Summary Sleep disturbances are often viewed as a secondary symptom of post-traumatic stress disorder (PTSD), thought to resolve once PTSD has been treated. Specific screening, diagnosis and treatment ...of sleep disturbances is therefore not commonly conducted in trauma centres. However, recent evidence shows that this view and consequent practices are as much unhelpful as incorrect. Several sleep disorders—nightmares, insomnia, sleep apnoea and periodic limb movements—are highly prevalent in PTSD, and several studies found disturbed sleep to be a risk factor for the subsequent development of PTSD. Moreover, sleep disturbances are a frequent residual complaint after successful PTSD treatment: a finding that applies both to psychological and pharmacological treatment. In contrast, treatment focusing on sleep does alleviate both sleep disturbances and PTSD symptom severity. A growing body of evidence shows that disturbed sleep is more than a secondary symptom of PTSD—it seems to be a core feature. Sleep-focused treatment can be incorporated into any standard PTSD treatment, and PTSD research needs to start including validated sleep measurements in longitudinal epidemiologic and treatment outcome studies. Further clinical and research implications are discussed, and possible mechanisms for the role of disturbed (REM) sleep in PTSD are described.
In human fear conditioning studies, different physiological readouts can be used to track conditioned responding during fear learning. Commonly employed readouts such as skin conductance responses ...(SCR) or startle responses have in recent years been complemented by pupillary readouts, but to date it is unknown how pupillary readouts relate to other measures of the conditioned response. To examine differences and communalities among pupil responses, SCR, and startle responses, we simultaneously recorded pupil diameter, skin conductance, and startle electromyography in 47 healthy subjects during fear acquisition, extinction, and a recall test on 2 consecutive days. The different measures correlated only weakly, displaying most prominent differences in their response patterns during fear acquisition. Whereas SCR and startle responses habituated, pupillary measures did not. Instead, they increased in response to fear conditioned stimuli and most closely followed ratings of unconditioned stimulus (US) expectancy. Moreover, we observed that startle‐induced pupil responses showed stimulus discrimination during fear acquisition, suggesting a fear potentiation of the auditory pupil reflex. We conclude that different physiological outcome measures of the conditioned response inform about different cognitive‐affective processes during fear learning, with pupil responses being least affected by physiological habituation and most closely following US expectancy.
The reward system may provide an interesting intermediate phenotype for anhedonia in affective disorders. Reward anticipation is characterized by an increase in arousal, and previous studies have ...linked the anterior cingulate cortex (ACC) to arousal responses such as dilation of the pupil. Here, we examined pupil dynamics during a reward anticipation task in forty-six healthy human subjects and evaluated its neural correlates using functional magnetic resonance imaging (fMRI). Pupil size showed a strong increase during monetary reward anticipation, a moderate increase during verbal reward anticipation and a decrease during control trials. For fMRI analyses, average pupil size and pupil change were computed in 1-s time bins during the anticipation phase. Activity in the ventral striatum was inversely related to the pupil size time course, indicating an early onset of activation and a role in reward prediction processing. Pupil dilations were linked to increased activity in the salience network (dorsal ACC and bilateral insula), which likely triggers an increase in arousal to enhance task performance. Finally, increased pupil size preceding the required motor response was associated with activity in the ventral attention network. In sum, pupillometry provides an effective tool for disentangling different phases of reward anticipation, with relevance for affective symptomatology.
•Pupil dilation increases during reward anticipation.•Salience network activity correlates with pupil dilation during reward anticipation.•Ventral striatal activity temporally precedes salience network activity.•Salience network activity is followed by ventral attention network activity.•Reward anticipation-related pupil dilation bears potential for anhedonia assessment.
