Crodelle Jennifer, Maia Pedro D
Department of Mathematics, Middlebury College, Middlebury, VT 05753, USA.
Department of Mathematics, University of Texas at Arlington, Arlington, TX 76019, USA.
Brain Sci. 2021 Apr 16;11(4):505. doi: 10.3390/brainsci11040505.
Computational modeling of the neural activity in the human spinal cord may help elucidate the underlying mechanisms involved in the complex processing of painful stimuli. In this study, we use a biologically-plausible model of the dorsal horn circuitry as a platform to simulate pain processing under healthy and pathological conditions. Specifically, we distort signals in the receptor fibers akin to what is observed in axonal damage and monitor the corresponding changes in five quantitative markers associated with the pain response. Axonal damage may lead to spike-train delays, evoked potentials, an increase in the refractoriness of the system, and intermittent blockage of spikes. We demonstrate how such effects applied to mechanoreceptor and nociceptor fibers in the pain processing circuit can give rise to dramatically distinct responses at the network/population level. The computational modeling of damaged neuronal assemblies may help unravel the myriad of responses observed in painful neuropathies and improve diagnostics and treatment protocols.
对人类脊髓神经活动进行计算建模，可能有助于阐明参与疼痛刺激复杂处理过程的潜在机制。在本研究中，我们使用背角神经回路的生物合理模型作为平台，来模拟健康和病理条件下的疼痛处理过程。具体而言，我们类似于在轴突损伤中观察到的情况来扭曲受体纤维中的信号，并监测与疼痛反应相关的五个定量指标的相应变化。轴突损伤可能导致脉冲序列延迟、诱发电位、系统不应期增加以及脉冲间歇性阻断。我们展示了在疼痛处理回路中，应用于机械感受器和伤害感受器纤维的此类效应如何在网络/群体水平上产生截然不同的反应。受损神经元组件的计算建模可能有助于揭示在疼痛性神经病变中观察到的无数反应，并改进诊断和治疗方案。
