Antidepressant effects of selective slow wave sleep deprivation in major depression: a high-density EEG investigation

Regional Patterns of Elevated Alpha and High-Frequency Electroencephalographic Activity during Nonrapid Eye Movement Sleep in Chronic Insomnia: A Pilot Study

STUDY OBJECTIVES

To examine nonrapid eye movement (NREM) sleep in insomnia using high-density electroencephalography (EEG).

METHODS

All-night sleep recordings with 256 channel high-density EEG were analyzed for 8 insomnia subjects (5 females) and 8 sex and age-matched controls without sleep complaints. Spectral analyses were conducted using unpaired t-tests and topographical differences between groups were assessed using statistical non-parametric mapping. Five minute segments of deep NREM sleep were further analyzed using sLORETA cortical source imaging.

RESULTS

The initial topographic analysis of all-night NREM sleep EEG revealed that insomnia subjects had more high-frequency EEG activity (> 16 Hz) compared to good sleeping controls and that the difference between groups was widespread across the scalp. In addition, the analysis also showed that there was a more circumscribed difference in theta (4-8 Hz) and alpha (8-12 Hz) power bands between groups. When deep NREM sleep (N3) was examined separately, the high-frequency difference between groups diminished, whereas the higher regional alpha activity in insomnia subjects persisted. Source imaging analysis demonstrated that sensory and sensorimotor cortical areas consistently exhibited elevated levels of alpha activity during deep NREM sleep in insomnia subjects relative to good sleeping controls.

CONCLUSIONS

These results suggest that even during the deepest stage of sleep, sensory and sensorimotor areas in insomnia subjects may still be relatively active compared to control subjects and to the rest of the sleeping brain.

The two-process model of sleep regulation: a reappraisal

In the last three decades the two-process model of sleep regulation has served as a major conceptual framework in sleep research. It has been applied widely in studies on fatigue and performance and to dissect individual differences in sleep regulation. The model posits that a homeostatic process (Process S) interacts with a process controlled by the circadian pacemaker (Process C), with time-courses derived from physiological and behavioural variables. The model simulates successfully the timing and intensity of sleep in diverse experimental protocols. Electrophysiological recordings from the suprachiasmatic nuclei (SCN) suggest that S and C interact continuously. Oscillators outside the SCN that are linked to energy metabolism are evident in SCN-lesioned arrhythmic animals subjected to restricted feeding or methamphetamine administration, as well as in human subjects during internal desynchronization. In intact animals these peripheral oscillators may dissociate from the central pacemaker rhythm. A sleep/fast and wake/feed phase segregate antagonistic anabolic and catabolic metabolic processes in peripheral tissues. A deficiency of Process S was proposed to account for both depressive sleep disturbances and the antidepressant effect of sleep deprivation. The model supported the development of novel non-pharmacological treatment paradigms in psychiatry, based on manipulating circadian phase, sleep and light exposure. In conclusion, the model remains conceptually useful for promoting the integration of sleep and circadian rhythm research. Sleep appears to have not only a short-term, use-dependent function; it also serves to enforce rest and fasting, thereby supporting the optimization of metabolic processes at the appropriate phase of the 24-h cycle.

Sleep Disturbances in Mood Disorders

The article provides an overview of common and differentiating self-reported and objective sleep disturbances seen in mood-disordered populations. The importance of considering sleep disturbances in the context of mood disorders is emphasized, because a large body of evidence supports the notion that sleep disturbances are a risk factor for onset, exacerbation, and relapse of mood disorders. In addition, potential mechanisms for sleep disturbance in depression, other primary sleep disorders that often occur with mood disorders, effects of antidepressant and mood-stabilizing drugs on sleep, and the adjunctive effect of treating sleep in patients with mood disorders are discussed.

Synaptic plasticity model of therapeutic sleep deprivation in major depression

Therapeutic sleep deprivation (SD) is a rapid acting treatment for major depressive disorder (MDD). Within hours, SD leads to a dramatic decrease in depressive symptoms in 50-60% of patients with MDD. Scientifically, therapeutic SD presents a unique paradigm to study the neurobiology of MDD. Yet, up to now, the neurobiological basis of the antidepressant effect, which is most likely different from today's first-line treatments, is not sufficiently understood. This article puts the idea forward that sleep/wake-dependent shifts in synaptic plasticity, i.e., the neural basis of adaptive network function and behavior, represent a critical mechanism of therapeutic SD in MDD. Particularly, this article centers on two major hypotheses of MDD and sleep, the synaptic plasticity hypothesis of MDD and the synaptic homeostasis hypothesis of sleep-wake regulation, and on how they can be integrated into a novel synaptic plasticity model of therapeutic SD in MDD. As a major component, the model proposes that therapeutic SD, by homeostatically enhancing cortical synaptic strength, shifts the initially deficient inducibility of associative synaptic long-term potentiation (LTP) in patients with MDD in a more favorable window of associative plasticity. Research on the molecular effects of SD in animals and humans, including observations in the neurotrophic, adenosinergic, monoaminergic, and glutamatergic system, provides some support for the hypothesis of associative synaptic plasticity facilitation after therapeutic SD in MDD. The model proposes a novel framework for a mechanism of action of therapeutic SD that can be further tested in humans based on non-invasive indices and in animals based on direct studies of synaptic plasticity. Further determining the mechanisms of action of SD might contribute to the development of novel fast acting treatments for MDD, one of the major health problems worldwide.

