M. Gorgoni

Recalling and Forgetting Dreams: Theta and Alpha Oscillations during Sleep Predict Subsequent Dream Recall

Under the assumption that dream recall is a peculiar form of declarative memory, we have hypothesized that (1) the encoding of dream contents during sleep should share some electrophysiological mechanisms with the encoding of episodic memories of the awake brain and (2) recalling a dream(s) after awakening from non-rapid eye movement (NREM) and rapid eye movement (REM) sleep should be associated with different brain oscillations. Here, we report that cortical brain oscillations of human sleep are predictive of successful dream recall. In particular, after morning awakening from REM sleep, a higher frontal 5–7 Hz (theta) activity was associated with successful dream recall. This finding mirrors the increase in frontal theta activity during successful encoding of episodic memories in wakefulness. Moreover, in keeping with the different EEG background, a different predictive relationship was found after awakening from stage 2 NREM sleep. Specifically, a lower 8–12 Hz (alpha) oscillatory activity of the right temporal area was associated with a successful dream recall. These findings provide the first evidence of univocal cortical electroencephalographic correlates of dream recall, suggesting that the neurophysiological mechanisms underlying the encoding and recall of episodic memories may remain the same across different states of consciousness.

How we fall asleep: regional and temporal differences in electroencephalographic synchronization at sleep onset

OBJECTIVES We hypothesized that the brain shows specific and predictable patterns of spatial and temporal differences during sleep onset (SO) reflecting a temporal uncoupling of electrical activity between different cortical regions and a dissociated wakelike and sleeplike electrocortical activity in different cortical areas. METHODS We analyzed full-scalp electroencephalographic (EEG) recordings of 40 healthy subjects to investigate spatial and temporal changes of EEG activity across the wake-sleep transition. We quantified EEG sleep recordings by a fast Fourier transform (FFT) algorithm and by a better oscillation (BOSC) detection method to the EEG signals, which measured oscillatory activity within a signal containing a nonrhythmic portion. RESULTS The most representative spatial change at SO is the frontalization of slow-wave activity (SWA), while the θ activity, which mostly shares a similar temporal and spatial pattern with SWA, exhibits a temporo-occipital diffusion. The time course of these oscillations confirms that the changes of the dominant waves coexist with topographic changes. The waking occipital prevalence of α oscillations is progressively replaced by an occipital prevalence of θ oscillations. On the other hand, more anterior areas show a wide synchronization pattern mainly expressed by slow waves just below 4 Hz and by spindle oscillations. CONCLUSIONS The whole pattern of results confirms that the centrofrontal areas showed an earlier synchronization (i.e., they fall asleep first). This finding implies a coexistence of wakelike and sleeplike electrical activity during sleep in different cortical areas. It also implies that the process of progressive brain disconnection from the external world as we fall asleep does not necessarily affect primary and higher-order cortices at the same time.

Is Sleep Essential for Neural Plasticity in Humans, and How Does It Affect Motor and Cognitive Recovery?

There is a general consensus that sleep is strictly linked to memory, learning, and, in general, to the mechanisms of neural plasticity, and that this link may directly affect recovery processes. In fact, a coherent pattern of empirical findings points to beneficial effect of sleep on learning and plastic processes, and changes in synaptic plasticity during wakefulness induce coherent modifications in EEG slow wave cortical topography during subsequent sleep. However, the specific nature of the relation between sleep and synaptic plasticity is not clear yet. We reported findings in line with two models conflicting with respect to the underlying mechanisms, that is, the “synaptic homeostasis hypothesis” and the “consolidation” hypothesis, and some recent results that may reconcile them. Independently from the specific mechanisms involved, sleep loss is associated with detrimental effects on plastic processes at a molecular and electrophysiological level. Finally, we reviewed growing evidence supporting the notion that plasticity-dependent recovery could be improved managing sleep quality, while monitoring EEG during sleep may help to explain how specific rehabilitative paradigms work. We conclude that a better understanding of the sleep-plasticity link could be crucial from a rehabilitative point of view.

EEG oscillations during sleep and dream recall: state- or trait-like individual differences?

Dreaming represents a peculiar form of cognitive activity during sleep. On the basis of the well-known relationship between sleep and memory, there has been a growing interest in the predictive role of human brain activity during sleep on dream recall. Neuroimaging studies indicate that rapid eye movement (REM) sleep is characterized by limbic activation and prefrontal cortex deactivation. This pattern could explain the presence of emotional contents in dream reports. Furthermore, the morphoanatomical measures of amygdala and hippocampus predict some features of dream contents (bizarreness, vividness, and emotional load). More relevant for a general view of dreaming mechanisms, empirical data from neuropsychological and electroencephalographic (EEG) studies support the hypothesis that there is a sort of continuity between the neurophysiological mechanisms of encoding and retrieval of episodic memories across sleep and wakefulness. A notable overlap between the electrophysiological mechanisms underlying emotional memory formation and some peculiar EEG features of REM sleep has been suggested. In particular, theta (5–8 Hz) EEG oscillations on frontal regions in the pre-awakening sleep are predictive of dream recall, which parallels the predictive relation during wakefulness between theta activity and successful retrieval of episodic memory. Although some observations support an interpretation more in terms of an intraindividual than interindividual mechanism, the existing empirical evidence still precludes from definitely disentangling if this relation is explained by state- or trait-like differences.

