Neuronal activity induces symmetry breaking in neurodegenerative disease spreading
Neuronal activity induces symmetry breaking in neurodegenerative disease spreading
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DOI：
10.1101/2023.10.02.560495
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发表时间：
2023-10
期刊：
影响因子：
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通讯作者：
Christoffer G. Alexandersen;A. Goriely;C. Bick
中科院分区：
文献类型：
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作者：
Christoffer G. Alexandersen;A. Goriely;C. Bick
网络上的动力系统通常涉及几个在不同时间尺度上演化的动态过程。例如，在阿尔茨海默病中，有毒蛋白质在整个大脑中的传播不仅扰乱了神经元的活动，而且还受到神经元活动本身的影响，在快速的神经元活动和缓慢的蛋白质传播之间建立了一个反馈回路。受阿尔茨海默病的启发，我们在Kuramoto振荡器的自适应网络上研究了异二聚体传播过程的多时间尺度动力学。利用一个最小两节点模型，我们证明了异质振荡活动促进了毒物的爆发，并导致了传播模式的对称性破缺。然后，我们将模型公式扩展到更大的网络，并对常见的网络主题和大脑连接体进行了慢速动力学的数值模拟。这些模拟证实了最小模型的发现，强调了多时间尺度动力学在神经退行性疾病建模中的重要性。
Dynamical systems on networks typically involve several dynamical processes evolving at different timescales. For instance, in Alzheimer’s disease, the spread of toxic protein throughout the brain not only disrupts neuronal activity but is also influenced by neuronal activity itself, establishing a feed-back loop between the fast neuronal activity and the slow protein spreading. Motivated by the case of Alzheimer’s disease, we study the multiple-timescale dynamics of a heterodimer spreading process on an adaptive network of Kuramoto oscillators. Using a minimal two-node model, we establish that heterogeneous oscillatory activity facilitates toxic outbreaks and induces symmetry breaking in the spreading patterns. We then extend the model formulation to larger networks and perform numerical simulations of the slow-fast dynamics on common network motifs and on the brain connectome. The simulations corroborate the findings from the minimal model, underscoring the significance of multiple-timescale dynamics in the modeling of neurodegenerative diseases.