Altering neuronal excitability to preserve network connectivity in a computational model of Alzheimer's disease.
Altering neuronal excitability to preserve network connectivity in a computational model of Alzheimer's disease.
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DOI：
10.1371/journal.pcbi.1005707
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发表时间：
2017-09
影响因子：
4.3
通讯作者：
Stam CJ
中科院分区：
文献类型：
--
作者：
de Haan W;van Straaten ECW;Gouw AA;Stam CJ
在临床前阿尔茨海默病（AD）中，越来越多地观察到大脑皮层和海马区域的神经元过度活跃和过度兴奋现象。在后期阶段，振荡减慢和功能连接的丧失是普遍存在的。最近的证据表明，神经元动力学在AD病理生理学中具有突出的作用，使其成为潜在的有趣的治疗靶点。然而，尽管神经元活动可以通过各种（非）药理学手段来操纵，但对依赖于复杂动力学的高度集成系统进行干预可能会产生违反直觉的不良影响。计算动态网络建模可以作为制定有效干预措施的虚拟试验场。为了探索这种方法，使用先前引入的具有人脑拓扑结构的大规模神经质量网络来模拟AD样的活动依赖性网络退化的时间演化。此外，六个防御策略，无论是增强或减弱神经元的兴奋性进行了测试，对退化过程中，兴奋性和抑制性神经元的组合或单独为目标。结果测量描述了受损网络的振荡，连通性和拓扑特征。随着时间的推移，各种干预措施产生了不同的大规模网络效应。与我们的假设相反，最成功的策略是选择性刺激网络中的所有兴奋性神经元;它大大延长了网络完整性的保存。这项研究的结果意味着，由于病理性神经元活动的功能网络损伤，可以反对有针对性的调整神经元兴奋性水平。目前的方法可能有助于探索旨在保护或恢复神经元网络完整性的治疗效果，并有助于在未来的AD临床试验中更好地了解干预选择。阿尔茨海默病（AD）是一个日益增长的社会负担，目前还没有治愈的方法。病理性高神经元活性和兴奋性是在早期AD中越来越多地观察到的现象。它在疾病过程中的确切作用尚不清楚，但它可能形成一个有趣的治疗靶点。然而，尽管大脑动力学可以在许多方面受到影响，但大脑的高度复杂性使得很难预测哪种方法最有效。为了验证我们的假设，即神经元过度活跃可以通过改变神经元兴奋性水平来有效地对抗，我们研究了各种策略，旨在保持人脑的计算AD模型中的脑网络完整性。在这些策略中，涉及刺激兴奋性神经元的方案最成功地延长了具有正常网络功能的时间。这个“虚拟试验”的结果表明，病理性神经元活动的网络效应可以通过选择性改变神经元兴奋性水平来对抗。总的来说，这种方法可以探索旨在保持或恢复脑网络完整性的治疗效果，从而有助于为未来的AD临床试验选择有前途的干预措施。
Neuronal hyperactivity and hyperexcitability of the cerebral cortex and hippocampal region is an increasingly observed phenomenon in preclinical Alzheimer’s disease (AD). In later stages, oscillatory slowing and loss of functional connectivity are ubiquitous. Recent evidence suggests that neuronal dynamics have a prominent role in AD pathophysiology, making it a potentially interesting therapeutic target. However, although neuronal activity can be manipulated by various (non-)pharmacological means, intervening in a highly integrated system that depends on complex dynamics can produce counterintuitive and adverse effects. Computational dynamic network modeling may serve as a virtual test ground for developing effective interventions. To explore this approach, a previously introduced large-scale neural mass network with human brain topology was used to simulate the temporal evolution of AD-like, activity-dependent network degeneration. In addition, six defense strategies that either enhanced or diminished neuronal excitability were tested against the degeneration process, targeting excitatory and inhibitory neurons combined or separately. Outcome measures described oscillatory, connectivity and topological features of the damaged networks. Over time, the various interventions produced diverse large-scale network effects. Contrary to our hypothesis, the most successful strategy was a selective stimulation of all excitatory neurons in the network; it substantially prolonged the preservation of network integrity. The results of this study imply that functional network damage due to pathological neuronal activity can be opposed by targeted adjustment of neuronal excitability levels. The present approach may help to explore therapeutic effects aimed at preserving or restoring neuronal network integrity and contribute to better-informed intervention choices in future clinical trials in AD. Alzheimer’s disease (AD) is a growing burden on society, without a cure in sight. Pathological high neuronal activity and excitability is an increasingly observed phenomenon in early stage AD. Its exact role in the disease process is unclear, but it may form an interesting therapeutic target. However, although brain dynamics can be influenced in many ways, the highly complex nature of the brain makes it difficult to predict what approach will be most effective. To test our hypothesis that neuronal hyperactivity can be countered effectively by altering neuronal excitability levels, we examined various strategies aimed at preserving brain network integrity in a computational AD model of the human brain. Of these strategies, a scenario involving stimulation of excitatory neurons extends the period with normal network function most successfully. The results of this ‘virtual trial’ suggest that network effects of pathological neuronal activity can be opposed by selective altering of neuronal excitability levels. In general, this approach can explore therapeutic effects aimed at preserving or restoring brain network integrity, and thereby contribute to selecting promising interventions for future clinical trials in AD.
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影响因子：
4.3
作者：
de Haan W;Mott K;van Straaten EC;Scheltens P;Stam CJ
通讯作者：
Stam CJ
影响因子：
3.4
作者：
de Haan, Willem;van der Flier, Wiesje M.;Stam, Cornelis J.
通讯作者：
Stam, Cornelis J.
DOI：
10.1093/brain/awu132
发表时间：
2014-08
期刊：
Brain : a journal of neurology
影响因子：
--
作者：
Crossley NA;Mechelli A;Scott J;Carletti F;Fox PT;McGuire P;Bullmore ET
通讯作者：
Bullmore ET
影响因子：
3.7
作者：
de Waal H;Stam CJ;Lansbergen MM;Wieggers RL;Kamphuis PJ;Scheltens P;Maestú F;van Straaten EC
通讯作者：
van Straaten EC
影响因子：
16.2
作者：
Bakker A;Krauss GL;Albert MS;Speck CL;Jones LR;Stark CE;Yassa MA;Bassett SS;Shelton AL;Gallagher M
通讯作者：
Gallagher M