Análisis de la asimetría estructural y funcional del cerebro a lo largo de la vida usando base de datos del HCP de envejecimiento.
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Date
2025
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Universidad de Concepción
Abstract
El envejecimiento cerebral conlleva cambios graduales en la estructura y funcionalidad del cerebro, afectando las capacidades cognitivas y los patrones de comportamiento. En este contexto, la asimetría cerebral, entendida como la diferencia entre los hemisferios, ofrece información valiosa sobre la organización cerebral y puede contribuir a la detección temprana de alteraciones estructurales asociadas a enfermedades neurodegenerativas.
El presente estudio analizó cómo el envejecimiento influye en la asimetría cerebral, mediante el análisis de métricas estructurales (materia gris y blanca) y funcionales del cerebro. El objetivo principal fue caracterizar las asimetrías de la conectividad estructural y funcional en individuos sanos. Para ello, se utilizó la base de datos del Human Connectome Project– Aging, que incluye datos de 725 sujetos con edades comprendidas entre los 36 y 100 años.
Mediante la aplicación de modelos estadísticos, se identificaron patrones específicos de asimetría asociados al envejecimiento. Los resultados evidenciaron tanto tendencias lineales como no lineales, observadas en métricas estructurales y funcionales. Además, se evaluó la relación entre estructura y función, identificándose un componente significativo que vincula una métrica de la materia gris con una de conectividad funcional, sugiriendo una correspondencia entre la organización anatómica y la dinámica funcional del cerebro.
En la materia gris, se encontró un componente principal significativo para el área superficial, compuesto por 2 regiones, para el espesor cortical medio, 3 componentes principales que en conjunto incluyen 21 regiones corticales, y para el volumen, 2 componentes principales que abarcan 4 regiones subcorticales en total. Se destaca que, para la métrica de volumen, el cambio de los componentes principales se explicaba en un 7.13% por la edad, siendo este el valor más alto entre las métricas de materia gris, mientras que el área superficial presentó el valor más bajo, con un 2.64%.
En la materia blanca se observó, en general, una mayor variabilidad asociada con la edad en comparación con la materia gris, coincidiendo con lo reportado en la literatura. De manera más específica, las fibras cortas, a diferencia de las largas, muestran una mayor variabilidad con la edad. Esto podría estar relacionado con el hecho, descrito en la literatura, de que las fibras cortas poseen menor cantidad de mielina que las fibras largas, lo que las puede hacer más susceptibles a procesos de desmielinización vinculados al envejecimiento y reflejarse en una mayor vulnerabilidad estructural.
Dentro de las fibras cortas, se destaca la métrica promedio de anisotropía fraccional (FA), donde el cambio de los componentes principales se explicaba en un 26.96% por la edad, siendo este el valor más alto entre las métricas de materia blanca y gris. La métrica promedio de difusividad media (MD) presentó el valor más bajo, con un 7.56%. En las fibras largas, el mayor valor correspondió a la métrica promedio de difusividad axial (AD) con un 5.16%, mientras que la menor fue la anisotropía cuantitativa (QA) con un 3.5%.
Respecto a los componentes principales en fibras cortas, se identificaron un total de 7 componentes significativos en la métrica de FA, compuestos por 22 fascículos. En QA se obtuvieron 4 componentes principales, que en conjunto incluyen 15 fascículos. Para AD se identificó un componente con 4 fascículos, para RDuncomponentecon3fascículosyparaMDuncomponentecon3fascículos.Enfibraslargas, para la métrica promedio de FA, un componente principal significativo compuesto por 2 fascículos, en QA, un componente compuesto por 2 fascículos, en AD, un componente compuesto por 4 fascículos, en RD, un componente compuesto con 3 fascículos, y en MD, 2 componentes que abarcan un total de 6 fascículos.
En la conectividad funcional, se observó que la métrica de longitud del camino más corto presentó el mayor porcentaje de variación asociado a la edad, con un 56.07%, superando al resto de las métricas funcionales y estructurales. Esto sugiere que los cambios en la eficiencia de integración funcional del cerebro son particularmente sensibles al envejecimiento y podrían reflejar procesos de reorganización de la red funcional.
Estos hallazgos, pueden servir como referencia para futuras investigaciones, facilitando la compa ración con poblaciones que presentan alguna patología neurológica y contribuyendo a una evaluación más precisa de cómo estas condiciones afectan la asimetría cerebral en contraste con el envejecimiento normal.
