Dr Zsofia Zavecz

Lucid dreaming (LD) is a state of conscious awareness of the ongoing oneiric state, predominantly linked to REM sleep. Progress in understanding its neurobiological basis has been hindered by small sample sizes, diverse EEG setups, and artifacts like saccadic eye movements. To address these challenges in characterizing the electrophysiological correlates of LD, we introduced an adaptive multistage preprocessing pipeline, applied to human data (male and female) pooled across laboratories, allowing us to explore sensor- and source-level markers of LD. We observed that, while sensor-level differences between LD and nonlucid REM sleep were minimal, mixed-frequency analysis revealed broad low alpha to gamma power reductions during LD compared with wakefulness. Source-level analyses showed significant beta power (12-30 Hz) reductions in right central and parietal areas, including the temporoparietal junction, during LD. Moreover, functional connectivity in the alpha band (8-12 Hz) increased during LD compared with nonlucid REM sleep. During initial LD eye signaling compared with the baseline, source-level gamma1 power (30-36 Hz) increased in right temporo-occipital regions, including the right precuneus. Finally, functional connectivity analysis revealed increased interhemispheric and inter-regional gamma1 connectivity during LD, reflecting widespread network engagement. These results suggest that distinct source-level power and connectivity patterns characterize the dynamic neural processes underlying LD, including shifts in network communication and regional activation that may underlie the specific changes in perception, memory processing, self-awareness, and cognitive control. Taken together, these findings illuminate the electrophysiological correlates of LD, laying the groundwork for decoding the mechanisms of this intriguing state of consciousness.

Spontaneous reactivation of brain activity from learning to a subsequent off-line period has been implicated as a neural mechanism underlying memory consolidation. However, similarities in brain activity may also emerge as a result of individual, trait-like characteristics. Here, we introduced a novel approach for analyzing continuous electroencephalography (EEG) data to investigate learning-induced changes as well as trait-like characteristics in brain activity underlying memory consolidation. Thirty-one healthy young adults performed a learning task, and their performance was retested after a short (∼1 h) delay. Consolidation of two distinct types of information (serial-order and probability) embedded in the task were tested to reveal similarities in functional networks that uniquely predict the changes in the respective memory performance. EEG was recorded during learning and pre- and post-learning rest periods. To investigate brain activity associated with consolidation, we quantified similarities in EEG functional connectivity between learning and pre-learning rest (baseline similarity) and learning and post-learning rest (post-learning similarity). While comparable patterns of these two could indicate trait-like similarities, changes from baseline to post-learning similarity could indicate learning-induced changes, possibly spontaneous reactivation. Higher learning-induced changes in alpha frequency connectivity (8.5–9.5 Hz) were associated with better consolidation of serial-order information, particularly for long-range connections across central and parietal sites. The consolidation of probability information was associated with learning-induced changes in delta frequency connectivity (2.5–3 Hz) specifically for more local, short-range connections. Furthermore, there was a substantial overlap between the baseline and post-learning similarities and their associations with consolidation performance, suggesting robust (trait-like) differences in functional connectivity networks underlying memory processes.

Healthy sleep is essential in children’s cognitive, behavioral, and emotional development. However, remarkably little is known about the influence of sleep disorders on different memory processes in childhood. Such data could give us a deeper insight into the effect of sleep on the developing brain and memory functions and how the relationship between sleep and memory changes from childhood to adulthood. In the present study we examined the effect of sleep disorder on declarative and non-declarative memory consolidation by testing children with sleep-disordered breathing (SDB) which is characterized by disrupted sleep structure. We used a story recall task to measure declarative memory and Alternating Serial Reaction time (ASRT) task to assess non-declarative memory. This task enables us to measure two aspects of non-declarative memory, namely general motor skill learning and sequence-specific learning. There were two sessions: a learning phase and a testing phase, separated by a 12 h offline period with sleep. Our data showed that children with SDB exhibited a generally lower declarative memory performance both in the learning and testing phase; however, both the SDB and control groups exhibited retention of the previously recalled items after the offline period. Here we showed intact non-declarative consolidation in SDB group in both sequence-specific and general motor skill. These findings suggest that sleep disorders in childhood have a differential effect on different memory processes (online vs. offline) and give us insight into how sleep disturbances affects developing brain.

Probabilistic learning is a fundamental cognitive ability that extracts and represents regularities of our environment enabling predictive processing during perception and acquisition of perceptual, motor, cognitive, and social skills. Previous studies show competition between neural networks related to executive function/working memory vs. probabilistic learning. Theta synchronization has been associated with the former while desynchronization with the latter in correlational studies. In the present paper our aim was to test causal relationship between fronto-parietal midline theta synchronization and probabilistic learning with non-invasive transcranial alternating current (tACS) stimulation. We hypothesize that theta synchronization disrupts probabilistic learning performance by modulating the competitive relationship. Twenty-six young adults performed the Alternating Serial Reaction Time (ASRT) task to assess probabilistic learning in two sessions that took place one week apart. Stimulation was applied in a double-blind cross-over within-subject design with an active theta tACS and a sham stimulation in a counter-balanced order between participants. Sinusoidal current was administered with 1 mA peak-to-peak intensity throughout the task (approximately 20 min) for the active stimulation and 30 s for the sham. We did not find an effect of fronto-parietal midline theta tACS on probabilistic learning comparing performance during active and sham stimulation. To influence probabilistic learning, we suggest applying higher current intensity and stimulation parameters more precisely aligned to endogenous brain activity for future studies.

