Sleep and sleep disorders during pregnancy and postpartum: The Life-ON study.

OBJECTIVE: to prospectively assess sleep and sleep disorders during pregnancy and postpartum in a large cohort of women. METHODS: multicenter prospective Life-ON study, recruiting consecutive pregnant women at a gestational age between 10 and 15 weeks, from the local gynecological departments. The study included home polysomnography performed between the 23rd and 25th week of pregnancy and sleep-related questionnaires at 9 points in time during pregnancy and 6 months postpartum. RESULTS: 439 pregnant women (mean age 33.7 ± 4.2 yrs) were enrolled. Poor quality of sleep was reported by 34% of women in the first trimester of pregnancy, by 46% of women in the third trimester, and by as many as 71% of women in the first month after delivery. A similar trend was seen for insomnia. Excessive daytime sleepiness peaked in the first trimester (30% of women), and decreased in the third trimester, to 22% of women. Prevalence of restless legs syndrome was 25%, with a peak in the third trimester of pregnancy. Polysomnographic data, available for 353 women, revealed that 24% of women slept less than 6 h, and 30.6% of women had a sleep efficiency below 80%. Sleep-disordered breathing (RDI≥5) had a prevalence of 4.2% and correlated positively with BMI. CONCLUSIONS: The Life-ON study provides the largest polysomnographic dataset coupled with longitudinal subjective assessments of sleep quality in pregnant women to date. Sleep disorders are highly frequent and distributed differently during pregnancy and postpartum. Routine assessment of sleep disturbances in the perinatal period is necessary to improve early detection and clinical management.

Optimal risk and diagnosis assessment strategies in perinatal depression: A machine learning approach from the life-ON study cohort.

This study aimed to assess the concordance of various psychometric scales in detecting Perinatal Depression (PND) risk and diagnosis. A cohort of 432 women was assessed at 10-15th and 23-25th gestational weeks, 33-40 days and 180-195 days after delivery using the Edinburgh Postnatal Depression Scale (EPDS), Visual Analogue Scale (VAS), Hamilton Depression Rating Scale (HDRS), Montgomery-Åsberg Depression Rating Scale (MADRS), and Mini International Neuropsychiatric Interview (MINI). Spearman's rank correlation coefficient was used to assess agreement across instruments, and multivariable classification models were developed to predict the values of a binary scale using the other scales. Moderate agreement was shown between the EPDS and VAS and between the HDRS and MADRS throughout the perinatal period. However, agreement between the EPDS and HDRS decreased postpartum. A well-performing model for the estimation of current depression risk (EPDS > 9) was obtained with the VAS and MADRS, and a less robust one for the estimation of current major depressive episode (MDE) diagnosis (MINI) with the VAS and HDRS. When the EPDS is not feasible, the VAS may be used for rapid and comprehensive postpartum screening with reliability. However, a thorough structured interview or clinical examination remains necessary to diagnose a MDE.

State of Mind Assessment in Relation to Adult Attachment and Text Analysis of Adult Attachment Interviews in a Sample of Patients with Anorexia Nervosa.

BACKGROUND: Attachment theory represents one of the most important references for the study of the development of an individual throughout their life cycle and provides the clinician with a profound key for the purposes of understanding the suffering that underlies severe psychopathologies such as eating disorders. As such, we conducted a cross-sectional study with a mixed-methods analysis on a sample of 32 young women with anorexia nervosa (AN); this study was embedded in the utilized theoretical framework with the following aims: 1. to evaluate the state of mind (SoM) in relation to adult attachment, assuming a prevalence of the dismissing (DS) SoM and 2. to analyze the linguistic attachment profile emerging from the transcripts of the AAIs. METHODS: Interviews were transcribed verbatim, coded, and analyzed using the linguistic inquiry and word count (LIWC) method. RESULTS: The results were observed to be consistent with the referenced literature. The prevalence of a DS SoM (68.75%) is observed in the study sample, whereas the results of the lexical analysis of the stories deviate from expectations. Notably, the lexical results indicate the coexistence of the dismissing and entangled aspects at the representational level. CONCLUSIONS: The study results suggest a high level of specificity in the emotional functioning of patients with AN, with a focusing on a pervasive control of emotions that is well illustrated by the avoidant/ambivalent (A/C) strategy described in Crittenden's dynamic-maturational model. These findings and considerations have important implications for clinical work and treatment, which we believe must be structured on the basis of starting from a reappraisal of emotional content.

Decoding Brain Responses to Names and Voices across Different Vigilance States.

