Boxwell Alison, Terman David, Frank Marion, Yanagawa Yuchio, Travers Joseph B
College of Medicine, Ohio State University , Columbus, Ohio.
Department of Mathematics, Ohio State University , Columbus, Ohio.
J Neurophysiol. 2018 Mar 1;119(3):771-785. doi: 10.1152/jn.00624.2017. Epub 2017 Nov 1.
Neurons in the rostral nucleus of the solitary tract (rNST) convey taste information to both local circuits and pathways destined for forebrain structures. This nucleus is more than a simple relay, however, because rNST neurons differ in response rates and tuning curves relative to primary afferent fibers. To systematically study the impact of convergence and inhibition on firing frequency and breadth of tuning (BOT) in rNST, we constructed a mathematical model of its two major cell types: projection neurons and inhibitory neurons. First, we fit a conductance-based neuronal model to data derived from whole cell patch-clamp recordings of inhibitory and noninhibitory neurons in a mouse expressing Venus under the control of the VGAT promoter. We then used in vivo chorda tympani (CT) taste responses as afferent input to modeled neurons and assessed how the degree and type of convergence influenced model cell output frequency and BOT for comparison with in vivo gustatory responses from the rNST. Finally, we assessed how presynaptic and postsynaptic inhibition impacted model cell output. The results of our simulations demonstrated 1) increasing numbers of convergent afferents (2-10) result in a proportional increase in best-stimulus firing frequency but only a modest increase in BOT, 2) convergence of afferent input selected from the same best-stimulus class of CT afferents produced a better fit to real data from the rNST compared with convergence of randomly selected afferent input, and 3) inhibition narrowed the BOT to more realistically model the in vivo rNST data. NEW & NOTEWORTHY Using a combination of in vivo and in vitro neurophysiology together with conductance-based modeling, we show how patterns of convergence and inhibition interact in the rostral (gustatory) solitary nucleus to maintain signal fidelity. Although increasing convergence led to a systematic increase in firing frequency, tuning specificity was maintained with a pattern of afferent inputs sharing the best-stimulus compared with random inputs. Tonic inhibition further enhanced response fidelity.
孤束吻侧核（rNST）中的神经元将味觉信息传递至局部回路以及通向脑前叶结构的通路。然而，该核并非只是一个简单的中继站，因为rNST神经元相对于初级传入纤维，其反应速率和调谐曲线有所不同。为了系统地研究汇聚和抑制对rNST中放电频率和调谐宽度（BOT）的影响，我们构建了其两种主要细胞类型的数学模型：投射神经元和抑制性神经元。首先，我们将基于电导的神经元模型与在VGAT启动子控制下表达金星的小鼠中抑制性和非抑制性神经元的全细胞膜片钳记录数据进行拟合。然后，我们将体内鼓索神经（CT）味觉反应作为传入输入施加于模拟神经元，并评估汇聚的程度和类型如何影响模型细胞的输出频率和BOT，以便与rNST的体内味觉反应进行比较。最后，我们评估了突触前和突触后抑制如何影响模型细胞的输出。我们模拟结果表明：1）汇聚传入纤维数量增加（2 - 10条）会导致最佳刺激放电频率成比例增加，但BOT仅适度增加；2）与随机选择的传入输入汇聚相比，从同一最佳刺激类别的CT传入纤维中选择的传入输入汇聚能更好地拟合rNST的真实数据；3）抑制使BOT变窄，从而更逼真地模拟体内rNST数据。新发现与值得注意之处我们结合体内和体外神经生理学以及基于电导的建模方法，展示了汇聚和抑制模式如何在吻侧（味觉）孤束核中相互作用以维持信号保真度。尽管汇聚增加导致放电频率系统性增加，但与随机输入相比，如果传入输入模式共享最佳刺激，则调谐特异性得以维持。持续性抑制进一步提高了反应保真度。
