Suppr超能文献

在自由活动的大鼠中,慢γ节律和快γ节律的γ频率与奔跑速度之间的关系有所不同。

The relationship between gamma frequency and running speed differs for slow and fast gamma rhythms in freely behaving rats.

作者信息

Zheng Chenguang, Bieri Kevin Wood, Trettel Sean Gregory, Colgin Laura Lee

机构信息

Center for Learning and Memory, University of Texas, Austin, Texas.

Institute for Neuroscience, University of Texas, Austin, Texas.

出版信息

Hippocampus. 2015 Aug;25(8):924-38. doi: 10.1002/hipo.22415. Epub 2015 Jan 20.

Abstract

In hippocampal area CA1 of rats, the frequency of gamma activity has been shown to increase with running speed (Ahmed and Mehta, 2012). This finding suggests that different gamma frequencies simply allow for different timings of transitions across cell assemblies at varying running speeds, rather than serving unique functions. However, accumulating evidence supports the conclusion that slow (∼25-55 Hz) and fast (∼60-100 Hz) gamma are distinct network states with different functions. If slow and fast gamma constitute distinct network states, then it is possible that slow and fast gamma frequencies are differentially affected by running speed. In this study, we tested this hypothesis and found that slow and fast gamma frequencies change differently as a function of running speed in hippocampal areas CA1 and CA3, and in the superficial layers of the medial entorhinal cortex (MEC). Fast gamma frequencies increased with increasing running speed in all three areas. Slow gamma frequencies changed significantly less across different speeds. Furthermore, at high running speeds, CA3 firing rates were low, and MEC firing rates were high, suggesting that CA1 transitions from CA3 inputs to MEC inputs as running speed increases. These results support the hypothesis that slow and fast gamma reflect functionally distinct states in the hippocampal network, with fast gamma driven by MEC at high running speeds and slow gamma driven by CA3 at low running speeds.

摘要

在大鼠海马体CA1区,γ活动频率已被证明会随着奔跑速度增加(艾哈迈德和梅塔,2012年)。这一发现表明,不同的γ频率只是在不同奔跑速度下允许在细胞集合之间进行不同时间的转换,而非具有独特功能。然而,越来越多的证据支持这样的结论:慢γ(约25 - 55赫兹)和快γ(约60 - 100赫兹)是具有不同功能的不同网络状态。如果慢γ和快γ构成不同的网络状态,那么慢γ和快γ频率可能会受到奔跑速度的不同影响。在本研究中,我们检验了这一假设,发现慢γ和快γ频率在海马体CA1区和CA3区以及内侧内嗅皮层(MEC)浅层中,随奔跑速度的变化方式不同。在所有这三个区域中,快γ频率都随着奔跑速度增加而升高。慢γ频率在不同速度下的变化显著较小。此外,在高奔跑速度时,CA3的放电率较低,而MEC的放电率较高,这表明随着奔跑速度增加,CA1从接收CA3输入转变为接收MEC输入。这些结果支持了以下假设:慢γ和快γ反映了海马体网络中功能上不同的状态,在高奔跑速度下快γ由MEC驱动,在低奔跑速度下慢γ由CA3驱动。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/137b/4499477/070fff896754/nihms695933f1.jpg

相似文献

引用本文的文献

1
Theta Oscillons in Behaving Rats.行为大鼠中的θ振荡子
J Neurosci. 2025 May 14;45(20):e0164242025. doi: 10.1523/JNEUROSCI.0164-24.2025.
2
Theta oscillons in behaving rats.行为大鼠中的θ振荡子
bioRxiv. 2024 Apr 25:2024.04.21.590487. doi: 10.1101/2024.04.21.590487.
10
Theta-gamma phase amplitude coupling in a hippocampal CA1 microcircuit.海马 CA1 微电路中的θ-γ 相位幅度耦合。
PLoS Comput Biol. 2023 Mar 23;19(3):e1010942. doi: 10.1371/journal.pcbi.1010942. eCollection 2023 Mar.

本文引用的文献

1
Speed cells in the medial entorhinal cortex.中脑内侧缰核中的快细胞。
Nature. 2015 Jul 23;523(7561):419-24. doi: 10.1038/nature14622. Epub 2015 Jul 15.
3
Vestibular control of entorhinal cortex activity in spatial navigation.空间导航中内嗅皮层活动的前庭控制
Front Integr Neurosci. 2014 Jun 5;8:38. doi: 10.3389/fnint.2014.00038. eCollection 2014.
10

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验