Miller Neilan Rachael, Reith Carley, Anandan Iniya, Kraeuter Kayla, Allen Heather N, Kolber Benedict J
Department of Mathematics and Computer Science, Duquesne University, Pittsburgh, PA, United States.
Department of Neuroscience and Center for Advanced Pain Studies, University of Texas at Dallas, Richardson, TX, United States.
Front Pain Res (Lausanne). 2023 May 30;4:1183553. doi: 10.3389/fpain.2023.1183553. eCollection 2023.
Neuropathic and nociplastic pain are major causes of pain and involve brain areas such as the central nucleus of the amygdala (CeA). Within the CeA, neurons expressing protein kinase c-delta (PKCδ) or somatostatin (SST) have opposing roles in pain-like modulation. In this manuscript, we describe our progress towards developing a 3-D computational model of PKCδ and SST neurons in the CeA and the use of this model to explore the pharmacological targeting of these two neural populations in modulating nociception. Our 3-D model expands upon our existing 2-D computational framework by including a realistic 3-D spatial representation of the CeA and its subnuclei and a network of directed links that preserves morphological properties of PKCδ and SST neurons. The model consists of 13,000 neurons with cell-type specific properties and behaviors estimated from laboratory data. During each model time step, neuron firing rates are updated based on an external stimulus, inhibitory signals are transmitted between neurons via the network, and a measure of nociceptive output from the CeA is calculated as the difference in firing rates of pro-nociceptive PKCδ neurons and anti-nociceptive SST neurons. Model simulations were conducted to explore differences in output for three different spatial distributions of PKCδ and SST neurons. Our results show that the localization of these neuron populations within CeA subnuclei is a key parameter in identifying spatial and cell-type pharmacological targets for pain.
神经性疼痛和伤害感受性疼痛是疼痛的主要原因，涉及诸如杏仁核中央核（CeA）等脑区。在CeA内，表达蛋白激酶c-δ（PKCδ）或生长抑素（SST）的神经元在疼痛样调制中具有相反的作用。在本手稿中，我们描述了在开发CeA中PKCδ和SST神经元的三维计算模型方面取得的进展，以及使用该模型探索这两个神经群体在调节伤害感受中的药理学靶点。我们的三维模型在我们现有的二维计算框架基础上进行了扩展，包括CeA及其亚核的真实三维空间表示以及保留PKCδ和SST神经元形态特性的定向连接网络。该模型由13000个具有根据实验室数据估计的细胞类型特异性特性和行为的神经元组成。在每个模型时间步长中，根据外部刺激更新神经元的放电率，抑制性信号通过网络在神经元之间传递，并计算CeA的伤害感受输出量，作为促伤害感受性PKCδ神经元和抗伤害感受性SST神经元放电率的差值。进行模型模拟以探索PKCδ和SST神经元三种不同空间分布的输出差异。我们的结果表明，这些神经元群体在CeA亚核内的定位是识别疼痛的空间和细胞类型药理学靶点的关键参数。