Brain aging involves gradual changes in the structure and functionality of the brain, affecting cog nitive abilities and behavioral patterns. In this context, brain asymmetry, understood as the difference between hemispheres, provides valuable information about brain organization and can contribute to the early detection of structural alterations associated with neurodegenerative diseases. This study analyzed how aging influences brain asymmetry through the examination of structural (gray and white matter) and functional brain metrics. The main objective was to characterize asymmetries in structural and functional connectivity in healthy individuals. For this purpose, data from the Human Connectome Project– Aging was used, which includes information from 725 subjects aged between 36 and 100 years. Byapplying statistical models, specific asymmetry patterns associated with aging were identified. The results revealed both linear and nonlinear trends across structural and functional metrics. Furthermore, the structure–function relationship was evaluated, identifying a significant component that links a gray matter metric with a functional connectivity metric, suggesting a correspondence between anatomical organization and functional dynamics of the brain. In gray matter, a significant principal component was found for surface area, consisting of 2 regions, for mean cortical thickness, 3 principal components collectively including 21 cortical regions, and for volume, 2 principal components encompassing a total of 4 subcortical regions. It should be noted that, for the volume metric, changes in the principal components were explained 7.13% by age, the highest value among gray matter metrics, whereas surface area showed the lowest value, at 2.64%. In white matter, overall, greater variability associated with age was observed compared to gray matter, consistent with what has been reported in the literature. More specifically, short fibers, unlike long fibers, show greater variability with age. This could be related to the fact, described in the literature, that short f ibers contain less myelin than long fibers, making them more susceptible to age related demyelination processes and reflecting higher structural vulnerability. Within short fibers, the mean fractional anisotropy (FA) metric stands out, where principal compo nent changes were explained 26.96% by age, the highest value among white and gray matter metrics. The mean diffusivity (MD) metric showed the lowest value, at 7.56%. In long fibers, the highest va lue corresponded to the mean axial diffusivity (AD) metric at 5.16%, while the lowest was quantitative anisotropy (QA) at 3.5%. Regarding principal components in short fibers, a total of 7 significant components were identified in the FA metric, comprising 22 bundles. In QA, 4 principal components were obtained, collectively including 15 bundles. For AD, 1 component with 4 bundles was identified, for RD, 1 component with 3 bundles, and for MD, 1 component with 3 bundles. In long fibers, for the mean FA metric, 1 significant principal component consisting of 2 bundles, in QA, 1 component of 2 bundles, in AD, 1 component of 4 bundles, in RD, 1 component of 3 bundles; and in MD, 2 components encompassing a total of 6 bundles. In functional connectivity, the shortest path length metric showed the highest percentage of variation associated with age, at 56.07%, surpassing the other functional metrics as well as the structural ones. This suggests that changes in the brain’s functional integration efficiency are particularly sensitive to aging and may reflect processes of functional network reorganization. The findings of this study may serve as a reference for future research, enabling comparisons with populations affected by neurological conditions and contributing to a more precise understanding of how such conditions influence brain asymmetry in contrast to normal aging.
Brain aging involves gradual changes in the structure and functionality of the brain, affecting cog nitive abilities and behavioral patterns. In this context, brain asymmetry, understood as the difference between hemispheres, provides valuable information about brain organization and can contribute to the early detection of structural alterations associated with neurodegenerative diseases. This study analyzed how aging influences brain asymmetry through the examination of structural (gray and white matter) and functional brain metrics. The main objective was to characterize asymmetries in structural and functional connectivity in healthy individuals. For this purpose, data from the Human Connectome Project– Aging was used, which includes information from 725 subjects aged between 36 and 100 years. Byapplying statistical models, specific asymmetry patterns associated with aging were identified. The results revealed both linear and nonlinear trends across structural and functional metrics. Furthermore, the structure–function relationship was evaluated, identifying a significant component that links a gray matter metric with a functional connectivity metric, suggesting a correspondence between anatomical organization and functional dynamics of the brain. In gray matter, a significant principal component was found for surface area, consisting of 2 regions, for mean cortical thickness, 3 principal components collectively including 21 cortical regions, and for volume, 2 principal components encompassing a total of 4 subcortical regions. It should be noted that, for the volume metric, changes in the principal components were explained 7.13% by age, the highest value among gray matter metrics, whereas surface area showed the lowest value, at 2.64%. In white matter, overall, greater variability associated with age was observed compared to gray matter, consistent with what has been reported in the literature. More specifically, short fibers, unlike long fibers, show greater variability with age. This could be related to the fact, described in the literature, that short f ibers contain less myelin than long fibers, making them more susceptible to age related demyelination processes and reflecting higher structural vulnerability. Within short fibers, the mean fractional anisotropy (FA) metric stands out, where principal compo nent changes were explained 26.96% by age, the highest value among white and gray matter metrics. The mean diffusivity (MD) metric showed the lowest value, at 7.56%. In long fibers, the highest va lue corresponded to the mean axial diffusivity (AD) metric at 5.16%, while the lowest was quantitative anisotropy (QA) at 3.5%. Regarding principal components in short fibers, a total of 7 significant components were identified in the FA metric, comprising 22 bundles. In QA, 4 principal components were obtained, collectively including 15 bundles. For AD, 1 component with 4 bundles was identified, for RD, 1 component with 3 bundles, and for MD, 1 component with 3 bundles. In long fibers, for the mean FA metric, 1 significant principal component consisting of 2 bundles, in QA, 1 component of 2 bundles, in AD, 1 component of 4 bundles, in RD, 1 component of 3 bundles; and in MD, 2 components encompassing a total of 6 bundles. In functional connectivity, the shortest path length metric showed the highest percentage of variation associated with age, at 56.07%, surpassing the other functional metrics as well as the structural ones. This suggests that changes in the brain’s functional integration efficiency are particularly sensitive to aging and may reflect processes of functional network reorganization. The findings of this study may serve as a reference for future research, enabling comparisons with populations affected by neurological conditions and contributing to a more precise understanding of how such conditions influence brain asymmetry in contrast to normal aging.
Description
Tesis presentada para optar al grado de Magíster en Ciencias de la Ingeniería con mención en Ingeniería Eléctrica.
Keywords
Cerebro Envejecimiento, Fisiología Bases de datos