RIA: A Self-Organizing Neural Network Model of The PrimaryVisual cortex

在一项试点研究中， 连接和动态过程中的哺乳动物新皮层， 一种新的皮质自组织模型LCSOFM（Laterally 连接自组织特征映射）。 这 研究集中在LCSOFM作为主要的计算模型， 视觉皮层 主要的假设是， 视觉皮层的连通性调节合作， 竞争是自组织和低层次竞争的必要条件 知觉现象 该假设将通过建立一个 视皮层的LCSOFM模型及其行为分析 通过模拟神经科学实验。 LCSOFM模型 允许在一个新的，更高的水平上对视觉皮层进行计算研究， 比早期的模型，并允许我们测试 关于它的结构和功能的几个新假说。 基于 在试点研究中，有理由相信该模型可以 验证（1）自组织是否可以基于合作 侧连神经元之间的竞争;（2）观察到的 长距离横向联系的模式来自于相关性 （3）大脑皮层的可塑性， 横向连接重组;（4）出现倾斜错觉 从横向连接的神经反应的竞争 视网膜定位图;（5）完形原则可以从 视觉体验和编码到横向连接;和（6） 横向联系、合作竞争、联合收割机 采用锁相装订，可负责分段 将视觉输入转化为连贯的整体。

In a pilot study motivated by recent results on the lateral connectivity and dynamic processes in the mammalian neocortex, a new model of coritcal self-organization called LCSOFM (Laterally Connected Self-Organizing Feature Map) was developed. This research focuses on LCSOFM as a computational model of the primary visual cortex. The main hypothesis is that the lateral connectivity in the visual cortex mediates cooperation and competition necessary for the self-organization and low-level perceptual phenomena. The hypothesis will be tested by building a LCSOFM model of the visual cortex and analyzing its behavior through simulated neuroscience experiments. The LCSOFM model permits computational study of the visual cortex at a new, more fundamental level than earlier models, and allows us to test several new hypotheses about its structure and function. Based on the pilot study, there is reason to believe that the model can verify whether (1) self-organization can be based on cooperation and competition among laterally connected neurons; (2) the observed patterns of long-range lateral connections arise from correlations in neural activity; (3) plasticity of the cortex results from reorganization of lateral connections; (4) tilt illusions arise from competition of neural responses in laterally connected retinotopic maps; (5) gestalt principles can be extracted from visual experience and encoded into lateral connections; and (6) cooperation and competition through lateral connection, combine with binding by phase-locking, can be responsible for segmentation of visual input into coherent wholes.//