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Poster A76 in Poster Session A - Tuesday, August 6, 2024, 4:15 – 6:15 pm, Johnson Ice Rink
Topological turning points across the human lifespan
Alexa Mousley1 (), Duncan Astle1; 1University of Cambridge
Structural topology of neural networks develops non-linearly across the lifespan and is strongly related to cognitive outcomes. Here, we aggregated diffusion imaging from nine datasets with a collective age range of zero to 90 years old (N = 4,216). Our analysis focused on understanding how network organization changes across age. We projected this data into a three-dimensional manifold space using Uniform Manifold Projection and Approximation. Using this manifold, we identified four major turning points in topology across the lifespan: at ages 8, 32, 62, and 85 years. These turning points demarcate five major epochs within which topological development occurs along similar trajectories. By comparing correlations, principal components analysis scores, and dynamic time warping distances, we conclude these epochs mark important shifts in topological development based on directionality, driving forces, and trajectories. Our findings underscore the significance of generalizing topological development beyond individual organizational metrics to enrich our understanding of network development trajectories and crucial turning points across the lifespan. Future directions for this project include using weighted generative network modeling and cognitive analysis to investigate potential disparities in topological trajectories among individuals.
Keywords: topology structural networks manifold learning lifespan trajectories