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Cooperative and Competitive Interactions Facilitate Stereo Computations in Macaque Primary Visual Cortex

机译:协作和竞争相互作用促进猕猴初级视觉皮层的立体计算。

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摘要

Inferring depth from binocular disparities is a difficult problem for the visual system because local features in the left- and right-eye images must be matched correctly to solve this “stereo correspondence problem.” Cortical architecture and computational studies suggest that lateral interactions among neurons could help resolve local uncertainty about disparity encoded in individual neurons by incorporating contextual constraints. We found that correlated activity among pairs of neurons in primary visual cortex depended both on disparity-tuning relationships and the stimuli displayed within the receptive fields of the neurons. Nearby pairs of neurons with distinct disparity tuning exhibited a decrease in spike correlation at competing disparities soon after response onset. Distant neuronal pairs of similar disparity tuning exhibited an increase in spike correlation at mutually preferred disparities. The observed correlated activity and response dynamics suggests that local competitive and distant cooperative interactions improve disparity tuning of individual neurons over time. Such interactions could represent a neural substrate for the principal constraints underlying cooperative stereo algorithms.
机译:从双目视差推断深度对于视觉系统而言是一个难题,因为必须正确匹配左眼图像和右眼图像中的局部特征才能解决此“立体对应问题”。皮质结构和计算研究表明,神经元之间的横向相互作用可以通过结合上下文约束来帮助解决有关个别神经元中编码的视差的局部不确定性。我们发现,初级视皮层中成对的神经元之间的相关活动既取决于视差调整关系,也取决于神经元感受野内显示的刺激。反应开始后不久,具有明显差异调整的附近神经元对在竞争差异处的峰值相关性降低。相似视差调整的遥远神经元对在相互优选的视差处显示出尖峰相关性增加。观察到的相关活动和反应动力学表明,局部竞争性和远程合作性相互作用随着时间的推移改善了单个神经元的视差调节。这样的相互作用可以代表合作立体算法背后的主要约束的神经基础。

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