Suppr超能文献

跨脑状态的大规模时空活动模式分布的变化。

Variation in the distribution of large-scale spatiotemporal patterns of activity across brain states.

作者信息

Meyer-Baese Lisa, Anumba Nmachi, Bolt T, Daley L, LaGrow T J, Zhang Xiaodi, Xu Nan, Pan Wen-Ju, Schumacher E H, Keilholz Shella

机构信息

Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, GA, United States.

Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, United States.

出版信息

Front Syst Neurosci. 2024 Aug 2;18:1425491. doi: 10.3389/fnsys.2024.1425491. eCollection 2024.

Abstract

A few large-scale spatiotemporal patterns of brain activity (quasiperiodic patterns or QPPs) account for most of the spatial structure observed in resting state functional magnetic resonance imaging (rs-fMRI). The QPPs capture well-known features such as the evolution of the global signal and the alternating dominance of the default mode and task positive networks. These widespread patterns of activity have plausible ties to neuromodulatory input that mediates changes in nonlocalized processes, including arousal and attention. To determine whether QPPs exhibit variations across brain conditions, the relative magnitude and distribution of the three strongest QPPs were examined in two scenarios. First, in data from the Human Connectome Project, the relative incidence and magnitude of the QPPs was examined over the course of the scan, under the hypothesis that increasing drowsiness would shift the expression of the QPPs over time. Second, using rs-fMRI in rats obtained with a novel approach that minimizes noise, the relative incidence and magnitude of the QPPs was examined under three different anesthetic conditions expected to create distinct types of brain activity. The results indicate that both the distribution of QPPs and their magnitude changes with brain state, evidence of the sensitivity of these large-scale patterns to widespread changes linked to alterations in brain conditions.

摘要

少数大规模的脑活动时空模式(准周期性模式或QPPs)构成了静息态功能磁共振成像(rs-fMRI)中观察到的大部分空间结构。QPPs捕捉到了一些众所周知的特征,比如全局信号的演变以及默认模式网络和任务积极网络的交替主导。这些广泛的活动模式与神经调节输入有着合理的联系,神经调节输入介导了包括觉醒和注意力在内的非局部过程的变化。为了确定QPPs在不同脑状态下是否存在差异,研究人员在两种情况下检查了三种最强QPPs的相对大小和分布。首先,在人类连接组计划的数据中,假设困倦感增加会使QPPs的表达随时间发生变化,在此假设下,研究人员在扫描过程中检查了QPPs的相对发生率和大小。其次,研究人员使用一种能将噪声降至最低的新方法获得大鼠的rs-fMRI数据,在三种不同的麻醉条件下检查了QPPs的相对发生率和大小,这三种麻醉条件预计会产生不同类型的脑活动。结果表明,QPPs的分布及其大小均随脑状态而变化,这证明了这些大规模模式对与脑状态改变相关的广泛变化具有敏感性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c006/11327057/5878db912221/fnsys-18-1425491-g001.jpg

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

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验