Increased frontal sleep slow wave activity in adolescents with major depression

Sleep slow wave activity (SWA), the major electrophysiological characteristic of deep sleep, mirrors both cortical restructuring and functioning. The incidence of Major Depressive Disorder (MDD) substantially rises during the vulnerable developmental phase of adolescence, where essential cortical restructuring is taking place. The goal of this study was to assess characteristics of SWA topography in adolescents with MDD, in order to assess abnormalities in both cortical restructuring and functioning on a local level. All night high-density EEG was recorded in 15 patients meeting DSM-5 criteria for MDD and 15 sex- and age-matched healthy controls. The actual symptom severity was assessed using the Children's Depression Rating Scale-Revised (CDRS-R). Topographical power maps were calculated based on the average SWA of the first non-rapid eye movement (NREM) sleep episode. Depressed adolescents exhibited significantly more SWA in a cluster of frontal electrodes compared to controls. SWA over frontal brain regions correlated positively with the CDRS-R subscore "morbid thoughts". Self-reported sleep latency was significantly higher in depressed adolescents compared to controls whereas sleep architecture did not differ between the groups. Higher frontal SWA in depressed adolescents may represent a promising biomarker tracing cortical regions of intense use and/or restructuring.

Astrocytic adenosine: from synapses to psychiatric disorders

Although it is considered to be the most complex organ in the body, the brain can be broadly classified into two major types of cells, neuronal cells and glial cells. Glia is a general term that encompasses multiple types of non-neuronal cells that function to maintain homeostasis, form myelin, and provide support and protection for neurons. Astrocytes, a major class of glial cell, have historically been viewed as passive support cells, but recently it has been discovered that astrocytes participate in signalling activities both with the vasculature and with neurons at the synapse. These cells have been shown to release D-serine, TNF-α, glutamate, atrial natriuretic peptide (ANP) and ATP among other signalling molecules. ATP and its metabolites are well established as important signalling molecules, and astrocytes represent a major source of ATP release in the nervous system. Novel molecular and genetic tools have recently shown that astrocytic release of ATP and other signalling molecules has a major impact on synaptic transmission. Via actions at the synapse, astrocytes have now been shown to regulate complex network signalling in the whole organism with impacts on respiration and the sleep-wake cycle. In addition, new roles for astrocytes are being uncovered in psychiatric disorders, and astrocyte signalling mechanisms represents an attractive target for novel therapeutic agents.

Feature Selection and Classification of Electroencephalographic Signals: An Artificial Neural Network and Genetic Algorithm Based Approach

Feature selection is an important step in many pattern recognition systems aiming to overcome the so-called curse of dimensionality. In this study, an optimized classification method was tested in 147 patients with major depressive disorder (MDD) treated with repetitive transcranial magnetic stimulation (rTMS). The performance of the combination of a genetic algorithm (GA) and a back-propagation (BP) neural network (BPNN) was evaluated using 6-channel pre-rTMS electroencephalographic (EEG) patterns of theta and delta frequency bands. The GA was first used to eliminate the redundant and less discriminant features to maximize classification performance. The BPNN was then applied to test the performance of the feature subset. Finally, classification performance using the subset was evaluated using 6-fold cross-validation. Although the slow bands of the frontal electrodes are widely used to collect EEG data for patients with MDD and provide quite satisfactory classification results, the outcomes of the proposed approach indicate noticeably increased overall accuracy of 89.12% and an area under the receiver operating characteristic (ROC) curve (AUC) of 0.904 using the reduced feature set.

Slow-wave disruption enhances the accessibility of positive memory traces

The purpose of this study was to explore the effects of slow-wave disruption on positive and negative word recognition in a sample of healthy control participants and those with major depressive disorder. Prior to sleep, participants learned a set of emotional and neutral words during an encoding task by responding whether or not the word described them. Following baseline sleep, participants underwent one night of selective slow-wave disruption by auditory stimuli. Accuracy and reaction time to a recognition word set, including both positive and negative words, was assessed in the morning. Repeated-measures ANOVA revealed a significant interaction between word valence and condition, with positive words recognized significantly faster than negative words after disruption, in only healthy control participants. There were no significant results in those with major depressive disorder, or with regard to accuracy. These results may add to the increasing body of literature suggesting a hedonic bias to positive stimuli following sleep disruption.