The role of subjective sleep quality in cognitive performance has gained increasing attention in recent decades. In this paper, our aim was to test the relationship between subjective sleep quality and a wide range of cognitive functions in a healthy young adult sample combined across three studies. Sleep quality was assessed by the Pittsburgh Sleep Quality Index, the Athens Insomnia Scale, and a sleep diary to capture general subjective sleep quality, and the Groningen Sleep Quality Scale to capture prior night’s sleep quality. Within cognitive functions, we tested working memory, executive functions, and several sub-processes of procedural learning. To provide more reliable results, we included robust frequentist as well as Bayesian statistical analyses. Unequivocally across all analyses, we showed that there is no association between subjective sleep quality and cognitive performance in the domains of working memory, executive functions and procedural learning in healthy young adults. Our paper can contribute to a deeper understanding of subjective sleep quality and its measures, and we discuss various factors that may affect whether associations can be observed between subjective sleep quality and cognitive performance.

Study Objectives. Voluntary sleep restriction is a common phenomenon in industrialized societies aiming to increase time spent awake and thus productivity. We explored how restricting sleep to a radically polyphasic schedule affects neural, cognitive, and endocrine characteristics. Methods. Ten young healthy participants were restricted to one 20-minute nap opportunity at the end of every 4 hours (i.e. six sleep episodes per 24 hours) without any extended core sleep window, which resulted in a cumulative sleep amount of just 2 hours per day (i.e. similar to 20 minutes per bout). Results. All but one participant terminated this schedule during the first month. The remaining participant (a 25-year-old male) succeeded in adhering to a polyphasic schedule for five out of the eight planned weeks. Cognitive and psychiatric measures showed modest changes during polyphasic as compared to monophasic sleep, while in-blood cortisol or melatonin release patterns and amounts were apparently unaltered. In contrast, growth hormone release was almost entirely abolished (>95% decrease), with the residual release showing a considerably changed polyphasic secretional pattern. Conclusions. Even though the study was initiated by volunteers with exceptional intrinsic motivation and commitment, none of them could tolerate the intended 8 weeks of the polyphasic schedule. Considering the decreased vigilance, abolished growth hormone release, and neurophysiological sleep changes observed, it is doubtful that radically polyphasic sleep schedules can subserve the different functions of sleep to a sufficient degree.

A great body of research indicates that eveningness is associated with negative psychological outcomes, including depressive and anxiety symptoms, behavioral dyscontrol and different health impairing behaviors. Impaired subjective sleep quality, increased circadian misalignment and daytime sleepiness were also reported in evening-type individuals in comparison with morning-types. Although sleep problems were consistently reported to be associated with poor psychological functioning, the effects of sleep disruption on the relationship between eveningness preference and negative emotionality have scarcely been investigated. Here, based on questionnaire data of 756 individuals (25.5% males, age range = 18-43 years, mean = 25.3 +/- 5.8 years), as well as of the evening-type (N = 211) and morning-type (N = 189) subgroups, we examined the relationship among sleep problems, eveningness and negative emotionality. Subjects completed the Hungarian Version of the Horne and Ostberg Morningness-Eveningness Questionnaire (MEQ-14), The Athen Insomnia Scale (AIS) and the Epworth Sleepiness Scale (ESS). Moreover, a composite score of Negative Emotionality (NE) was computed based on the scores of the Short Beck Depression Inventory (BDI-9), the Perceived Stress Scale (PSS-4) and the General Health Questionnaire (GHQ-12). Morning and evening circadian misalignment was calculated based on the difference between preferred and real wake-and bedtimes. Two possible models were tested, hypothesizing that sleep problems (circadian misalignment, insomniac symptoms and daytime sleepiness) moderate or mediate the association between eveningness and negative emotionality. Eveningness preference was correlated with increased NE and increased AIS, ESS and circadian misalignment scores. Our results indicate that eveningness-preference is an independent risk factor for higher negative emotionality regardless of the effects of age, gender, circadian misalignment and sleep complaints. Nevertheless, while chronotype explained similar to 6%, sleep problems (AIS and ESS) accounted for a much larger proportion (similar to 28%) of the variance of NE. We did not find a significant effect of interaction (moderation) between chronotype and sleep problems. In contrast, insomniac symptoms (AIS) emerged as a partial mediator between chronotype and NE. These findings argue against the assumption that indicators of mental health problems in evening-type individuals can be explained exclusively on the basis of disturbed sleep. Nevertheless, negative psychological outcomes seem to be partially attributable to increased severity of insomniac complaints in evening-types.

Statistical learning is a fundamental mechanism of the brain, which extracts and represents regularities of our environment. Statistical learning is crucial in predictive processing, and in the acquisition of perceptual, motor, cognitive, and social skills. Although previous studies have revealed competitive neu-rocognitive processes underlying statistical learning, the neural communication of the related brain regions (functional connectivity, FC) has not yet been investigated. The present study aimed to fill this gap by investigating FC networks that promote statistical learning in humans. Young adults (N = 28) performed a statistical learning task while 128-channels EEG was acquired. The task involved probabilistic sequences, which enabled to measure incidental/implicit learning of conditional probabilities. Phase synchronization in seven frequency bands was used to quantify FC between cortical regions during the first, second, and third periods of the learning task, respectively. Here we show that statistical learning is negatively correlated with FC of the anterior brain regions in slow (theta) and fast (beta) oscillations. These negative correlations increased as the learning progressed. Our findings provide evidence that dynamic antagonist brain networks serve a hallmark of statistical learning. (C) 2017 Elsevier Inc. All rights reserved.