Quality of life in children with epilepsy: The role of parental mental health and sleep disruption.

BACKGROUND: Parents of children with epilepsy (CWE) are at increased risk of mental health difficulties including anxiety and depression, as well as sleep difficulties. From both the child's and parent's perspectives, health-related quality of life has been shown to be strongly related to parental mental health. However, there is no literature on parental sleep as a predictor of child health-related quality of life. The role of parental variables has been assessed in relation to epilepsy-specific variables (e.g., seizure severity, anti-seizure medications) and how these relate to health-related quality of life, but prior studies have failed to consider the role of co-occurring conditions which are prevalent in CWE. The current study aims to assess how common anxiety symptoms, depression symptoms and sleep problems are in parents of CWE; and to determine the impact these parental variables as well as child co-occurring conditions have on health-related quality of life in CWE. METHODS: 33 CWE aged 4-14 years old were recruited from two hospitals and parents were asked to complete a series of questionnaires assessing both child and parental variables. RESULTS: It was found that 33.3 % and 12.0 % of parents of CWE experienced clinically significant anxiety and depression symptoms respectively. In addition 67.9 % of parents presented with significant sleep problems. In initial analysis, parental anxiety symptoms, depression symptoms and sleep problems were all significantly predictive of child health-related quality of life. However when co-occurring child sleep problems and neurodevelopmental characteristics were included, parental variables were no longer significantly predictive of child health-related quality of life. CONCLUSION: These results suggest that child co-occurrences mediate the relationship between parental variables and child health-related quality of life. The current data highlight the need for a systemic approach to epilepsy management and suggest that support for co-occurrences could benefit health-related quality of life for children and their parents.

Brain state dynamics differ between eyes open and eyes closed rest.

The human brain exhibits spatio-temporally complex activity even in the absence of external stimuli, cycling through recurring patterns of activity known as brain states. Thus far, brain state analysis has primarily been restricted to unimodal neuroimaging data sets, resulting in a limited definition of state and a poor understanding of the spatial and temporal relationships between states identified from different modalities. Here, we applied hidden Markov model (HMM) to concurrent electroencephalography-functional magnetic resonance imaging (EEG-fMRI) eyes open (EO) and eyes closed (EC) resting-state data, training models on the EEG and fMRI data separately, and evaluated the models' ability to distinguish dynamics between the two rest conditions. Additionally, we employed a general linear model approach to identify the BOLD correlates of the EEG-defined states to investigate whether the fMRI data could be used to improve the spatial definition of the EEG states. Finally, we performed a sliding window-based analysis on the state time courses to identify slower changes in the temporal dynamics, and then correlated these time courses across modalities. We found that both models could identify expected changes during EC rest compared to EO rest, with the fMRI model identifying changes in the activity and functional connectivity of visual and attention resting-state networks, while the EEG model correctly identified the canonical increase in alpha upon eye closure. In addition, by using the fMRI data, it was possible to infer the spatial properties of the EEG states, resulting in BOLD correlation maps resembling canonical alpha-BOLD correlations. Finally, the sliding window analysis revealed unique fractional occupancy dynamics for states from both models, with a selection of states showing strong temporal correlations across modalities. Overall, this study highlights the efficacy of using HMMs for brain state analysis, confirms that multimodal data can be used to provide more in-depth definitions of state and demonstrates that states defined across different modalities show similar temporal dynamics.

Shorter night-time sleep duration and later sleep timing from infancy to adolescence.

