Department of Neuroscience Brain Technology, Istituto Italiano di Tecnologia Genova, Italy.
Neurophysiology Unit, Department of Brain and Behavioral Sciences, University of Pavia Pavia, Italy ; Neurophysiology, Brain Connectivity Center, C. Mondino National Neurological Institute, IRCCS Pavia, Italy.
Front Cell Neurosci. 2014 Aug 25;8:246. doi: 10.3389/fncel.2014.00246. eCollection 2014.
The complex interplay of multiple molecular mechanisms taking part to synaptic integration is hard to disentangle experimentally. Therefore, we developed a biologically realistic computational model based on the rich set of data characterizing the cerebellar glomerulus microcircuit. A specific issue was to determine the relative role of phasic and tonic inhibition in dynamically regulating granule cell firing, which has not been clarified yet. The model comprised the excitatory mossy fiber-granule cell and the inhibitory Golgi cell-granule cell synapses and accounted for vesicular release processes, neurotransmitter diffusion and activation of different receptor subtypes. Phasic inhibition was based on stochastic GABA release and spillover causing activation of two major classes of postsynaptic receptors, α1 and α6, while tonic inhibition was based on steady regulation of a Cl(-) leakage. The glomerular microcircuit model was validated against experimental responses to mossy fiber bursts while metabotropic receptors were blocked. Simulations showed that phasic inhibition controlled the number of spikes during burst transmission but predicted that it specifically controlled time-related parameters (firing initiation and conclusion and first spike precision) when the relative phase of excitation and inhibition was changed. In all conditions, the overall impact of α6 was larger than that of α1 subunit-containing receptors. However, α1 receptors controlled granule cell responses in a narrow ±10 ms band while α6 receptors showed broader ±50 ms tuning. Tonic inhibition biased these effects without changing their nature substantially. These simulations imply that phasic inhibitory mechanisms can dynamically regulate output spike patterns, as well as calcium influx and NMDA currents, at the mossy fiber-granule cell relay of cerebellum without the intervention of tonic inhibition.
参与突触整合的多种分子机制的复杂相互作用很难通过实验来解析。因此,我们基于丰富的小脑小球微电路数据,开发了一个具有生物学现实性的计算模型。一个具体的问题是确定相位和紧张性抑制在动态调节颗粒细胞放电中的相对作用,这一点尚未得到澄清。该模型包括兴奋性苔藓纤维-颗粒细胞和抑制性高尔基细胞-颗粒细胞突触,并考虑了囊泡释放过程、神经递质扩散和不同受体亚型的激活。相位抑制基于随机 GABA 释放和溢出,导致两种主要类型的突触后受体(α1 和 α6)的激活,而紧张性抑制基于 Cl(-)渗漏的稳定调节。在代谢型受体被阻断的情况下,小球微电路模型通过对苔藓纤维爆发的实验反应进行验证。模拟结果表明,相位抑制控制了爆发传递过程中的尖峰数量,但预测当兴奋和抑制的相对相位发生变化时,它特别控制了与时间相关的参数(起始和结束的放电以及第一尖峰的精度)。在所有条件下,α6 的整体影响大于包含α1 亚基的受体。然而,α1 受体在 ±10 ms 的窄带内控制颗粒细胞的反应,而 α6 受体则显示出 ±50 ms 的较宽调谐。紧张性抑制在不改变其本质的情况下影响这些效果。这些模拟表明,相位抑制机制可以在小脑苔藓纤维-颗粒细胞中继无紧张性抑制的情况下,动态调节输出尖峰模式以及钙内流和 NMDA 电流。