Elsevier

Cortex

Volume 142, September 2021, Pages 94-103
Cortex

Exploratory Report
fMRI lag structure during waking up from early sleep stages

https://doi.org/10.1016/j.cortex.2021.06.005Get rights and content

Abstract

The brain mechanisms by which we transition from sleep to a conscious state remain largely unknown in humans, partly because of methodological challenges. Here we study a pre-existing dataset of waking up participants originally designed for a study of dreaming (Horikawa, Tamaki, Miyawaki, & Kamitani, 2013) and suggest that suddenly awakening from early sleep stages results from a two-stage process that involves a sequence of cortical and subcortical brain activity. First, subcortical and sensorimotor structures seem to be recruited before most cortical regions, followed by fast, ignition-like whole-brain activation—with frontal regions engaging a little after the rest of the brain. Second, a comparably slower and possibly mirror-reversed stage might take place, with cortical regions activating before subcortical structures and the cerebellum. This pattern of activation points to a key role of subcortical structures for the initiation and maintenance of conscious states.

Introduction

Understanding how the human brain generates and reversibly loses consciousness remains one of the biggest challenges in modern neuroscience. Every day, we transition between states of consciousness, including the sleep–wake cycle (Chow et al., 2013; Siclari et al., 2017; Tagliazucchi et al., 2013; Tagliazucchi & Laufs, 2014; Tagliazucchi & van Someren, 2017). While some transitions between these states have been extensively studied, others remain almost unexplored, mostly due to methodological challenges.

The most widely studied transition is sleep-related loss of consciousness (Ogilvie, 2001; Saper, Fuller, Pedersen, Lu, & Scammell, 2010; Stevner et al., 2019)—a process typically occurring over seconds to minutes in a series of well-known sequential stages, each involving specific behavioral (Bareham, Manly, Pustovaya, Scott, & Bekinschtein, 2014; Goupil & Bekinschtein, 2012), and neural (Comsa, Bekinschtein, & Chennu, 2019; Jagannathan et al., 2018; Stevner et al., 2019; Wu et al., 2012) patterns. Though synchronized in vigilance states, at sleep onset, the thalamus and the cortex become functionally de-coupled as the former deactivates first (Magnin et al., 2010). In fact, the amount of cortico-thalamic connectivity indexes an individual's level of arousal (Barttfeld et al., 2015; Schroter et al., 2012). Substantial research has also addressed the transition from rapid eye movement (REM) sleep to non-REM (NREM), consisting in a ≤20-s state (Gottesmann, 1973) with large-amplitude sleep spindles in the electroencephalographic (EEG) signal. During a night's sleep, alternations between NREM and REM states occur every 60–90 min (Carley & Farabi, 2016; Ibanez, Silva, & Cauli, 2018; Saper et al., 2010).

In marked contrast to falling asleep, the process of waking up remains relatively less explored. Single-unit recording in mice (Takahashi, Kayama, Lin, & Sakai, 2010) showed that locus coeruleus and centromedial thalamus neurons—part of the wake-promoting subcortical networks (Saper et al., 2010)—phasically promote fast NREM–wake transitions. In humans, research on this process has focused on the states before and—especially—after the actual waking up event (i.e., wakefulness vs sleep/sedation resting states). The first minutes after awakening are typically marked by reduced vigilance, confusion, and diminished performance, a state termed sleep inertia (Marzano, Ferrara, Moroni, & De Gennaro, 2011; Trotti, 2017; Tsai et al., 2014; Vallat, Meunier, Nicolas, & Ruby, 2019). PET signal comparisons (Balkin et al., 2002) showed that cerebral blood flow during sleep inertia is most rapidly re-established in the brainstem and the thalamus, followed by anterior cortical regions, highlighting their role in the re-establishment of conscious awareness. Sleep inertia is also characterized by a loss of negative correlation between task-positive (dorsal attention, salience, sensorimotor) and task-negative (default mode) networks (Marzano et al., 2011). A similar scenario is observed after deep sedation (Barttfeld et al., 2015; Nir et al., 2019), as the thalamus becomes disconnected from the frontal cortex, and more connected to the temporal and occipital cortices. Also, the process of regaining consciousness is mediated by discrete ordered states, leading to full reestablishment (Hudson, Calderon, Pfaff, & Proekt, 2014).