Topographic electroencephalogram changes associated with psychomotor vigilance task performance after sleep deprivation

OBJECTIVES The psychomotor vigilance task (PVT) is a widely used method for the assessment of vigilance after sleep deprivation (SDEP). However, the neural basis of PVT performance during SDEP has not been fully understood. In particular, no studies have investigated the possible relation between EEG topographical changes after sleep loss and PVT performance. The aim of the present study is to assess the EEG topographic correlates of PVT performance after SDEP. METHODS During 40 h of SDEP, 16 healthy male subjects were evaluated in four sessions performed at the same time (11:00 a.m. and 11:00 p.m.) of the first and second day with: (a) subjective sleepiness recordings by means of the Karolinska Sleepiness Scale (KSS); (b) EEG recordings (5 min eyes-open condition); and (c) PVT. RESULTS SDEP induced a slowing of PVT reaction times (RTs), higher level of subjective sleepiness and an increase of delta, theta, alpha and beta 1 EEG activity. Only slowest PVT RTs were influenced by circadian factors, with longer RTs in the morning. Both fastest PVT RTs and KSS scores were positively correlated with post-SDEP changes in EEG theta activity, mainly in centro-posterior areas, but not with other EEG frequencies. KSS scores and PVT measures were also positively correlated. CONCLUSIONS These findings suggest that SDEP differently affects PVT variables, and that an increase in theta activity may be the principal EEG basis of the post-SDEP slowing of fastest PVT RTs. Similar neural mechanisms seem to underlie both performance deterioration to PVT and the increase of subjective sleepiness.

Parietal Fast Sleep Spindle Density Decrease in Alzheimer’s Disease and Amnesic Mild Cognitive Impairment

Several studies have identified two types of sleep spindles: fast (13–15 Hz) centroparietal and slow (11–13 Hz) frontal spindles. Alterations in spindle activity have been observed in Alzheimers disease (AD) and Mild Cognitive Impairment (MCI). Only few studies have separately assessed fast and slow spindles in these patients showing a reduction of fast spindle count, but the possible local specificity of this phenomenon and its relation to cognitive decline severity are not clear. Moreover, fast and slow spindle density have never been assessed in AD/MCI. We have assessed fast and slow spindles in 15 AD patients, 15 amnesic MCI patients, and 15 healthy elderly controls (HC). Participants underwent baseline polysomnographic recording (19 cortical derivations). Spindles during nonrapid eye movements sleep were automatically detected, and spindle densities of the three groups were compared in the derivations where fast and slow spindles exhibited their maximum expression (parietal and frontal, resp.). AD and MCI patients showed a significant parietal fast spindle density decrease, positively correlated with Minimental State Examination scores. Our results suggest that AD-related changes in spindle density are specific for frequency and location, are related to cognitive decline severity, and may have an early onset in the pathology development.

The Fall of Sleep K-Complex in Alzheimer Disease

Although a slowing of electroencephalographic (EEG) activity during wakefulness and –to some extent- sleep of Alzheimer disease (AD) patients (i.e., increased slow-frequency activity) was documented, recent findings in healthy elderly show a decreased 0.6–1 Hz slow wave activity (SWA) during NREM, which was associated to β-amyloid deposition and impaired hippocampal memory consolidation. We hypothesize that the apparent contradiction may be explained by the partial overlap between 0.6–1 Hz EEG activity and K-Complex (KC). According to this view, we studied both frontal KCs and SWA in 20 AD patients and 20 healthy age-matched controls (HC) during nightly sleep, under the hypothesis that KCs better discriminate patients from healthy elderly than ≤1 Hz SWA. A drastic decrease of KC density during stage 2 NREM was found in AD compared to HC. Patients show more than 40% reduction of the KC density, allowing a correct classification of 80%. On the other hand, ≤1 Hz SWA of AD patients is slightly (not significantly) higher in most cortical areas compared to HC. Although no significant changes of ≤1 Hz SWA are detectable over frontal areas in AD, KC density decreases over the same location, and its decrease is related to the cognitive decline.

Predicting Dream Recall: EEG Activation During NREM Sleep or Shared Mechanisms with Wakefulness?

