Chawanya T, Aoyagi T, Nishikawa I, Okuda K, Kuramoto Y
Department of Physics, Kyoto University, Japan.
Biol Cybern. 1993;68(6):483-90. doi: 10.1007/BF00200807.
A neural network model for explaining experimentally observed neuronal responses in cat primary visual cortex is proposed. In our model, the basic functional unit is an orientation column which is represented by a large homogeneous population of neurons modeled as integrate-and-fire type excitable elements. The orientation column exhibits spontaneous collective oscillations in activity in response to suitable visual stimuli. Such oscillations are caused by mutual synchronization among the neurons within the column. Numerical simulation for various stimulus patterns shows that as a result of activity correlations between different columns, the amplitude and the phase of the oscillation in each column depend strongly on the global feature of the stimulus pattern. These results satisfactorily account for experimental observations.
提出了一种用于解释猫初级视觉皮层中实验观察到的神经元反应的神经网络模型。在我们的模型中，基本功能单元是一个方位柱，它由大量均匀的神经元群体表示，这些神经元被建模为积分发放型可兴奋元件。方位柱在受到合适的视觉刺激时会表现出自发的集体活动振荡。这种振荡是由柱内神经元之间的相互同步引起的。对各种刺激模式的数值模拟表明，由于不同柱之间的活动相关性，每个柱中振荡的幅度和相位强烈依赖于刺激模式的全局特征。这些结果令人满意地解释了实验观察结果。
