Department of Ophthalmology, University Medical Center Göttingen, Göttingen, 37073, Germany.
Bernstein Center for Computational Neuroscience Göttingen, Göttingen, 37073, Germany.
J Neurosci. 2021 Apr 14;41(15):3479-3498. doi: 10.1523/JNEUROSCI.3075-20.2021. Epub 2021 Mar 4.
How neurons encode natural stimuli is a fundamental question for sensory neuroscience. In the early visual system, standard encoding models assume that neurons linearly filter incoming stimuli through their receptive fields, but artificial stimuli, such as contrast-reversing gratings, often reveal nonlinear spatial processing. We investigated to what extent such nonlinear processing is relevant for the encoding of natural images in retinal ganglion cells in mice of either sex. We found that standard linear receptive field models yielded good predictions of responses to flashed natural images for a subset of cells but failed to capture the spiking activity for many others. Cells with poor model performance displayed pronounced sensitivity to fine spatial contrast and local signal rectification as the dominant nonlinearity. By contrast, sensitivity to high-frequency contrast-reversing gratings, a classical test for nonlinear spatial integration, was not a good predictor of model performance and thus did not capture the variability of nonlinear spatial integration under natural images. In addition, we also observed a class of nonlinear ganglion cells with inverse tuning for spatial contrast, responding more strongly to spatially homogeneous than to spatially structured stimuli. These findings highlight the diversity of receptive field nonlinearities as a crucial component for understanding early sensory encoding in the context of natural stimuli. Experiments with artificial visual stimuli have revealed that many types of retinal ganglion cells pool spatial input signals nonlinearly. However, it is still unclear how relevant this nonlinear spatial integration is when the input signals are natural images. Here we analyze retinal responses to natural scenes in large populations of mouse ganglion cells. We show that nonlinear spatial integration strongly influences responses to natural images for some ganglion cells, but not for others. Cells with nonlinear spatial integration were sensitive to spatial structure inside their receptive fields, and a small group of cells displayed a surprising sensitivity to spatially homogeneous stimuli. Traditional analyses with contrast-reversing gratings did not predict this variability of nonlinear spatial integration under natural images.
神经元如何对自然刺激进行编码是感觉神经科学的一个基本问题。在早期视觉系统中，标准的编码模型假设神经元通过其感受野对输入刺激进行线性滤波，但人工刺激，如对比度反转光栅，往往揭示了非线性的空间处理。我们研究了这种非线性处理在多大程度上与雌雄小鼠的视网膜神经节细胞对自然图像的编码有关。我们发现，标准的线性感受野模型对一部分细胞的闪光自然图像反应有很好的预测，但对许多其他细胞的尖峰活动却无法捕捉。表现出较差模型性能的细胞对精细空间对比度和局部信号整流具有显著的敏感性，作为主要的非线性。相比之下，对高频对比度反转光栅的敏感性，一种经典的非线性空间整合测试，不是模型性能的良好预测因子，因此不能捕捉到自然图像下非线性空间整合的可变性。此外，我们还观察到一类具有空间对比度反向调谐的非线性神经节细胞，对空间均匀的刺激比空间结构的刺激反应更强。这些发现强调了感受野非线性的多样性作为理解自然刺激下早期感觉编码的一个关键组成部分。使用人工视觉刺激的实验已经揭示出许多类型的视网膜神经节细胞以非线性方式对空间输入信号进行汇总。然而，当输入信号是自然图像时，这种非线性空间整合的相关性仍然不清楚。在这里，我们分析了大量小鼠神经节细胞对自然场景的反应。我们表明，对于一些神经节细胞来说，非线性空间整合强烈影响对自然图像的反应，但对于另一些细胞则不然。具有非线性空间整合的细胞对其感受野内的空间结构敏感，一小部分细胞对空间均匀的刺激显示出惊人的敏感性。传统的用对比度反转光栅的分析并没有预测到这种在自然图像下非线性空间整合的可变性。
