, M., Walecki, J., & Barcikowska-Kotowicz, M. (2015). Predicting the conversion of mild cognitive impairment to Alzheimer’s disease based on the volumetric measurements of the selected brain structures in magnetic resonance imaging. Neurologia I Neurochirurgia Polska, 49(6), 349-353. https://doi.org/10.1016/j.pjnns.2015.09.003
dc.relationNeurocognitive Disorders. (2013). En Diagnostic and Statistical Manual of Mental Disorders. American Psychiatric Association. https://doi.org/10.1176/appi.books.9780890425596.dsm17
dc.relationNuwer, M. R., Lehmann, D., da Silva, F. L., Matsuoka, S., Sutherling, W., & Vibert, J. F. (1999). IFCN guidelines for topographic and frequency analysis of EEGs and EPs.The International Federation of Clinical Neurophysiology. Electroencephalography and Clinical Neurophysiology. Supplement, 52, 15-20.
dc.relationO’Driscoll, C., & Shaikh, M. (2017). Cross-Cultural Applicability of the Montreal Cognitive Assessment (MoCA): A Systematic Review. Journal of Alzheimer’s Disease: JAD, 58(3), 789-801. https://doi.org/10.3233/JAD-161042
dc.relationOkamura, N., Harada, R., Furumoto, S., Arai, H., Yanai, K., & Kudo, Y. (2014). Tau PET Imaging in Alzheimer’s Disease. Current Neurology and Neuroscience Reports, 14(11). Scopus. https://doi.org/10.1007/s11910-014-0500-6
dc.relationOlabarrieta-Landa, L., Rivera, D., Galarza-del-Angel, J., Garza, M., Saracho, C., Rodríguez, W., Chávez-Oliveros, M., Rábago, B., Leibach, G., Schebela, S., Martínez, C., Luna, M., Longoni, M., Ocampo-Barba, N., Rodríguez, G., Aliaga, A., Esenarro, L., García de la Cadena, C., Perrin, B., & Arango-Lasprilla, J. (2015). Verbal fluency tests: Normative data for the Latin American Spanish speaking adult population. NeuroRehabilitation, 37(4), 515-561. https://doi.org/10.3233/NRE-151279
dc.relationOMS | La demencia: Una prioridad para la salud pública. (s. f.). WHO; World Health Organization. Recuperado 5 de diciembre de 2020, de http://www.who.int/mental_health/neurology/dementia/es/
dc.relationOnishi, J., Suzuki, Y., Yoshiko, K., Hibino, S., & Iguchi, A. (2005). Predictive model for assessing cognitive impairment by quantitative electroencephalography. Cognitive and Behavioral Neurology: Official Journal of the Society for Behavioral and Cognitive Neurology, 18(3), 179-184. https://doi.org/10.1097/01.wnn.0000178227.54315.38
dc.relationOostenveld, R., Fries, P., Maris, E., & Schoffelen, J.-M. (2010). FieldTrip: Open Source Software for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data. Computational Intelligence and Neuroscience, 2011, e156869. https://doi.org/10.1155/2011/156869
dc.relationOosterman, J. M., Oosterveld, S., Rikkert, M. G. O., Claassen, J. A., & Kessels, R. P. C. (2012). Medial temporal lobe atrophy relates to executive dysfunction in Alzheimer’s disease. International Psychogeriatrics, 24(9), 1474-1482. https://doi.org/10.1017/S1041610212000506
dc.relationOppenheim, A. V. (1999). Discrete-time signal processing. Pearson Education India.
dc.relationOppenheim, A. V., Buck, J. R., & Schafer, R. W. (2001). Discrete-time signal processing. Vol. 2. Upper Saddle River, NJ: Prentice Hall.
dc.relationOrta-Salazar, E., Cuellar-Lemus, C. A., Díaz-Cintra, S., & Feria-Velasco, A. I. (2014). Marcaje colinérgico en la corteza cerebral y el hipocampo en algunas especies animales y su relación con la enfermedad de Alzheimer. Neurología, 29(8), 497-503. https://doi.org/10.1016/j.nrl.2012.10.007
dc.relationPaddick, S.-M., Gray, W. K., McGuire, J., Richardson, J., Dotchin, C., & Walker, R. W. (2017). Cognitive screening tools for identification of dementia in illiterate and low-educated older adults, a systematic review and meta-analysis. International Psychogeriatrics, 29(6), 897-929. Scopus. https://doi.org/10.1017/S1041610216001976
dc.relationPascual-Marqui, R. D. (2007). Discrete, 3D distributed, linear imaging methods of electric neuronal activity. Part 1: Exact, zero error localization. arXiv:0710.3341 [math-ph, physics:physics, q-bio]. http://arxiv.org/abs/0710.3341
dc.relationPasquier, F., Leys, D., Weerts, J. G., Mounier-Vehier, F., Barkhof, F., & Scheltens, P. (1996). Inter- and intraobserver reproducibility of cerebral atrophy assessment on MRI scans with hemispheric infarcts. European Neurology, 36(5), 268-272. https://doi.org/10.1159/000117270
dc.relationPavlov, I. P. (1927). Conditional reflexes: An investigation of the physiological activity of the cerebral cortex.
