Department of Biology, Emory University, Atlanta, Georgia 30322, USA.
J Neurosci. 2010 Feb 3;30(5):1686-98. doi: 10.1523/JNEUROSCI.3098-09.2010.
In activity-dependent homeostatic regulation (ADHR) of neuronal and network properties, the intracellular Ca(2+) concentration is a good candidate for sensing activity levels because it is correlated with the electrical activity of the cell. Previous ADHR models, developed with abstract activity sensors for model pyloric neurons and networks of the crustacean stomatogastric ganglion, showed that functional activity can be maintained by a regulation mechanism that senses activity levels solely from Ca(2+). At the same time, several intracellular pathways have been discovered for Ca(2+)-dependent regulation of ion channels. To generate testable predictions for dynamics of these signaling pathways, we undertook a parameter study of model Ca(2+) sensors across thousands of model pyloric networks. We found that an optimal regulation signal can be generated for 86% of model networks with a sensing mechanism that activates with a time constant of 1 ms and that inactivates within 1 s. The sensor performed robustly around this optimal point and did not need to be specific to the role of the cell. When multiple sensors with different time constants were used, coverage extended to 88% of the networks. Without changing the sensors, it extended to 95% of the networks by letting the sensors affect the readout nonlinearly. Specific to this pyloric network model, the sensor of the follower pyloric constrictor cell was more informative than the pacemaker anterior burster cell for producing a regulatory signal. Conversely, a global signal indicating network activity that was generated by summing the sensors in individual cells was less informative for regulation.
在神经元和网络性质的活动依赖性稳态调节(ADHR)中,细胞内 Ca(2+)浓度是感应活动水平的良好候选物,因为它与细胞的电活动相关。先前的 ADHR 模型,使用抽象的活动传感器为甲壳类动物 stomatogastric 神经节的模型幽门神经元和网络开发,表明功能活动可以通过仅从 Ca(2+)感应活动水平的调节机制来维持。同时,已经发现了几种用于 Ca(2+)依赖的离子通道调节的细胞内途径。为了为这些信号通路的动力学生成可测试的预测,我们对跨数千个模型幽门网络的模型 Ca(2+)传感器进行了参数研究。我们发现,对于 86%的模型网络,可以生成一个最佳的调节信号,使用的感应机制具有 1 ms 的时间常数并且在 1 秒内失活。传感器在这个最佳点周围表现稳健,并且不需要针对细胞的作用特异性。当使用具有不同时间常数的多个传感器时,覆盖率扩展到 88%的网络。通过不让传感器对读出产生非线性影响,而不改变传感器,它将覆盖率扩展到 95%的网络。对于这个幽门网络模型来说,跟随性幽门收缩细胞的传感器比起搏性前脉冲细胞更能产生调节信号。相反,通过在单个细胞中对传感器进行求和来生成指示网络活动的全局信号,对于调节来说信息较少。