Neurosciences & Mental Health, The Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada.
Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario M5S 3G9, Canada.
J Neurosci. 2022 Apr 13;42(15):3133-3149. doi: 10.1523/JNEUROSCI.1199-21.2022. Epub 2022 Mar 1.
Pain-related sensory input is processed in the spinal dorsal horn (SDH) before being relayed to the brain. That processing profoundly influences whether stimuli are correctly or incorrectly perceived as painful. Significant advances have been made in identifying the types of excitatory and inhibitory neurons that comprise the SDH, and there is some information about how neuron types are connected, but it remains unclear how the overall circuit processes sensory input or how that processing is disrupted under chronic pain conditions. To explore SDH function, we developed a computational model of the circuit that is tightly constrained by experimental data. Our model comprises conductance-based neuron models that reproduce the characteristic firing patterns of spinal neurons. Excitatory and inhibitory neuron populations, defined by their expression of genetic markers, spiking pattern, or morphology, were synaptically connected according to available qualitative data. Using a genetic algorithm, synaptic weights were tuned to reproduce projection neuron firing rates (model output) based on primary afferent firing rates (model input) across a range of mechanical stimulus intensities. Disparate synaptic weight combinations could produce equivalent circuit function, revealing degeneracy that may underlie heterogeneous responses of different circuits to perturbations or pathologic insults. To validate our model, we verified that it responded to the reduction of inhibition (i.e., disinhibition) and ablation of specific neuron types in a manner consistent with experiments. Thus validated, our model offers a valuable resource for interpreting experimental results and testing hypotheses to plan experiments for examining normal and pathologic SDH circuit function. We developed a multiscale computer model of the posterior part of spinal cord gray matter (spinal dorsal horn), which is involved in perceiving touch and pain. The model reproduces several experimental observations and makes predictions about how specific types of spinal neurons and synapses influence projection neurons that send information to the brain. Misfiring of these projection neurons can produce anomalous sensations associated with chronic pain. Our computer model will not only assist in planning future experiments, but will also be useful for developing new pharmacotherapy for chronic pain disorders, connecting the effect of drugs acting at the molecular scale with emergent properties of neurons and circuits that shape the pain experience.
疼痛相关的感觉输入在脊髓背角 (SDH) 中进行处理，然后再传递到大脑。这种处理过程极大地影响了刺激是否被正确或错误地感知为疼痛。在确定构成 SDH 的兴奋性和抑制性神经元类型方面已经取得了重大进展，并且有一些关于神经元类型如何连接的信息，但仍不清楚整个电路如何处理感觉输入，或者在慢性疼痛条件下该处理过程如何受到干扰。为了探索 SDH 的功能，我们开发了一个紧密受实验数据约束的电路计算模型。我们的模型由基于电导率的神经元模型组成，这些模型再现了脊髓神经元的特征放电模式。兴奋性和抑制性神经元群体根据其遗传标记、放电模式或形态学定义，根据可用的定性数据进行突触连接。使用遗传算法，根据初级传入放电率（模型输入）在一系列机械刺激强度下调整突触权重，以再现投射神经元的放电率（模型输出）。不同的突触权重组合可以产生等效的电路功能，揭示了可能是不同电路对扰动或病理损伤产生异质反应的基础的简并性。为了验证我们的模型，我们验证了它以与实验一致的方式响应抑制的减少（即去抑制）和特定神经元类型的消融。经过验证，我们的模型为解释实验结果和测试假设提供了有价值的资源，以计划检查正常和病理 SDH 电路功能的实验。我们开发了一个脊髓灰质后部（脊髓背角）的多尺度计算机模型，该模型参与了触觉和疼痛的感知。该模型再现了几个实验观察结果，并对特定类型的脊髓神经元和突触如何影响向大脑发送信息的投射神经元产生影响做出了预测。这些投射神经元的错误放电会产生与慢性疼痛相关的异常感觉。我们的计算机模型不仅有助于计划未来的实验，而且对于开发治疗慢性疼痛障碍的新药物治疗也非常有用，它将药物在分子尺度上的作用与塑造疼痛体验的神经元和电路的涌现特性联系起来。