Reduction in delta activity predicted improved negative affect in Major Depressive Disorder

While prior research has demonstrated a paradoxical antidepressant effect of slow-wave disruption (SWD), the specific dimensions of depression affected is still unclear. The current study aimed to extend this research by utilizing a dimensional approach in examining the antidepressant effects of SWD. Of particular interest is the affective dimension, as negative affect in depression is arguably the most salient characteristic of depression. This sample included 16 individuals with depression (10 female) recruited from the community. Participants slept in the lab for three nights (adaptation, baseline night, and SWD) with polysomnography, and completed measures of negative affect and depression severity the following morning. Results show that reduction in delta power was linearly associated with improved negative affect. Comparison of individual change scores revealed that half of the individuals showed improved negative affect, which is comparable to the reported 40-60% antidepressant response rate to sleep deprivation. Results suggest that vulnerability in the sleep homeostatic system may be a contributing individual differences factor in response to slow-wave disruption in depression.

Sleep Disturbances in Depression

Major depressive disorder is frequently accompanied by sleep disturbances such as insomnia or hypersomnia and polysomnographic sleep findings of increased rapid-eye-movement sleep and decreased slow wave sleep. For many patients, insomnia persists even after mood symptoms have been adequately treated. These patients have poorer outcomes than patients without sleep problems. These outcomes suggest that overlapping neural mechanisms regulate sleep and mood. Treatment of these patients can incorporate sedating antidepressants, nonbenzodiazepine γ-aminobutyric acid agonists, and cognitive behavioral therapy. Sleep restriction has been found to improve mood in depressed patients; however, the benefits typically disappear after recovery sleep.

Putative role of monoamines in the antidepressant-like mechanism induced by striatal MT2 blockade

It has been observed that the secretion pattern of melatonin is modified in Parkinson's disease (PD). Hence, it is hypothesized that dysregulations of melatonin MT2 receptors may be involved in the installation of depression in PD patients. Together with recent evidence based on the use of the intranigral rotenone model of PD, have led to the hypothesis that modulating the striatal MT2 receptor could provide a more comprehensive understanding of the antidepressant properties triggered. To further investigate this issue, male Wistar rats were infused with intranigral rotenone (12μg/μL) and seven days later subjected to a rapid eye movement sleep deprivation (REMSD) for 24h. After, we injected within the striatum the MT2 selective agonist, 8-M-PDOT (10μg/μL), the MT2 selective antagonist, 4-P-PDOT (5μg/μL) or vehicle. Subsequently, they were tested in the forced swimming test and were allowed to perform the sleep rebound (REB). Then, the rats were re-tested, and the striatum, hippocampus and substantia nigra pars compacta (SNpc) were collected for neurochemical purposes. Results indicated substantial antidepressant effects promoted by the blockade of striatal MT2 receptors that were potentiated by REMSD. MT2 activation increased DA levels in the striatum and hippocampus, while MT2 blockade increase DA in the SNpc. 4-P-PDOT treatment of the rotenone REMSD group generated a decrement in 5-HT levels within the striatum, hippocampus and SNpc. However, increased 5-HT turnover was observed among these structures. Therefore, we demonstrated the neurochemical antidepressant effect induced by striatal MT2 blockage associated with REMSD in the rotenone model of PD.

Sleep architecture and cognitive changes in olanzapine-treated patients with depression: a double blind randomized placebo controlled trial

BACKGROUND

Disturbance in sleep quality is a symptom of Major Depressive Disorder (MDD) and Bipolar Disorder (BD) and thus improving quality of sleep is an important aspect of successful treatment. Here, a prospective, double-blind, randomized, placebo-controlled study examined the effect of olanzapine (an atypical antipsychotic) augmentation therapy on sleep architecture, specifically slow wave sleep (SWS), in the treatment of depression. The effect of olanzapine augmentation therapy on other features of sleep (e.g., sleep continuity) and depression (e.g., illness severity and cognitive function) were also determined.

METHODS

Patients currently experiencing a major depressive episode and who were on a stable medication were included. Sleep architecture was measured by overnight ambulatory polysomnography. Illness severity was determined using the Montgomery-Asberg Depression Rating Scale (MADRS). Cognitive function was examined using Cambridge Neuropsychological Test Automated Battery (CANTAB): Spatial Working Memory (SWM), Spatial Span (SSP), and Reaction Time (RTI) tasks. Polysomnographs, clinical measures and cognitive tests were administered at baseline, after 2-4 days of treatment and after 28-31 days of treatment. Twenty-five patients participated in the study (N = 10, N = 15 for placebo and olanzapine treated groups respectively).

RESULTS

The primary objective of the study was to assess the objective (polysomnographic) changes in sleep quality, defined as changes in SWS, following olanzapine treatment for depression. Latency to but not duration of SWS was found to significantly differ between olanzapine- and placebo-treated participants (Hedge's g: 0.97, 0.13 respectively). A significant improvement in olanzapine-treated participants over placebo-treated participants was observed in secondary outcome measures, including sleep efficiency, total sleep time, and sleep latency. Secondary objectives assessed the subjective changes in sleep quality parameters and correlated them with measures of illness severity and changes in cognition. MADRS scores were significantly improved in olanzapine-treated participants over time but not more than placebo treatment. There was no significant difference between olanzapine- and placebo-treated participants in SWM, SSP or RTI tasks.

