Data from: Error-robust modes of the retinal population code

Across the nervous system, certain population spiking patterns are observed far more frequently than others. A hypothesis about this structure is that these collective activity patterns function as population codewords–collective modes–carrying information distinct from that of any single cell. We investigate this phenomenon in recordings of ∼150 retinal ganglion cells, the retina’s output. We develop a novel statistical model that decomposes the population response into modes; it predicts the distribution of spiking activity in the ganglion cell population with high accuracy. We found that the modes represent localized features of the visual stimulus that are distinct from the features represented by single neurons. Modes form clusters of activity states that are readily discriminated from one another. When we repeated the same visual stimulus, we found that the same mode was robustly elicited. These results suggest that retinal ganglion cells’ collective signaling is endowed with a form of error-correcting code–a principle that may hold in brain areas beyond retina.

在神经系统中，特定的群体锋电位模式（population spiking patterns）出现的频率远高于其他模式。针对这一结构的一项假说认为，这些集体活动模式可作为群体码字（population codewords）——即集体模态（collective modes）——承载着与单个神经元完全不同的信息。我们对作为视网膜输出通路的约150个视网膜神经节细胞（retinal ganglion cells）的电活动记录展开研究，以此探究该现象。我们提出了一种全新的统计模型，可将群体响应（population response）分解为各类模态；该模型能够高精度地预测神经节细胞群体的锋电位活动分布。我们发现，这些模态所表征的是视觉刺激的局部特征，与单个神经元所表征的特征存在显著差异。模态会形成彼此易于区分的活动状态簇。当我们重复呈现同一视觉刺激时，发现同一模态会被稳定地激活。上述结果表明，视网膜神经节细胞的集体信号传递具备一种纠错编码（error-correcting code）机制——这一原则或许也适用于视网膜以外的大脑区域。