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      Alteración de la entropía en la precuña y la corteza cingulada posterior en la enfermedad de Alzheimer: estudio de resonancia magnética funcional en reposo Translated title: Alteration of Entropy in the Precuneus and Posterior Cingulate Cortex in Alzheimer’s Disease: A Resting-State Functional Magnetic Resonance Study

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          Abstract

          Resumen El cerebro humano ha sido descrito como un sistema complejo. Su estudio por medio de señales neurofisiológicas ha desvelado la presencia de interacciones lineales y no lineales. En este contexto, se han utilizado métricas de entropía para descubrir el comportamiento cerebral en presencia y ausencia de alteraciones neurológicas. El mapeo de la entropía es de gran interés para el estudio de enfermedades neurodegenerativas progresivas como la enfermedad de Alzheimer. El objetivo de este estudio fue caracterizar la dinámica de las oscilaciones cerebrales en dicha enfermedad por medio de la entropía y la amplitud de las oscilaciones de baja frecuencia a partir de señales Bold de la red por defecto y la red de control ejecutivo en pacientes con Alzheimer e individuos sanos, utilizando una base de datos extraída de la serie de estudios de imágenes de acceso abierto. Los resultados revelaron mayor poder discriminatorio de la entropía por permutaciones en comparación a la amplitud de fluctuación de baja frecuencia y la amplitud fraccional de fluctuaciones de baja frecuencia. Se obtuvo un incremento de la entropía por permutaciones en regiones de la red por defecto y la red de control ejecutivo en pacientes. La corteza cingulada posterior y la precuña manifestaron característica diferencial al evaluar la entropía por permutaciones en ambos grupos. No hubo hallazgos al correlacionar las métricas con las escalas clínicas. Los resultados demostraron que la entropía por permutaciones permite caracterizar la función cerebral en pacientes con Alzheimer, además revela información sobre las interacciones no lineales complementaria a las características obtenidas por medio del cálculo de la amplitud de las oscilaciones de baja frecuencia.

          Translated abstract

          Abstract The human brain has been described as a complex system. Its study using neurophysiological signals has revealed the presence of linear and non-linear interactions. In this context, entropy metrics have been used to discover brain behavior in the presence and absence of neurological alterations. Entropy mapping is of great interest for the study of progressive neurodegenerative diseases such as Alzheimer’s Disease (AD). The objective of this study was to characterize the dynamics of brain oscillations in AD using entropy and the Amplitude of Low-Frequency Fluctuations (ALFF) of BOLD signals from the default network and the executive control network in patients with AD and healthy individuals. For this purpose, the data was extracted from the Open Access Series of Imaging Studies (OASIS). The results revealed greater discriminatory power in Permutation Entropy (PE) than in ALFF and fractional ALFF metrics. An increase in PE was obtained in regions of the default network and the executive control network in patients. The posterior cingulate cortex and the precuneus exhibited a differential characteristic when PE was evaluated in both groups. There were no findings when the metrics were correlated with clinical scales. The results showed that PE can be used to characterize the brain function in patients with AD and reveals information about non-linear interactions complementary to the characteristics obtained by calculating the ALFF.

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          Most cited references45

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          Conn: a functional connectivity toolbox for correlated and anticorrelated brain networks.

          Resting state functional connectivity reveals intrinsic, spontaneous networks that elucidate the functional architecture of the human brain. However, valid statistical analysis used to identify such networks must address sources of noise in order to avoid possible confounds such as spurious correlations based on non-neuronal sources. We have developed a functional connectivity toolbox Conn ( www.nitrc.org/projects/conn ) that implements the component-based noise correction method (CompCor) strategy for physiological and other noise source reduction, additional removal of movement, and temporal covariates, temporal filtering and windowing of the residual blood oxygen level-dependent (BOLD) contrast signal, first-level estimation of multiple standard functional connectivity magnetic resonance imaging (fcMRI) measures, and second-level random-effect analysis for resting state as well as task-related data. Compared to methods that rely on global signal regression, the CompCor noise reduction method allows for interpretation of anticorrelations as there is no regression of the global signal. The toolbox implements fcMRI measures, such as estimation of seed-to-voxel and region of interest (ROI)-to-ROI functional correlations, as well as semipartial correlation and bivariate/multivariate regression analysis for multiple ROI sources, graph theoretical analysis, and novel voxel-to-voxel analysis of functional connectivity. We describe the methods implemented in the Conn toolbox for the analysis of fcMRI data, together with examples of use and interscan reliability estimates of all the implemented fcMRI measures. The results indicate that the CompCor method increases the sensitivity and selectivity of fcMRI analysis, and show a high degree of interscan reliability for many fcMRI measures.
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            DPABI: Data Processing & Analysis for (Resting-State) Brain Imaging.

