基于细胞外电生理特性的大鼠腹侧被盖区神经元群体的层次聚类。
Hierarchical Clustering of Neuronal Populations in the Rat Ventral Tegmental Area Based on Extracellular Electrophysiological Properties.
机构信息
Pharmacology and Neuroscience Research Group, Leicester School of Pharmacy, De Montfort University, Leicester, United Kingdom.
Laboratoire NutriNeuro, UMR INRAE 1286, Université de Bordeaux, Bordeaux, France.
出版信息
Front Neural Circuits. 2020 Aug 13;14:51. doi: 10.3389/fncir.2020.00051. eCollection 2020.
The ventral tegmental area (VTA) is a heterogeneous brain region, containing different neuronal populations. During recordings, electrophysiological characteristics are classically used to distinguish the different populations. However, the VTA is also considered as a region harboring neurons with heterogeneous properties. In the present study, we aimed to classify VTA neurons using approaches, in an attempt to determine if homogeneous populations could be extracted. Thus, we recorded 291 VTA neurons during extracellular recordings in anesthetized rats. Initially, 22 neurons with high firing rates (>10 Hz) and short-lasting action potentials (AP) were considered as a separate subpopulation, in light of previous studies. To segregate the remaining 269 neurons, presumably dopaminergic (DA), we performed analyses, using a combination of different electrophysiological parameters. These parameters included: (1) firing rate; (2) firing rate coefficient of variation (CV); (3) percentage of spikes in a burst; (4) AP duration; (5) Δt duration (i.e., time from initiation of depolarization until end of repolarization); and (6) presence of a notched AP waveform. Unsupervised hierarchical clustering revealed two neuronal populations that differed in their bursting activities. The largest population presented low bursting activities (<17.5% of total spikes in burst), while the remaining neurons presented higher bursting activities (>17.5%). Within non-high-firing neurons, a large heterogeneity was noted concerning AP characteristics. In conclusion, this analysis based on conventional electrophysiological criteria clustered two subpopulations of putative DA VTA neurons that are distinguishable by their firing patterns (firing rates and bursting activities) but not their AP properties.
腹侧被盖区(VTA)是一个异质的脑区,包含不同的神经元群体。在记录过程中,电生理特征通常被用来区分不同的群体。然而,VTA 也被认为是一个包含具有不同特性的神经元的区域。在本研究中,我们旨在使用机器学习方法对 VTA 神经元进行分类,试图确定是否可以提取出同质的群体。因此,我们在麻醉大鼠的体外记录中记录了 291 个 VTA 神经元。最初,根据先前的研究,我们认为 22 个具有高放电率(>10 Hz)和短持续时间动作电位(AP)的神经元是一个单独的亚群。为了分离其余 269 个假定为多巴胺能(DA)的神经元,我们使用不同电生理参数的组合进行了无监督层次聚类分析。这些参数包括:(1)放电率;(2)放电率变异系数(CV);(3)爆发中尖峰的百分比;(4)AP 持续时间;(5)Δt 持续时间(即,从去极化开始到复极化结束的时间);和(6)存在 Notch AP 波形。无监督层次聚类揭示了两个神经元群体,它们在爆发活动方面存在差异。最大的群体表现出低爆发活动(爆发中总尖峰的<17.5%),而其余神经元表现出更高的爆发活动(>17.5%)。在非高放电神经元中,AP 特征存在很大的异质性。总之,基于传统电生理标准的分析将两个假定的 VTA DA 神经元亚群聚类在一起,这些亚群可以通过其放电模式(放电率和爆发活动)而不是其 AP 特性来区分。