论文标题
不断发展的网络上的神经元振荡：动态，损害，降解，衰落，痴呆和死亡
Neuronal Oscillations on Evolving Networks: Dynamics, Damage, Degradation, Decline, Dementia, and Death
论文作者
论文摘要
神经退行性疾病，例如阿尔茨海默氏病或帕金森氏病，显示出结构性脑网络的特征性降解。这种降解最终导致网络动力学和认知功能的降解发生变化。在这里，我们根据耦合的物理过程对进展进行建模：通过非线性反应 - 扩散传输过程给出的有毒蛋白的积累产生了不断发展的脑连接组，其特征是加权边缘，神经元质量模型在其上演变。可以通过模拟不断发展的大脑网络上的静息状态活动来测试大脑功能的进展。我们表明，尽管边缘权重的演变在疾病的整体进展中起着较小的作用，但动态生物标志物预测在与强烈认知下降的10年期间的过渡过程中的过渡。
Neurodegenerative diseases, such as Alzheimer's or Parkinson's disease, show characteristic degradation of structural brain networks. This degradation eventually leads to changes in the network dynamics and degradation of cognitive functions. Here, we model the progression in terms of coupled physical processes: The accumulation of toxic proteins, given by a nonlinear reaction-diffusion transport process, yields an evolving brain connectome characterized by weighted edges on which a neuronal-mass model evolves. The progression of the brain functions can be tested by simulating the resting-state activity on the evolving brain network. We show that while the evolution of edge weights plays a minor role in the overall progression of the disease, dynamic biomarkers predict a transition over a period of 10 years associated with strong cognitive decline.
