文献检索文档翻译深度研究
Suppr Zotero 插件Zotero 插件
邀请有礼套餐&价格历史记录

新学期,新优惠

限时优惠:9月1日-9月22日

30天高级会员仅需29元

1天体验卡首发特惠仅需5.99元

了解详情
不再提醒
插件&应用
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
高级版
套餐订阅购买积分包
AI 工具
文献检索文档翻译深度研究
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2025

皮质群体活动在快速和超慢时间尺度上的独特结构。

Distinct Structure of Cortical Population Activity on Fast and Infraslow Timescales.

机构信息

Centre for Systems Neuroscience and Department of Neuroscience, Psychology and Behaviour, University of Leicester, Leicester, UK.

Institute of Neurology, University College London, London, UK.

出版信息

Cereb Cortex. 2019 May 1;29(5):2196-2210. doi: 10.1093/cercor/bhz023.


DOI:10.1093/cercor/bhz023
PMID:30796825
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6458908/
Abstract

Cortical activity is organized across multiple spatial and temporal scales. Most research on the dynamics of neuronal spiking is concerned with timescales of 1 ms-1 s, and little is known about spiking dynamics on timescales of tens of seconds and minutes. Here, we used frequency domain analyses to study the structure of individual neurons' spiking activity and its coupling to local population rate and to arousal level across 0.01-100 Hz frequency range. In mouse medial prefrontal cortex, the spiking dynamics of individual neurons could be quantitatively captured by a combination of interspike interval and firing rate power spectrum distributions. The relative strength of coherence with local population often differed across timescales: a neuron strongly coupled to population rate on fast timescales could be weakly coupled on slow timescales, and vice versa. On slow but not fast timescales, a substantial proportion of neurons showed firing anticorrelated with the population. Infraslow firing rate changes were largely determined by arousal rather than by local factors, which could explain the timescale dependence of individual neurons' population coupling strength. These observations demonstrate how neurons simultaneously partake in fast local dynamics, and slow brain-wide dynamics, extending our understanding of infraslow cortical activity beyond the mesoscale resolution of fMRI.

摘要

皮质活动在多个时空尺度上组织起来。大多数关于神经元尖峰放电动力学的研究都集中在 1 毫秒到 1 秒的时间尺度上,而对于数十秒到数分钟的尖峰放电动力学知之甚少。在这里,我们使用频域分析来研究个体神经元放电活动的结构及其在 0.01-100 Hz 频率范围内与局部群体率和觉醒水平的耦合。在小鼠内侧前额叶皮层中,单个神经元的放电动力学可以通过尖峰间隔和放电率功率谱分布的组合来定量捕获。与局部群体的相干性相对强度经常因时间尺度而异:在快速时间尺度上与群体率强耦合的神经元在缓慢时间尺度上可能弱耦合,反之亦然。在缓慢但不是快速的时间尺度上,相当一部分神经元的放电与群体呈反相关。亚慢的放电率变化主要由觉醒决定,而不是由局部因素决定,这可以解释个体神经元群体耦合强度的时间尺度依赖性。这些观察结果表明,神经元如何同时参与快速的局部动力学和缓慢的全脑动力学,从而扩展了我们对亚慢皮质活动的理解,超越了 fMRI 的中尺度分辨率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b631/6458908/ff0f56010e77/bhz023f06.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b631/6458908/2a490fd10c89/bhz023f01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b631/6458908/9881c34d0b56/bhz023f02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b631/6458908/9948af623798/bhz023f03.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b631/6458908/9d612a3d6a24/bhz023f04.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b631/6458908/355edae1e8ef/bhz023f05.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b631/6458908/ff0f56010e77/bhz023f06.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b631/6458908/2a490fd10c89/bhz023f01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b631/6458908/9881c34d0b56/bhz023f02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b631/6458908/9948af623798/bhz023f03.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b631/6458908/9d612a3d6a24/bhz023f04.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b631/6458908/355edae1e8ef/bhz023f05.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b631/6458908/ff0f56010e77/bhz023f06.jpg

相似文献

[1]
Distinct Structure of Cortical Population Activity on Fast and Infraslow Timescales.

