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Contour integration and segmentation with self-organized lateral connections

机译:具有自组织横向连接的轮廓整合和分段

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摘要

Contour integration in low-level vision is believed to occur based on lateral interaction between neurons with similar orientation tuning. How such interactions could arise in the brain has been an open question. Our model suggests that the interactions can be learned through input-driven self-organization, i.e., through the same mechanism that underlies many other developmental and functional phenomena in the visual cortex. The model also shows how synchronized firing mediated by these lateral connections can represent the percept of a contour, resulting in performance similar to that of human contour integration. The model further demonstrates that contour integration performance can differ in different parts of the visual field, depending on what kinds of input distributions they receive during development. The model thus grounds an important perceptual phenomenon onto detailed neural mechanisms so that various structural and functional properties can be measured and predictions can be made to guide future experiments. [References: 75]
机译:人们认为,基于类似取向调整的神经元之间的侧向交互作用,会发生低水平视觉中的轮廓整合。这种相互作用如何在大脑中发生是一个悬而未决的问题。我们的模型表明,可以通过输入驱动的自组织(即通过视觉皮层中许多其他发育和功能现象的基础相同的机制)来学习交互作用。该模型还显示了由这些横向连接介导的同步射击如何表示轮廓的感知,从而产生与人类轮廓集成相似的性能。该模型进一步证明,轮廓积分性能在视野的不同部分可能会有所不同,这取决于它们在开发过程中会收到哪种输入分布。因此,该模型将重要的感知现象建立在详细的神经机制上,以便可以测量各种结构和功能特性,并可以进行预测以指导将来的实验。 [参考:75]

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