dc.relationPavlov, I. P. (1941). Lectures on conditioned reflexes. Vol. II. Conditioned reflexes and psychiatry. http://psycnet.apa.org/psycinfo/1941-04246-000
dc.relationPavlov, I. P., & Thompson, W. H. (1902). The work of the digestive glands. Charles Griffin. http://scholar.google.com/scholar?cluster=18207307312015685009&hl=en&oi=scholarr
dc.relationPedraza, O. L., Salazar, A. M., Sierra, F. A., Soler, D., Castro, J., Castillo, P., Hernández, A., Piñeros, C., Pedraza, O. L., Salazar, A. M., Sierra, F. A., Soler, D., Castro, J., Castillo, P., Hernández, A., & Piñeros, C. (2016). Contabilidad, validez de criterio y discriminante del Montreal Cognitive Assessment (MoCA) test, en un grupo de adultos de Bogotá. Acta Medica Colombiana, 41(4), 221-228.
dc.relationPennanen, C., Kivipelto, M., Tuomainen, S., Hartikainen, P., Hänninen, T., Laakso, M. P., Hallikainen, M., Vanhanen, M., Nissinen, A., Helkala, E.-L., Vainio, P., Vanninen, R., Partanen, K., & Soininen, H. (2004). Hippocampus and entorhinal cortex in mild cognitive impairment and early AD. Neurobiology of Aging, 25(3), 303-310. https://doi.org/10.1016/S0197-4580(03)00084-8
dc.relationPereda, E., Quiroga, R. Q., & Bhattacharya, J. (2005). Nonlinear multivariate analysis of neurophysiological signals. Progress in Neurobiology, 77(1-2), 1-37. https://doi.org/10.1016/j.pneurobio.2005.10.003
dc.relationPessoa, R. M. P., Bomfim, A. J. L., Ferreira, B. L. C., & Chagas, M. H. N. (2019). Diagnostic criteria and prevalence of mild cognitive impairment in older adults living in the community: A systematic review and meta-analysis. Revista de Psiquiatria Clinica, 46(3), 72-79. Scopus. https://doi.org/10.1590/0101-60830000000197
dc.relationPetersen, R. C., Lopez, O., Armstrong, M. J., Getchius, T. S. D., Ganguli, M., Gloss, D., Gronseth, G. S., Marson, D., Pringsheim, T., Day, G. S., Sager, M., Stevens, J., & Rae-Grant, A. (2018). Practice guideline update summary: Mild cognitive impairment: Report of the Guideline Development, Dissemination, and Implementation Subcommittee of the American Academy of Neurology. Neurology, 90(3), 126-135. https://doi.org/10.1212/WNL.0000000000004826
dc.relationPetersen, R. C., Smith, G. E., Waring, S. C., Ivnik, R. J., Tangalos, E. G., & Kokmen, E. (1999). Mild cognitive impairment: Clinical characterization and outcome. Archives of Neurology, 56(3), 303-308. https://doi.org/10.1001/archneur.56.3.303
dc.relationPetrella, J. R., Wang, L., Krishnan, S., Slavin, M. J., Prince, S. E., Tran, T.-T. T., & Doraiswamy, P. M. (2007). Cortical deactivation in mild cognitive impairment: High-field-strength functional MR imaging. Radiology, 245(1), 224-235. https://doi.org/10.1148/radiol.2451061847
dc.relationPievani, M., Filippini, N., van den Heuvel, M. P., Cappa, S. F., & Frisoni, G. B. (2014). Brain connectivity in neurodegenerative diseases—From phenotype to proteinopathy. Nature Reviews. Neurology, 10(11), 620-633. https://doi.org/10.1038/nrneurol.2014.178
dc.relationPihlajamäki, M., Jauhiainen, A. M., & Soininen, H. (2009). Structural and functional MRI in mild cognitive impairment. Current Alzheimer Research, 6(2), 179-185. https://doi.org/10.2174/156720509787602898
dc.relationPijnenburg, Y. A. L., vd Made, Y., van Cappellen van Walsum, A. M., Knol, D. L., Scheltens, Ph., & Stam, C. J. (2004). EEG synchronization likelihood in mild cognitive impairment and Alzheimer’s disease during a working memory task. Clinical Neurophysiology, 115(6), 1332-1339. https://doi.org/10.1016/j.clinph.2003.12.029
dc.relationPikovsky, A., Rosenblum, M., & Kurths, J. (2003). Synchronization: A Universal Concept in Nonlinear Sciences.