Cereb Cortex. 2019-5-1

[2]
Spiking activity in the visual thalamus is coupled to pupil dynamics across temporal scales.

PLoS Biol. 2024-5

[3]
Overexpression of Dyrk1A, a Down Syndrome Candidate, Decreases Excitability and Impairs Gamma Oscillations in the Prefrontal Cortex.

J Neurosci. 2016-3-30

[4]
Single-neuron firing cascades underlie global spontaneous brain events.

Proc Natl Acad Sci U S A. 2021-11-23

[5]
Distinct Temporal Coordination of Spontaneous Population Activity between Basal Forebrain and Auditory Cortex.

Front Neural Circuits. 2017-9-14

[6]
Behavior-dependent short-term assembly dynamics in the medial prefrontal cortex.

Nat Neurosci. 2008-7

[7]
Distributed representations of temporal stimulus associations across regular-firing and fast-spiking neurons in rat medial prefrontal cortex.

J Neurophysiol. 2020-1-1

[8]
Large-scale changes in cortical dynamics triggered by repetitive somatosensory electrical stimulation.

J Neuroeng Rehabil. 2019-5-24

[9]
Infraslow LFP correlates to resting-state fMRI BOLD signals.

Neuroimage. 2013-2-26

[10]
Sequentially switching cell assemblies in random inhibitory networks of spiking neurons in the striatum.

J Neurosci. 2010-4-28

引用本文的文献

[1]
Global and local origins of trial-to-trial spike count variability in visual cortex.

bioRxiv. 2025-8-12

[2]
Isolating single cycles of neural oscillations in population spiking.

PLoS Comput Biol. 2025-6-4

[3]
Desynchronization Increased in the Synchronized State: Subsets of Neocortical Neurons Become Strongly Anticorrelated during NonREM Sleep.

eNeuro. 2025-3-19

[4]
Hemodynamic cortical ripples through cyclicity analysis.

Netw Neurosci. 2024-12-10

[5]
Spatial and temporal correlations in neural networks with structured connectivity.

Phys Rev Res. 2023

[6]
Spiking activity in the visual thalamus is coupled to pupil dynamics across temporal scales.

PLoS Biol. 2024-5

[7]
What the eyes, confidence, and partner's identity can tell about change of mind.

Neurosci Conscious. 2024-5-7

[8]
Low-dimensional criticality embedded in high-dimensional awake brain dynamics.

Sci Adv. 2024-4-26

[9]
Arousal as a universal embedding for spatiotemporal brain dynamics.

bioRxiv. 2025-2-18

[10]
Fast-local and slow-global neural ensembles in the mouse brain.

Netw Neurosci. 2023-6-30

本文引用的文献

[1]
Spontaneous behaviors drive multidimensional, brainwide activity.

Science. 2019-4-18

[2]
Beyond Trial-Based Paradigms: Continuous Behavior, Ongoing Neural Activity, and Natural Stimuli.

J Neurosci. 2018-7-23

[3]
Origin of slow spontaneous resting-state neuronal fluctuations in brain networks.

Proc Natl Acad Sci U S A. 2018-6-8

[4]
Spontaneous Infra-slow Brain Activity Has Unique Spatiotemporal Dynamics and Laminar Structure.

Neuron. 2018-3-29

[5]
The Basal Forebrain Regulates Global Resting-State fMRI Fluctuations.

Neuron. 2018-2-1

[6]
Weak correlations between hemodynamic signals and ongoing neural activity during the resting state.

Nat Neurosci. 2017-12

[7]
Fully integrated silicon probes for high-density recording of neural activity.

Nature. 2017-11-8

[8]
Entrainment of Arteriole Vasomotor Fluctuations by Neural Activity Is a Basis of Blood-Oxygenation-Level-Dependent "Resting-State" Connectivity.

Neuron. 2017-11-15

[9]
Visual experience sculpts whole-cortex spontaneous infraslow activity patterns through an Arc-dependent mechanism.

Proc Natl Acad Sci U S A. 2017-10-30

[10]
Random Recurrent Networks Near Criticality Capture the Broadband Power Distribution of Human ECoG Dynamics.

Cereb Cortex. 2018-10-1

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

推荐工具

医学文档翻译智能文献检索