            Brain imaging efforts are being increasingly devoted to decode the functioning of the human brain. Among neuroimaging techniques, resting-state fMRI (R-fMRI) is currently expanding exponentially. Beyond the general neuroimaging analysis packages (e.g., SPM, AFNI and FSL), REST and DPARSF were developed to meet the increasing need of user-friendly toolboxes for R-fMRI data processing. To address recently identified methodological challenges of R-fMRI, we introduce the newly developed toolbox, DPABI, which was evolved from REST and DPARSF. DPABI incorporates recent research advances on head motion control and measurement standardization, thus allowing users to evaluate results using stringent control strategies. DPABI also emphasizes test-retest reliability and quality control of data processing. Furthermore, DPABI provides a user-friendly pipeline analysis toolkit for rat/monkey R-fMRI data analysis to reflect the rapid advances in animal imaging. In addition, DPABI includes preprocessing modules for task-based fMRI, voxel-based morphometry analysis, statistical analysis and results viewing. DPABI is designed to make data analysis require fewer manual operations, be less time-consuming, have a lower skill requirement, a smaller risk of inadvertent mistakes, and be more comparable across studies. We anticipate this open-source toolbox will assist novices and expert users alike and continue to support advancing R-fMRI methodology and its application to clinical translational studies.
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              Synergy between amyloid-β and tau in Alzheimer’s disease

              Patients with Alzheimer's disease (AD) present with both extracellular amyloid-β (Aβ) plaques and intracellular tau-containing neurofibrillary tangles in the brain. For many years, the prevailing view of AD pathogenesis has been that changes in Aβ precipitate the disease process and initiate a deleterious cascade involving tau pathology and neurodegeneration. Beyond this 'triggering' function, it has been typically presumed that Aβ and tau act independently and in the absence of specific interaction. However, accumulating evidence now suggests otherwise and contends that both pathologies have synergistic effects. This could not only help explain negative results from anti-Aβ clinical trials but also suggest that trials directed solely at tau may need to be reconsidered. Here, drawing from extensive human and disease model data, we highlight the latest evidence base pertaining to the complex Aβ-tau interaction and underscore its crucial importance to elucidating disease pathogenesis and the design of next-generation AD therapeutic trials.
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                Author and article information

                Journal
                teclo
                TecnoLógicas
                TecnoL.
                Instituto Tecnológico Metropolitano - ITM (Medellín, Antioquia, Colombia )
                0123-7799
                2256-5337
                December 2021
                : 24
                : 52
                : 136-157
                Affiliations
                [1] Medellín Antioquía orgnameUniversidad de Antioquia Colombia aura.puche@ 123456udea.edu.co
                [2] Medellín Antioquía orgnameUniversidad de Antioquia Colombia john.ochoa@ 123456udea.edu.co
                [5] Medellín orgnameInstitución Prestadora de Servicios de Salud IPS Universitaria Colombia carlos.tobonq@ 123456udea.edu.co
                [3] Medellín Antioquía orgnameUniversidad de Antioquia Colombia yesika.agudelo@ 123456udea.edu.co
                [4] Medellín orgnameInstitución Prestadora de Servicios de Salud IPS Universitaria Colombia jan.rodas@ 123456udea.edu.co
                Article
                S0123-77992021000300136 S0123-7799(21)02405200136
                10.22430/22565337.2118
                06ee74d6-8faf-4554-a865-006660664ef0

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

                History
                : 09 August 2021
                : 23 November 2021
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 45, Pages: 22
                Product

                SciELO Colombia

                Categories
                Artículos de investigación

                Functional magnetic resonance imaging,Alzheimer’s disease,Permutation entropy,Medical image processing,Default mode network,Executive network,Resonancia magnética funcional,enfermedad de Alzheimer,procesamiento de imágenes médicas,entropía por permutaciones,red por defecto,red de control ejecutivo

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