dc.relationPinto, E., & Peters, R. (2009). Literature review of the Clock Drawing Test as a tool for cognitive screening. Dementia and geriatric cognitive disorders, 27(3), 201-213.
dc.relationPinto, T. C. C., Machado, L., Bulgacov, T. M., Rodrigues-Júnior, A. L., Costa, M. L. G., Ximenes, R. C. C., & Sougey, E. B. (2019). Is the Montreal Cognitive Assessment (MoCA) screening superior to the Mini-Mental State Examination (MMSE) in the detection of mild cognitive impairment (MCI) and Alzheimer’s Disease (AD) in the elderly? International Psychogeriatrics, 31(4), 491-504. Scopus. https://doi.org/10.1017/S1041610218001370
dc.relationPoil, S.-S., de Haan, W., van der Flier, W. M., Mansvelder, H. D., Scheltens, P., & Linkenkaer-Hansen, K. (2013). Integrative EEG biomarkers predict progression to Alzheimer’s disease at the MCI stage. Frontiers in Aging Neuroscience, 5, 58. https://doi.org/10.3389/fnagi.2013.00058
dc.relationPortelius, E., Hansson, S. F., Tran, A. J., Zetterberg, H., Grognet, P., Vanmechelen, E., Höglund, K., Brinkmalm, G., Westman-Brinkmalm, A., Nordhoff, E., Blennow, K., & Gobom, J. (2008). Characterization of tau in cerebrospinal fluid using mass spectrometry. Journal of Proteome Research, 7(5), 2114-2120. https://doi.org/10.1021/pr7008669
dc.relationPortelius, E., Hansson, S. F., Tran, A. J., Zetterberg, H., Grognet, P., Vanmechelen, E., Höglund, K., Brinkmalm, G., Westman-Brinkmalm, A., Nordhoff, E., Blennow, K., & Gobom, J. (2008). Characterization of tau in cerebrospinal fluid using mass spectrometry. Journal of Proteome Research, 7(5), 2114-2120. https://doi.org/10.1021/pr7008669
dc.relationPrichep, L. S. (2007). Quantitative EEG and Electromagnetic Brain Imaging in Aging and in the Evolution of Dementia. Annals of the New York Academy of Sciences, 1097(1), 156-167. https://doi.org/10.1196/annals.1379.008
dc.relationPrichep, L. S., John, E. R., Ferris, S. H., Rausch, L., Fang, Z., Cancro, R., Torossian, C., & Reisberg, B. (2006). Prediction of longitudinal cognitive decline in normal elderly with subjective complaints using electrophysiological imaging. Neurobiology of Aging, 27(3), 471-481. https://doi.org/10.1016/j.neurobiolaging.2005.07.021
dc.relationPrichep, L. S., John, E. R., Ferris, S. H., Reisberg, B., Almas, M., Alper, K., & Cancro, R. (1994). Quantitative EEG correlates of cognitive deterioration in the elderly. Neurobiology of Aging, 15(1), 85-90. https://doi.org/10.1016/0197-4580(94)90147-3
dc.relationPrimavera, A., Novello, P., Finocchi, C., Canevari, E., & Corsello, L. (1990). Correlation between Mini-Mental State examination and quantitative electroencephalography in senile dementia of Alzheimer type. Neuropsychobiology, 23(2), 74-78. Scopus. https://doi.org/10.1159/000119430
dc.relationPuttaert, D., Coquelet, N., Wens, V., Peigneux, P., Fery, P., Rovai, A., Trotta, N., Sadeghi, N., Coolen, T., Bier, J.-C., Goldman, S., & De Tiège, X. (2020). Alterations in resting-state network dynamics along the Alzheimer’s disease continuum. Scientific Reports, 10(1), Art. 1. https://doi.org/10.1038/s41598-020-76201-3
dc.relationResting-state EEG source localization and functional connectivity in schizophrenia-like psychosis of epilepsy—PubMed. (s. f.). Recuperado 14 de marzo de 2022, de https://pubmed.ncbi.nlm.nih.gov/22125634/
dc.relationResumen-Ejecutivo-Encuesta-SABE.pdf. (s. f.). Recuperado 15 de marzo de 2022, de https://www.minsalud.gov.co/sites/rid/Lists/BibliotecaDigital/RIDE/VS/ED/GCFI/Resumen-Ejecutivo-Encuesta-SABE.pdf
dc.relationRivera, D., Ruiz, N. C., Gutiérrez-Hernández, C., & Calderón, J. A. (s. f.). Test de Aprendizaje Verbal de Hopkins-Revisado (HVLT-R). Datos normativos basados en regresiones múltiples para población colombiana. 13.