Past research has demonstrated differential responses of the brain during sleep in response especially to variations in paralinguistic properties of auditory stimuli, suggesting they can still be processed "offline". However, the nature of the underlying mechanisms remains unclear. Here, we therefore used multivariate pattern analyses to directly test the similarities in brain activity among different sleep stages (non-rapid eye movement stages N1-N3, as well as rapid-eye movement sleep REM, and wake). We varied stimulus salience by manipulating subjective (own vs. unfamiliar name) and paralinguistic (familiar vs. unfamiliar voice) salience in 16 healthy sleepers during an 8-h sleep opportunity. Paralinguistic salience (i.e., familiar vs. unfamiliar voice) was reliably decoded from EEG response patterns during both N2 and N3 sleep. Importantly, the classifiers trained on N2 and N3 data generalized to N3 and N2, respectively, suggesting similar processing mode in these states. Moreover, projecting the classifiers' weights using a forward model revealed similar fronto-central topographical patterns in NREM stages N2 and N3. Finally, we found no generalization from wake to any sleep stage (and vice versa) suggesting that "processing modes" or the overall processing architecture with respect to relevant oscillations and/or networks substantially change from wake to sleep. However, the results point to a single and rather uniform NREM-specific mechanism that is involved in (auditory) salience detection during sleep.

Memory Traces Formed in Utero-Newborns' Autonomic and Neuronal Responses to Prenatal Stimuli and the Maternal Voice.

In our pilot study, we exposed third-trimester fetuses, from week 34 of gestation onwards, twice daily to a maternal spoken nursery rhyme. Two and five weeks after birth, 34 newborns, who were either familiarized with rhyme stimulation in utero or stimulation naïve, were (re-)exposed to the familiar, as well as to a novel and unfamiliar, rhyme, both spoken with the maternal and an unfamiliar female voice. For the stimulation-naïve group, both rhymes were unfamiliar. During stimulus presentation, heart rate activity and high-density electroencephalography were collected and newborns' responses during familiar and unfamiliar stimulation were analyzed. All newborns demonstrated stronger speech-brain coupling at 1 Hz during the presentation of the maternal voice vs. the unfamiliar female voice. Rhyme familiarity originating from prenatal exposure had no effect on speech-brain coupling in experimentally stimulated newborns. Furthermore, only stimulation-naïve newborns demonstrated an increase in heart rate during the presentation of the unfamiliar female voice. The results indicate prenatal familiarization to auditory speech and point to the specific significance of the maternal voice already in two- to five-week-old newborns.

Sleep, Little Baby: The Calming Effects of Prenatal Speech Exposure on Newborns' Sleep and Heartrate.

In a pilot study, 34 fetuses were stimulated daily with a maternal spoken nursery rhyme from week 34 of gestation onward and re-exposed two and five weeks after birth to this familiar, as well as to an unfamiliar rhyme, both spoken with the maternal and an unfamiliar female voice. During auditory stimulation, newborns were continuously monitored with polysomnography using video-monitored hdEEG. Afterward, changes in sleep-wake-state proportions during familiar and unfamiliar voice stimulation were analyzed. Our preliminary results demonstrate a general calming effect of auditory stimulation exclusively in infants who were prenatally "familiarized" with a spoken nursery rhyme, as evidenced by less waking states, more time spent in quiet (deep) sleep, and lower heartrates. A stimulation naïve group, on the other hand, demonstrated no such effects. Stimulus-specific effects related to the familiarity of the prenatally replayed voice or rhyme were not evident in newborns. Together, these results suggest "fetal learning" at a basic level and point to a familiarization with auditory stimuli prior to birth, which is evident in the first weeks of life in behavioral states and heartrate physiology of the newborn.

On the development of sleep states in the first weeks of life.

Human newborns spend up to 18 hours sleeping. The organization of their sleep differs immensely from adult sleep, and its quick maturation and fundamental changes correspond to the rapid cortical development at this age. Manual sleep classification is specifically challenging in this population given major body movements and frequent shifts between vigilance states; in addition various staging criteria co-exist. In the present study we utilized a machine learning approach and investigated how EEG complexity and sleep stages evolve during the very first weeks of life. We analyzed 42 full-term infants which were recorded twice (at week two and five after birth) with full polysomnography. For sleep classification EEG signal complexity was estimated using multi-scale permutation entropy and fed into a machine learning classifier. Interestingly the baby's brain signal complexity (and spectral power) revealed developmental changes in sleep in the first 5 weeks of life, and were restricted to NREM ("quiet") and REM ("active sleep") states with little to no changes in state wake. Data demonstrate that our classifier performs well over chance (i.e., >33% for 3-class classification) and reaches almost human scoring accuracy (60% at week-2, 73% at week-5). Altogether, these results demonstrate that characteristics of newborn sleep develop rapidly in the first weeks of life and can be efficiently identified by means of machine learning techniques.

