Computational modeling predicts regulation of central pattern generator oscillations by size and density of the underlying heterogenous network
Computational modeling predicts regulation of central pattern generator oscillations by size and density of the underlying heterogenous network
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DOI：
10.1007/s10827-022-00835-7
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发表时间：
2022-10-06
影响因子：
1.2
通讯作者：
Zupanc, Gunther K. H.
中科院分区：
文献类型：
--
作者：
Ilies, Iulian;Zupanc, Gunther K. H.
中枢模式发生器的细胞组成具有异质性，不同的细胞类型在节律信号的产生和传递中发挥着不同的作用。然而，人们对细胞相对分布及其连接模式的个体差异的功能含义知之甚少。本文以弱电鱼类leptorhynchus的起搏器核为研究对象，结合形态学数据分析和计算模型来解决这一问题。该神经网络由60-110个相互连接的起搏器细胞和15-30个中继细胞组成，将其输出传递给脊髓中的电运动神经元，该核以高达1khz的频率连续产生神经信号，具有很高的时间精度。我们系统地探索了网络大小和密度对振荡频率的影响，以及它们在细胞内和细胞间的变化。为了准确地确定效应大小，我们使用排除微分延迟的简化设置最小化了复杂动态的可能性。为了识别自然约束，参数范围超出了实验记录的细胞和连接数。模拟结果表明，起搏器细胞比中继细胞具有更高的频率和更低的种群内变异性。细胞内精度和细胞间频率同步随着起搏器细胞数量的增加和任何一种类型连接的增加而增加，随着中继细胞数量的增加而减少。网络级频率同步振荡发生在大约一半的模拟中，在生物学上观察到的参数范围内具有最大的可能性和射击精度。这些发现表明生物起搏器核的结构是为产生同步持续振荡而优化的。
Central pattern generators are characterized by a heterogeneous cellular composition, with different cell types playing distinct roles in the production and transmission of rhythmic signals. However, little is known about the functional implications of individual variation in the relative distributions of cells and their connectivity patterns. Here, we addressed this question through a combination of morphological data analysis and computational modeling, using the pacemaker nucleus of the weakly electric fish Apteronotus leptorhynchus as case study. A neural network comprised of 60-110 interconnected pacemaker cells and 15-30 relay cells conveying its output to electromotoneurons in the spinal cord, this nucleus continuously generates neural signals at frequencies of up to 1 kHz with high temporal precision. We systematically explored the impact of network size and density on oscillation frequencies and their variation within and across cells. To accurately determine effect sizes, we minimized the likelihood of complex dynamics using a simplified setup precluding differential delays. To identify natural constraints, parameter ranges were extended beyond experimentally recorded numbers of cells and connections. Simulations revealed that pacemaker cells have higher frequencies and lower within-population variability than relay cells. Within-cell precision and between-cells frequency synchronization increased with the number of pacemaker cells and of connections of either type, and decreased with relay cell count in both populations. Network-level frequency-synchronized oscillations occurred in roughly half of simulations, with maximized likelihood and firing precision within biologically observed parameter ranges. These findings suggest the structure of the biological pacemaker nucleus is optimized for generating synchronized sustained oscillations.