CONCLUSIONS

Olanzapine augmentation treatment generally did not improve SWS but did improve sleep continuity and depression. Olanzapine may be one of few medications that improve sleep continuity, thus directly targeting symptoms of depression.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT00520507.

Basic sleep and circadian science as building blocks for behavioral interventions: a translational approach for mood disorders

Sleep and circadian functioning has been of particular interest to researchers focused on improving treatments for psychiatric illness. The goal of the present paper is to highlight the exciting research that utilizes basic sleep and circadian science as building blocks for intervention in the mood disorders. The reviewed evidence suggests that the sleep and circadian systems are a) disrupted in the mood disorders and linked to symptoms, b) open systems that can be modified, c) the focus of interventions which have been developed to effectively treat sleep disturbance within mood disorders, and d) intimately linked with mood, such that improvements in sleep are associated with improvements in mood. Although significant positive treatment effects are evident, more research is needed to fill the gap in our basic understanding of the relationship between sleep and mood.

High-density electroencephalography as an innovative tool to explore sleep physiology and sleep related disorders

High density EEG represents a promising tool to achieve new insights regarding sleep physiology and pathology. It combines the advantages of an EEG technique as an optimal temporal resolution with the spatial resolution of the neuroimaging. So far its application in sleep research contributed to better characterize some of the peculiar microstructural figures of sleep such as spindles and K-complexes, and to understand the fundamental relationships between sleep and synaptic plasticity, learning and consciousness. Its application is not limited to neurophysiology, being recently also applied to study some sleep related psychiatric and neurological disorders such as depression, schizophrenia, attention-deficit hyperactivity disorder, and stroke. adding some interesting new pieces in the pathophysiological puzzle of these diseases. Due to its non-invasive, repetitive and reliable tempo-spatial resolution it is reasonable that the field of application of this tool will be soon enlarged to other areas of neuroscience. The present review aims to offer a complete overview regarding the use of high density EEG over the last decade in sleep research and sleep medicine, including its possible future perspective.

Comparison of feature and classifier algorithms for online automatic sleep staging based on a single EEG signal

Automatic sleep staging on an online basis has recently emerged as a research topic motivated by fundamental sleep research. The aim of this paper is to find optimal signal processing methods and machine learning algorithms to achieve online sleep staging on the basis of a single EEG signal. The classification performance obtained using six different EEG signals and various signal processing feature sets is compared using the kappa statistic which has very recently become popular in sleep staging research. A variable duration of the EEG segment (or epoch) to decide on the sleep stage is also analyzed. Spectral-domain, time-domain, linear, and nonlinear features are compared in terms of performance and two types of machine learning approaches (random forests and support vector machines) are assessed. We have determined that frontal EEG signals, with spectral linear features, epoch durations between 18 and 30 seconds, and a random forest classifier lead to optimal classification performance while ensuring real-time online operation.

Sleep Organisation in Depression and Schizophrenia: Index of Endogenous Periodicity of Sleep as a State Marker [Retracted]

Background: Sleep disorders are frequent symptoms described in psychiatric patients with major depression or schizophrenia. These patients also exhibit changes in the sleep architecture measured by polysomnography (PSG) during sleep. The aim of the present study was to identify potential biomarkers that would facilitate the diagnosis based on polysomnography (PSG) measurements.Subjects and Methods: 30 patients with schizophrenia, 30 patients with major depression and 30 healthy control subjects were investigated in the present study. The mean age in the group with schizophrenia was 36.73 (SD 6.43), in the group of patients with depression 40.77 (SD 7.66), in the healthy controls group 34.40 (SD 5.70). The gender distribution was as follows: 18 male, 12 female in the group with schizophrenia; in the group of patients with depression 11 male, 19 female; in the control group 16 male and 14 female. All subjects underwent polysomnography (PSG) for a minimum time of 8 hours according to the criteria of Rechtschaffen & Kales (1968). The following polysomnographic (PSG) parameters were analyzed: sleep latency (SL), total sleep time (TST), waking time after sleep onset (WTASO), number of awakenings (NAW), slow wave sleep (SWS), rapid eye movement sleep (REM), rapid eye movement sleep latency (REML), first REM period (REM 1), and first NREM period (NREM 1). We tested the potential of multiple sleep variables to predict diagnosis in different groups by using linear discriminate analysis (LDA).Results: There were significant differences in polysomnography (PSG) variables between healthy control subjects and psychiatric patients (total sleep time, sleep latency, number of awakenings, time of awakening after sleep onset, REM 1 latency, REM 1 and index of endogenous periodicity). Importantly, LDA was able to predict the correct diagnosis in 88% of all cases.Conclusions: The presented analysis showed commonalities and differences in polysomnography (PSG) changes in patients with major depressive disorder and in patients with schizophrenia. Our results underline the potential of polysomnography (PSG) measurements to facilitate diagnostic processes.

Developmental changes in sleep and their relationships to psychiatric illnesses

PURPOSE OF REVIEW

Sleep undergoes major changes during development. Its relationship to the complex process of maturation in health and disease has recently received increased attention. This review aims to highlight the recent literature examining the interplay of altered sleep, brain development and emerging psychiatric illnesses in children and adolescents.

