Computational models of cortical visual processing
Computational models of cortical visual processing
复制标题
DOI：
10.1073/pnas.93.2.623
复制
发表时间：
1996-01-23
影响因子：
11.1
通讯作者：
Movshon, JA
中科院分区：
文献类型：
--
作者：
Heeger, DJ;Simoncelli, EP;Movshon, JA
D·H·胡贝尔和T·N·威塞尔[(1962)J.Physiol]在20世纪60年代首次充分描述了大脑皮层神经元的视觉反应。(伦敦)160,106-154；(1968)J.Physiol。(伦敦)195,215-243]使用基于简单几何视觉目标的定性分析，在过去的30年里，通过试图对它们在视觉图像上执行的转换进行正式描述来考虑这些神经元的属性已经变得很常见，大多数这样的模型都植根于C.Enroth-Cugell和J.R.Robson[(1966)J.Physiol，(London)187,517-552]在视网膜中开创的线性系统方法，但很明显，纯粹的皮质神经元的线性模型是不够的。我们提出了两个相关的模型：一个设计用来解释初级视觉皮质(V1)中简单细胞的反应，另一个设计用来解释MT(或V5)中图案方向选择细胞的反应，MT(或V5)是一个被认为参与视觉运动分析的纹状外视区。这些模型共享一个共同的结构，以相同的方式对不同类型的输入进行操作，并例证了广泛持有的观点，即计算策略在整个大脑皮层都是相似的。这些模型的实现可用于Macintosh微型计算机，并可用于探索模型的特性。
The visual responses of neurons in the cerebral cortex were first adequately characterized in the 1960s by D. H. Hubel and T. N. Wiesel [(1962) J. Physiol. (London) 160, 106-154; (1968) J. Physiol. (London) 195, 215-243] using qualitative analyses based on simple geometric visual targets, Over the past 30 years, it has become common to consider the properties of these neurons by attempting to make formal descriptions of the transformations they execute on the visual image, Most such models have their roots in linear-systems approaches pioneered in the retina by C. Enroth-Cugell and J. R. Robson [(1966) J. Physiol, (London) 187, 517-552], but it is clear that purely linear models of cortical neurons are inadequate. We present two related models: one designed to account for the responses of simple cells in primary visual cortex (V1) and one designed to account for the responses of pattern direction selective cells in MT (or V5), an extrastriate visual area thought to be involved in the analysis of visual motion. These models share a common structure that operates in the same way on different kinds of input, and instantiate the widely held view that computational strategies are similar throughout the cerebral cortex, Implementations of these models for Macintosh microcomputers are available and can be used to explore the models' properties.