Developing a 3-D computational model of neurons in the central amygdala to understand pharmacological targets for pain.
Developing a 3-D computational model of neurons in the central amygdala to understand pharmacological targets for pain.
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DOI：
10.3389/fpain.2023.1183553
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发表时间：
2023
影响因子：
--
通讯作者：
Kolber, Benedict J.
中科院分区：
文献类型：
--
作者：
Miller Neilan, Rachael;Reith, Carley;Anandan, Iniya;Kraeuter, Kayla;Allen, Heather N.;Kolber, Benedict J.
关键词：
神经性和肿瘤性疼痛是疼痛的主要原因，涉及杏仁中央核(CEA)等大脑区域。在CEA内，表达蛋白激酶C-增量(PKCδ)或生长抑素(Sst)的神经元在痛样调制中具有相反的作用。在这篇手稿中，我们描述了我们在建立CEA内PKC、δ和Sst神经元的三维计算模型方面的进展，并利用该模型来探索这两个神经群体在调节伤害性感觉方面的药理学靶点。我们的3D模型扩展了我们现有的2D计算框架，包括CEA及其亚核的真实3D空间表示，以及保留PKC、δ和SST神经元的形态特征的定向链接网络。该模型由13,000个神经元组成，这些神经元具有根据实验室数据估计的细胞类型特定属性和行为。在每个模型时间步中，神经元的放电频率根据外部刺激进行更新，抑制信号通过网络在神经元之间传递，并且通过计算前伤害感受性PKCδ神经元和反伤害感受性SST神经元的放电速率之差来计算来自CEA的伤害性输出的度量。模型模拟被用来探索三种不同空间分布的PKC、δ和SST神经元的输出差异。我们的结果表明，这些神经元群体在CEA亚核中的定位是确定空间和细胞类型疼痛药理靶点的关键参数。
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.
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影响因子：
4.3
作者：
Miller Neilan R;Majetic G;Gil-Silva M;Adke AP;Carrasquillo Y;Kolber BJ
通讯作者：
Kolber BJ
影响因子：
5.8
作者：
O'Leary, Timothy P.;Kendrick, Rennie M.;Bristow, Brianna N.;Sullivan, Kaitlin E.;Wang, Lihua;Clements, Jody;Lemire, Andrew L.;Cembrowski, Mark S.
通讯作者：
Cembrowski, Mark S.
影响因子：
3.3
作者：
Miyazawa Y;Takahashi Y;Watabe AM;Kato F
通讯作者：
Kato F
影响因子：
16.6
作者：
Bowen AJ;Huang YW;Chen JY;Pauli JL;Campos CA;Palmiter RD
通讯作者：
Palmiter RD
影响因子：
3.4
作者：
Barbier, Marie;Fellmann, Dominique;Risold, Pierre-Yves
通讯作者：
Risold, Pierre-Yves