RECENT FINDINGS

In addition to a temporal relationship of sleep disturbances preceding the onset of psychiatric illnesses, a bi-directional interaction of altered sleep and symptom severity has increasingly been shown. Sleep architecture shows drastic age-dependent alterations on a structural level during the first 2 decades of life. However, findings regarding disease-specific patterns have remained inconsistent. On a functional level, recent evidence about sleep electroencephalographic characteristics points to a close relationship between slow waves, reflecting the depth of sleep, and cortical plasticity.

SUMMARY

Sleep provides a rich source of information to gain insight into both the healthy and disturbed processes of brain function and maturation. Emerging data suggest that the investigation of slow wave activity is a novel and promising tool for monitoring both of these processes. It is important to understand when and how deviations from typical developmental sleep alterations occur in order to improve prevention and early treatment of disorders affecting a substantial number of children and adolescents.

EEG biomarkers in major depressive disorder: discriminative power and prediction of treatment response

Major depressive disorder (MDD) has high population prevalence and is associated with substantial impact on quality of life, not least due to an unsatisfactory time span of sometimes several weeks from initiation of treatment to clinical response. Therefore extensive research focused on the identification of cost-effective and widely available electroencephalogram (EEG)-based biomarkers that not only allow distinguishing between patients and healthy controls but also have predictive value for treatment response for a variety of treatments. In this comprehensive overview on EEG research on MDD, biomarkers that are either assessed at baseline or during the early course of treatment and are helpful in discriminating patients from healthy controls and assist in predicting treatment outcome are reviewed, covering recent decades up to now. Reviewed markers include quantitative EEG (QEEG) measures, connectivity measures, EEG vigilance-based measures, sleep-EEG-related measures and event-related potentials (ERPs). Further, the value and limitations of these different markers are discussed. Finally, the need for integrated models of brain function and the necessity for standardized procedures in EEG biomarker research are highlighted to enhance future research in this field.

Altered overnight modulation of spontaneous waking EEG reflects altered sleep homeostasis in major depressive disorder: a high-density EEG investigation

BACKGROUND

Prior investigations have suggested sleep homeostasis is altered in major depressive disorder (MDD). Low frequency activity (LFA) in the electroencephalogram during waking has been correlated with sleep slow wave activity (SWA), suggesting that waking LFA reflects sleep homeostasis in healthy individuals. This study investigated whether the overnight change in waking LFA and its relationship with sleep SWA are altered in MDD.

METHODS

256-channel high-density electroencephalography (hdEEG) recordings during waking (pre- and post-sleep) and during sleep were collected in 14 unmedicated, unipolar MDD subjects (9 women) and age- and sex-matched healthy controls (HC).

RESULTS

Waking LFA (3.25-6.25 Hz) declined significantly overnight in the HC group, but not in the group of MDD subjects. Overnight decline of waking LFA correlated with sleep SWA in frontal brain regions in HC, but a comparable relationship was not found in MDD.

LIMITATIONS

This study is not able to definitely segregate overnight changes in the waking EEG that may occur due to homeostatic and/or circadian factors.

CONCLUSIONS

MDD involves altered overnight modulation of waking low frequency EEG activity that may reflect altered sleep homeostasis in the disorder. Future research is required to determine the functional significance and clinical implications of these findings.

Ketamine, sleep, and depression: current status and new questions

Ketamine, an N-methyl-D-aspartate (NMDA) receptor antagonist, has well-described rapid antidepressant effects in clinical studies of individuals with treatment-resistant major depressive disorder (MDD). Preclinical studies investigating the effects of ketamine on brain-derived neurotrophic factor (BDNF) and on sleep slow wave activity (SWA) support its use as a prototype for investigating the neuroplastic mechanisms presumably involved in the mechanism of rapidly acting antidepressants. This review discusses human EEG slow wave sleep parameters and plasma BDNF as central and peripheral surrogate markers of plasticity, and their use in assessing ketamine's effects. Acutely, ketamine elevates BDNF levels, as well as early night SWA and high-amplitude slow waves; each of these measures correlates with change in mood in depressed patients who respond to ketamine. The slow wave effects are limited to the first night post-infusion, suggesting that their increase is part of an early cascade of events triggering improved mood. Increased total sleep and decreased waking occur during the first and second night post infusion, suggesting that these measures are associated with the enduring treatment response observed with ketamine.

