Modeling the spinal pudendo-vesical reflex for bladder control by pudendal afferent stimulation
Modeling the spinal pudendo-vesical reflex for bladder control by pudendal afferent stimulation
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DOI：
10.1007/s10827-016-0597-5
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发表时间：
2016-06-01
影响因子：
1.2
通讯作者：
Grill, Warren M.
中科院分区：
文献类型：
--
作者：
McGee, Meredith J.;Grill, Warren M.
电刺激阴部神经(PN)是恢复因神经系统疾病或损伤引起的膀胱功能障碍后排尿和排尿的一种有前途的方法。虽然-膀胱反射及其生理特性已被很好地建立，但对调节这种反射的特定神经机制的了解有限。我们试图开发一种脊髓神经网络的计算模型，该模型管理对PN刺激的反射膀胱反应。基于先前的神经解剖学和电生理学研究，我们实施并验证了一个神经网络结构。使用突触连接的整合和放电模型神经元，我们创建了一个具有真实尖峰行为的网络模型。该模型从指定的神经输入产生预期的骶骨副交感神经核(SPN)神经元的放电率，并预测不同频率的阴部传入刺激对膀胱的激活和抑制。此外，该模型与之前对阴部传入刺激的时间模式和选择性药物阻断抑制性神经元的实验结果相吻合。阴部传入刺激的频率依赖效应和模式依赖效应由脊髓中间神经元放电频率的变化决定，这表明腰骶水平的神经网络相互作用可以介导膀胱对不同频率或时间模式的阴部传入刺激的反应。此外，网络模型中兴奋性和抑制性中间神经元的解剖结构是重现-膀胱反射的关键特征的必要条件和充分条件，该模型可能有助于指导新的、更有效的膀胱控制电刺激技术的发展。
Electrical stimulation of the pudendal nerve (PN) is a promising approach to restore continence and micturition following bladder dysfunction resulting from neurological disease or injury. Although the pudendo-vesical reflex and its physiological properties are well established, there is limited understanding of the specific neural mechanisms that mediate this reflex. We sought to develop a computational model of the spinal neural network that governs the reflex bladder response to PN stimulation. We implemented and validated a neural network architecture based on previous neuroanatomical and electrophysiological studies. Using synaptically-connected integrate and fire model neurons, we created a network model with realistic spiking behavior. The model produced expected sacral parasympathetic nucleus (SPN) neuron firing rates from prescribed neural inputs and predicted bladder activation and inhibition with different frequencies of pudendal afferent stimulation. In addition, the model matched experimental results from previous studies of temporal patterns of pudendal afferent stimulation and selective pharmacological blockade of inhibitory neurons. The frequency- and pattern-dependent effects of pudendal afferent stimulation were determined by changes in firing rate of spinal interneurons, suggesting that neural network interactions at the lumbosacral level can mediate the bladder response to different frequencies or temporal patterns of pudendal afferent stimulation. Further, the anatomical structure of excitatory and inhibitory interneurons in the network model was necessary and sufficient to reproduce the critical features of the pudendo-vesical reflex, and this model may prove useful to guide development of novel, more effective electrical stimulation techniques for bladder control.