Department of Computer Science, State University of Rio Grande do Norte, Natal, Brazil.
Graduate Program in Bioinformatics, Federal University of Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil.
PLoS Comput Biol. 2024 Jul 31;20(7):e1011820. doi: 10.1371/journal.pcbi.1011820. eCollection 2024 Jul.
The pulsatile activity of gonadotropin-releasing hormone neurons (GnRH neurons) is a key factor in the regulation of reproductive hormones. This pulsatility is orchestrated by a network of neurons that release the neurotransmitters kisspeptin, neurokinin B, and dynorphin (KNDy neurons), and produce episodic bursts of activity driving the GnRH neurons. We show in this computational study that the features of coordinated KNDy neuron activity can be explained by a neural network in which connectivity among neurons is modular. That is, a network structure consisting of clusters of highly-connected neurons with sparse coupling among the clusters. This modular structure, with distinct parameters for intracluster and intercluster coupling, also yields predictions for the differential effects on synchronization of changes in the coupling strength within clusters versus between clusters.
促性腺激素释放激素神经元（GnRH 神经元）的脉冲活动是调节生殖激素的关键因素。这种脉冲活动是由一个神经元网络协调的，该网络释放神经递质 kisspeptin、神经激肽 B 和强啡肽（KNDy 神经元），并产生驱动 GnRH 神经元的阵发性活动爆发。在这项计算研究中，我们表明，协调的 KNDy 神经元活动的特征可以用一个神经元网络来解释，该网络中神经元之间的连接具有模块性。也就是说，网络结构由具有稀疏簇间耦合的高度连接神经元簇组成。这种模块化结构，以及簇内和簇间耦合强度变化对同步的影响的不同预测，也为簇内和簇间耦合强度变化对同步的影响的不同预测提供了依据。
