Obermayer K, Sejnowski T, Blasdel G G
Howard Hughes Medical Institute, La Jolla, CA, USA.
Behav Brain Res. 1995 Jan 23;66(1-2):161-7. doi: 10.1016/0166-4328(94)00136-4.
In this contribution we investigate a simple pattern formation process [9,10] based on Hebbian learning and competitive interactions within cortex. This process generates spatial representations of afferent (sensory) information which strongly resemble patterns of response properties of neurons commonly called brain maps. For one of the most thoroughly studied phenomena in cortical development, the formation of topographic maps, orientation and ocular dominance columns in macaque striate cortex, the process, for example, generates the observed patterns of receptive field properties including the recently described correlations between orientation preference and ocular dominance. Competitive Hebbian learning has not only proven to be a useful concept in the understanding of development and plasticity in several brain areas, but the underlying principles have have been successfully applied to problems in machine learning [22]. The model's universality, simplicity, predictive power, and usefulness warrants a closer investigation.
在本论文中，我们研究了一种基于赫布学习和皮层内竞争相互作用的简单模式形成过程[9,10]。该过程生成传入（感觉）信息的空间表征，这些表征与通常称为脑图谱的神经元反应特性模式极为相似。例如，对于猕猴纹状皮层中最深入研究的皮层发育现象之一——地形图、方位柱和眼优势柱的形成，该过程产生了所观察到的感受野特性模式，包括最近描述的方位偏好与眼优势之间的相关性。竞争性赫布学习不仅已被证明是理解多个脑区发育和可塑性的有用概念，而且其基本原理已成功应用于机器学习问题[22]。该模型的通用性、简单性、预测能力和实用性值得更深入的研究。