Sexually dimorphic, developmental, and chronobiological behavioral profiles of a mouse mania model

Bipolar disorders are heritable psychiatric conditions often abstracted by separate animal models for mania and depression. The principal mania models involve transgenic manipulations or treatment with stimulants. An additional approach involves analysis of naturally occurring mania models including an inbred strain our lab has recently characterized, the Madison (MSN) mouse strain. These mice show a suite of behavioral and neural genetic alterations analogous to manic aspects of bipolar disorders. In the current study, we extended the MSN strain's behavioral phenotype in new directions by examining in-cage locomotor activity. We found that MSN activity presentation is sexually dimorphic, with MSN females showing higher in-cage activity than MSN males. When investigating development, we found that MSN mice display stable locomotor hyperactivity already observable when first assayed at 28 days postnatal. Using continuous monitoring and analysis for 1 month, we did not find evidence of spontaneous bipolarism in MSN mice. However, we did find that the MSN strain displayed an altered diurnal activity profile, getting up earlier and going to sleep earlier than control mice. Long photoperiods were associated with increased in-cage activity in MSN, but not in the control strain. The results of these experiments reinforce the face validity of the MSN strain as a complex mania model, adding sexual dimorphism, an altered diurnal activity profile, and seasonality to the suite of interesting dispositional phenomena related to mania seen in MSN mice.

Brain rhythms and neural syntax: implications for efficient coding of cognitive content and neuropsychiatric disease

The perpetual activity of the cerebral cortex is largely supported by the variety of oscillations the brain generates, spanning a number of frequencies and anatomical locations, as well as behavioral correlates. First, we review findings from animal studies showing that most forms of brain rhythms are inhibition-based, producing rhythmic volleys of inhibitory inputs to principal cell populations, thereby providing alternating temporal windows of relatively reduced and enhanced excitability in neuronal networks. These inhibition-based mechanisms offer natural temporal frames to group or "chunk" neuronal activity into cell assemblies and sequences of assemblies, with more complex multi-oscillation interactions creating syntactical rules for the effective exchange of information among cortical networks. We then review recent studies in human psychiatric patients demonstrating a variety alterations in neural oscillations across all major psychiatric diseases, and suggest possible future research directions and treatment approaches based on the fundamental properties of brain rhythms.

Acute escitalopram treatment inhibits REM sleep rebound and activation of MCH-expressing neurons in the lateral hypothalamus after long term selective REM sleep deprivation

RATIONALE

Selective rapid eye movement sleep (REMS) deprivation using the platform-on-water ("flower pot") method causes sleep rebound with increased REMS, decreased REMS latency, and activation of the melanin-concentrating hormone (MCH) expressing neurons in the hypothalamus. MCH is implicated in the pathomechanism of depression regarding its influence on mood, feeding behavior, and REMS.

OBJECTIVES

We investigated the effects of the most selective serotonin reuptake inhibitor escitalopram on sleep rebound following REMS deprivation and, in parallel, on the activation of MCH-containing neurons.

METHODS

Escitalopram or vehicle (10 mg/kg, intraperitoneally) was administered to REMS-deprived (72 h) or home cage male Wistar rats. During the 3-h-long "rebound sleep", electroencephalography was recorded, followed by an MCH/Fos double immunohistochemistry.

RESULTS

During REMS rebound, the time spent in REMS and the number of MCH/Fos double-labeled neurons in the lateral hypothalamus increased markedly, and REMS latency showed a significant decrease. All these effects of REMS deprivation were significantly attenuated by escitalopram treatment. Besides the REMS-suppressing effects, escitalopram caused an increase in amount of and decrease in latency of slow wave sleep during the rebound.

CONCLUSIONS

These results show that despite the high REMS pressure caused by REMS deprivation procedure, escitalopram has the ability to suppress REMS rebound, as well as to diminish the activation of MCH-containing neurons, in parallel. Escitalopram caused a shift from REMS to slow wave sleep during the rebound. Furthermore, these data point to the potential connection between the serotonergic system and MCH in sleep regulation, which can be relevant in depression and in other mood disorders.

Slow spindles' cortical generators overlap with the epileptogenic zone in temporal epileptic patients: an electrical source imaging study

OBJECTIVE

To determine whether temporal epileptic patients and normal volunteers display similar sleep spindles' cortical generators as determined by electrical source imaging (ESI), and whether such generators overlap in epilepsy patients with the epileptogenic zone identified by ESI.

METHODS

Twelve healthy subjects and twelve temporal lobe pharmaco-resistant epileptic patients underwent a 256-channel EEG recording during a daytime nap. Sleep spindles were analyzed off line, distinguishing slow (10-12 Hz) and fast (12-14 Hz) ones, and the final averaged signal was projected onto a MNI (Montreal Neurological Institute) space to localize cortical generators. The same procedure was performed for averaged epileptic spikes, obtaining their cortical source. Intra- and inter-group statistical analyses were conducted.

RESULTS

Multiple, concomitant generators were detected in both populations for slow and fast spindles. Slow spindles in epileptics displayed higher source amplitude in comparison to healthy volunteers (Z=0.001), as well as a preferential localization over the affected temporal cortices (p=0.039). Interestingly, at least one of slow spindles' generators overlapped with the epileptogenic zone.

CONCLUSION

Slow spindles, but not fast ones, in temporal epilepsy are mainly generated by the affected temporal lobe.

SIGNIFICANCE

These results point to the strict relation between sleep and epilepsy and to the possible cognitive implications of spikes arising from memory-encoding brain structures.

