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<p>Adult neurogenesis is defined as the process by which new neurons are produced from neural stem cells in the adult brain. A comprehensive understanding of the mechanisms that regulate this process is essential for the development of effective interventions aimed at decelerating the decline of adult neurogenesis associated with ageing. Mathematical models provide a valuable tool for studying the dynamics of neural stem cells and their lineage, and have revealed alterations in these processes during the ageing process. The present study draws upon experimental data to explore how these processes are modulated by investigating regulatory feedback mechanisms among neural populations through the lens of nonlinear differential equations models. Our observations indicate that the time evolution of the neural lineage is predominantly regulated by neural stem cells, with more differentiated neural populations exerting a comparatively weaker influence. Furthermore, we shed light on the manner in which different subpopulations govern these regulations and gain insights into the impact of specific perturbations on the system.</p>

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Unraveling regulatory feedback mechanisms in adult neurogenesis through mathematical modelling

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年7月26日

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  • Diana-Patricia Danciu,
  • Filip Z. Klawe,
  • Alexey Kazarnikov,
  • Laura Femmer,
  • Ekaterina Kostina,
  • Ana Martin-Villalba,
  • Anna Marciniak-Czochra

摘要

Adult neurogenesis is defined as the process by which new neurons are produced from neural stem cells in the adult brain. A comprehensive understanding of the mechanisms that regulate this process is essential for the development of effective interventions aimed at decelerating the decline of adult neurogenesis associated with ageing. Mathematical models provide a valuable tool for studying the dynamics of neural stem cells and their lineage, and have revealed alterations in these processes during the ageing process. The present study draws upon experimental data to explore how these processes are modulated by investigating regulatory feedback mechanisms among neural populations through the lens of nonlinear differential equations models. Our observations indicate that the time evolution of the neural lineage is predominantly regulated by neural stem cells, with more differentiated neural populations exerting a comparatively weaker influence. Furthermore, we shed light on the manner in which different subpopulations govern these regulations and gain insights into the impact of specific perturbations on the system.