Postnatal maternal symptoms of depression and child emotion dysregulation: The mediation role of infant EEG alpha asymmetry.

In a community-based sample of 104 infants and their mothers, we hypothesized a pathway from postnatal maternal symptoms of depression to child emotion dysregulation, and tested at 6 months of age the mediation role of alpha asymmetry at frontal and parietal sites. We recorded infant resting-state EEG at 6 months of age. Child emotion dysregulation was measured at 24 months by the Child Behavior Checklist Dysregulation Profile derived from the CBCL 1½-5. Maternal depression symptoms were scored 6 months after the delivery by the Anxious/Depressed scale of the Adult Self-Report. We used structural equation modeling to test the mediation model from maternal depression symptoms to child emotion dysregulation mediated by frontal and parietal alpha asymmetry. The mediation model provided an excellent fit to the data [χ2(3) = 3.088, p = .378; RMSEA = .017, CFI = .1.00; SRMR = 0.040] and explained 23.3% of the variance in child emotion dysregulation. The indirect path via parietal alpha asymmetry was significant (ß = .065; SE = .033; 95% CI = .001-.139; p = .048), i.e. greater levels of maternal depression symptoms predicted left parietal alpha asymmetry, which predicted higher levels of child emotion dysregulation. The direct effect, i.e. the pathway linking maternal depression symptoms and child emotion dysregulation above and beyond the indirect effects, was also significant. We found evidence for a partial mediation role of left parietal alpha asymmetry in a longitudinal pathway from postnatal maternal symptoms of depression to child emotion dysregulation, providing support for left parietal asymmetry as an index of biological vulnerability to emotion dysregulation in the first years of life.

Standing sentinel during human sleep: Continued evaluation of environmental stimuli in the absence of consciousness.

While it is a well-established finding that subjects' own names (SON) and familiar voices are salient during wakefulness, we here investigated processing of environmental stimuli during sleep including deep N3 and REM sleep. Besides the effects of sleep depth we investigated how sleep-specific EEG patterns (i.e. sleep spindles and slow oscillations [SOs]) relate to stimulus processing. Using 256-channel EEG we studied processing of auditory stimuli by means of event-related oscillatory responses (de-/synchronisation, ERD/ERS) and potentials (ERPs) in N = 17 healthy sleepers. We varied stimulus salience by manipulating subjective (SON vs. unfamiliar name) and paralinguistic emotional relevance (familiar vs. unfamiliar voice, FV/UFV). Results reveal that evaluation of voice familiarity continues during all NREM sleep stages and even REM sleep suggesting a 'sentinel processing mode' of the human brain in the absence of wake-like consciousness. Especially UFV stimuli elicit larger responses in a 1-15 Hz range suggesting they continue being salient. Beyond this, we find that sleep spindles and the negative slope of SOs attenuate information processing. However, unlike previously suggested they do not uniformly inhibit information processing, but inhibition seems to be scaled to stimulus salience.

Sleep in patients with disorders of consciousness characterized by means of machine learning.

Sleep has been proposed to indicate preserved residual brain functioning in patients suffering from disorders of consciousness (DOC) after awakening from coma. However, a reliable characterization of sleep patterns in this clinical population continues to be challenging given severely altered brain oscillations, frequent and extended artifacts in clinical recordings and the absence of established staging criteria. In the present study, we try to address these issues and investigate the usefulness of a multivariate machine learning technique based on permutation entropy, a complexity measure. Specifically, we used long-term polysomnography (PSG), along with video recordings in day and night periods in a sample of 23 DOC; 12 patients were diagnosed as Unresponsive Wakefulness Syndrome (UWS) and 11 were diagnosed as Minimally Conscious State (MCS). Eight hour PSG recordings of healthy sleepers (N = 26) were additionally used for training and setting parameters of supervised and unsupervised model, respectively. In DOC, the supervised classification (wake, N1, N2, N3 or REM) was validated using simultaneous videos which identified periods with prolonged eye opening or eye closure.The supervised classification revealed that out of the 23 subjects, 11 patients (5 MCS and 6 UWS) yielded highly accurate classification with an average F1-score of 0.87 representing high overlap between the classifier predicting sleep (i.e. one of the 4 sleep stages) and closed eyes. Furthermore, the unsupervised approach revealed a more complex pattern of sleep-wake stages during the night period in the MCS group, as evidenced by the presence of several distinct clusters. In contrast, in UWS patients no such clustering was found. Altogether, we present a novel data-driven method, based on machine learning that can be used to gain new and unambiguous insights into sleep organization and residual brain functioning of patients with DOC.

