Dynamic Configuration of Coactive Micropatterns in the Default Mode Network during Wakefulness and Sleep
The default mode network (DMN) is a prominent intrinsic network that is observable in many mammalian brains. However, few studies have investigated the temporal dynamics of this network based on direct physiological recordings. Herein, we addressed this issue by characterizing the dynamics of local field potentials (LFPs) from the rat DMN during wakefulness and sleep with an exploratory analysis. We constructed a novel coactive micropattern (CAMP) algorithm to evaluate the configurations of rat DMN dynamics and further revealed the relationship between DMN dynamics with different wakefulness and alertness levels. From the gamma activity (40-80 Hz) in the DMN across wakefulness and sleep, three spatially stable CAMPs were detected: a common low-activity level micropattern (cDMN), an anterior high-activity level micropattern (aDMN) and a posterior high-activity level micropattern (pDMN). A dynamic balance across CAMPs emerged during wakefulness and was disrupted in sleep stages. In the slow-wave sleep (SWS) stage, cDMN became the primary activity pattern, whereas aDMN and pDMN were the major activity patterns in the rapid eye movement sleep (REM) stage. Additionally, further investigation revealed phasic relationships between CAMPs and the up-down states of the slow DMN activity in the SWS stage. Our study revealed that the dynamic configurations of CAMPs were highly associated with different stages of wakefulness and provided a potential three-state model to describe the DMN dynamics for wakefulness and alertness. Impact StatementIn the current study, a novel coactive micropattern method (CAMP) was developed to elucidate fast DMN dynamics during wakefulness and sleep. Our findings demonstrated that the dynamic configurations of DMN activity are specific to different wakefulness stages and provided a three-state DMN CAMP model to depict wakefulness levels, thus revealing a potentially new neurophysiological representation of alertness levels. This work could elucidate the DMN dynamics underlying different stages of wakefulness and have important implications for the theoretical understanding of the neural mechanism of wakefulness and alertness.
- Downloaded 298 times
- Download rankings, all-time:
- Site-wide: 95,988
- In bioinformatics: 8,343
- Year to date:
- Site-wide: 62,588
- Since beginning of last month:
- Site-wide: 96,393
Downloads over time
Distribution of downloads per paper, site-wide
- 27 Nov 2020: The website and API now include results pulled from medRxiv as well as bioRxiv.
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!