BACKGROUND: Here, we (a) examined the trajectories of night-time sleep duration, bedtime and midpoint of night-time sleep (MPS) from infancy to adolescence, and (b) explored perinatal risk factors for persistent poor sleep health. METHODS: This study used data from 12,962 participants in the Avon Longitudinal Study of Parents and Children (ALSPAC). Parent or self-reported night-time sleep duration, bedtime and wake-up time were collected from questionnaires at 6, 18 and 30 months, and at 3.5, 4-5, 5-6, 6-7, 9, 11 and 15-16 years. Child's sex, birth weight, gestational age, health and temperament, together with mother's family adversity index (FAI), age at birth, prenatal socioeconomic status and postnatal anxiety and depression, were included as risk factors for persistent poor sleep health. Latent class growth analyses were applied first to detect trajectories of night-time sleep duration, bedtime and MPS, and we then applied logistic regressions for the longitudinal associations between risk factors and persistent poor sleep health domains. RESULTS: We obtained four trajectories for each of the three sleep domains. In particular, we identified a trajectory characterized by persistent shorter sleep, a trajectory of persistent later bedtime and a trajectory of persistent later MPS. Two risk factors were associated with the three poor sleep health domains: higher FAI with increased risk of persistent shorter sleep (OR = 1.20, 95% CI = 1.11-1.30, p < .001), persistent later bedtime (OR = 1.28, 95% CI = 1.19-1.39, p < .001) and persistent later MPS (OR = 1.30, 95% CI = 1.22-1.38, p < .001); and higher maternal socioeconomic status with reduced risk of persistent shorter sleep (OR = 0.99, 95% CI = 0.98-1.00, p = .048), persistent later bedtime (OR = 0.98, 95% CI = 0.97-0.99, p < .001) and persistent later MPS (OR = 0.99, 95% CI = 0.98-0.99, p < .001). CONCLUSIONS: We detected trajectories of persistent poor sleep health (i.e. shorter sleep duration, later bedtime and later MPS) from infancy to adolescence, and specific perinatal risk factors linked to persistent poor sleep health domains.

Exploring an objective measure of overactivity in children with rare genetic syndromes.

BACKGROUND: Overactivity is prevalent in several rare genetic neurodevelopmental syndromes, including Smith-Magenis syndrome, Angelman syndrome, and tuberous sclerosis complex, although has been predominantly assessed using questionnaire techniques. Threats to the precision and validity of questionnaire data may undermine existing insights into this behaviour. Previous research indicates objective measures, namely actigraphy, can effectively differentiate non-overactive children from those with attention-deficit hyperactivity disorder. This study is the first to examine the sensitivity of actigraphy to overactivity across rare genetic syndromes associated with intellectual disability, through comparisons with typically-developing peers and questionnaire overactivity estimates. METHODS: A secondary analysis of actigraphy data and overactivity estimates from The Activity Questionnaire (TAQ) was conducted for children aged 4-15 years with Smith-Magenis syndrome (N=20), Angelman syndrome (N=26), tuberous sclerosis complex (N=16), and typically-developing children (N=61). Actigraphy data were summarized using the M10 non-parametric circadian rhythm variable, and 24-hour activity profiles were modelled via functional linear modelling. Associations between actigraphy data and TAQ overactivity estimates were explored. Differences in actigraphy-defined activity were also examined between syndrome and typically-developing groups, and between children with high and low TAQ overactivity scores within syndromes. RESULTS: M10 and TAQ overactivity scores were strongly positively correlated for children with Angelman syndrome and Smith-Magenis syndrome. M10 did not substantially differ between the syndrome and typically-developing groups. Higher early morning activity and lower evening activity was observed across all syndrome groups relative to typically-developing peers. High and low TAQ group comparisons revealed syndrome-specific profiles of overactivity, persisting throughout the day in Angelman syndrome, occurring during the early morning and early afternoon in Smith-Magenis syndrome, and manifesting briefly in the evening in tuberous sclerosis complex. DISCUSSION: These findings provide some support for the sensitivity of actigraphy to overactivity in children with rare genetic syndromes, and offer syndrome-specific temporal descriptions of overactivity. The findings advance existing descriptions of overactivity, provided by questionnaire techniques, in children with rare genetic syndromes and have implications for the measurement of overactivity. Future studies should examine the impact of syndrome-related characteristics on actigraphy-defined activity and overactivity estimates from actigraphy and questionnaire techniques.

Circadian distribution of epileptiform discharges in epilepsy: Candidate mechanisms of variability.

