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An analysis of Hebb's cell assembly as a mechanism for perceptual generalization.

机译:分析赫布的细胞组装作为一种感知泛化的机制。

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摘要

For a species as oriented to objects as we are, recognizing objects is essential. Without this capacity, gathering and storing information would be useless, since any information that was stored could never be accessed or applied.; Recognizing objects is made difficult by the fact that the same object rarely if ever produces identical stimulus patterns. Every time an object is encountered, different features of the object are available in different combinations; further, there is variability both in these features and in the object's background. In order to manage this perpetual novelty, the ability to selectively generalize is essential. One must be able to generalize over the appropriate equivalence class of stimulus patterns, such that all of the stimulus patterns in an equivalence class indicate the presence of the same object. This ability is called perceptual generalization.; The focus of this dissertation is a simulation-based analysis of the perceptual generalization capabilities of Hebb's cell assembly. A cell assembly is a group of highly interconnected neurons that forms a reverberatory circuit capable of sustaining activity. Because of the reverberatory potential of this structure, nonidentical stimulus patterns can lead to the full activation of the same cell assembly. This provides a mechanism for producing the same response despite variability in the parts of the cell assembly that were initially activated.; Despite the importance of perceptual generalization and the potential that cell assembly theory has for providing a solution, the perceptual generalization capabilities of the cell assembly have never been explored via simulation. This dissertation: (1) explores these capabilities by studying the formation of cell assemblies through unsupervised perceptual learning. (2) demonstrates the utility of failure-driven experiments in incrementally developing a model of cell assembly functioning. (3) provides new insights on ways to visualize activity levels and connection strengths, two key factors in understanding the behavior of cell assemblies. (4) demonstrates the ability of cell assemblies to generalize despite the two most fundamental challenges to achieving perceptual generalization: variability and noise in the stimulus patterns.
机译:对于像我们这样面向对象的物种,识别对象至关重要。没有这种能力,收集和存储信息将毫无用处,因为任何存储的信息都将永远无法被访问或应用。由于同一物体很少会产生相同的刺激模式,因此很难识别物体。每次遇到一个对象时,对象的不同特征都有不同的组合。此外,这些特征和物体的背景都有变化。为了管理这种永恒的新颖性,选择性概括的能力至关重要。一个人必须能够对适当的激励模式等价类进行概括,以使等价类中的所有激励模式都指示同一对象的存在。这种能力称为感知概括。本文的重点是基于仿真的赫布细胞装配感知能力的分析。细胞组件是一组高度相互连接的神经元,它们形成能够维持活动的回响回路。由于这种结构具有回声的潜力,因此不同的刺激模式可能导致同一细胞装配体的完全激活。这提供了产生相同响应的机制,尽管最初被激活的电池组件的各个部分是可变的。尽管感知概括的重要性以及单元格组装理论具有提供解决方案的潜力,但从未通过模拟探索单元格组装件的感知概括能力。本文主要研究内容:(1)通过无监督的感知学习研究细胞组装的形成来探索这些能力。 (2)演示了故障驱动实验在逐步开发电池组装功能模型中的实用性。 (3)提供了关于可视化活动水平和连接强度的方法的新见解,这是了解细胞装配行为的两个关键因素。 (4)展示了细胞装配体泛化的能力,尽管实现感知泛化的两个最基本的挑战是:刺激模式的可变性和噪声。

著录项

  • 作者

    Fu, Leeann Liang.;

  • 作者单位

    University of Michigan.;

  • 授予单位 University of Michigan.;
  • 学科 Computer Science.
  • 学位 Ph.D.
  • 年度 2003
  • 页码 112 p.
  • 总页数 112
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自动化技术、计算机技术 ;
  • 关键词

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