• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Cognitive science >Integrating the Automatic and the Controlled: Strategies in Semantic Priming in an Attractor Network With Latching Dynamics
【24h】

Integrating the Automatic and the Controlled: Strategies in Semantic Priming in an Attractor Network With Latching Dynamics

机译：集成自动和受控：具有闩锁动力学的吸引者网络中的语义启动策略

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

AbstractSemantic priming has long been recognized to reflect, along with automatic semantic mechanisms, the contribution of controlled strategies. However, previous theories of controlled priming were mostly qualitative, lacking common grounds with modern mathematical models of automatic priming based on neural networks. Recently, we introduced a novel attractor network model of automatic semantic priming with latching dynamics. Here, we extend this work to show how the same model can also account for important findings regarding controlled processes. Assuming the rate of semantic transitions in the network can be adapted using simple reinforcement learning, we show how basic findings attributed to controlled processes in priming can be achieved, including their dependency on stimulus onset asynchrony and relatedness proportion and their unique effect on associative, category-exemplar, mediated and backward prime-target relations. We discuss how our mechanism relates to the classic expectancy theory and how it can be further extended in future developments of the model.
机译：摘要长期以来，人们已经认识到语义启动可以反映自动控制机制对受控策略的贡献。但是，以前的控制启动理论大多是定性的，缺乏基于神经网络的现代自动启动数学模型的共同基础。最近，我们介绍了一种具有锁存动力学的自动语义启动的新型吸引子网络模型。在这里，我们扩展了这项工作，以显示同一模型如何也可以解释有关受控过程的重要发现。假设可以使用简单的强化学习来适应网络中语义转换的速率，我们将展示如何实现归因于启动过程中受控过程的基本发现，包括其对刺激发作异步性和相关性比例的依赖性以及它们对关联，类别的独特影响-示例性，中介和后退主要目标关系。我们讨论了我们的机制与经典期望理论的关系以及如何在模型的未来发展中进一步扩展它。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号