Epilepsy is a serious neurological disorder characterised by a tendency to have recurrent, spontaneous, seizures. Classically, seizures are assumed to occur at random. However, recent research has uncovered underlying rhythms both in seizures and in key signatures of epilepsy-so-called interictal epileptiform activity-with timescales that vary from hours and days through to months. Understanding the physiological mechanisms that determine these rhythmic patterns of epileptiform discharges remains an open question. Many people with epilepsy identify precipitants of their seizures, the most common of which include stress, sleep deprivation and fatigue. To quantify the impact of these physiological factors, we analysed 24-hour EEG recordings from a cohort of 107 people with idiopathic generalized epilepsy. We found two subgroups with distinct distributions of epileptiform discharges: one with highest incidence during sleep and the other during day-time. We interrogated these data using a mathematical model that describes the transitions between background and epileptiform activity in large-scale brain networks. This model was extended to include a time-dependent forcing term, where the excitability of nodes within the network could be modulated by other factors. We calibrated this forcing term using independently-collected human cortisol (the primary stress-responsive hormone characterised by circadian and ultradian patterns of secretion) data and sleep-staged EEG from healthy human participants. We found that either the dynamics of cortisol or sleep stage transition, or a combination of both, could explain most of the observed distributions of epileptiform discharges. Our findings provide conceptual evidence for the existence of underlying physiological drivers of rhythms of epileptiform discharges. These findings should motivate future research to explore these mechanisms in carefully designed experiments using animal models or people with epilepsy.

Concordance of objective and subjective measures of sleep in children with neurodevelopmental conditions: A systematic review and meta-analysis.

The purpose of this systematic review and meta-analysis is to delineate the concordance of objective and subjective measures of sleep in children with neurodevelopmental conditions (NDCs). A systematic literature search identified 31 studies that compare objective and subjective estimates of sleep parameters in autism, ADHD or rare genetic syndromes associated with intellectual disability. The meta-analyses revealed smaller mean differences and larger correlations indicative of greater concordance for parameters associated with sleep scheduling compared to parameters associated with sleep duration and night awakenings. Relative to objective measures, subjective measures produced: 1) greater estimates of total sleep time, sleep efficiency and time in bed; and 2) lower estimates of wake after sleep onset and number of night awakenings. Subgroup analyses also revealed differences in concordance between measurement comparison types (e.g., stronger correlations between actigraphy and sleep diaries, compared to actigraphy and questionnaires) and NDC diagnostic groups. The results predominantly replicate concordance trends observed in typically-developing samples, although some NDC-specific patterns of concordance were identified. This indicates that objective and subjective sleep measures retain broadly similar properties across populations, although researchers and clinicians should be cautious of the impact of NDC-related characteristics on sleep parameter estimates. These findings should inform sleep assessment design and the interpretation of sleep parameter estimates in NDCs, increasing the rigour of sleep parameter description across research and clinical settings.

The contribution of sleep and co-occurring neurodevelopmental conditions to quality of life in children with epilepsy.

BACKGROUND: Health-related quality of life (HRQOL) in children with epilepsy (CWE) is multifactorial and can be affected not only by epilepsy-specific variables but also co-occurring conditions such as sleep disturbances, autism, and attention deficit hyperactivity disorder (ADHD). While highly prevalent in CWE, these conditions are underdiagnosed despite having a significant impact on HRQOL. Sleep problems have a complex relationship with epilepsy and neurodevelopmental characteristics. However, little is known about how these issues interact and contribute to HRQOL. OBJECTIVES: The current study aims to explore the relationship between sleep and neurodevelopmental characteristics on HRQOL in CWE. METHODS: 36 CWE aged 4-16 years old were recruited from two hospitals and asked to wear an actiwatch for a period of 14 days and caregivers completed a series of questionnaires assessing co-occurrences and epilepsy-specific variables. RESULTS: A high proportion of CWE (78.13%) presented significant sleep problems. Informant-reported sleep problems were significantly predictive of HRQOL above seizure severity and the number of antiseizure medications. Interestingly, informant-reported sleep problems were no longer significantly predictive of HRQOL when neurodevelopmental characteristics were considered, indicating a possible mediating effect. Similarly, actigraphy-defined sleep (variability in sleep onset latency) displayed a similar effect but only for ADHD characteristics, whereas autistic characteristics and variability in sleep onset latency continued to exert an individual effect on HRQOL. CONCLUSION: These data from our study shed light on the complicated relationship between sleep, neurodevelopmental characteristics and epilepsy. Findings suggest that the impact of sleep on HRQOL in CWE is possibly mediated by neurodevelopmental characteristics. Furthermore, the impact this triangular relationship exerts on HRQOL is dependent on the type of tool used to measure sleep. These findings highlight the importance of a multidisciplinary approach to epilepsy management.

