Clustering Predicted by an Electrophysiological Model of the Suprachiasmatic Nucleus
Clustering Predicted by an Electrophysiological Model of the Suprachiasmatic Nucleus
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DOI：
10.1177/0748730409337601
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发表时间：
2009-08-01
影响因子：
3.5
通讯作者：
Forger, Daniel B.
中科院分区：
文献类型：
--
作者：
Diekman, Casey O.;Forger, Daniel B.
尽管在视交叉上核（SCN）的单个神经元的电生理学的实验数据丰富，SCN的神经代码仍然在很大程度上是未知的。为了预测SCN的电活动，作者使用SCN神经元内离子电流的详细模型模拟了10，000个GABA能SCN神经元的网络。他们的目标是了解神经元放电（发生在比一秒更快的时间尺度上）如何编码昼夜（24小时）周期的设定阶段。作者研究了关键网络特性的影响，包括：1）SCN内的突触密度，2）突触后电流的大小，3）神经元群体中昼夜节律相位的异质性，4）突触噪声的程度，以及5）兴奋和抑制之间的平衡。他们的主要结果是，在各种各样的条件下，SCN网络自发地组织成（通常为3）组同步放电的神经元。他们表明，这种类型的聚类可能导致神经元的沉默，这些神经元的细胞内时钟与其他群体的生物钟不一致。他们的研究结果提供了线索，SCN如何在组织水平上产生相干的电输出信号，以控制整个身体的节奏。
Despite the wealth of experimental data on the electrophysiology of individual neurons in the suprachiasmatic nuclei (SCN), the neural code of the SCN remains largely unknown. To predict the electrical activity of the SCN, the authors simulated networks of 10,000 GABAergic SCN neurons using a detailed model of the ionic currents within SCN neurons. Their goal was to understand how neuronal firing, which occurs on a time scale faster than a second, can encode a set phase of the circadian (24-h) cycle. The authors studied the effects of key network properties including: 1) the synaptic density within the SCN, 2) the magnitude of postsynaptic currents, 3) the heterogeneity of circadian phase in the neuronal population, 4) the degree of synaptic noise, and 5) the balance between excitation and inhibition. Their main result was that under a wide variety of conditions, the SCN network spontaneously organized into (typically 3) groups of synchronously firing neurons. They showed that this type of clustering can lead to the silencing of neurons whose intracellular clocks are out of circadian phase with the rest of the population. Their results provide clues to how the SCN may generate a coherent electrical output signal at the tissue level to time rhythms throughout the body.