An electroencephalographic fingerprint of human sleep

Abstract

Homeostatic and circadian processes are basic mechanisms of human sleep which challenge the common knowledge of large individual variations in sleep need or differences in circadian types. However, since sleep research has mostly focused on group measures, an approach which emphasizes the similarities between subjects, the biological foundations of the individual differences in normal sleep are still poorly understood. In the present work, we assessed individual differences in a range of EEG frequencies including sigma activity during non-REM sleep (8.0–15.5 Hz range) in a group of 10 subjects who had participated in a slow-wave sleep (SWS) deprivation study. We showed that, like a “fingerprint”, a particular topographic distribution of the electroencephalogram (EEG) power along the antero-posterior cortical axis distinguishes each individual during non-REM sleep. This individual EEG-trait is substantially invariant across six consecutive nights characterized by large experimentally induced changes of sleep architecture. One possible hypothesis is that these EEG invariances can be related to individual differences in genetically determined functional brain anatomy, rather than to sleep-dependent mechanisms.

Introduction

Notwithstanding the increasing use of neuroimaging techniques, electroencephalography is still the most universally employed technique in human sleep research. Quantitative analyses of sleep EEG by spectral analysis have led to the development of the 2-process model of sleep regulation (Borbely, 1982). According to this model, the timing of sleep and wakefulness is regulated by the interaction of a homeostatic, sleep–wake-dependent Process S and a circadian, sleep–wake-independent Process C (Borbely, 1982). Well-established evidence on the homeostatic facet of sleep regulation suggests that slow-wave activity (EEG power in the 0.75–4.5 Hz range) depends on the duration of previous sleep and wakefulness, representing a marker of non-REM sleep intensity (Borbely and Achermann, 2000). This feature of sleep has been consistently shown in a broad range of species, including humans, cats, mice, rats, and squirrels (Tobler, 1995). Manipulations of sleep intensity by means, for example, of sleep deprivation, lead to clear homeostatic recovery processes (Borbely and Achermann, 2000) which do not involve the whole cerebral cortex in the same manner. Indeed, these recovery processes are local in nature, as shown in dolphins (Oleksenko et al., 1992), birds (Rattenborg et al., 1999), mice (Huber et al., 2000), rats (Vyazovskiy et al., 2002), and humans (Ferrara et al., 2002, Finelli et al., 2001a). The most striking regional phenomenon of the human sleep EEG is the hyperfrontality of low-frequency EEG activity during baseline and post deprivation non-REM sleep, probably due to a high “recovery need” of the frontal heteromodal association areas of the cortex (Cajochen et al., 1999, Ferrara et al., 2002, Finelli et al., 2001a).

Homeostatic, circadian and regional EEG changes are basic mechanisms of human sleep that seem to challenge the common notion of large individual variations in sleep need or differences in circadian types. These differences are often ignored or considered as experimental noise, to be actively suppressed through the use of statistical methods that emphasize group rather than individual results. Nevertheless, the recent extensive use of blood flow imaging techniques in the neurosciences made it clear that, for example, a large variability in the detected hemodynamic responses across sessions of the same subject and across subjects is actually present (Aguirre et al., 1998, Handwerker et al., 2004, Wei et al., 2004). The importance of taking such individual differences into account has recently been pointed out also in the sleep research field, at least as regards individual variability in the susceptibility to sleep deprivation (Bell-McGinty et al., 2004, Leproult et al., 2003, Van Dongen et al., 2004). However, although inter-individual differences in neurobehavioral deficits from sleep loss constitute a differential vulnerability trait, its neurobiological correlates have yet to be discovered. The elucidation of some biological mechanisms for the behavioral trait of morningness–eveningness (Duffy et al., 2001), for individual differences in the circadian pacemaker program (i.e., long and short sleepers) (Aeschbach et al., 1996, Aeschbach et al., 2001, Aeschbach et al., 2003) and for the variability of sleep duration in the general population (Aeschbach et al., 2003), also encourages a neurophysiological approach to individual differences in sleep characteristics.

Sleep spindles seem to be a natural candidate for this analysis: they are one of the hallmarks of non-REM sleep, one of the few transient EEG events which are unique to sleep, and it has been reported that their incidence shows great inter-individual differences in humans (Werth et al., 1997). As far as their electrophysiological mechanisms are concerned, sleep spindles depend on variations in membrane potentials of thalamocortical neurons that oscillate in the frequency range of spindles at an intermediate level of hyperpolarization (Steriade, 1999). At the macroscopic EEG level, spindle frequency in humans encompasses the 12–14 Hz range (sigma activity¹), although many studies bulk these standard bounds of sigma band (Rechtschaffen and Kales, 1968), including frequency bins traditionally considered to be part of the alpha band (for a review, De Gennaro and Ferrara, 2003). Furthermore, large genotype differences between the relative contribution of power in the sigma range have been found in the non-REM sleep of inbred mice (Franken et al., 1998).

Given the large individual differences in spindle frequency activity in human subjects (Werth et al., 1997) and since it has been suggested that such differences are invariant within individuals and could be related to the individual traits of functional anatomy rather than to sleep-dependent mechanisms (Finelli et al., 2001b), in the present work, we decided to specifically analyze both group and individual differences in a range of EEG frequencies including sigma activity during non-REM sleep [8.0–15.5 Hz range (0.25-Hz resolution)] in a group of 10 subjects who had previously participated in a slow-wave sleep (SWS) deprivation study (Ferrara et al., 1999). The six consecutive nights of the experimental paradigm were characterized by profound differences in quantitative EEG measures, as assessed by spectral analysis of the EEG (Ferrara et al., 2002). Whether or not spindle frequency activity is an individual EEG-trait, we hypothesize that its invariance within individuals will be maintained also during nights with a largely different sleep architecture.