Functional neuroimaging insights into the physiology of human sleep

Abstract

Functional brain imaging has been used in humans to noninvasively investigate the neural mechanisms underlying the generation of sleep stages. On the one hand, REM sleep has been associated with the activation of the pons, thalamus, limbic areas, and temporo-occipital cortices, and the deactivation of prefrontal areas, in line with theories of REM sleep generation and dreaming properties. On the other hand, during non-REM (NREM) sleep, decreases in brain activity have been consistently found in the brainstem, thalamus, and in several cortical areas including the medial prefrontal cortex (MPFC), in agreement with a homeostatic need for brain energy recovery. Benefiting from a better temporal resolution, more recent studies have characterized the brain activations related to phasic events within specific sleep stages. In particular, they have demonstrated that NREM sleep oscillations (spindles and slow waves) are indeed associated with increases in brain activity in specific subcortical and cortical areas involved in the generation or modulation of these waves. These data highlight that, even during NREM sleep, brain activity is increased, yet regionally specific and transient. Besides refining the understanding of sleep mechanisms, functional brain imaging has also advanced the description of the functional properties of sleep. For instance, it has been shown that the sleeping brain is still able to process external information and even detect the pertinence of its content. The relationship between sleep and memory has also been refined using neuroimaging, demonstrating post-learning reactivation during sleep, as well as the reorganization of memory representation on the systems level, sometimes with long-lasting effects on subsequent memory performance. Further imaging studies should focus on clarifying the role of specific sleep patterns for the processing of external stimuli, as well as the consolidation of freshly encoded information during sleep.

Keywords: EEG; PET; REM sleep; Sleep; delta wave; fMRI; memory; neuroimaging; non-REM sleep; sensory processing; slow oscillation; spindle.

Figures

Figure 1

Neural correlates of NREM sleep oscillations as demonstrated by PET A. PET correlates of spindles. The upper panel shows a (stage 2) NREM sleep epoch depicting a typical spindle on scalp EEG recording. Brain activity is averaged over the duration of PET acquisition (˜1 min) within the NREM sleep epoch and correlated with sigma activity calculated for the corresponding period. The middle panel shows that the only significant correlation is located in the thalamus bilaterally. Images sections are centered on the global maximum located in the dorsal thalamus (x = −6 mm, y = −22 mm, z = 14 mm). Displayed voxels are significant at P 2) during NREM sleep. It shows that the correlation is negative: brain activity decreases in the thalamus when sigma power increases. Each black dot represents one scan (gray dot = standard error). B. PET correlates of slow waves. The upper panel shows a (stage 4) NREM sleep epoch depicting typical slow waves on scalp EEG recording. Brain activity is averaged over the duration of PET acquisition (˜1 min) within the NREM sleep epoch and correlated with delta activity calculated for the corresponding period. The middle panel shows the significant correlations located in vMPFC, anterior cingulate cortex, basal forebrain, striatum, insula, and precuneus. Images sections are centered on the global maximum located in vMPFC (x = −2 mm, y = 48 mm, z = 8 mm). Displayed voxels are significant at P 2) during NREM sleep. It shows that the correlation is negative: brain activity decreases in vMPFC when delta power increases. Each circle/cross represents one scan: green circles are stage 2 scans; red crosses are stages 3–4 scans. The blue line is the linear regression. Adapted from Neuroimage; Vol. 28(1); Dang-Vu TT, Desseilles M, Laureys S, Degueldre C, Perrin F, Philips C, Maquet P, and Peigneux P. “Cerebral correlates of delta waves during non-REM sleep revisited”; pp 14–21; Copyright 2005, with permission from Elsevier.

Figure 2

Neural correlates of NREM sleep oscillations as evidenced by fMRI A. fMRI correlates of spindles. The upper panel shows a (stage 2) NREM sleep epoch depicting a typical spindle on scalp EEG recording. Brain activity is estimated for each detected spindle compared to the baseline brain activity of NREM sleep. The lower left panels shows the significant brain responses associated with spindles (P

Figure 3

Classical experimental designs adopted in neuroimaging when studying sleep-dependent memory consolidation A. Studies truly examining reactivations or reorganization (connectivity change) after learning. Note that these reactivations sometimes are related directly to behavioral outcome post-sleep. The marked study (*) is a special case, as no linear relationship between reactivation and memory change is shown; yet “reactivation by odor cuing” during SWS enhanced declarative memory performance. B. Studies manipulating sleep by either (partial) sleep deprivation or by comparing “early SWS-rich” with “late REM-rich” sleep. In order to circumvent fatigue effects in sleep deprived subjects, 1–2 nights of recovery sleep are usually scheduled before retesting. Note that not all studies finding modified brain activity after sleep (vs. sleep deprivation) find related behavioral change. C. A new set of studies requires subjects to learn before (remote items), and after sleep close to retrieval (recent items). This design allows to focus on the neuronal correlates (brain activity and connectivity) of “fresh” vs. already (due to sleep) consolidated memory traces. Note that in the marked study (*) old and new (motor) sequences were tested post-sleep without prior training on the new sequences. A whole set of studies is relying on EEG during sleep and focuses on sleep architecture and sleep mechanism changes after learning. Specifically, studies of this kind can reveal overnight changes in performance relative to (i) the amount of sleep stages (S2, SWS, or REM sleep), or (ii) even in relation to specific sleep mechanisms such as sleep spindles, individual slow waves, the number of rapid eye movements, or theta oscillations.