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Cortical Synchronization and Perceptual Framing

机译:皮质同步和知觉框架

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摘要

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.
机译:大脑如何将对象的不同部分组合在一起,形成连贯的视觉对象表示形式?物体的不同部分可能会被大脑以不同的速率处理,因此可能会变得不同步。感知框架是重新同步对应于同一视网膜对象的皮层活动的过程。提出了一种神经网络模型,该模型能够快速重新同步去同步的神经活动。该模型提供了感知数据和大脑数据之间的链接。模型属性定量地模拟感知框架数据,包括有关时间顺序判断的心理物理数据以及阈值对比度随刺激长度的降低。早先使用这种模型来解释有关虚幻的轮廓形成,纹理分离,阴影形状,3-D视觉和皮质感受野的数据。该模型在此显示了多少数据可以理解为皮质分组过程的表现形式,该过程可以快速重新同步属于视觉对象表示形式的图像部分。该模型在有噪声的情况下显示出比没有噪声(一种随机共振)更好的同步性,并且当代表不同刺激方向的单元竞争时,该模型具有强大的同步性。当快速的远程协作和慢的短程竞争通过非线性反馈相互作用与服从分流方程的单元相互作用时,就会出现这些属性。

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