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首页> 外文期刊>The European Journal of Neuroscience >Spike train signatures of retinal ganglion cell types.
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Spike train signatures of retinal ganglion cell types.

机译：视网膜神经节细胞类型的峰值训练信号。

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摘要

The mammalian retina deconstructs the visual world using parallel neural channels, embodied in the morphological and physiological types of ganglion cells. We sought distinguishing features of each cell type in the temporal pattern of their spikes. As a first step, conventional physiological properties were used to cluster cells in eight types by a statistical analysis. We then adapted a method of P. Reinagel et al. (1999: J. Neurophysiol., 81, 2558-2569) to define epochs within the spike train of each cell. The spike trains of many cells were found to contain robust patterns that are defined by the (averaged) timing of successive interspike intervals in brief activity epochs. The patterns were robust across four different types of visual stimulus. Although the patterns are conserved in different visual environments, they do not prevent the cell from signaling the strength of its response to a particular stimulus, which is expressed in the number of spikes contained in each coding epoch. Clustering based on the spike train patterns alone showed that the spike train patterns correspond, in most but not all cases, to cell types pre-defined by traditional criteria. That the congruence is less than perfect suggests that the typing of rabbit ganglion cells may need further refinement. Analysis of the spike train patterns may be useful in this regard and for distinguishing the many unidentified ganglion cell types that exist in other mammalian retinas.
机译：哺乳动物的视网膜使用平行的神经通道来解构视觉世界，具体体现在神经节细胞的形态和生理类型上。我们在其尖峰的时间模式中寻求每种细胞类型的区别特征。第一步，通过统计分析，将常规生理特性用于将八种类型的细胞聚集在一起。然后，我们采用了P. Reinagel等人的方法。 （1999：J.Neurophysiol。，81，2558-2569）来定义每个细胞的尖峰序列内的时期。发现许多单元格的尖峰序列包含鲁棒的模式，这些模式由短暂活动时期中连续的尖峰间隔的（平均）时序定义。该模式在四种不同类型的视觉刺激中均很稳定。尽管这些模式在不同的视觉环境中是保守的，但是它们并不能阻止细胞发信号通知其对特定刺激的反应强度，这可以通过每个编码时期包含的尖峰数来表示。仅基于峰值序列模式的聚类表明，峰值序列模式在大多数情况下（并非全部）对应于由传统标准预先定义的单元格类型。一致性不够完美表明，兔子神经节细胞的类型可能需要进一步完善。在这方面，对穗序列模式的分析可能很有用，并且可以用于区分存在于其他哺乳动物视网膜中的许多未识别的神经节细胞类型。

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