Classification of human chronotype based on fMRI network-based statistics.

Chronotype-the relationship between the internal circadian physiology of an individual and the external 24-h light-dark cycle-is increasingly implicated in mental health and cognition. Individuals presenting with a late chronotype have an increased likelihood of developing depression, and can display reduced cognitive performance during the societal 9-5 day. However, the interplay between physiological rhythms and the brain networks that underpin cognition and mental health is not well-understood. To address this issue, we use rs-fMRI collected from 16 people with an early chronotype and 22 people with a late chronotype over three scanning sessions. We develop a classification framework utilizing the Network Based-Statistic methodology, to understand if differentiable information about chronotype is embedded in functional brain networks and how this changes throughout the day. We find evidence of subnetworks throughout the day that differ between extreme chronotypes such that high accuracy can occur, describe rigorous threshold criteria for achieving 97.3% accuracy in the Evening and investigate how the same conditions hinder accuracy for other scanning sessions. Revealing differences in functional brain networks based on extreme chronotype suggests future avenues of research that may ultimately better characterize the relationship between internal physiology, external perturbations, brain networks, and disease.

SLIPMAT: A pipeline for extracting tissue-specific spectral profiles from 1H MR spectroscopic imaging data.

1H Magnetic Resonance Spectroscopy (MRS) is an important non-invasive tool for measuring brain metabolism, with numerous applications in the neuroscientific and clinical domains. In this work we present a new analysis pipeline (SLIPMAT), designed to extract high-quality, tissue-specific, spectral profiles from MR spectroscopic imaging data (MRSI). Spectral decomposition is combined with spatially dependant frequency and phase correction to yield high SNR white and grey matter spectra without partial-volume contamination. A subsequent series of spectral processing steps are applied to reduce unwanted spectral variation, such as baseline correction and linewidth matching, before direct spectral analysis with machine learning and traditional statistical methods. The method is validated using a 2D semi-LASER MRSI sequence, with a 5-minute duration, from data acquired in triplicate across 8 healthy participants. Reliable spectral profiles are confirmed with principal component analysis, revealing the importance of total-choline and scyllo-inositol levels in distinguishing between individuals - in good agreement with our previous work. Furthermore, since the method allows the simultaneous measurement of metabolites in grey and white matter, we show the strong discriminative value of these metabolites in both tissue types for the first time. In conclusion, we present a novel and time efficient MRSI acquisition and processing pipeline, capable of detecting reliable neuro-metabolic differences between healthy individuals, and suitable for the sensitive neurometabolic profiling of in-vivo brain tissue.

Bisulfite probing reveals DNA structural intricacies.

In recent decades, study of DNA structure has largely been focused on the interrelationships between nucleotides at the level of nearest neighbours. A little-utilized approach to probing structure on a larger scale is non-denaturing bisulfite modification of genomic DNA in conjunction with high-throughput sequencing. This technique revealed a marked gradient in reactivity increasing towards the 5' end of poly-dC:dG mononucleotide repeats as short as two base pairs, suggesting that access of the anion may be greater at these points due to positive-roll bending not predicted by existing models. Consistent with this, the 5' ends of these repeats are strikingly enriched at positions relative to the nucleosome dyad that bend towards the major groove, while their 3' ends tend to sit outside these areas. Mutation rates are also higher at the 5' ends of poly-dC:dG when CpG dinucleotides are excluded. These findings shed light on the mechanisms underlying bending/flexibility of the DNA double helix as well as the sequences that facilitate DNA packaging.

