Wang R
Department of Engineering, Harvey Mudd College, Claremont, CA 91711, USA.
Neural Comput. 1995 Mar;7(2):290-306. doi: 10.1162/neco.1995.7.2.290.
A simple and biologically plausible model is proposed to simulate the optic flow computation taking place in the dorsal part of medial superior temporal (MSTd) area of the visual cortex in the primates' brain. The model is a neural network composed of competitive learning layers. The input layer of the network simulates the neurons in the middle temporal (MT) area that selectively respond to the visual stimuli of the input motion patterns with different local velocities. The output layer of the network simulates the MSTd neurons that selectively respond to different types of optic flow motion patterns including planar, circular, radial, and spiral motions. Simulation results obtained from this model show that the behaviors of the output nodes of the network resemble very closely the known responsive properties of the MSTd neurons found neurophysiologically, such as the existence of three types of MSTd neurons that respond, respectively, to one, two, or three types of the input motion patterns with different position dependences, and the continuum of response selectivity formed by the three types of neurons.
提出了一个简单且符合生物学原理的模型，用于模拟灵长类动物大脑视觉皮层内侧颞叶背侧（MSTd）区域中发生的光流计算。该模型是一个由竞争学习层组成的神经网络。网络的输入层模拟颞中（MT）区域的神经元，这些神经元选择性地响应具有不同局部速度的输入运动模式的视觉刺激。网络的输出层模拟MSTd神经元，这些神经元选择性地响应不同类型的光流运动模式，包括平面、圆形、径向和螺旋运动。从该模型获得的模拟结果表明，网络输出节点的行为与神经生理学上发现的MSTd神经元的已知响应特性非常相似，例如存在三种类型的MSTd神经元，它们分别以不同的位置依赖性响应一种、两种或三种类型的输入运动模式，以及由这三种类型的神经元形成的响应选择性的连续性。