Significance of circadian rhythms in severely brain-injured patients: A clue to consciousness?

OBJECTIVE: To investigate the relationship between the presence of a circadian body temperature rhythm and behaviorally assessed consciousness levels in patients with disorders of consciousness (DOC; i.e., vegetative state/unresponsive wakefulness syndrome or minimally conscious state). METHODS: In a cross-sectional study, we investigated the presence of circadian temperature rhythms across 6 to 7 days using external skin temperature sensors in 18 patients with DOC. Beyond this, we examined the relationship between behaviorally assessed consciousness levels and circadian rhythmicity. RESULTS: Analyses with Lomb-Scargle periodograms revealed significant circadian rhythmicity in all patients (range 23.5-26.3 hours). We found that especially scores on the arousal subscale of the Coma Recovery Scale-Revised were closely linked to the integrity of circadian variations in body temperature. Finally, we piloted whether bright light stimulation could boost circadian rhythmicity and found positive evidence in 2 out of 8 patients. CONCLUSION: The study provides evidence for an association between circadian body temperature rhythms and arousal as a necessary precondition for consciousness. Our findings also make a case for circadian rhythms as a target for treatment as well as the application of diagnostic and therapeutic means at times when cognitive performance is expected to peak.

Night and day variations of sleep in patients with disorders of consciousness.

Brain injuries substantially change the entire landscape of oscillatory dynamics and render detection of typical sleep patterns difficult. Yet, sleep is characterized not only by specific EEG waveforms, but also by its circadian organization. In the present study we investigated whether brain dynamics of patients with disorders of consciousness systematically change between day and night. We recorded ~24 h EEG at the bedside of 18 patients diagnosed to be vigilant but unaware (Unresponsive Wakefulness Syndrome) and 17 patients revealing signs of fluctuating consciousness (Minimally Conscious State). The day-to-night changes in (i) spectral power, (ii) sleep-specific oscillatory patterns and (iii) signal complexity were analyzed and compared to 26 healthy control subjects. Surprisingly, the prevalence of sleep spindles and slow waves did not systematically vary between day and night in patients, whereas day-night changes in EEG power spectra and signal complexity were revealed in minimally conscious but not unaware patients.

Preferential processing of emotionally and self-relevant stimuli persists in unconscious N2 sleep.

Information processing has been suggested to depend on the current state of the brain as well as stimulus characteristics (e.g. salience). We compared processing of salient stimuli (subject's own names [SONs] and angry voice [AV] stimuli) to processing of unfamiliar names (UNs) and neutral voice (NV) stimuli across different vigilance stages (i.e. wakefulness as well as sleep stages N1 and N2) by means of event-related oscillatory responses during wakefulness and a subsequent afternoon nap. Our findings suggest that emotional prosody and self-relevance drew more attentional resources during wakefulness with specifically AV stimuli being processed more strongly. During N1, SONs were more arousing than UNs irrespective of prosody. Moreover, emotional and self-relevant stimuli evoked stronger responses also during N2 sleep suggesting a 'sentinel processing mode' of the brain during this state of naturally occurring unconsciousness. Finally, this initial preferential processing of salient stimuli during N2 sleep seems to be followed by an inhibitory sleep-protecting process, which is reflected by a K-complex-like response.

The Voice of Anger: Oscillatory EEG Responses to Emotional Prosody.

Emotionally relevant stimuli and in particular anger are, due to their evolutionary relevance, often processed automatically and able to modulate attention independent of conscious access. Here, we tested whether attention allocation is enhanced when auditory stimuli are uttered by an angry voice. We recorded EEG and presented healthy individuals with a passive condition where unfamiliar names as well as the subject's own name were spoken both with an angry and neutral prosody. The active condition instead, required participants to actively count one of the presented (angry) names. Results revealed that in the passive condition the angry prosody only elicited slightly stronger delta synchronization as compared to a neutral voice. In the active condition the attended (angry) target was related to enhanced delta/theta synchronization as well as alpha desynchronization suggesting enhanced allocation of attention and utilization of working memory resources. Altogether, the current results are in line with previous findings and highlight that attention orientation can be systematically related to specific oscillatory brain responses. Potential applications include assessment of non-communicative clinical groups such as post-comatose patients.

Can self-relevant stimuli help assessing patients with disorders of consciousness?

