首页> 外文期刊>Journal of the Optical Society of America, A. Optics, image science, and vision >Neural dynamics of motion grouping: from aperture ambiguity to object speed and direction
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Neural dynamics of motion grouping: from aperture ambiguity to object speed and direction

机译:运动分组的神经动力学:从光圈模糊度到物体速度和方向

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A neural network model of visual motion perception and speed discrimination is developed to simulate dat concerning the conditions under which components of moving stimuli cohere or not into a global direction of motion, as in barberpole and plaid patterns (both type 1 and type 2). The model also simulates how the perceived speed of lines moving in a prescribed direction depends on their orientation, length, duration, and contrast. Motion direction and speed both emerge as part of an interactive motion grouping or segmentation process. The model proposes a solution to the global aperture problem by showing how information from feature tracking points, namely, locations from which unambiguous motion directions can be computed, can propagate to ambiguous motion direction points and capture the motion signals there. The model does this without computing intersections of constraints or parallel Fourier and non-Fourier pathways. Instead, the model uses orientationally unselective cell responses to activate directionally tuned transient cells. These transient cells, in turn, activate spatially short-range filters and competitive mechanisms over multiple spatial scales to generate speed-tuned and rectionally tuned cells. Spatially long-range filters and top-down feedback from grouping cells are then used to track motion of featural points and to select and propagate correct motion directions to ambiguous motion points. Top-down grouping can also prime the system to attend a: particular motion direction. The model hereby links low-level automatic motion processing with tentionbased motion processing. Homologs of model mechanisms have been used in models of other brain systems to simulate data about visual grouping, figureground separation, and speech perception. Earlier versions of the model have simulated data about short-range and long-range apparent motion, second-order motion, and the effects of parvocellular and magnocellular lateral geniculate nucleus lesions on motion perception, #1997 Optical Society of America [S0740-3232(97)00810-7]
机译:开发了视觉运动感知和速度辨别的神经网络模型,以模拟dat所涉及的条件,在该条件下,运动刺激的成分在整体运动方向上凝聚或不凝聚,例如在理发店和格子图案(类型1和类型2)中。该模型还模拟了沿指定方向移动的线的感知速度如何取决于其方向,长度,持续时间和对比度。运动方向和速度都作为交互式运动分组或分段过程的一部分出现。该模型通过显示来自特征跟踪点(即可以从其计算出明确运动方向的位置)的信息如何传播到歧义运动方向点并捕获那里的运动信号,从而提出了一种解决全局孔径问题的解决方案。该模型无需计算约束的交叉点或并行的傅里叶和非傅里叶路径。取而代之的是,模型使用定向非选择性细胞响应来激活定向调谐的瞬时细胞。这些瞬态细胞继而在多个空间尺度上激活空间短程滤波器和竞争机制,以生成速度调整和正向调整的细胞。然后使用空间远程滤波器和来自分组单元的自上而下的反馈来跟踪特征点的运动,并选择正确的运动方向并将其传播到模糊的运动点。自上而下的分组还可以使系统参与特定的运动方向。该模型在此将低级自动运动处理与基于意图的运动处理联系起来。模型机制的同系物已用于其他大脑系统的模型中,以模拟有关视觉分组,图形背景分离和语音感知的数据。该模型的早期版本具有有关近距离和远距离视在运动,二阶运动以及小细胞和大细胞侧膝状核损伤对运动知觉的模拟数据,#1997美国光学学会[S0740-3232( 97)00810-7]

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