The common knowledge of a uniqueness of REM sleep as a privileged scenario of dreaming still persists, although consolidated empirical evidence shows that the assumption that dreaming is just an epiphenomenon of REM sleep is no longer tenable. However, the brain mechanisms underlying dream generation and its encoding in memory during NREM sleep are still mostly unknown. In fact, only few studies have investigated on the mechanisms of dream phenomenology related to NREM sleep. For this reason, our study is specifically aimed to elucidate the electrophysiological (EEG) correlates of dream recall (DR) upon NREM sleep awakenings. Under the assumption that EEG activity predicts the presence/absence of DR also during NREM sleep, we have investigated whether DR from stage 2 NREM sleep shares similar brain mechanisms to those involved in the encoding of episodic memory during wakefulness, or it depends on the specific electrophysiological milieu of the sleep period along the desynchronized/synchronized EEG continuum. We collected DR from a multiple nap protocol in a within-subjects design. We found that DR is predicted by an extensive reduction of delta activity during the last segment of sleep, encompassing left frontal and temporo-parietal areas. The results could represent an update on the mechanisms underlying the sleep mentation during NREM sleep. In particular, they support the hypothesis that an increased cortical EEG activation is a prerequisite for DR, and they are not necessarily in conflict with the hypothesis of common wake-sleep mechanisms. We also confirmed that EEG correlates of DR depend on a state-like relationship.

Electrical stimulation of the frontal cortex enhances slow-frequency EEG activity and sleepiness

Our aim was to enhance the spontaneous slow-frequency EEG activity during the resting state using oscillating transcranial direct currents (tDCS) with a stimulation frequency that resembles the spontaneous oscillations of sleep onset. Accordingly, in this preliminary study, we assessed EEG after-effects of a frontal oscillatory tDCS with different frequency (0.8 vs. 5 Hz) and polarity (anodal, cathodal, and sham). Two single-blind experiments compared the after effects on the resting EEG of oscillatory tDCS [Exp. 1=0.8 Hz, 10 subjects (26.2 ± 2.5 years); Exp. 2=5 Hz, 10 subjects (27.4 ± 2.4 years)] by manipulating its polarity. EEG signals recorded (28 scalp derivations) before and after stimulation [slow oscillations (0.5-1 Hz), delta (1-4 Hz), theta (5-7 Hz), alpha (8-12 Hz), beta 1 (13-15 Hz) and beta 2 (16-24 Hz)] were compared between conditions as a function of polarity (anodal vs. cathodal vs. sham) and frequency of stimulation (0.8 vs. 5 Hz). We found a significant relative enhancement of the delta activity after the anodal tDCS at 5 Hz compared to that at 0.8 Hz. This increase, even though not reaching the statistical significance compared to sham, is concomitant to a significant increase of subjective sleepiness, as assessed by a visual analog scale. These two phenomena are linearly related with a regional specificity, correlations being restricted to cortical areas perifocal to the stimulation site. We have shown that a frontal oscillating anodal tDCS at 5 Hz results in an effective change of both subjective sleepiness and spontaneous slow-frequency EEG activity. These changes are critically associated to both stimulation polarity (anodal) and frequency (5 Hz). However, evidence of frequency-dependence seems more unequivocal than evidence of polarity-dependence.

EEG topography during sleep inertia upon awakening after a period of increased homeostatic sleep pressure

OBJECTIVE Behavioral and physiological indexes of high sleep inertia (SI) characterize the awakening from recovery (REC) sleep after prolonged wakefulness, but the associated electroencephalogram (EEG) topography has never been investigated. Here, we compare the EEG topography following the awakening from baseline (BSL) and REC sleep. METHODS We have recorded the EEG waking activity of 26 healthy subjects immediately after the awakening from BSL sleep and from REC sleep following 40 h of prolonged wakefulness. In both BSL and REC conditions, 12 subjects were awakened from stage 2 sleep, and 14 subjects from rapid eye movement (REM) sleep. The full-scalp waking EEG (eyes closed) was recorded after all awakenings. RESULTS Subjects awakened from REC sleep showed a reduction of fronto-central alpha and beta-1 activities, while no significant effects of the sleep stage of awakening have been observed. Positive correlations between pre- and post-awakening EEG modifications following REC sleep have been found in the posterior and lateral cortices in the frequency ranges from theta to beta-2 and (only for REM awakenings) extending to the fronto-central regions in the beta-1 band, and in the midline central and parietal derivations for the alpha and delta bands, respectively. CONCLUSIONS These findings suggest that the higher SI after REC sleep may be due to the fronto-central decrease of alpha and beta-1 activity and to the persistence of the sleep EEG features after awakening in the posterior, lateral, and fronto-central cortices, without influences of the sleep stage of awakening.