Estudio espectral y de sincronía fase como biomarcadores para detección temprana de enfermedades neurodegenerativa

Authors

  • Lucas Sánchez Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Argentina
  • Ana Carolina Maldonado Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Argentina. Centro de Investigación y Estudios en Matemática. (CIEM-CONICET). Consejo Nacional de Investigaciones Científicas y Tecnológicas (CONICET).
  • Diego Mateos  Universidad Autónoma de Entre Ríos. Facultad de Ciencias y Tecnología. Consejo Nacional de Investigaciones Científicas y Tecnológicas (CONICET). Argentina Instituto de Matemática Aplicada del Litoral (CONICET-IMAL-UNL) 

Keywords:

Enfermedades Neurodegenerativas, Biomarcadores, Conectividad, Espectro de Potencia

Abstract

Neurodegenerative diseases as Alzheimer's disease (AD) leading cause of dementia worldwide, Mild Cognitive Impairment (MCI) and possible precursor of dementia are highly prevalent diseases with a strong impact on the quality of life of the patient. Finding tools that allow an early diagnosis would provide the possibility of early treatment. Using the database of resting state Magnetoencephalography studies, spectral and connectivity methods were applied to study the development of new biomarkers that can be used for the early detection of AD and MCI. The results showed the existence of significant differences between the Control, AD and MCI groups on particular electrophysiological frequency bands. It is hoped that this analysis can be a complementary aid for the early diagnosis of these diseases in the clinical area.

References

Bergen, D. C., & Silberberg, D. (2002). Nervous system disorders: a global epidemic. Archives of neurology, 59(7), 1194-1196.

Cancino, M., & Rehbein, L. (2016). Factores de riesgo y precursores del Deterioro Cognitivo Leve (DCL): Una mirada sinóptica. Terapia psicológica, 34(3), 183-189.

Higdon, R., Foster, N. L., Koeppe, R. A., DeCarli, C. S., Jagust, W. J., Clark, C. M., ... & Minoshima, S. (2004). A comparison of classification methods for differentiating fronto-temporal dementia from Alzheimer's disease using FDG-PET imaging. Statistics in medicine, 23(2), 315-326.

Price, D. L. (2001). Aging of the brain and dementia of the Alzheimer type. Principles of neural science.

Mora-Simón, S., García-García, R., Perea-Bartolomé, M. V., Ladera-Fernández, V., Unzueta-Arce, J., Patino-Alonso, M. C., & Rodríguez-

Sánchez, E. (2012). Deterioro cognitivo leve: detección temprana y nuevas perspectivas. Rev Neurol, 54(5), 303-310.

Mormann, F., Lehnertz, K., David, P., & Elger, C. E. (2000). Mean phase coherence as a measure for phase synchronization and its application to the EEG of epilepsy patients. Physica D: Nonlinear Phenomena, 144(3-4), 358-369.

Test de Wilcoxon Mann Whitney como alternativa al t-test by Joaquín Amat Rodrigo, available under a Attribution 4.0 International (CC BY 4.0) at https://www.cienciadedatos.net/documentos/17_mann–whitney_u_test

Nakamura, A., Cuesta, P., Fernández, A., Arahata, Y., Iwata, K., Kuratsubo, I., ... & Kato, T. (2018). Electromagnetic signatures of the preclinical and prodromal stages of Alzheimer’s disease. Brain, 141(5), 1470-1485.

López-Sanz, D., Serrano, N., & Maestú, F. (2018). The role of magnetoencephalography in the early stages of Alzheimer’s disease. Frontiers in neuroscience, 12, 572.

Berendse, H. W., Verbunt, J. P. A., Scheltens, P., Van Dijk, B. W., & Jonkman, E. J. (2000). Magnetoencephalographic analysis of cortical activity in Alzheimer's disease: a pilot study. Clinical Neurophysiology, 111(4), 604-612.

Huang, C., Wahlund, L. O., Dierks, T., Julin, P., Winblad, B., & Jelic, V. (2000). Discrimination of Alzheimer's disease and mild cognitive impairment by equivalent EEG sources: a cross-sectional and longitudinal study. Clinical Neurophysiology, 111(11), 1961-1967.

