使用静态和运动刺激的双模块连续吸引神经网络
Min Yan1, Wen-Hao Zhang2,3, He Wang1,4
1Department of Physics, Hong Kong University of Science and Technology, Hong Kong SAR, People's Republic of China.
Physical review. E
|July 19, 2023
概括
有互动模块的神经网络表现出复杂的动态,影响感官集成. 激发性和抑制性合调节神经活动,影响大脑如何处理多感官信息.
科学领域:
- 计算神经科学是一种神经科学.
- 系统神经科学 系统神经科学
- 人工智能的人工智能
背景情况:
- 双模块连续吸引器神经网络处理不同的感官输入.
- 模块之间的相互作用影响网络动态和信息处理.
研究的目的:
- 研究双模块神经网络中的动态行为.
- 分析模块间合在感官集成中的作用.
- 扩展贝叶斯框架用于多感官集成解码.
主要方法:
- 模拟双模块连续吸引器神经网络.
- 在不同的合下分析了碰撞动态 (位置,高度).
- 扩展贝叶斯框架以模拟网络解码.
主要成果:
- 激发性合将颠转移到输入;抑制性转移远离.
- 随着混合合,出现了暂时调节和瞬间的人口峰值.
- 撞击高度随着激发性合而增加.
- 合编码有吸引力 (刺激性) 和排斥性 (抑制性) 的先验.
- 网络动态表现出多个稳定状态和对移动刺激的输入依赖过渡.
结论:
- 模块间合关键地塑造神经动力学和多感官集成.
- 网络行为与解码感官信息的贝叶斯原则保持一致.
- 该模型解释了静态和动态刺激是如何集成的.
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