Since the discovery of the close association between rapid eye movement (REM) sleep and dreaming, much effort has been devoted to link physiological signatures of REM sleep to the contents of ...associated dreams 1–4. Due to the impossibility of experimentally controlling spontaneous dream activity, however, a direct demonstration of dream contents by neuroimaging methods is lacking. By combining brain imaging with polysomnography and exploiting the state of “lucid dreaming,” we show here that a predefined motor task performed during dreaming elicits neuronal activation in the sensorimotor cortex. In lucid dreams, the subject is aware of the dreaming state and capable of performing predefined actions while all standard polysomnographic criteria of REM sleep are fulfilled 5, 6. Using eye signals as temporal markers, neural activity measured by functional magnetic resonance imaging (fMRI) and near-infrared spectroscopy (NIRS) was related to dreamed hand movements during lucid REM sleep. Though preliminary, we provide first evidence that specific contents of REM-associated dreaming can be visualized by neuroimaging.
► Eye signals can be used to access dream content with concurrent EEG and neuroimaging ► Dreamed hand movements correspond to activity in the contralateral sensorimotor cortex
Falling asleep is paralleled by a loss of conscious awareness and reduced capacity to process external stimuli. Little is known on sleep-associated changes of spontaneously synchronized anatomical ...networks as detected by resting-state functional magnetic resonance imaging (rs-fMRI). We employed functional connectivity analysis of rs-fMRI series obtained from 25 healthy participants, covering all non-rapid eye movement (NREM) sleep stages. We focused on the default mode network (DMN) and its anticorrelated network (ACN) that are involved in internal and external awareness during wakefulness. Using independent component analysis, cross-correlation analysis (CCA), and intraindividual dynamic network tracking, we found significant changes in DMN/ACN integrity throughout the NREM sleep. With increasing sleep depth, contributions of the posterior cingulate cortex (PCC)/retrosplenial cortex (RspC), parahippocampal gyrus, and medial prefrontal cortex to the DMN decreased. CCA revealed a breakdown of corticocortical functional connectivity, particularly between the posterior and anterior midline node of the DMN and the DMN and the ACN. Dynamic tracking of the DMN from wakefulness into slow wave sleep in a single subject added insights into intraindividual network fluctuations. Results resonate with a role of the PCC/RspC for the regulation of consciousness. We further submit that preserved corticocortical synchronization could represent a prerequisite for maintaining internal and external awareness.
Abstract
Study Objectives
Frequent nightmares have a high prevalence and constitute a risk factor for psychiatric conditions, but their pathophysiology is poorly understood. Our aim was to examine ...sleep architecture and electroencephalographic markers—with a specific focus on state transitions—related to sleep regulation and hyperarousal in participants with frequent nightmares (NM participants) versus healthy controls.
Methods
Healthy controls and NM participants spent two consecutive nights in the sleep laboratory. Second night spectral power during NREM to REM sleep (pre-REM) and REM to NREM (post-REM) transitions as well as during NREM and REM periods were evaluated for 22 NM participants compared to 22 healthy controls with a similar distribution of age, gender, and dream recall frequency.
Results
We found significant differences between the groups in the pre-REM to post-REM changes in low- and high-frequency domains. NM participants experienced a lower amount of slow-wave sleep and showed increased beta and gamma power during NREM and pre-REM periods. No difference was present during REM and post-REM phases. Furthermore, while increased pre-REM high-frequency power seems to be mainly driven by post-traumatic stress disorder (PTSD) symptom intensity, decreased low-frequency activity occurred regardless of PTSD symptom severity.
Conclusion
Our findings indicate that NM participants had increased high-frequency spectral power during NREM and pre-REM periods, as well as relatively reduced slow frequency and increased fast frequency spectral power across pre-and post-REM periods. This combination of reduced sleep-protective activity and increased hyperarousal suggests an imbalance between sleep regulatory and wake-promoting systems in NM participants.
Fear conditioning and extinction are prevailing experimental and etiological models for normal and pathological anxiety. Pupil dilations in response to conditioned stimuli are increasingly used as a ...robust psychophysiological readout of fear learning, but their neural correlates remain unknown. We aimed at identifying the neural correlates of pupil responses to threat and safety cues during a fear learning task.
Thirty-four healthy subjects underwent a fear conditioning and extinction paradigm with simultaneous functional magnetic resonance imaging (fMRI) and pupillometry. After a stringent preprocessing and artifact rejection procedure, trial-wise pupil responses to threat and safety cues were entered as parametric modulations to the fMRI general linear models.
