Modeling Development and Perceptual Phenomena in the Visual Cortex

视觉皮层的建模发展和感知现象

基本信息

  • 批准号:
    9811478
  • 负责人:
  • 金额:
    $ 23.14万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    1998
  • 资助国家:
    美国
  • 起止时间:
    1998-12-15 至 2001-11-30
  • 项目状态:
    已结题

项目摘要

Although much progress has been made in understanding the development and function of the visual cortex experimentally, the exact mechanisms are still not completely understood. With the advent of parallel supercomputers in the past few years, it has become viable to test theories about these mechanisms in detailed computational simulations. In the PIs previous project, a model of the primary visual cortex was developed that showed how the observed receptive fields, columnar organization, and lateral connectivity can arise through input-driven Hebbian self-organization. The current project continues the research in four directions: (1) The self-organizing model is extended to a hierarchy of visual representations, taking into account feedback from higher levels of visual processing. (2) Internal pattern generators are included in the model and the hypothesis that they implement genetic control over the self-organized structures is verified against data on chick imprinting and the development of face recognition in infants. (3) The hypothesis that visual illusions and aftereffects occur as a side effect of the adapting lateral interactions in the system is tested computationally. (4) The hypothesis that perceptual grouping occurs based on synchronization mediated by the lateral and feedback connections is tested, verifying that Gestalt phenomena emerge from self-organized interactions. The project lends strong computational support to the idea that the visual cortex is a continuously-adapting recurrent structure, and that perceptual phenomena such as face recognition, illusions, and grouping are its emergent effects.http://www.cs.utexas.edu/users/nn/pages/research/selforg.html
虽然在实验上对视皮层的发育和功能的了解已经取得了很大的进展,但其确切的机制仍然不完全清楚。随着过去几年并行超级计算机的出现,在详细的计算模拟中测试关于这些机制的理论已经成为可能。在PIS之前的项目中,开发了一个初级视觉皮质的模型,该模型展示了观察到的感受野、柱状组织和横向连接如何通过输入驱动的Hebbian自组织产生。本课题从四个方面继续研究:(1)将自组织模型扩展到视觉表征的层次结构,考虑了来自更高视觉加工水平的反馈。(2)模型中包含了内部模式生成器,并根据婴儿的小鸡印记和面孔识别发展的数据验证了内部模式生成器对自组织结构实施遗传控制的假设。(3)对视错觉和后效是系统中适应性横向相互作用的副作用的假设进行了计算验证。(4)检验了知觉分组是基于侧向连接和反馈连接的同步而发生的假设,验证了格式塔现象是由自组织交互作用产生的。该项目为这样的观点提供了强有力的计算支持,即视觉皮质是一个不断适应的递归结构,而诸如人脸识别、错觉和分组等知觉现象是其出现的effects.http://www.cs.utexas.edu/users/nn/pages/research/selforg.html

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

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Risto Miikkulainen其他文献

Holdout Evaluation
坚持评估
  • DOI:
    10.1007/978-0-387-30164-8_369
  • 发表时间:
    2010
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Antal van den Bosch;B. Hengst;J. Lloyd;Risto Miikkulainen;Hendrik Blockeel
  • 通讯作者:
    Hendrik Blockeel
MARLEDA: Effective distribution estimation through Markov random fields
  • DOI:
    10.1016/j.tcs.2015.07.049
  • 发表时间:
    2016-06-20
  • 期刊:
  • 影响因子:
  • 作者:
    Matthew Alden;Risto Miikkulainen
  • 通讯作者:
    Risto Miikkulainen
Evolutionary Supervised Machine Learning
  • DOI:
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Risto Miikkulainen
  • 通讯作者:
    Risto Miikkulainen
Extracting the dynamics of the Hodgkin-Huxley model using recurrent neural networks
  • DOI:
    10.1186/1471-2202-8-s2-p100
  • 发表时间:
    2007-07-06
  • 期刊:
  • 影响因子:
    2.300
  • 作者:
    Sari Andoni;Manish Saggar;Tekin Meriçli;Risto Miikkulainen
  • 通讯作者:
    Risto Miikkulainen
Modeling self-organizing tri-chromatic color selective regions in primary visual cortex
  • DOI:
    10.1186/1471-2202-8-s2-s24
  • 发表时间:
    2007-07-06
  • 期刊:
  • 影响因子:
    2.300
  • 作者:
    Judah De Paula;Jim Bednar;Risto Miikkulainen
  • 通讯作者:
    Risto Miikkulainen

Risto Miikkulainen的其他文献

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{{ truncateString('Risto Miikkulainen', 18)}}的其他基金

Collaborative Research: MOD and TLS: A Predictive Simulation Model of Competitive Dynamics in Innovation
合作研究:MOD 和 TLS:创新竞争动态的预测模拟模型
  • 批准号:
    0914796
  • 财政年份:
    2009
  • 资助金额:
    $ 23.14万
  • 项目类别:
    Standard Grant
RI: Small: Learning Strategic Behavior in Sequential Decision Tasks
RI:小:学习顺序决策任务中的策略行为
  • 批准号:
    0915038
  • 财政年份:
    2009
  • 资助金额:
    $ 23.14万
  • 项目类别:
    Standard Grant
Pilot: Leveraging Human Creativity with Machine Discovery
试点:通过机器发现利用人类创造力
  • 批准号:
    0757479
  • 财政年份:
    2008
  • 资助金额:
    $ 23.14万
  • 项目类别:
    Standard Grant
RI: Mastodon: A Large-Memory, High-Throughput Simulation Infrastructure
RI:Mastodon:大内存、高吞吐量的模拟基础设施
  • 批准号:
    0303609
  • 财政年份:
    2003
  • 资助金额:
    $ 23.14万
  • 项目类别:
    Continuing Grant
Cooperative Coevolution of Neural Networks in Sequential Decision Tasks
顺序决策任务中神经网络的协同协同进化
  • 批准号:
    0083776
  • 财政年份:
    2000
  • 资助金额:
    $ 23.14万
  • 项目类别:
    Continuing Grant
Symbiotic Evolution of Neural Networks in Sequential Decision Tasks
神经网络在顺序决策任务中的共生进化
  • 批准号:
    9504317
  • 财政年份:
    1995
  • 资助金额:
    $ 23.14万
  • 项目类别:
    Continuing Grant
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
  • 财政年份:
    1993
  • 资助金额:
    $ 23.14万
  • 项目类别:
    Standard Grant

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