Engels, M. M. A., Van der Flier, W. M., Stam, C. J., Hillebrand, A., Scheltens, P., & van Straaten, E. C. W. (2017). Alzheimer’s disease: the state of the art in resting-state magnetoencephalography.Clinical Neurophysiology, 128(8), 1426-1437.

Fernández, A., Arrazola, J., Maestú, F., Amo, C., Gil-Gregorio, P., Wienbruch, C., & Ortiz, T. (2003). Correlations of hippocampal atrophy and focal low-frequency magnetic activity in Alzheimer disease: volumetric MR imaging-magnetoencephalographic study. American Journal of Neuroradiology, 24(3), 481-487.

Stam, C. J., van Walsum, A. M. V. C., Pijnenburg, Y. A., 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.

Stam, C. J., Jones, B. F., Manshanden, I., Van Walsum, A. V. C., Montez, T., Verbunt, J. P., ... & Scheltens, P. (2006). Magnetoencephalographic evaluation of resting-state functional connectivity in Alzheimer's disease. Neuroimage, 32(3), 1335-1344.

López, M. E., Cuesta, P., Garcés, P., Castellanos, P. N., Aurtenetxe, S., Bajo, R., ... & Fernandez, A. (2014). MEG spectral analysis in subtypes of mild cognitive impairment. Age, 36(3), 1095-1112.

Babiloni, C., Del Percio, C., Boccardi, M., Lizio, R., Lopez, S., Carducci, F., ... & Frisoni, G. B. (2015). Occipital sources of resting-state alpha rhythms are related to local gray matter density in subjects with amnesic mild cognitive impairment and Alzheimer's disease. Neurobiology of aging, 36(2), 556-570.

Akinori Nakamura, Pablo Cuesta, Alberto Fernández, Yutaka Arahata, Kaori Iwata, Izumi Kuratsubo, Ma-sahiko Bundo, Hideyuki Hattori, Takashi Sakurai, Koji Fukuda, et al. Electromagnetic signatures of the preclinical and prodromal stages of Alzheimer's disease. Brain, 141(5):1470–1485, 2018.

Poirier, J., Delisle, M. C., Quirion, R., Aubert, I., Farlow, M., Lahiri, D., ... & Gilfix, B. M. (1995). Apolipoprotein E4 allele as a predictor of cholinergic deficits and treatment outcome in Alzheimer disease. Proceedings of the National Academy of Sciences, 92(26), 12260-12264.

Garcés, P., Vicente, R., Wibral, M., Pineda Pardo, J. A., López, M. E., Aurtenetxe, S., ... & Fernández, A. (2013). Brain-wide slowing of spontaneous alpha rhythms in mild cognitive impairment. Frontiers in aging neuroscience, 5, 100.

Fernández, A., Hornero, R., Mayo, A., Poza, J., Gil-Gregorio, P., & Ortiz, T. (2006). MEG spectral profile in Alzheimer's disease and mild cognitive impairment. Clinical Neurophysiology, 117(2), 306-314.

Engels, M., Hillebrand, A., van der Flier, W. M., Stam, C. J., Scheltens, P., & van Straaten, E. C. (2016). Slowing of hippocampal activity correlates with cognitive decline in early onset Alzheimer’s disease. An MEG study with virtual electrodes. Frontiers in human neuroscience, 10, 238.

López, M. E., Turrero, A., Cuesta, P., López-Sanz, D., Bruña, R., Marcos, A., ... & Fernández, A. (2016). Searching for primary predictors of conversion from mild cognitive impairment to Alzheimer’s disease: a multivariate follow-up study. Journal of Alzheimer's Disease, 52(1), 133-143.

Downloads

Published

2022-11-30

How to Cite

Sánchez, L., Maldonado, A. C., & Mateos , D. (2022). Estudio espectral y de sincronía fase como biomarcadores para detección temprana de enfermedades neurodegenerativa. Revista Argentina De ingeniería, 20, 54–59. Retrieved from https://radi.org.ar/index.php/radi/article/view/119

Issue

Vol. 20 (10)

Section

ARTÍCULOS

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.