Boston University.
J Cogn Neurosci. 1997 Jan;9(1):117-32. doi: 10.1162/jocn.1997.9.1.117.
How does the brain group together different parts of an object into a coherent visual object representation? Different parts of an object may be processed by the brain at different rates and may thus become desynchronized. Perceptual framing is a process that resynchronizes cortical activities corresponding to the same retinal object. A neural network model is presented that is able to rapidly resynchronize desynchronized neural activities. The model provides a link between perceptual and brain data. Model properties quantitatively simulate perceptual framing data, including psychophysical data about temporal order judgments and the reduction of threshold contrast as a function of stimulus length. Such a model has earlier been used to explain data about illusory contour formation, texture segregation, shape-from-shading, 3-D vision, and cortical receptive fields. The model hereby shows how many data may be understood as manifestations of a cortical grouping process that can rapidly resynchronize image parts that belong together in visual object representations. The model exhibits better synchronization in the presence of noise than without noise, a type of stochastic resonance, and synchronizes robustly when cells that represent different stimulus orientations compete. These properties arise when fast long-range cooperation and slow short-range competition interact via nonlinear feedback interactions with cells that obey shunting equations.
大脑如何将物体的不同部分组合成一个连贯的视觉对象表示？物体的不同部分可能由大脑以不同的速度处理，因此可能会失去同步。感知框架是一个重新同步对应于相同视网膜物体的皮质活动的过程。本文提出了一个能够快速重新同步去同步神经活动的神经网络模型。该模型提供了感知和大脑数据之间的联系。模型特性定量模拟了感知框架数据，包括关于时间顺序判断和阈值对比度随刺激长度变化的心理物理数据。这种模型以前曾被用于解释关于错觉轮廓形成、纹理分离、阴影形状、3D 视觉和皮质感受野的数据。该模型表明，许多数据可以被理解为快速重新同步属于视觉对象表示中同一部分的图像部分的皮质分组过程的表现。与没有噪声的情况相比，该模型在存在噪声时具有更好的同步性，这是一种随机共振，并且当代表不同刺激方向的细胞竞争时，它可以稳健地同步。当通过服从分流方程的细胞进行非线性反馈相互作用时，快速的远程协作和缓慢的短程竞争相互作用会产生这些特性。
