通过封闭的接收能力传输分级信息,以广播信号
bioRxiv : the preprint server for biology
|November 19, 2025
概括
大脑使用动态的神经群体来整合决策的证据. 一个新的模型显示了分级信号如何在神经元之间传输,从而在不断变化的参考框架中实现连续认知.
科学领域:
- 神经科学是一个神经科学.
- 认知科学 认知科学
- 计算神经科学是一种神经科学.
背景情况:
- 准确的决策依赖于大脑保持不断演变的积累证据表示的能力.
- 编码证据的神经群体可能会在积累过程中发生变化,受到眼睛运动等行为的影响.
- 有证据表明,在不同类型的眼动过程中,神经元之间会传递信号.
研究的目的:
- 介绍神经群体灵活信息传输的计算模型.
- 解释如何持续的证据整合可以发生,尽管神经表示的变化.
- 为在动态环境中提供认知连续性的一般框架.
主要方法:
- 开发了一个模拟分级信号传输的计算模型.
- 整合了一个动态关门机制来控制神经元对分级信息的受感性.
- 专注于一种不需要改变突触连接的模型.
主要成果:
- 该模型展示了分级信息的灵活传输,而不会改变突触连接.
- 动态门机制允许在神经群体内控制信息流.
- 该框架支持跨越不断变化的参考框架的持续决策.
结论:
- 拟议的模型提供了一种机制,在动态证据积累期间保持认知连续性.
- 动态门提供了一种管理神经系统信息流的方法,而无需突触可塑性.
- 这种方法可以为理解大脑中的灵活信息处理提供一个可概括的框架.
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