Optical Imaging of Network Activities in Dentate Gyrus by Sparse-Dye Loading Method

从多个神经元监测神经元活动是理解神经元网络活动的必要条件。虽然细胞群的钙成像是研究神经结构网络动力学的有效方法，但由于细胞重叠，很难从密集排列的结构（如齿状回的颗粒细胞层）中成像。我们开发了一种新的方法，用俄勒冈绿488 BAPTA-1 AM标记大鼠海马切片中Ca^<2+>指标的多个颗粒细胞。利用放置于齿状回颗粒细胞层的玻璃电极，对施加50 μM -氨基吡啶诱导的同步爆发活动（0.3 ~ 1.4 Hz）进行监测。在爆发活动期间，用单细胞分辨率的冷却CCD相机监测了多个（4-12）颗粒细胞自发发生的动作电位诱导的Ca^<2+>瞬态。多神经元放电模式的时间结构由Ca^<2+>瞬态确定。在细胞外电极记录的每一个脉冲事件中，每个神经元在200毫秒的时间窗内同步放电。随着时间的推移（<7.5 min），从单个突发事件的开始时间到其中一个Ca^<2+>瞬态的潜伏期及其方差减小。这些结果表明，随着脉冲活动的进行，单个脉冲事件内动作电位的同步性增强。渐进式同步可能是实现自组织网络活动的关键特征。

Monitoring neuronal activities from multiple neurons is essential for understanding neuronal network activities. While calcium imaging from a population of cells is an effective method to study the network dynamics of a neural structure, it has been difficult to image from densely packed structures, such as the granule cell layer of the dentate gyrus, due to overlap of the cells. We have developed a novel method to label multiple granule cells with a Ca^<2+> indicator in rat hippocampal slices using Oregon Green 488 BAPTA-1 AM. Synchronized burst activities (0.3-1.4 Hz), which were induced by applying 50 μM 4-aminopyridine, were monitored extracellularly with a glass electrode placed at the granule cell layer in the dentate gyrus. During the burst activities, spontaneous occurring action potential-induced Ca^<2+> transients from multiple (4-12) granule cells were monitored with a cooled CCD camera with single-cell resolution. Temporal structures of firing patterns from the multiple neurons were determined from Ca^<2+> transients. In each single burst event recorded from the extracellular electrode, each neuron fired synchronously within a 200 ms time window. The latency and its variance from the onset time of the single burst events to one of the Ca^<2+> transients were decreased over time (<7.5 min). These results indicate that the synchrony of the action potentials within a single burst event was enhanced as the burst activities proceeded. The progressive synchronization may be a key feature to make self-organizing network activities.