dc.relationRoalf, D. R., Moberg, P. J., Xie, S. X., Wolk, D. A., Moelter, S. T., & Arnold, S. E. (2013). Comparative accuracies of two common screening instruments for the classification of Alzheimer’s disease, mild cognitive impairment and healthy aging. Alzheimer’s & dementia : the journal of the Alzheimer’s Association, 9(5), 529-537. https://doi.org/10.1016/j.jalz.2012.10.001
dc.relationRodrigues, S. M., Schafe, G. E., & LeDoux, J. E. (2001). Intra-Amygdala Blockade of the NR2B Subunit of the NMDA Receptor Disrupts the Acquisition But Not the Expression of Fear Conditioning. Journal of Neuroscience, 21(17), 6889-6896.
dc.relationRossini, P. M., Di Iorio, R., Vecchio, F., Anfossi, M., Babiloni, C., Bozzali, M., Bruni, A. C., Cappa, S. F., Escudero, J., Fraga, F. J., Giannakopoulos, P., Guntekin, B., Logroscino, G., Marra, C., Miraglia, F., Panza, F., Tecchio, F., Pascual-Leone, A., & Dubois, B. (2020). Early diagnosis of Alzheimer’s disease: The role of biomarkers including advanced EEG signal analysis. Report from the IFCN-sponsored panel of experts. Clinical Neurophysiology, 131(6), 1287-1310. https://doi.org/10.1016/j.clinph.2020.03.003
dc.relationSalmon, D. P. (2008). Chapter 5 Neuropsychology of aging and dementia. Handbook of Clinical Neurology, 88, 113-135. Scopus. https://doi.org/10.1016/S0072-9752(07)88005-5
dc.relationSamuraki, M., Matsunari, I., & Yamada, M. (2017). Neuroimaging study of Alzheimer’s disease in volunteer-based cohort. En Neuroimaging Diagnosis for Alzheimer’s Disease and Other Dementias (pp. 243-255). Scopus. https://doi.org/10.1007/978-4-431-55133-1_14
dc.relationSankari, Z., Adeli, H., & Adeli, A. (2012). Wavelet Coherence Model for Diagnosis of Alzheimer Disease. Clinical EEG and Neuroscience, 43(4), 268-278. https://doi.org/10.1177/1550059412444970
dc.relationScheltens, P., Leys, D., Barkhof, F., Huglo, D., Weinstein, H. C., Vermersch, P., Kuiper, M., Steinling, M., Wolters, E. C., & Valk, J. (1992). Atrophy of medial temporal lobes on MRI in «probable» Alzheimer’s disease and normal ageing: Diagnostic value and neuropsychological correlates. Journal of Neurology, Neurosurgery, and Psychiatry, 55(10), 967-972. https://doi.org/10.1136/jnnp.55.10.967
dc.relationSchindler, S. E., Bollinger, J. G., Ovod, V., Mawuenyega, K. G., Li, Y., Gordon, B. A., Holtzman, D. M., Morris, J. C., Benzinger, T. L. S., Xiong, C., Fagan, A. M., & Bateman, R. J. (2019). High-precision plasma β-amyloid 42/40 predicts current and future brain amyloidosis. Neurology, 93(17), e1647-e1659. https://doi.org/10.1212/WNL.0000000000008081
dc.relationScoville, W. B., & Milner, B. (1957). Loss of recent memory after bilateral hippocampal lesions. Journal of neurology, neurosurgery, and psychiatry, 20(1), 11.
dc.relationSekeres, M. J., Moscovitch, M., & Winocur, G. (2017). Mechanisms of Memory Consolidation and Transformation. En Cognitive Neuroscience of Memory Consolidation (pp. 17-44). Springer.
dc.relationSeppälä, T. T., Nerg, O., Koivisto, A. M., Rummukainen, J., Puli, L., Zetterberg, H., Pyykkö, O. T., Helisalmi, S., Alafuzoff, I., Hiltunen, M., Jääskeläinen, J. E., Rinne, J., Soininen, H., Leinonen, V., & Herukka, S. K. (2012). CSF biomarkers for Alzheimer disease correlate with cortical brain biopsy findings. Neurology, 78(20), 1568-1575. https://doi.org/10.1212/WNL.0b013e3182563bd0
dc.relationSerra, L., Cercignani, M., Lenzi, D., Perri, R., Fadda, L., Caltagirone, C., Macaluso, E., & Bozzali, M. (2010). Grey and white matter changes at different stages of Alzheimer’s disease. Journal of Alzheimer’s Disease: JAD, 19(1), 147-159. https://doi.org/10.3233/JAD-2010-1223
dc.relationSerra, L., Cercignani, M., Petrosini, L., Basile, B., Perri, R., Fadda, L., Spanò, B., Marra, C., Giubilei, F., Carlesimo, G. A., Caltagirone, C., & Bozzali, M. (2011). Neuroanatomical correlates of cognitive reserve in Alzheimer disease. Rejuvenation Research, 14(2), 143-151. https://doi.org/10.1089/rej.2010.1103
dc.relationShaughnessy, L., Sheard, S., Goldfarb, D., & Atri, A. (2019). Cognitive Assessment of Alzheimer’s Disease and Dementias in Clinical Practice: Pragmatics of Brief Instruments and Neuropsychological Evaluation. The Journal of Clinical Psychiatry, 80(4), MS18002BR2C. https://doi.org/10.4088/JCP.MS18002BR2C
dc.relationSherrington, C. S. (1910). Flexion-reflex of the limb, crossed extension-reflex, and reflex stepping and standing. The Journal of Physiology, 40(1-2), 28-121.
