A cognitive model of recurrent nightmares

Nightmares are a prevalent mental disorder resulting in disturbed sleep, distress, and impairment in daily functioning. Elaborating on previous theoretical models for anxiety disorders, sleep disorders and dreaming, this study introduces a cognitive model of recurrent nightmares, the central element of which concerns representation of the nightmare’s repetitive storyline in the memory as a script. It is suggested that activation of this script during REM sleep results in a replay of the nightmare, and that activation occurs through perceived similarity between dream elements and the nightmare script. The model proposes a central role for cognitive processes in the persistence of nightmares over time. The success of cognitive-behavioural treatments is explained and clinical implications are discussed

Frontoparietal Connectivity and Hierarchical Structure of the Brain’s Functional Network during Sleep

Frontal and parietal regions are associated with some of the most complex cognitive functions, and several frontoparietal resting-state networks can be observed in wakefulness. We used functional magnetic resonance imaging data acquired in polysomnographically validated wakefulness, light sleep, and slow-wave sleep to examine the hierarchical structure of a low-frequency functional brain network, and to examine whether frontoparietal connectivity would disintegrate in sleep. Whole-brain analyses with hierarchical cluster analysis on predefined atlases were performed, as well as regression of inferior parietal lobules (IPL) seeds against all voxels in the brain, and an evaluation of the integrity of voxel time-courses in subcortical regions-of-interest. We observed that frontoparietal functional connectivity disintegrated in sleep stage 1 and was absent in deeper sleep stages. Slow-wave sleep was characterized by strong hierarchical clustering of local submodules. Frontoparietal connectivity between IPL and superior medial and right frontal gyrus was lower in sleep stages than in wakefulness. Moreover, thalamus voxels showed maintained integrity in sleep stage 1, making intrathalamic desynchronization an unlikely source of reduced thalamocortical connectivity in this sleep stage. Our data suggest a transition from a globally integrated functional brain network in wakefulness to a disintegrated network consisting of local submodules in slow-wave sleep, in which frontoparietal inter-modular nodes may play a role, possibly in combination with the thalamus

Hyperarousal captured in increased number of arousal events during pre-REM periods in individuals with frequent nightmares

The aim of this study was to investigate hyperarousal in individuals with frequent nightmares (NM participants) by calculating arousal events during nocturnal sleep. We hypothesized an increased number of arousals in NM participants compared with controls, especially during those periods where the probability of spontaneous arousal occurrence is already high, such as non-rapid eye movement to rapid eye movement transitions (pre-rapid eye movement periods). Twenty-two NM participants and 23 control participants spent two consecutive nights in our sleep laboratory, monitored by polysomnography. Arousal number and arousal length were calculated only for the second night, for 10 min before rapid eye movement (pre-rapid eye movement) and 10 min after rapid eye movement (post-rapid eye movement) periods, as well as non-rapid eye movement and rapid eye movement phases separately. Repeated-measures ANOVA model testing revealed significant Group (NM participants, controls) x Phase (pre-rapid eye movement, post-rapid eye movement) interaction in case of the number of arousals. Furthermore, post hoc analysis showed a significantly increased number of arousals during pre-rapid eye movement periods in NM participants, compared with controls, a difference that disappeared in post-rapid eye movement periods. We propose that focusing the analyses of arousals specifically on state transitory periods offers a unique perspective into the fragile balance between the sleep-promoting and arousal systems. This outlook revealed an increased number of arousals in NM participants, reflecting hyperarousal during pre-rapid eye movement periods

Validation of non-REM sleep stage decoding from resting state fMRI using linear support vector machines

A growing body of literature suggests that changes in consciousness are reflected in specific connectivity patterns of the brain as obtained from resting state fMRI (rs-fMRI). As simultaneous electroencephalography (EEG) is often unavailable, decoding of potentially confounding sleep patterns from rs-fMRI itself might be useful and improve data interpretation. Linear support vector machine classifiers were trained on combined rs-fMRI/EEG recordings from 25 subjects to separate wakefulness (S0) from non-rapid eye movement (NREM) sleep stages 1 (S1), 2 (S2), slow wave sleep (SW) and all three sleep stages combined (SX). Classifier performance was quantified by a leave-one-subject-out cross-validation (LOSO-CV) and on an independent validation dataset comprising 19 subjects. Results demonstrated excellent performance with areas under the receiver operating characteristics curve (AUCs) close to 1.0 for the discrimination of sleep from wakefulness (S0|SX), S0|S1, S0|S2 and S0|SW, and good to excellent performance for the classification between sleep stages (S1|S2:~0.9; S1|SW:~1.0; S2|SW:~0.8). Application windows of fMRI data from about 70 s were found as minimum to provide reliable classifications. Discrimination patterns pointed to subcortical-cortical connectivity and within-occipital lobe reorganization of connectivity as strongest carriers of discriminative information. In conclusion, we report that functional connectivity analysis allows valid classification of NREM sleep stages

