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A laminar cortical model of stereopsis and 3D surface perception: closure and da Vinci stereopsis

机译:立体视觉和3D表面感知的层状皮质模型:闭合和达芬奇立体视觉

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A laminar cortical model of stereopsis and 3D surface perception is developed and simulated. The model describes how monocular and binocular oriented filtering interact with later stages of 3D boundary formation and surface filling-in in the LGN and cortical areas V1, V2, and V4. It proposes how interactions between layers 4, 3B, and 2/3 in VI and V2 contribute to stereopsis, and how binocular and monocular information combine to form 3D boundary and surface representations. The model includes two main new developments: (1) It clarifies how surface-to-boundary feedback from V2 thin stripes to pale stripes helps to explain data about stereopsis. This feedback has previously been used to explain data about 3D figure-ground perception. (2) It proposes that the binocular false match problem is subsumed under the Gestalt grouping problem. In particular, the disparity filter, which helps to solve the correspondence problem by eliminating false matches, is realized using inhibitory interneurons as part of the perceptual grouping process by horizontal connections in layer 2/3 of cortical area V2. The enhanced model explains all the psychophysical data previously simulated by Grossberg and Howe (2003), such as contrast variations of dichoptic masking and the correspondence problem, the effect of interocular contrast differences on stereoacuity, Panurrf s limiting case, the Venetian blind illusion, stereopsis with polarity-reversed stereograms, and da Vinci stereopsis. It also explains psychophysical data about perceptual closure and variations of da Vinci stereopsis that previous models cannot yet explain.
机译:开发并模拟了立体视觉和3D表面感知的层状皮质模型。该模型描述了单眼和双眼定向过滤如何与LGN和皮质区域V1,V2和V4中的3D边界形成和表面填充的后期阶段相互作用。它提出了VI和V2中的第4、3B和2/3层之间的交互作用如何有助于立体视,以及双目和单眼信息如何结合以形成3D边界和表面表示。该模型包括两个主要的新发展:(1)阐明了从V2细条纹到浅条纹的表面到边界反馈如何帮助解释有关立体视的数据。该反馈先前已用于解释有关3D图形地面感知的数据。 (2)建议将双目错误匹配问题归入格式塔分组问题。特别地,视差滤波器通过在皮层区域V2的第2/3层中进行水平连接,将抑制性中间神经元用作感知分组过程的一部分,从而通过消除错误匹配来帮助解决对应问题。增强的模型解释了以前由Grossberg和Howe(2003)模拟的所有心理物理数据,例如两视掩蔽的对比度变化和对应问题,眼内对比度差异对立体视敏度的影响,Panurrf极限情况,威尼斯盲幻觉,立体视极性反转的立体图和达芬奇立体图像。它还解释了有关达芬奇立体视的知觉闭合和变异的心理物理学数据,以前的模型尚无法解释。

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