dc.relationShi, S.-H., Hayashi, Y., Petralia, R. S., Zaman, S. H., Wenthold, R. J., Svoboda, K., & Malinow, R. (1999). Rapid Spine Delivery and Redistribution of AMPA Receptors After Synaptic NMDA Receptor Activation. Science, 284(5421), 1811-1816. https://doi.org/10.1126/science.284.5421.1811
dc.relationShum, D. H., McFarland, K. A., & Bain, J. D. (1990). Construct validity of eight tests of attention: Comparison of normal and closed head injured samples. The Clinical Neuropsychologist, 4(2), 151-162.
dc.relationSilva, A. J., Kogan, J. H., Frankland, P. W., & Kida, S. (1998). CREB and memory. Annual Review of Neuroscience, 21, 127-148. https://doi.org/10.1146/annurev.neuro.21.1.127
dc.relationSir Charles Sherrington—Nobel Lecture: Inhibition as a Coordinative Factor. (s. f.). Recuperado 11 de mayo de 2017, de https://www.nobelprize.org/nobel_prizes/medicine/laureates/1932/sherrington-lecture.html
dc.relationSmall, S. A., Perera, G. M., DeLaPaz, R., Mayeux, R., & Stern, Y. (1999). Differential regional dysfunction of the hippocampal formation among elderly with memory decline and Alzheimer’s disease. Annals of Neurology, 45(4), 466-472. https://doi.org/10.1002/1531-8249(199904)45:4<466::aid-ana8>3.0.co;2-q
dc.relationSmith, G. (2016). Dementia care: A practical approach. CRC Press. https://books.google.com/books?hl=en&lr=&id=6hRjDAAAQBAJ&oi=fnd&pg=PP1&dq=%22Ann+Hayes,+Lorraine+Shaw,+and+Grahame%22+%22Psychological+interventions+in%22+%22Parker+and+Robert+G.%22+%22Smith+and+Denise%22+%22Rylance+and+Donal%22+%22End+of+life%22+%22Knott+and+Denise%22+&ots=2g0s9zCAMk&sig=pE__72LTF6oiZoKm4x5-3CR3vos
dc.relationSoltani Zangbar, H., Soltani Zangbar, H., Ghadiri, T., Seyedi Vafaee, M., Ebrahimi Kalan, A., Fallahi, S., Ghorbani, M., & Shahabi, P. (2020). Theta Oscillations through Hippocampal/Prefrontal Pathway: Importance in Cognitive Performances. Brain Connectivity, 10(4), 157-169. Scopus. https://doi.org/10.1089/brain.2019.0733
dc.relationSperling, R. A., Bates, J. F., Chua, E. F., Cocchiarella, A. J., Rentz, D. M., Rosen, B. R., Schacter, D. L., & Albert, M. S. (2003). FMRI studies of associative encoding in young and elderly controls and mild Alzheimer’s disease. Journal of Neurology, Neurosurgery, and Psychiatry, 74(1), 44-50. https://doi.org/10.1136/jnnp.74.1.44
dc.relationSquire, L. R. (1992). Memory and the hippocampus: A synthesis from findings with rats, monkeys, and humans. Psychological Review, 99(2), 195-231.
dc.relationStam, C. J., van Cappellen van Walsum, A. M., Pijnenburg, Y. A. L., Berendse, H. W., de Munck, J. C., Scheltens, P., & van Dijk, B. W. (2002). Generalized Synchronization of MEG Recordings in Alzheimer’s Disease: Evidence for Involvement of the Gamma Band. Journal of Clinical Neurophysiology, 19(6), 562-574.
dc.relationStam, C. J., van der Made, Y., Pijnenburg, Y. a. L., & Scheltens, P. (2003). EEG synchronization in mild cognitive impairment and Alzheimer’s disease. Acta Neurologica Scandinavica, 108(2), 90-96. https://doi.org/10.1034/j.1600-0404.2003.02067.x
dc.relationStanton, P. K., & Sarvey, J. M. (1984). Blockade of long-term potentiation in rat hippocampal CA1 region by inhibitors of protein synthesis. Journal of Neuroscience, 4(12), 3080-3088.
dc.relationStefanowska, M. (1897). Les appendices terminaux des dendrites cérébraux et leurs différents états physiologiques. Hayez, Imprimeur de l’Académie royale des sciences, des lettres et des beaux-arts de Belgique.