The role of rapid eye movement sleep for amygdala-related memory processing

Contains fulltext : 154252.pdf (Publisher’s version ) (Open Access)Over the years, rapid eye movement (REM) sleep has been associated with general memory consolidation, specific consolidation of perceptual, procedural, emotional and fear memories, brain maturation and preparation of waking consciousness. More recently, some of these associations (e.g., general and procedural memory consolidation) have been shown to be unlikely, while others (e.g., brain maturation and consciousness) remain inconclusive. In this review, we argue that both behavioral and neurophysiological evidence supports a role of REM sleep for amygdala-related memory processing: the amygdala-hippocampus-medial prefrontal cortex network involved in emotional processing, fear memory and valence consolidation shows strongest activity during REM sleep, in contrast to the hippocampus-medial prefrontal cortex only network which is more active during non-REM sleep. However, more research is needed to fully understand the mechanisms.12 p

Anxiety and depression mediate the relationship between self-disgust and insomnia disorder

Objectives: There is limited research on the association between insomnia and negative self-conscious emotions. This study assessed if individuals with insomnia reported higher scores in self-disgust than normal sleepers, and if the association between insomnia and self-disgust was mediated by depression and anxiety. Methods: Twenty seven individuals with DSM-5 Insomnia Disorder and 30 normal sleepers completed self-reported measures of self-disgust, anxiety and depression. Results: Individuals with insomnia reported significantly higher scores in self-disgust, anxiety and depression than normal sleepers. Insomnia significantly predicted self-disgust, but this association was mediated by anxiety and depression. Conclusions: This is the first study that demonstrated the association between clinically diagnosed insomnia in young adults and self-disgust, and highlighted the mediating effects of anxiety and depression. Keywords

Baseline depression levels do not affect efficacy of cognitive-behavioral self-help treatment for insomnia

Background Cognitive-behavioral therapy can effectively treat insomnia (CBT-I). Randomized controlled trials have shown efficacy of self-help CBT-I, but unclear is whether excluding depressive patients boosted treatment effects. Method We administered unsupported self-help CBT-I to insomnia patients with low and high depression levels. Based on the validated Centre of Epidemiological Studies-Depression (CES-D) scale, the internet-recruited sample (N = 479) was divided into three groups: low depression scores (n = 198), mild depression scores (n = 182), and high depression scores (n = 99). Follow-ups were 4 and 18 weeks after completion of the treatment. Results At 4-week follow-up, all groups had a similar amelioration on the primary sleep measures (d = 0.1-0.7; P < 0.05) and the secondary insomnia ratings (d = 1.2; P < 0.001). The only difference was that the high/mild depression groups had a steeper reduction in depression (d = 1.0-1.1; P < 0.001) and anxiety scores (d = 0.7-0.8; P < 0.001) than the low depression group (depression and anxiety: d = 0.3; P < 0.01), possibly due to floor effects in the latter group. The observed effects were sustained at the 18-week follow-up. Conclusions This study showed that CBT-I is effective regardless of baseline depression levels. Treating the combination of insomnia and depression is an extra challenge since it is associated with increased sleep problems. These data may help us understand the relationship between insomnia and depression and indicate that self-help CBT-I may be a promising addition to regular depression treatment. © 2012 Wiley Periodicals, Inc

Anxiety and depression mediate the relationship between insomnia symptoms and the personality traits of conscientiousness and emotional stability

This study examined the relationship between the Big Five personality traits and insomnia symptoms in the general population. Additionally, the mediating role of anxiety and depression was examined. Participants (N=625) completed online measures of the big five personality traits and insomnia severity. Insomnia symptoms were independently related to extroversion, agreeableness, conscientiousness, emotional stability, anxiety and depression in univariate analysis. Linear regression determined conscientiousness and emotional stability to be the only traits predicting insomnia symptoms. However, these relationships were at least partially mediated by anxiety and depression. Whilst reduced levels of conscientiousness and emotional stability has previously associated with poor sleep and insomnia, the current outcomes shed light on the mechanisms which serve to mediate this relationship

Nothing is safe: intolerance of uncertainty is associated with compromised fear extinction learning

Extinction-resistant fear is considered to be a central feature of pathological anxiety. Here we sought to determine if individual differences in Intolerance of Uncertainty (IU), a potential risk factor for anxiety disorders, underlies compromised fear extinction. We tested this hypothesis by recording electrodermal activity in 38 healthy participants during fear acquisition and extinction. We assessed the temporality of fear extinction, by examining early and late extinction learning. During early extinction, low IU was associated with larger skin conductance responses to learned threat vs. safety cues, whereas high IU was associated with skin conductance responding to both threat and safety cues, but no cue discrimination. During late extinction, low IU showed no difference in skin conductance between learned threat and safety cues, whilst high IU predicted continued fear expression to learned threat, indexed by larger skin conductance to threat vs. safety cues. These findings suggest a critical role of uncertainty-based mechanisms in the maintenance of learned fear