在低级循环神经网络中的随机活动
Francesca Mastrogiuseppe1, Joana Carmona1, Christian K Machens1
1Champalimaud Foundation, Neuroscience Research Programme, Lisbon (Portugal).
bioRxiv : the preprint server for biology
|July 17, 2025
概括
大脑电路连接影响神经活动模式. 这项研究揭示了输入维度如何塑造循环神经网络中的新兴活动,影响维度和动态.
科学领域:
- 计算神经科学是一种计算神经科学.
- 网络科学 网络科学
- 系统神经科学 系统神经科学
背景情况:
- 神经电路连接是大脑活动的基础.
- 神经网络结构和新兴活动之间的关系尚未完全理解.
- 具有随机输入的循环神经网络被用来建模大脑功能.
研究的目的:
- 调查连接结构与循环神经网络中新兴活动之间的联系.
- 检查外部随机输入的维度如何影响神经活动几何.
- 为分析在噪音下结构化大脑电路提供一个框架.
主要方法:
- 利用具有附加性随机输入的循环神经网络.
- 以低级形式假设突触连接,通过连接向量进行参数化.
- 分析了与连接向量和输入维度相关的新兴活动的几何.
主要成果:
- 活动的维度取决于输入的维度.
- 低维输入导致由连接向量的子集定义的子空间内的低维活动.
- 高维输入可以导致由所有连接向量定义的子空间内的高维活动.
结论:
- 外部输入的维度决定了新兴神经活动的维度特性.
- 循环动态影响特定子空间内的活动,由连接结构和输入维度决定.
- 这些发现为激发-抑制网络的放大提供了洞察力,并为解释大脑活动的随机模型提供了一个框架.
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