Spatiotemporal analysis of relative convergence of EEGs reveals differences between brain dynamics of depressive women and men

A new nonlinear technique for analysis of brain dynamics called spatiotemporal analysis of relative convergence (STARC) of electroencephalograms (EEGs) is introduced, based on the relative convergence of EEGs of different loci. This technique shows how many times EEGs of each loci pair converge together, which in turn is used as an indicator to determine the different neuronal regions involved in performing the same task. A higher STARC value indicates that more regions are recruited to perform the same task. The STARC methodology was used to reveal sex difference pathophysiology and brain dynamics, using EEG data from 11 male and 11 female adults with major depressive disorder (MDD). The results show significant differences in relative convergences of EEGs of intraleft temporal and frontoleft temporal lobes at δ band, between male and female patients.

Human biomarkers of rapid antidepressant effects

Mood disorders such as major depressive disorder and bipolar disorder--and their consequent effects on the individual and society--are among the most disabling and costly of all medical illnesses. Although a number of antidepressant treatments are available in clinical practice, many patients still undergo multiple and lengthy medication trials before experiencing relief of symptoms. Therefore a tremendous need exists to improve current treatment options and to facilitate more rapid, successful treatment in patients suffering from the deleterious neurobiological effects of ongoing depression. Toward that end, ongoing research is exploring the identification of biomarkers that might be involved in prevention, diagnosis, treatment response, severity, or prognosis of depression. Biomarkers evaluating treatment response will be the focus of this review, given the importance of providing relief to patients in a more expedient and systematic manner. A novel approach to developing such biomarkers of response would incorporate interventions with a rapid onset of action--such as sleep deprivation or intravenous drugs (e.g., ketamine or scopolamine). This alternative translational model for new treatments in psychiatry would facilitate shorter studies, improve feasibility, and increase higher compound throughput testing for these devastating disorders.

Baseline delta sleep ratio predicts acute ketamine mood response in major depressive disorder

BACKGROUND

Electroencephalographic (EEG) sleep slow wave activity (SWA; EEG power between 0.6 and 4Hz) has been proposed as a marker of central synaptic plasticity. Decreased generation of sleep slow waves--a core feature of sleep in depression--indicates underlying plasticity changes in the disease. Various measures of SWA have previously been used to predict antidepressant treatment response. This study examined the relationship between baseline patterns of SWA in the first two NREM episodes and antidepressant response to an acute infusion of the N-methyl-d-aspartate (NMDA) antagonist ketamine.

METHODS

Thirty patients (20M, 10F, 18-65) fulfilling DSM-IV criteria for treatment-resistant major depressive disorder (MDD) who had been drug-free for two weeks received a single open-label infusion of ketamine hydrochloride (.5mg/kg) over 40 min. Depressive symptoms were assessed with the Montgomery-Asberg Depression Rating Scale (MADRS) before and after ketamine infusion. Sleep recordings were obtained the night before the infusion and were visually scored. SWA was computed for individual artifact-free NREM sleep epochs, and averaged for each NREM episode. Delta sleep ratio (DSR) was calculated as SWA(NREM1)/SWA(NREM2).

RESULTS

A significant positive correlation was observed between baseline DSR and reduced MADRS scores from baseline to Day 1 (r=.414, p=.02).

LIMITATIONS

The sample size was relatively small (N=30) and all subjects had treatment-resistant MDD, which may limit the generalizability of the findings. Further studies are needed to replicate and extend this observation to other patient groups.

CONCLUSIONS

DSR may be a useful baseline predictor of ketamine response in individuals with treatment-resistant MDD.

Sex-related differences in sleep slow wave activity in major depressive disorder: a high-density EEG investigation

BACKGROUND

Sleep disturbance plays an important role in major depressive disorder (MDD). Prior investigations have demonstrated that slow wave activity (SWA) during sleep is altered in MDD; however, results have not been consistent across studies, which may be due in part to sex-related differences in SWA and/or limited spatial resolution of spectral analyses. This study sought to characterize SWA in MDD utilizing high-density electroencephalography (hdEEG) to examine the topography of SWA across the cortex in MDD, as well as sex-related variation in SWA topography in the disorder.

METHODS

All-night recordings with 256 channel hdEEG were collected in 30 unipolar MDD subjects (19 women) and 30 age and sex-matched control subjects. Spectral analyses of SWA were performed to determine group differences. SWA was compared between MDD and controls, including analyses stratified by sex, using statistical non-parametric mapping to correct for multiple comparisons of topographic data.

RESULTS

As a group, MDD subjects demonstrated significant increases in all-night SWA primarily in bilateral prefrontal channels. When stratified by sex, MDD women demonstrated global increases in SWA relative to age-matched controls that were most consistent in bilateral prefrontal regions; however, MDD men showed no significant differences relative to age-matched controls. Further analyses demonstrated increased SWA in MDD women was most prominent in the first portion of the night.

CONCLUSIONS

Women, but not men with MDD demonstrate significant increases in SWA in multiple cortical areas relative to control subjects. Further research is warranted to investigate the role of SWA in MDD, and to clarify how increased SWA in women with MDD is related to the pathophysiology of the disorder.

