Temporal Patterns of Spinal Cord Stimulation

脊髓刺激(SCS)是一种治疗顽固性慢性疼痛的植入式医疗器械。然而，更少的 超过三分之二的患者通常经历至少50%的疼痛减轻，尽管有几十年的研究 随着时间的推移，患者取得临床成功的比例并没有增加。我们是 追求一个新的刺激参数维度--刺激的时间模式--以及这样做的目的 项目是设计和测试优化的刺激时间模式，以提高SCS的治疗效果 慢性神经病理性疼痛。我们将使用一个经过验证的基于生物物理学的模型来研究SCS对感觉的影响。 脊髓背角的信号处理，以设计SCS的优化时间模式。这个 优化的时间模式旨在探索大鼠脑背角抑制机制的动力学。 脊髓。SCS对痛觉传递的脊髓神经元和颞叶产生兴奋和抑制。 将优化模式，以减弱SCS介导的兴奋，同时放大SCS介导的抑制。我们会 使用灵敏度分析来确定刺激模式对电极电位变化的稳健性 背角神经网络的定位、刺激选择性和生物物理特性，尤其是 慢性疼痛中存在抑制机制受损的情况。随后，我们将衡量 SCS对大鼠备用神经损伤(SNI)模型疼痛相关行为结局的影响 慢性神经病理性疼痛。我们预计，SCS的新时间模式将产生更大的抑制 痛觉过敏和痛觉过敏，以及自发性疼痛，都比频率匹配的对照模式要好。我们的内部 硅胶和活体电生理数据表明，SCS的时间模式产生了超过 投射神经元放电率的抑制比传统的SCS高50%，这表明结果是 疼痛结果的改善将超过有意义变化的30%门槛。我们还将量化 优化的SCS时程模式对SNI大鼠脊髓投射神经元活动的影响 慢性疼痛模型。我们预计，优化的SCS时间模式将产生更大的减少 与频率匹配的脊髓宽动态范围和伤害性特异性神经元的放电频率和缠绕 控制模式。SCS的时间模式是一个新的和重要的参数，我们将利用它来扩展 SCS的设计空间从刺激的空间分布到时间模式 刺激。其结果将是对使用优化的SCS时间模式来 治疗神经性疼痛，并将为慢性疼痛患者的转化性研究提供基础。 重要的是，这种方法有一条清晰而相对较短的临床翻译之路，因为现有的植入 脉冲发生器可以被重新编程，以提供SCS的优化时间模式。

Spinal cord stimulation (SCS) is an implanted medical device therapy for refractory chronic pain. However, fewer than 2/3 of patients typically experience at least a 50% reduction in pain, and despite several decades of research and development, the proportion of patients achieving clinical success has not increased over time. We are pursuing a new stimulation parameter dimension – the temporal pattern of stimulation – and the purpose of this project is to design and test optimized temporal patterns of stimulation to improve the efficacy of SCS to treat chronic neuropathic pain. We will use a validated biophysically-based model of the effects of SCS on sensory signal processing in the dorsal horn of the spinal cord to design optimized temporal patterns of SCS. The optimized temporal patterns are intended to exploit the dynamics of inhibitory mechanisms in the dorsal horn of the spinal cord. SCS produces both excitation and inhibition of pain transmitting spinal neurons, and the temporal patterns will be optimized to weaken SCS-mediated excitation while amplifying SCS-mediated inhibition. We will use sensitivity analyses to determine the robustness of stimulation patterns to potential variations in electrode positioning, selectivity of stimulation, and the biophysical properties of the dorsal horn neural network, especially the compromised inhibitory mechanisms present in chronic pain. Subsequently, we will measure the effects of the temporal pattern of SCS on pain-related behavioral outcomes in the spared nerve injury (SNI) rat model of chronic neuropathic pain. We expect that novel temporal patterns of SCS will produce greater suppression of allodynia and hyperalgesia, as well as spontaneous pain, than will frequency-matched control patterns. Our in silico and in vivo electrophysiological data demonstrate that temporal patterns of SCS produced a more than 50% greater suppression of projection neuron firing rates than conventional SCS, and this suggests that resulting improvements in in pain outcomes will exceed the 30% threshold for meaningful change. We will also quantify the effects of optimized temporal pattern of SCS on the activity of spinal cord projection neurons in the SNI rat model of chronic pain. We expect that optimized temporal patterns of SCS will produce greater reductions in firing rates and wind up of spinal wide dynamic range and nociceptive specific neurons than frequency matched control patterns. The temporal pattern of SCS is a novel and important parameter that we will exploit to expand the design space for SCS from the spatial distribution–where–of stimulation to the temporal pattern–when–of stimulation. The outcome will be an assessment of the feasibility of using optimized temporal patterns of SCS to treat neuropathic pain, and will provide the foundation for translational studies in patients with chronic pain. Importantly, this approach has a clear and comparatively short road to clinical translation, as existing implanted pulse generators could be re-programmed to deliver optimized temporal patterns of SCS.