Reentrant Information Flow in Electrophysiological Rat Default Mode Network

Abstract

Functional MRI (fMRI) studies have demonstrated that the rodent brain shows a default mode network (DMN) activity similar to that in humans, offering a potential preclinical model both for physiological and pathophysiological studies. However, the neuronal mechanism underlying rodent DMN remains poorly understood. Here, we used electrophysiological data to analyze the power spectrum and estimate the directed phase transfer entropy (dPTE) within rat DMN across three vigilance states: wakeful rest (WR), slow-wave sleep (SWS), and rapid-eye-movement sleep (REMS). We observed decreased gamma powers during SWS compared with WR in most of the DMN regions. Increased gamma powers were found in prelimbic cortex, cingulate cortex, and hippocampus during REMS compared with WR, whereas retrosplenial cortex showed a reverse trend. These changed gamma powers are in line with the local metabolic variation of homologous brain regions in humans. In the analysis of directional interactions, we observed well-organized anterior-to-posterior patterns of information flow in the delta band, while opposite patterns of posterior-to-anterior flow were found in the theta band. These frequency-specific opposite patterns were only observed in WR and REMS. Additionally, most of the information senders in the delta band were also the receivers in the theta band, and vice versa. Our results provide electrophysiological evidence that rat DMN is similar to its human counterpart, and there is a frequency-dependent reentry loop of anterior-posterior information flow within rat DMN, which may offer a mechanism for functional integration, supporting conscious awareness.

Altered Coactive Micropattern Connectivity in the Default-Mode Network during the Sleep-Wake Cycle

“…The total dataset was separated into three different conscious states, including the awake resting state (AWAKE), the slow-wave sleep state (SWS), and the rapid eye movement sleep state (REM). The data for each state were selected by several experts, and the rules for selection have been summarized in our previous publication based on the LFP, EMG, and simultaneous videos [31]. For each rat, 30 segments were chosen for different states, and each segment lasted 10 s. In total, we obtained approximately 300 s of LFPs for each rat in each conscious state.…”

Optogenetic stimulation of anterior insular cortex neurons in male rats reveals causal mechanisms underlying suppression of the default mode network by the salience network

“…Here, we leverage optogenetic-fMRI technology 13,14,28,[33][34][35][36][37][38][39][40][41][42] and recent advances in computational modeling of brain-circuit dynamics 43 to characterize the causal role of the AI in dynamic functional interactions between putative nodes of the rat SN and DMN including the AI, Cg, PrL, and multiple subdivisions of the RSC. We selectively applied feedforward optogenetic stimulation to Chronosexpressing neurons in the AI of experimental rats (hereafter referred to as Chronos rats) and enhanced yellow fluorescent protein-expressing neurons in the AI of control rats (EYFP rats) (Fig.…”

Dynamic Configuration of Coactive Micropatterns in the Default Mode Network during Wakefulness and Sleep

“…The dataset used in the current study was selected from the last 24 h of the total recording and was separated into three stages, including the resting (AWAKE), slow wave sleep (SWS) and rapid eye movement (REM) sleep stages. The rules for selecting each stage were based on LFP, EMG and videos, which have been summarized in our previous publications (Jing et al, 2017). Briefly, the scoring of the awake and sleep stages were performed by several experts.…”