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

RIA：初级视觉皮层的自组织神经网络模型

• 批准号: 9309273
• 负责人: Risto Miikkulainen
• 金额: $ 14.12万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1993
• 资助国家: 美国
• 起止时间: 1993-06-15 至 1996-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9309273&HistoricalAwards=false
• 关键词: RIA; Self; Organizing; Neural; Network

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.//

在一项基于哺乳动物新皮质横向连接和动态过程最新结果的试点研究中，开发了一种新的皮质自组织模型，称为 LCSOFM（横向连接自组织特征图）。 本研究重点关注 LCSOFM 作为初级视觉皮层的计算模型。 主要假设是视觉皮层的横向连接介导自组织和低级感知现象所必需的合作和竞争。 该假设将通过建立视觉皮层的 LCSOFM 模型并通过模拟神经科学实验分析其行为来进行检验。 LCSOFM 模型允许在比早期模型更基础的新水平上对视觉皮层进行计算研究，并允许我们测试有关其结构和功能的几个新假设。 基于试点研究，有理由相信该模型可以验证：（1）自组织是否可以基于横向连接的神经元之间的合作和竞争； （2）观察到的长程横向连接模式源于神经活动的相关性； (3)皮质的可塑性来自于侧向连接的重组； （4）倾斜错觉是由于横向连接的视网膜专题图中神经反应的竞争而产生的； （5）格式塔原则可以从视觉经验中提取并编码为横向连接； (6)通过横向连接的合作和竞争，结合锁相绑定，可以负责将视觉输入分割成连贯的整体。//