在网格单元中群体活动的形拓
Richard J Gardner1, Erik Hermansen2, Marius Pachitariu3
1Kavli Institute for Systems Neuroscience and Centre for Neural Computation, Norwegian University of Science and Technology, Trondheim, Norway. richard.gardner@ntnu.no.
Nature
|January 13, 2022
概括
大脑中的电网细胞使用六角射击模式绘制了我们的位置. 新的研究显示它们的网络活动形成了一个圆柱体,
科学领域:
- 神经科学
- 计算神经科学
背景情况:
- 中间内皮层 (MEC) 对于空间导航至关重要.
- 在MEC内部的网格细胞表现出六边形的燃烧模式,并形成全中心位置的群体代码.
- 由于观察到的环境和行为状态不变性,持续吸引网络 (CAN) 被假设为基底电网细胞活动.
研究的目的:
- 研究电网电池的网络动态及其与连续吸引器网络 (CAN) 模型的关系.
- 澄清电网细胞网络如何处理环境输入和维护空间表示.
主要方法:
- 几百个电网单元的同时录制.
- 对神经活动的拓数据分析.
- 在不同环境和行为状态 (清醒和睡眠) 中分析网格细胞活动.
主要成果:
- 一个模块内的网格单元的联合活动被证明位于 toroidal 集群上,与二维 CAN 相一致.
- 形管上的位置与动物在环境中的位置直接相对应.
- 个别的网格细胞在体上的特定位置表现出优势活动.
- 在不同环境和清醒和睡眠之间保持这种形状.
结论:
- 这项研究提供了强有力的证据,证明了电网单元中的连续吸引器网络动态.
- 形多元体可视化提供了对网格细胞网络功能的人口层面的理解.
- 这些发现支持内在的CAN模型,而不是用于网格细胞网络组织和空间编码的前模型.
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