Electroencephalographic changes associated with subjective under- and overestimation of sleep duration

Abstract

Feeling awake although sleep recordings indicate clear-cut sleep sometimes occurs in good sleepers and to an extreme degree in patients with so-called paradoxical insomnia. It is unknown what underlies sleep misperception, as standard polysomnographic (PSG) parameters are often normal in these cases. Here we asked whether regional changes in brain activity could account for the mismatch between objective and subjective total sleep times (TST). To set cutoffs and define the norm, we first evaluated sleep perception in a population-based sample, consisting of 2,092 individuals who underwent a full PSG at home and estimated TST the next day. We then compared participants with a low mismatch (normoestimators, n = 1,147, ±0.5 SD of mean) with those who severely underestimated (n = 52, <2.5th percentile) or overestimated TST (n = 53, >97.5th percentile). Compared with normoestimators, underestimators displayed higher electroencephalographic (EEG) activation (beta/delta power ratio) in both rapid eye movement (REM) and non-rapid eye movement (NREM) sleep, while overestimators showed lower EEG activation (significant in REM sleep). To spatially map these changes, we performed a second experiment, in which 24 healthy subjects and 10 insomnia patients underwent high-density sleep EEG recordings. Similarly to underestimators, patients displayed increased EEG activation during NREM sleep, which we localized to central-posterior brain areas. Our results indicate that a relative shift from low- to high-frequency spectral power in central-posterior brain regions, not readily apparent in conventional PSG parameters, is associated with underestimation of sleep duration. This challenges the concept of sleep misperception, and suggests that instead of misperceiving sleep, insomnia patients may correctly perceive subtle shifts toward wake-like brain activity.

Brain mechanisms of insomnia: new perspectives on causes and consequences

“…The limitations of classic polysomnography does not allow it to adequately capture more fine graded neuronal processes and has likely resulted in inappropriate conclusions about discrepancy between objective and subjective assessments in insomnia patients. Big data, artificial intelligence tools and high-density EEG are now beginning to find multivariate and spatio-spectral signatures of objective sleep and wake disturbance that have remained hidden in classic polysomnographic measures of sleep (10,53,88,89,229,329,432,433).…”

Altered thalamic connectivity in insomnia disorder during wakefulness and sleep

“…Sleep misperception is a concept used to describe the discrepancy between subjective sleep experience measured by sleep questionnaires and objective parameters measured by polysomnography (PSG) (Feige et al, 2013). As a ubiquitous symptom of insomnia disorder (Harvey & Tang, 2012), sleep misperception has been found to be correlated with the number of cyclic alternating patterns and higher frequency activities in EEG during nonrapid eye movement (NREM) sleep (Krystal, Edinger, Wohlgemuth, & Marsh, 2002; Lecci et al, 2020; Parrino, Milioli, De Paolis, Grassi, & Terzano, 2009). It has been suggested that sleep misperception may be due to enhanced information processing related to hyperarousal (Riemann et al, 2010).…”

Cortico-autonomic local arousals and heightened somatosensory arousability during NREM sleep of mice in neuropathic pain

“…Patients with insomnia show such imbalances over widespread brain regions that include sensorimotor areas (Lecci et al, 2020). Furthermore, higher power in the beta frequencies has been related to the patients remaining hypervigilant or excessively ruminating at sleep onset (Perlis et al, 2001a), preventing the deactivation of cortical processes required for the loss of consciousness.…”

“…Standard polysomnography describes sleep as a sequence of discrete states and distinguishes between non-rapid-eye-movement sleep (NREMS) and rapid-eye-movement sleep (REMS), with the former further subdivided into transitional (N1), light (N2) and deep (N3) stages (Iber et al, 2007). Many reports on human patients find little change in the absolute or relative times spent in these stages and/or their principal spectral characteristics (Salin-Pascual et al, 1992;Perlis et al, 2001b;Buysse et al, 2008;Wei et al, 2017;Feige et al, 2018;Christensen et al, 2019;Lecci et al, 2020). Instead, cortical activity patterns are abnormally enriched in the alpha (8-12 Hz) (Krystal et al, 2002;Riedner et al, 2016), beta (18-30 Hz) (Krystal et al, 2002;Spiegelhalder et al, 2012;Maes et al, 2014;Riedner et al, 2016;Lecci et al, 2020) and/or low-gamma bands (30-45 Hz) (Perlis et al, 2001b;Lecci et al, 2020), in one or more NREMS stages and/or in REMS (Spiegelhalder et al, 2012;Christensen et al, 2019;Lecci et al, 2020) and/or in restricted brain areas (St-Jean et al, 2012;Riedner et al, 2016;Lecci et al, 2020).…”

“…We calculated an "activation index" (AI), defined by the ratio between the summed spectral power in the beta and low-gamma bands and the delta band power, to quantify alterations in spectral balance between high-and low-frequency power components, similarly to what has been done previously in studies on insomnia disorders (Lecci et al, 2020). The AI is a measure for the degree of EEG desynchronization and increases when NREMS moves closer to wakefulness.…”