Jun Na Young, Field Greg D, Pearson John M
Department of Neurobiology, Duke University, Durham, NC 27710.
Department of Biostatistics & Bioinformatics, Department of Neurobiology, Department of Electrical and Computer Engineering, Duke University, Durham, NC 27710.
Adv Neural Inf Process Syst. 2022 Dec;35:32311-32324.
Among the most striking features of retinal organization is the grouping of its output neurons, the retinal ganglion cells (RGCs), into a diversity of functional types. Each of these types exhibits a mosaic-like organization of receptive fields (RFs) that tiles the retina and visual space. Previous work has shown that many features of RGC organization, including the existence of ON and OFF cell types, the structure of spatial RFs, and their relative arrangement, can be predicted on the basis of efficient coding theory. This theory posits that the nervous system is organized to maximize information in its encoding of stimuli while minimizing metabolic costs. Here, we use efficient coding theory to present a comprehensive account of mosaic organization in the case of natural videos as the retinal channel capacity-the number of simulated RGCs available for encoding-is varied. We show that mosaic density increases with channel capacity up to a series of critical points at which, surprisingly, new cell types emerge. Each successive cell type focuses on increasingly high temporal frequencies and integrates signals over larger spatial areas. In addition, we show theoretically and in simulation that a transition from mosaic alignment to anti-alignment across pairs of cell types is observed with increasing output noise and decreasing input noise. Together, these results offer a unified perspective on the relationship between retinal mosaics, efficient coding, and channel capacity that can help to explain the stunning functional diversity of retinal cell types.
视网膜组织最显著的特征之一是其输出神经元,即视网膜神经节细胞(RGCs),被分为多种功能类型。这些类型中的每一种都表现出一种镶嵌式的感受野(RFs)组织,覆盖视网膜和视觉空间。先前的研究表明,RGC组织的许多特征,包括ON和OFF细胞类型的存在、空间RFs的结构及其相对排列,都可以基于高效编码理论进行预测。该理论假定,神经系统的组织方式是在编码刺激时最大化信息,同时最小化代谢成本。在这里,我们使用高效编码理论,在视网膜通道容量(即可用于编码的模拟RGC数量)变化的情况下,对镶嵌组织进行全面阐述。我们表明,镶嵌密度随着通道容量的增加而增加,直至达到一系列临界点,令人惊讶的是,此时会出现新的细胞类型。每一种相继出现的细胞类型都专注于越来越高的时间频率,并在更大的空间区域整合信号。此外,我们在理论和模拟中都表明,随着输出噪声增加和输入噪声降低,会观察到成对细胞类型之间从镶嵌对齐到反对齐的转变。这些结果共同为视网膜镶嵌、高效编码和通道容量之间的关系提供了一个统一的视角,有助于解释视网膜细胞类型惊人的功能多样性。