Liu L, Sun H, Guo A
Laboratory of Visual Information Processing, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, P.R. China.
J Theor Biol. 1997 Nov 21;189(2):121-31. doi: 10.1006/jtbi.1997.0481.
A biological plausible neural network which simulated the input-output transformation performed by primates during saccadic eye movements is constructed using a selective attention module and multi-layered neural networks with improved back propagation and a competitive learning algorithm. Simulation results show that the trained model can make fine saccades directed by the target. Representations and processing mechanisms in the saccade system are investigated. The features of most hidden units resemble those that have been observed in physiological recordings of neurons in primates visual cortex. The hidden layer even developed structures similar to those of area 7a.
利用选择性注意模块以及具有改进反向传播和竞争学习算法的多层神经网络，构建了一个具有生物学合理性的神经网络，该网络模拟了灵长类动物在扫视眼动过程中执行的输入-输出转换。仿真结果表明，训练后的模型能够做出由目标引导的精细扫视。研究了扫视系统中的表征和处理机制。大多数隐藏单元的特征类似于在灵长类动物视觉皮层神经元的生理记录中观察到的特征。隐藏层甚至发展出了与7a区相似的结构。