Emotional and self-relevant stimuli are able to automatically attract attention and their use in patients suffering from disorders of consciousness (DOC) might help detecting otherwise hidden signs of cognition. We here recorded EEG in three Locked-in syndrome (LIS) and four Vegetative State/Unresponsive Wakefulness Syndrome (VS/UWS) patients while they listened to the voice of a family member or an unfamiliar voice during a passive. Data indicate that, in a passive listening condition, the familiar voice induces stronger alpha desynchronization than the unfamiliar one. In an active condition, the target evoked stronger alpha desynchronization in controls, two LIS patients and one VS/UWS patient. Results suggest that self-relevant familiar voice stimuli can engage additional attentional resources and might allow the detection of otherwise hidden signs of instruction-following and thus residual awareness. Further studies are necessary to find sensitive paradigms that are suited to find subtle signs of cognition and awareness in DOC patients.

EEG oscillations reflect the complexity of social interactions in a non-verbal social cognition task using animated triangles.

The ability to attribute independent mental states (e.g. opinions, perceptions, beliefs) to oneself and others is termed Theory of Mind (ToM). Previous studies investigating ToM usually employed verbal paradigms and functional neuroimaging methods. Here, we studied oscillatory responses in the electroencephalogram (EEG) in a non-verbal social cognition task. The aim of this study was twofold: First, we wanted to investigate differences in oscillatory responses to animations differing with regard to the complexity of social "interactions". Secondly, we intended to evaluate the basic cognitive processes underlying social cognition. To this end, we analyzed theta, alpha, beta and gamma task-related de-/synchronization (TRD/TRS) during presentation of six non-verbal videos differing in the complexity of (social) "interactions" between two geometric shapes. Videos were adopted from Castelli et al. (2000)and belonged to three conditions: Videos designed to evoke attributions of mental states (ToM), interaction descriptions (goal-directed, GD) and videos in which the shapes moved randomly (R). Analyses revealed that only theta activity consistently varied as a function of social "interaction" complexity. Results suggest that ToM/GD videos attract more attention and working-memory resources and may have activated related memory contents. Alpha and beta results were less consistent. While alpha effects suggest that observation of social "interactions" may benefit from inhibition of self-centered processing, oscillatory responses in the beta range could be related to action observation. In summary, the results provide insight into basic cognitive processes involved in social cognition and render the paradigm attractive for the investigation of social cognitive processes in non-verbal populations.

Across the consciousness continuum-from unresponsive wakefulness to sleep.

Advances in the development of new paradigms as well as in neuroimaging techniques nowadays enable us to make inferences about the level of consciousness patients with disorders of consciousness (DOC) retain. They, moreover, allow to predict their probable development. Today, we know that certain brain responses (e.g., event-related potentials or oscillatory changes) to stimulation, circadian rhythmicity, the presence or absence of sleep patterns as well as measures of resting state brain activity can serve the diagnostic and prognostic evaluation process. Still, the paradigms we are using nowadays do not allow to disentangle VS/UWS and minimally conscious state (MCS) patients with the desired reliability and validity. Furthermore, even rather well-established methods have, unfortunately, not found their way into clinical routine yet. We here review current literature as well as recent findings from our group and discuss how neuroimaging methods (fMRI, PET) and particularly electroencephalography (EEG) can be used to investigate cognition in DOC or even to assess the degree of residual awareness. We, moreover, propose that circadian rhythmicity and sleep in brain-injured patients are promising fields of research in this context.

Oscillatory brain responses to own names uttered by unfamiliar and familiar voices.

Among auditory stimuli, the own name is one of the most powerful and it is able to automatically capture attention and elicit a robust electrophysiological response. The subject's own name (SON) is preferentially processed in the right hemisphere, mainly because of its self-relevance and emotional content, together with other personally relevant information such as the voice of a familiar person. Whether emotional and self-relevant information are able to attract attention and can be, in future, introduced in clinical studies remains unclear. In the present study we used EEG and asked participants to count a target name (active condition) or to just listen to the SON or other unfamiliar names uttered by a familiar or unfamiliar voice (passive condition). Data reveals that the target name elicits a strong alpha event related desynchronization with respect to non-target names and triggers in addition a left lateralized theta synchronization as well as delta synchronization. In the passive condition alpha desynchronization was observed for familiar voice and SON stimuli in the right hemisphere. Altogether we speculate that participants engage additional attentional resources when counting a target name or when listening to personally relevant stimuli which is indexed by alpha desynchronization whereas left lateralized theta synchronization may be related to verbal working memory load. After validating the present protocol in healthy volunteers it is suggested to move one step further and apply the protocol to patients with disorders of consciousness in which the degree of residual cognitive processing and self-awareness is still insufficiently understood.