dc.relationStomrud, E., Hansson, O., Minthon, L., Blennow, K., Rosén, I., & Londos, E. (2010). Slowing of EEG correlates with CSF biomarkers and reduced cognitive speed in elderly with normal cognition over 4 years. Neurobiology of Aging, 31(2), 215-223. https://doi.org/10.1016/j.neurobiolaging.2008.03.025
dc.relationStrauss, E., Sherman, E. M., & Spreen, O. (2006). A compendium of neuropsychological tests: Administration, norms, and commentary. American chemical society.
dc.relationSuárez-Calvet, M., Karikari, T. K., Ashton, N. J., Lantero Rodríguez, J., Milà-Alomà, M., Gispert, J. D., Salvadó, G., Minguillon, C., Fauria, K., Shekari, M., Grau-Rivera, O., Arenaza-Urquijo, E. M., Sala-Vila, A., Sánchez-Benavides, G., González-de-Echávarri, J. M., Kollmorgen, G., Stoops, E., Vanmechelen, E., Zetterberg, H., … ALFA Study. (2020). 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 Molecular Medicine, 12(12), e12921. https://doi.org/10.15252/emmm.202012921
dc.relationTabaton, M., Nunzi, M. G., Xue, R., Usiak, M., Autilio-Gambetti, L., & Gambetti, P. (1994). Soluble amyloid beta-protein is a marker of Alzheimer amyloid in brain but not in cerebrospinal fluid. Biochemical and Biophysical Research Communications, 200(3), 1598-1603. https://doi.org/10.1006/bbrc.1994.1634
dc.relationTang, Y. P., Wang, H., Feng, R., Kyin, M., & Tsien, J. Z. (2001). Differential effects of enrichment on learning and memory function in NR2B transgenic mice. Neuropharmacology, 41(6), 779-790.
dc.relationTangalos, E. G., & Petersen, R. C. (2018). Mild Cognitive Impairment in Geriatrics. Clinics in Geriatric Medicine, 34(4), 563-589. Scopus. https://doi.org/10.1016/j.cger.2018.06.005
dc.relationTapiola, T., Alafuzoff, I., Herukka, S.-K., Parkkinen, L., Hartikainen, P., Soininen, H., & Pirttilä, T. (2009). Cerebrospinal fluid {beta}-amyloid 42 and tau proteins as biomarkers of Alzheimer-type pathologic changes in the brain. Archives of Neurology, 66(3), 382-389. https://doi.org/10.1001/archneurol.2008.596
dc.relationTatebe, H., Kasai, T., Ohmichi, T., Kishi, Y., Kakeya, T., Waragai, M., Kondo, M., Allsop, D., & Tokuda, T. (2017). Quantification of plasma phosphorylated tau to use as a biomarker for brain Alzheimer pathology: Pilot case-control studies including patients with Alzheimer’s disease and down syndrome. Molecular Neurodegeneration, 12(1), 63. https://doi.org/10.1186/s13024-017-0206-8
dc.relationThe Alzheimer’s Association QC program for CSF and blood biomarkers | University of Gothenburg. (s. f.). Recuperado 11 de marzo de 2022, de https://www.gu.se/en/neuroscience-physiology/the-alzheimers-association-qc-program-for-csf-and-blood-biomarkers
dc.relationThiyagesh, S. N., Farrow, T. F. D., Parks, R. W., Accosta-Mesa, H., Young, C., Wilkinson, I. D., Hunter, M. D., & Woodruff, P. W. R. (2009). The neural basis of visuospatial perception in Alzheimer’s disease and healthy elderly comparison subjects: An fMRI study. Psychiatry Research, 172(2), 109-116. https://doi.org/10.1016/j.pscychresns.2008.11.002
dc.relationTononi, G., Edelman, G. M., & Sporns, O. (1998). Complexity and coherency: Integrating information in the brain. Trends in Cognitive Sciences, 2(12), 474-484. https://doi.org/10.1016/S1364-6613(98)01259-5
dc.relationTononi, G., Sporns, O., & Edelman, G. M. (1994). A measure for brain complexity: Relating functional segregation and integration in the nervous system. Proceedings of the National Academy of Sciences of the United States of America, 91(11), 5033-5037. https://doi.org/10.1073/pnas.91.11.5033
dc.relationTorisson, G., van Westen, D., Stavenow, L., Minthon, L., & Londos, E. (2015). Medial temporal lobe atrophy is underreported and may have important clinical correlates in medical inpatients. BMC Geriatrics, 15(1), 65. https://doi.org/10.1186/s12877-015-0066-4
dc.relationTse, D., Takeuchi, T., Kakeyama, M., Kajii, Y., Okuno, H., Tohyama, C., Bito, H., & Morris, R. G. (2011). Schema-dependent gene activation and memory encoding in neocortex. Science, 333(6044), 891-895.
dc.relationTulving, E. (1972). Episodic and semantic memory.