Trial-wise magnitude of pupil responses to both conditioned and safety stimuli correlated positively with activity in dorsal anterior cingulate cortex (dACC), thalamus, supramarginal gyrus and insula for the entire fear learning task, and with activity in the dACC during the fear conditioning phase in particular. Phasic pupil responses did not show habituation, but were negatively correlated with tonic baseline pupil diameter, which decreased during the task. Correcting phasic pupil responses for the tonic baseline pupil diameter revealed thalamic activity, which was also observed in an analysis employing a linear (declining) time modulation.
Pupil dilations during fear conditioning and extinction provide useful readouts to track fear learning on a trial-by-trial level, particularly with simultaneous fMRI. Whereas phasic pupil responses reflect activity in brain regions involved in fear learning and threat appraisal, most prominently in dACC, tonic changes in pupil diameter may reflect changes in general arousal.
•Pupil responses during fear learning are associated with dACC and thalamus activity.•Phasic pupil responses do not show substantial habituation during fear learning.•Phasic pupil responses are negatively correlated with tonic pupil size.•Pupillometry can track conditioned responses on a trial-by-trial level.
Summary
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) × 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.
Resting state functional magnetic resonance imaging (rs-fMRI) is increasingly applied for the development of functional biomarkers in brain disorders. Recent studies have revealed spontaneous ...vigilance drifts during the resting state, involving changes in brain activity and connectivity that challenge the validity of uncontrolled rs-fMRI findings. In a combined rs-fMRI/eye tracking study, the pupil size of 32 healthy subjects after 2h of sleep restriction was recorded as an indirect index for activity of the locus coeruleus, the brainstem's noradrenergic arousal center. The spontaneous occurrence of pupil dilations, but not pupil size per se, was associated with increased activity of the salience network, thalamus and frontoparietal regions. In turn, spontaneous constrictions of the pupil were associated with increased activity in visual and sensorimotor regions. These results were largely replicated in a sample of 36 healthy subjects who did not undergo sleep restriction, although in this sample the correlation between thalamus and pupil dilation fell below whole-brain significance. Our data show that spontaneous pupil fluctuations during rest are indeed associated with brain circuitry involved in tonic alertness and vigilance. Pupillometry is an effective method to control for changes in tonic alertness during rs-fMRI.
•Pupil size is not associated with robust brain network activity.•Spontaneous pupil dilations are associated with salience network activation.•Pupil constrictions involve activation of visual and sensorimotor areas.•Pupillometry provides a marker for alertness/vigilance during resting state fMRI.
We investigated human hippocampal functional connectivity in wakefulness and throughout non-rapid eye movement sleep. Young healthy subjects underwent simultaneous EEG and functional magnetic ...resonance imaging (fMRI) measurements at 1.5 T under resting conditions in the descent to deep sleep. Continuous 5 min epochs representing a unique sleep stage (i.e., wakefulness, sleep stages 1 and 2, or slow-wave sleep) were extracted. fMRI time series of subregions of the hippocampal formation (HF) (cornu ammonis, dentate gyrus, and subiculum) were extracted based on cytoarchitectonical probability maps. We observed sleep stage-dependent changes in HF functional coupling. The HF was integrated to variable strength in the default mode network (DMN) in wakefulness and light sleep stages but not in slow-wave sleep. The strongest functional connectivity between the HF and neocortex was observed in sleep stage 2 (compared with both slow-wave sleep and wakefulness). We observed a strong interaction of sleep spindle occurrence and HF functional connectivity in sleep stage 2, with increased HF/neocortical connectivity during spindles. Moreover, the cornu ammonis exhibited strongest functional connectivity with the DMN during wakefulness, while the subiculum dominated hippocampal functional connectivity to frontal brain regions during sleep stage 2. Increased connectivity between HF and neocortical regions in sleep stage 2 suggests an increased capacity for possible global information transfer, while connectivity in slow-wave sleep is reflecting a functional system optimal for segregated information reprocessing. Our data may be relevant to differentiating sleep stage-specific contributions to neural plasticity as proposed in sleep-dependent memory consolidation.
PDF
