信息瓶作为决策过程中多区域皮质表示的基础原则
Michael Kleinman1, Tian Wang2, Derek Xiao1
1Department of Electrical and Computer Engineering, University of California, Los Angeles, CA, USA.
bioRxiv : the preprint server for biology
|July 28, 2023
概括
大脑使用多个区域进行决策,创建最小的充分表示. 这项研究表明,背侧前额叶皮层 (DLPFC) 和背前运动皮层 (PMd) 如何通过优先信息传播实现这一目标.
科学领域:
- 神经科学是一个神经科学.
- 计算神经科学是一种神经科学.
- 认知科学 认知科学
背景情况:
- 决策涉及多个区域的分布式大脑计算.
- 在大脑中分布式计算的功能优势仍然不清楚.
- 人工神经网络利用多层架构来形成最佳的任务表示.
研究的目的:
- 为了研究为什么大脑分发用于决策的计算.
- 为了确定皮层区域如何形成最小足够的表示.
- 探索在决策任务中的最佳信息处理背后的神经机制.
主要方法:
- 在子的背侧前额皮层 (DLPFC) 和背前运动皮层 (PMd) 中记录了单个神经元和多个单元在感知决策任务期间.
- 训练了一个多区域递归神经网络 (RNN) 来执行相同的任务.
- 分析神经表征和区域间通信模式.
主要成果:
- DLPFC表示任务输入,而PMd包含了选择的最小足够表示.
- 一个多区域的RNN开发了类似于DLPFC和PMd的表示.
- 类似DLPFC的区域正交选择信息,并通过选择性连接优先传播下游.
结论:
- 跨多个区域的皮层计算产生了决策所需的最小足够的表示.
- 区域间相关信息的优先传播是一个关键机制.
- 这种多领域战略优化了用于认知任务的信息处理.
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