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A normalized contrast‐encoding model exhibits bright/dark asymmetries similar to early visual neurons

机译:标准化的对比编码模型表现出类似于早期视觉神经元的明/暗不对称性

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摘要

Biological sensory systems share a number of organizing principles. One such principle is the formation of parallel streams. In the visual system, information about bright and dark features is largely conveyed via two separate streams: the ON and OFF pathways. While brightness and darkness can be considered symmetric and opposite forms of visual contrast, the response properties of cells in the ON and OFF pathways are decidedly asymmetric. Here, we ask whether a simple contrast‐encoding model predicts asymmetries for brights and darks that are similar to the asymmetries found in the ON and OFF pathways. Importantly, this model does not include any explicit differences in how the visual system represents brights and darks, but it does include a common normalization mechanism. The phenomena captured by the model include (1) nonlinear contrast response functions, (2) greater nonlinearities in the responses to darks, and (3) larger responses to dark contrasts. We report a direct, quantitative comparison between these model predictions and previously published electrophysiological measurements from the retina and thalamus (guinea pig and cat, respectively). This work suggests that the simple computation of visual contrast may account for a range of early visual processing nonlinearities. Assessing explicit models of sensory representations is essential for understanding which features of neuronal activity these models can and cannot predict, and for investigating how early computations may reverberate through the sensory pathways.
机译:生物感觉系统共享许多组织原则。一种这样的原理是形成平行流。在视觉系统中,有关亮和暗特征的信息主要通过两个独立的流传递:ON和OFF路径。虽然可以将亮度和暗度视为对称且视觉对比度相反的形式,但ON和OFF路径中细胞的响应特性显然是不对称的。在这里,我们问一个简单的对比度编码模型是否可以预测亮和暗的不对称性,这些不对称性类似于在ON和OFF路径中发现的不对称性。重要的是,此模型在视觉系统表示明暗之间的方式上不包含任何明显的差异,但确实包含通用的归一化机制。该模型捕获的现象包括(1)非线性对比响应函数,(2)对暗的响应具有较大的非线性,以及(3)对暗的对比度具有较大的响应。我们报告了这些模型预测与先前从视网膜和丘脑(分别为豚鼠和猫)发表的电生理测量值之间的直接,定量比较。这项工作表明,视觉对比度的简单计算可能会解释早期视觉处理非线性的范围。评估感觉代表的显式模型对于理解这些模型可以预测和不能预测神经元活动的哪些特征,以及调查早期计算如何通过感觉途径产生回响至关重要。

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