dc.relationTzourio-Mazoyer, N., Landeau, B., Papathanassiou, D., Crivello, F., Etard, O., Delcroix, N., Mazoyer, B., & Joliot, M. (2002). Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain. NeuroImage, 15(1), 273-289. https://doi.org/10.1006/nimg.2001.0978
dc.relationvan den Heuvel, M. P., & Hulshoff Pol, H. E. (2010). Exploring the brain network: A review on resting-state fMRI functional connectivity. European Neuropsychopharmacology, 20(8), 519-534. Scopus. https://doi.org/10.1016/j.euroneuro.2010.03.008
dc.relationvan der Hiele, K., Vein, A. A., Reijntjes, R. H. a. M., Westendorp, R. G. J., Bollen, E. L. E. M., van Buchem, M. A., van Dijk, J. G., & Middelkoop, H. a. M. (2007). EEG correlates in the spectrum of cognitive decline. Clinical Neurophysiology: Official Journal of the International Federation of Clinical Neurophysiology, 118(9), 1931-1939. https://doi.org/10.1016/j.clinph.2007.05.070
dc.relationvan Kesteren, M. T., Fernández, G., Norris, D. G., & Hermans, E. J. (2010). Persistent schema-dependent hippocampal-neocortical connectivity during memory encoding and postencoding rest in humans. Proceedings of the National Academy of Sciences, 107(16), 7550-7555.
dc.relationvan Kesteren, M. T., Rijpkema, M., Ruiter, D. J., & Fernández, G. (2010). Retrieval of associative information congruent with prior knowledge is related to increased medial prefrontal activity and connectivity. Journal of Neuroscience, 30(47), 15888-15894.
dc.relationVanderWeele, T. J. (2019). Principles of confounder selection. European Journal of Epidemiology, 34(3), 211-219. https://doi.org/10.1007/s10654-019-00494-6
dc.relationVanhoenacker, A.-S., Sneyers, B., De Keyzer, F., Heye, S., & Demaerel, P. (2017). Evaluation and clinical correlation of practical cut-offs for visual rating scales of atrophy: Normal aging versus mild cognitive impairment and Alzheimer’s disease. Acta Neurologica Belgica, 117(3), 661-669. Scopus. https://doi.org/10.1007/s13760-017-0777-8
dc.relationVarela, F., Lachaux, J.-P., Rodriguez, E., & Martinerie, J. (2001). The brainweb: Phase synchronization and large-scale integration. Nature Reviews Neuroscience, 2(4), Art. 4. https://doi.org/10.1038/35067550
dc.relationVecchio, F., Miraglia, F., Iberite, F., Lacidogna, G., Guglielmi, V., Marra, C., Pasqualetti, P., Tiziano, F. D., & Rossini, P. M. (2018). Sustainable method for Alzheimer dementia prediction in mild cognitive impairment: Electroencephalographic connectivity and graph theory combined with apolipoprotein E: MCI Conversion. Annals of Neurology, 84(2), 302-314. https://doi.org/10.1002/ana.25289
dc.relationVecchio, F., Miraglia, F., Judica, E., Cotelli, M., Alù, F., & Rossini, P. M. (2020). Human brain networks: A graph theoretical analysis of cortical connectivity normative database from EEG data in healthy elderly subjects. GeroScience, 42(2), 575-584. https://doi.org/10.1007/s11357-020-00176-2
dc.relationVermunt, L., Sikkes, S. A. M., van den Hout, A., Handels, R., Bos, I., van der Flier, W. M., Kern, S., Ousset, P.-J., Maruff, P., Skoog, I., Verhey, F. R. J., Freund-Levi, Y., Tsolaki, M., Wallin, Å. K., Olde Rikkert, M., Soininen, H., Spiru, L., Zetterberg, H., Blennow, K., … ICTUS/DSA study groups. (2019). Duration of preclinical, prodromal, and dementia stages of Alzheimer’s disease in relation to age, sex, and APOE genotype. Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 15(7), 888-898. https://doi.org/10.1016/j.jalz.2019.04.001
dc.relationWahlund, L.-O., Westman, E., van Westen, D., Wallin, A., Shams, S., Cavallin, L., Larsson, E.-M., & From, the I. C. I. N. (ICINET). (2017). Imaging biomarkers of dementia: Recommended visual rating scales with teaching cases. Insights into Imaging, 8(1), 79-90. Scopus. https://doi.org/10.1007/s13244-016-0521-6
dc.relationWang, R., Wang, J., Yu, H., Wei, X., Yang, C., & Deng, B. (2015). Power spectral density and coherence analysis of Alzheimer’s EEG. Cognitive Neurodynamics, 9(3), 291-304. https://doi.org/10.1007/s11571-014-9325-x
dc.relationWanleenuwat, P., Iwanowski, P., & Kozubski, W. (2019). Alzheimer’s dementia: Pathogenesis and impact of cardiovascular risk factors on cognitive decline. Postgraduate Medicine, 131(7), 415-422. Scopus. https://doi.org/10.1080/00325481.2019.1657776
dc.relationWelle (www.dw.com), D. (s. f.). UNESCO: Dos de cada diez personas en América Latina no tienen los niveles mínimos de compresión de lectura | DW | 06.09.2019. DW.COM. Recuperado 12 de marzo de 2022, de https://www.dw.com/es/unesco-dos-de-cada-diez-personas-en-am%C3%A9rica-latina-no-tienen-los-niveles-m%C3%ADnimos-de-compresi%C3%B3n-de-lectura/a-50333467
dc.relationWeltgesundheitsorganisation, & Alzheimer’s Disease International (Eds.). (2012). Dementia: A public health priority.