The above mentioned studies focused on slow consciousness recovery. However, waking up can occur much faster: awakening is the only transition that can be triggered by an external stimulus, as explained by theories of global brain networks (Deco et al., 2019). This makes sense from an evolutionary perspective, since the capacity to quickly reconnect with the external world and respond to environmental stimuli should be a positively selected trait. This sudden transition remains unexplored. Here, we zoom into the actual and sudden waking up from early sleep stages due to external stimulation. To this end, we leveraged a unique, previously reported fMRI dataset (Horikawa & Kamitani, 2017; Horikawa, Tamaki, Miyawaki, & Kamitani, 2013) comprising three participants who were repeatedly awoken from early sleep stages by auditory stimulation (Fig. 1). Immediately after waking up, participants were asked to report their dreams –since the original study was design to decode neural correlates of dreaming- and remained inside the scanner until falling asleep again. The process was repeated several times per session. Polysomnography was simultaneously performed. This unique experimental design offers the opportunity of exploring the brain correlates of sudden awakenings from early sleeping stages.

Section snippets

Dataset

We used a dataset from previous fMRI sleep research (Horikawa & Kamitani, 2017; Horikawa et al., 2013). Potential participants underwent an interview about their sleeping and lifestyle habits, and three healthy candidates (all males, 27–39 years) were enrolled. They had no physical or psychiatric diseases, were receiving no medical treatment, were nonsmokers and nondrinkers, and had good sleeping habits. After giving written consent, they completed a two-day adaptation protocol in a mock

Analysis

Firstly, we wanted to identify the brain regions involved in the process of waking up from early sleep stages. To this end, we conducted a general linear model using SPM software. We modeled the waking up process as a discrete event at the time participants were woken up. We defined as event regressors all waking up events (event duration of 2 sec). We contrasted events of waking-up from sleep after name-calling to events of not waking-up following control sounds. In the original experiment the

Discussion

We explored the process of waking up from early sleep stages due to stimulation and found evidence suggesting that it is a rapid event involving both cortical and subcortical structures. Subcortical and sensorimotor regions seem to be the first regions responding to external stimulation, followed by most of the cortex. After this initial burst of activity, the pattern reverses; cortices activate before subcortical and sensorimotor structures. It should be taken into consideration, however, that

Hypothesis generation

The cortical-subcortical pattern of activation we observe should be interpreted in light of current theories of consciousness; especially those emphasizing the role of the arousal circuits. Theories of consciousness differ on whether the induction of consciousness is mainly governed by the thalamo-cortical arousal circuits—the thalamic “off-switch” (Barttfeld et al., 2015; Schiff, 2008; Schroter et al., 2012)—or by the ignition of a fronto-parietal cortices connection (Alkire, Hudetz, & Tononi,

Author contributions

TH organized the data. SA and PB had the idea for the analysis. SA, AR ACM, JS and PB performed the analysis. All authors wrote the paper.

Pre-registration status

No part of the study procedures or analysis was pre-registered prior to the research being conducted.

Open practices

The study in this article earned an Open Data badge for transparent practices. Code and data are available at https://github.com/alcaides/lag-structure-sleep.

Declaration of competing interest

There are no competing interests.

Acknowledgments

YK and TH were supported by a JSPS KAKENHI Grant number JP15H05710 and JP20H05705.

SA, AR and PB were supported by Agencia Nacional de Promoción Científica y Tecnológica (Argentina)—Préstamo BID PICT (Grant #2015-0753) PICT 2015 and PICT 2018. AI is partially supported by grants from CONICET; ANID/FONDECYT Regular (1210195 and 1210176); FONCYT-PICT 2017-1820; ANID/FONDAP/15150012; Takeda CW2680521; Sistema General de Regalías (BPIN2018000100059), Universidad del Valle (CI 5316); Alzheimer's

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