Data from: Spike-triggered covariance analysis reveals phenomenological diversity of contrast adaptation in the retina

When visual contrast changes, retinal ganglion cells adapt by adjusting their sensitivity as well as their temporal filtering characteristics. The latter has classically been described by contrast-induced gain changes that depend on temporal frequency. Here, we explored a new perspective on contrast-induced changes in temporal filtering by using spike-triggered covariance analysis to extract multiple parallel temporal filters for individual ganglion cells. Based on multielectrode-array recordings from ganglion cells in the isolated salamander retina, we found that contrast adaptation of temporal filtering can largely be captured by contrast-invariant sets of filters with contrast-dependent weights. Moreover, differences among the ganglion cells in the filter sets and their contrast-dependent contributions allowed us to phenomenologically distinguish three types of filter changes. The first type is characterized by newly emerging features at higher contrast, which can be reproduced by computational models that contain response-triggered gain-control mechanisms. The second type follows from stronger adaptation in the Off pathway as compared to the On pathway in On-Off-type ganglion cells. Finally, we found that, in a subset of neurons, contrast-induced filter changes are governed by particularly strong spike-timing dynamics, in particular by pronounced stimulus-dependent latency shifts that can be observed in these cells. Together, our results show that the contrast dependence of temporal filtering in retinal ganglion cells has a multifaceted phenomenology and that a multi-filter analysis can provide a useful basis for capturing the underlying signal-processing dynamics.

当视觉对比度发生变化时，视网膜神经节细胞（retinal ganglion cells）会通过调整自身敏感度与时间滤波特性来实现适应。经典理论中，这类时间滤波特性的变化通常被描述为依赖于时间频率的对比度诱导增益变化。
本研究通过峰电位触发协方差分析（spike-triggered covariance analysis）为单个视网膜神经节细胞提取多组并行时间滤波器，以此从全新视角探讨对比度诱导的时间滤波变化。
基于离体蝾螈视网膜中视网膜神经节细胞的多电极阵列（multielectrode-array）记录，我们发现：时间滤波的对比度适应在很大程度上可通过一组对比度不变的滤波器及其对比度依赖的权重来表征。此外，不同视网膜神经节细胞的滤波器组及其对比度依赖的贡献度存在差异，这使得我们能够从现象学层面区分三类滤波器变化。
第一类以高对比度下出现新特征为典型特征，此类变化可通过包含响应触发增益控制（gain-control）机制的计算模型复现。第二类则源于On-Off型视网膜神经节细胞中，撤光通路（Off pathway）相较给光通路（On pathway）存在更强的适应效应。最后，我们在部分神经元中发现：对比度诱导的滤波器变化由极强的峰电位时序动态（spike-timing dynamics）所主导，具体表现为这些细胞中可观测到显著的刺激依赖潜伏期偏移（latency shifts）。
综上，本研究结果表明：视网膜神经节细胞时间滤波的对比度依赖性具有多维度的现象学特征，而多滤波器分析可为解析其背后的信号处理动态提供有效基础。