dc.relationWillis, T. (1962). 1664. Cerebri anatome, cui accessit nervorum descriptio et usus. London: Martin & Allestry by University College London on, 5(09), 06.
dc.relationWysokiński, A., Zboralski, K., Orzechowska, A., Gałecki, P., Florkowski, A., & Talarowska, M. (2010). Normalization of the Verbal Fluency Test on the basis of results for healthy subjects, patients with schizophrenia, patients with organic lesions of the chronic nervous system and patients with type 1 and 2 diabetes. Archives of Medical Science, 6(3), 438-446.
dc.relationYetkin, F. Z., Rosenberg, R. N., Weiner, M. F., Purdy, P. D., & Cullum, C. M. (2006). FMRI of working memory in patients with mild cognitive impairment and probable Alzheimer’s disease. European Radiology, 16(1), 193-206. https://doi.org/10.1007/s00330-005-2794-x
dc.relationYi, H.-A., Won, K. S., Chang, H. W., & Kim, H. W. (2018). Association between white matter lesions and cerebral Aβ burden. PLoS ONE, 13(9). Scopus. https://doi.org/10.1371/journal.pone.0204313
dc.relationYin, Y., Edelman, G. M., & Vanderklish, P. W. (2002). The brain-derived neurotrophic factor enhances synthesis of Arc in synaptoneurosomes. Proceedings of the National Academy of Sciences, 99(4), 2368-2373. https://doi.org/10.1073/pnas.042693699
dc.relationYuste, R. (2010). Dendritic Spines. MIT Press.
dc.relationZegarra-Valdivia, J., Solís, L. D., & Chino-Vilca, B. (2019). Effectiveness of the photo-test front of the MMSE, for the screening of cognitive deterioration in Peruvian population. Revista Ecuatoriana de Neurologia, 28(1), 39-46. Scopus.
dc.relationZetterberg, H. (2016). Neurofilament Light: A Dynamic Cross-Disease Fluid Biomarker for Neurodegeneration. Neuron, 91(1), 1-3. https://doi.org/10.1016/j.neuron.2016.06.030
dc.relationZetterberg, H., Skillbäck, T., Mattsson, N., Trojanowski, J. Q., Portelius, E., Shaw, L. M., Weiner, M. W., Blennow, K., & Alzheimer’s Disease Neuroimaging Initiative. (2016). Association of Cerebrospinal Fluid Neurofilament Light Concentration With Alzheimer Disease Progression. JAMA Neurology, 73(1), 60-67. https://doi.org/10.1001/jamaneurol.2015.3037
dc.relationZhang, H., & Jacobs, J. (2015). Traveling theta waves in the human hippocampus. Journal of Neuroscience, 35(36), 12477-12487.
dc.rightsAtribución-NoComercial-CompartirIgual 4.0 Internacional (CC BY-NC-SA 4.0)
dc.rightshttps://creativecommons.org/licenses/by-nc-sa/4.0/
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.rightshttp://purl.org/coar/access_right/c_14cb
dc.subjectDemencia tipo alzheimer (DA)
dc.subjectDeterioro cognitivo veve (DCL)
dc.subjectElectroencefalograma (EEG)
dc.subjectEspectro de potencia
dc.subjectConectividad funcional
dc.subjectFototest
dc.subjectMoca
dc.subjectAlzheimer's dementia (AD)
dc.subjectMild cognitive impairment (MCI)
dc.subjectElectroencephalogram (EEG)
dc.subjectPower spectra
dc.subjectFunctional connectivity
dc.subjectFototest
dc.titlePerfil de conectividad cerebral y el rendimiento cognitivo en consulta neurológica
dc.typeTrabajo de grado - Doctorado
dc.typehttp://purl.org/coar/resource_type/c_db06
dc.typeText
dc.typeinfo:eu-repo/semantics/doctoralThesis
dc.typehttp://purl.org/redcol/resource_type/TD
dc.typeinfo:eu-repo/semantics/draft
dc.typehttp://purl.org/coar/version/c_b1a7d7d4d402bcce


Este ítem pertenece a la siguiente institución