Department of Neurobiology, Duke University, Durham, NC 27708.
Department of Neurobiology, Duke University, Durham, NC 27708;
Proc Natl Acad Sci U S A. 2021 Sep 28;118(39). doi: 10.1073/pnas.2105115118.
Many sensory systems utilize parallel ON and OFF pathways that signal stimulus increments and decrements, respectively. These pathways consist of ensembles or grids of ON and OFF detectors spanning sensory space. Yet, encoding by opponent pathways raises a question: How should grids of ON and OFF detectors be arranged to optimally encode natural stimuli? We investigated this question using a model of the retina guided by efficient coding theory. Specifically, we optimized spatial receptive fields and contrast response functions to encode natural images given noise and constrained firing rates. We find that the optimal arrangement of ON and OFF receptive fields exhibits a transition between aligned and antialigned grids. The preferred phase depends on detector noise and the statistical structure of the natural stimuli. These results reveal that noise and stimulus statistics produce qualitative shifts in neural coding strategies and provide theoretical predictions for the configuration of opponent pathways in the nervous system.
许多感觉系统利用分别为刺激增加和减少提供信号的并行 ON 和 OFF 通路。这些通路由跨越感觉空间的 ON 和 OFF 检测器的集合或网格组成。然而，对手通路的编码提出了一个问题：为了最优地编码自然刺激，应该如何排列 ON 和 OFF 检测器的网格？我们使用受有效编码理论指导的视网膜模型来研究这个问题。具体来说，我们针对给定噪声和约束发放率的自然图像，优化了空间感受野和对比响应函数。我们发现，ON 和 OFF 感受野的最优排列表现出从对齐到非对齐网格的转变。首选相位取决于检测器噪声和自然刺激的统计结构。这些结果表明，噪声和刺激统计产生了神经编码策略的定性转变，并为神经系统中对手通路的配置提供了理论预测。