Effect of antidepressive therapy on retinal contrast processing in depressive disorder

BACKGROUND

Recently, we reported a reduced retinal contrast gain in unmedicated and medicated patients with major depression.

AIMS

To analyse whether the contrast gain normalises after successful antidepressive therapy by recording the pattern electroretinogram (PERG) in healthy controls and patients with depression before and after antidepressive therapy.

METHOD

Fourteen patients diagnosed with major depression were repeatedly scanned and the results compared with that from 40 matched controls.

RESULTS

The retinal contrast gain was lower at baseline in patients with depression, was normalised with remission and correlated with the severity of depression. Patients who did not achieve remission retained significantly lower contrast gain at follow-up.

CONCLUSIONS

The study provides evidence for a state-dependent modulation of retinal contrast gain in patients with major depression. Reduced contrast gain normalised after therapy. A PERG-based contrast gain could serve as a state marker of depression.

Overnight changes in waking auditory evoked potential amplitude reflect altered sleep homeostasis in major depression

OBJECTIVE

Sleep homeostasis is altered in major depressive disorder (MDD). Pre- to postsleep decline in waking auditory evoked potential (AEP) amplitude has been correlated with sleep slow wave activity (SWA), suggesting that overnight changes in waking AEP amplitude are homeostatically regulated in healthy individuals. This study investigated whether the overnight change in waking AEP amplitude and its relation to SWA is altered in MDD.

METHOD

Using 256-channel high-density electroencephalography, all-night sleep polysomnography and single-tone waking AEPs pre- and postsleep were collected in 15 healthy controls (HC) and 15 non-medicated individuals with MDD.

RESULTS

N1 and P2 amplitudes of the waking AEP declined after sleep in the HC group, but not in MDD. The reduction in N1 amplitude also correlated with fronto-central SWA in the HC group, but a comparable relationship was not found in MDD, despite equivalent SWA between groups. No pre- to postsleep differences were found for N1 or P2 latencies in either group. These findings were not confounded by varying levels of alertness or differences in sleep variables between groups.

CONCLUSION

MDD involves altered sleep homeostasis as measured by the overnight change in waking AEP amplitude. Future research is required to determine the clinical implications of these findings.

High density electroencephalography in sleep research: potential, problems, future perspective

High density EEG (hdEEG) during sleep combines the superior temporal resolution of EEG recordings with high spatial resolution. Thus, this method allows a topographical analysis of sleep EEG activity and thereby fosters the shift from a global view of sleep to a local one. HdEEG allowed to investigate sleep rhythms in terms of their characteristic behavior (e.g., the traveling of slow waves) and in terms of their relationship to cortical functioning (e.g., consciousness and cognitive abilities). Moreover, recent studies successfully demonstrated that hdEEG can be used to study brain functioning in neurological and neuro-developmental disorders, and to evaluate therapeutic approaches. This review highlights the potential, the problems, and future perspective of hdEEG in sleep research.

Altered slow wave activity in major depressive disorder with hypersomnia: a high density EEG pilot study

Hypersomnolence in major depressive disorder (MDD) plays an important role in the natural history of the disorder, but the basis of hypersomnia in MDD is poorly understood. Slow wave activity (SWA) has been associated with sleep homeostasis, as well as sleep restoration and maintenance, and may be altered in MDD. Therefore, we conducted a post-hoc study that utilized high density electroencephalography (hdEEG) to test the hypothesis that MDD subjects with hypersomnia (HYS+) would have decreased SWA relative to age- and sex-matched MDD subjects without hypersomnia (HYS-) and healthy controls (n=7 for each group). After correction for multiple comparisons using statistical non-parametric mapping, HYS+ subjects demonstrated significantly reduced parieto-occipital all-night SWA relative to HYS- subjects. Our results suggest hypersomnolence may be associated with topographic reductions in SWA in MDD. Further research using an adequately powered prospective design is indicated to confirm these findings.

Electrophysiological traces of visuomotor learning and their renormalization after sleep

OBJECTIVE

Adapting movements to a visual rotation involves the activation of right posterior parietal areas. Further performance improvement requires an increase of slow wave activity in subsequent sleep in the same areas. Here we ascertained whether a post-learning trace is present in wake EEG and whether such a trace is influenced by sleep slow waves.

METHODS

In two separate sessions, we recorded high-density EEG in 17 healthy subjects before and after a visuomotor rotation task, which was performed both before and after sleep. High-density EEG was recorded also during sleep. One session aimed to suppress sleep slow waves, while the other session served as a control.

RESULTS

After learning, we found a trace in the eyes-open wake EEG as a local, parietal decrease in alpha power. After the control night, this trace returned to baseline levels, but it failed to do so after slow wave deprivation. The overnight change of the trace correlated with the dissipation of low frequency (<8 Hz) NREM sleep activity only in the control session.

CONCLUSIONS

Visuomotor learning leaves a trace in the wake EEG alpha power that appears to be renormalized by sleep slow waves.

SIGNIFICANCE

These findings link visuomotor learning to regional changes in wake EEG and sleep homeostasis.