Evidence for distinct neuro-metabolic phenotypes in humans.

Advances in magnetic resonance imaging have shown how individual differences in the structure and function of the human brain relate to health and cognition. The relationship between individual differences and the levels of neuro-metabolites, however, remains largely unexplored - despite the potential for the discovery of novel behavioural and disease phenotypes. In this study, we measured 14 metabolite levels, normalised as ratios to total-creatine, with 1H magnetic resonance spectroscopy (MRS) acquired from the bilateral anterior cingulate cortices of six healthy participants, repeatedly over a period of four months. ANOVA tests revealed statistically significant differences of 3 metabolites and 3 commonly used combinations (total-choline, glutamate + glutamine and total-N-acetylaspartate) between the participants, with scyllo-inositol (F=85, p=6e-26) and total-choline (F=39, p=1e-17) having the greatest discriminatory power. This was not attributable to structural differences. When predicting individuals from the repeated MRS measurements, a leave-one-out classification accuracy of 88% was achieved using a support vector machine based on scyllo-inositol and total-choline levels. Accuracy increased to 98% with the addition of total-N-acetylaspartate and myo-inositol - demonstrating the efficacy of combining MRS with machine learning and metabolomic methodology. These results provide evidence for the existence of neuro-metabolic phenotypes, which may be non-invasively measured using widely available 3 Tesla MRS. Establishing these phenotypes in a larger cohort and investigating their connection to brain health and function presents an important area for future study.

Proof-of-concept evidence for trimodal simultaneous investigation of human brain function.

The link between spatial (where) and temporal (when) aspects of the neural correlates of most psychological phenomena is not clear. Elucidation of this relation, which is crucial to fully understand human brain function, requires integration across multiple brain imaging modalities and cognitive tasks that reliably modulate the engagement of the brain systems of interest. By overcoming the methodological challenges posed by simultaneous recordings, the present report provides proof-of-concept evidence for a novel approach using three complementary imaging modalities: functional magnetic resonance imaging (fMRI), event-related potentials (ERPs), and event-related optical signals (EROS). Using the emotional oddball task, a paradigm that taps into both cognitive and affective aspects of processing, we show the feasibility of capturing converging and complementary measures of brain function that are not currently attainable using traditional unimodal or other multimodal approaches. This opens up unprecedented possibilities to clarify spatiotemporal integration of brain function.

Role of the Ipsilateral Primary Motor Cortex in the Visuo-Motor Network During Fine Contractions and Accurate Performance.

It is widely recognized that continuous sensory feedback plays a crucial role in accurate motor control in everyday life. Feedback information is used to adapt force output and to correct errors. While primary motor cortex contralateral to the movement (cM1) plays a dominant role in this control, converging evidence supports the idea that ipsilateral primary motor cortex (iM1) also directly contributes to hand and finger movements. Similarly, when visual feedback is available, primary visual cortex (V1) and its interactions with the motor network also become important for accurate motor performance. To elucidate this issue, we performed and integrated behavioral and electroencephalography (EEG) measurements during isometric compression of a compliant rubber bulb, at 10% and 30% of maximum voluntary contraction, both with and without visual feedback. We used a semi-blind approach (functional source separation (FSS)) to identify separate functional sources of mu-frequency (8-13[Formula: see text]Hz) EEG responses in cM1, iM1 and V1. Here for the first time, we have used orthogonal FSS to extract multiple sources, by using the same functional constraint, providing the ability to extract different sources that oscillate in the same frequency range but that have different topographic distributions. We analyzed the single-trial timecourses of mu power event-related desynchronization (ERD) in these sources and linked them with force measurements to understand which aspects are most important for good task performance. Whilst the amplitude of mu power was not related to contraction force in any of the sources, it was able to provide information on performance quality. We observed stronger ERDs in both contralateral and ipsilateral motor sources during trials where contraction force was most consistently maintained. This effect was most prominent in the ipsilateral source, suggesting the importance of iM1 to accurate performance. This ERD effect was sustained throughout the duration of visual feedback trials, but only present at the start of no feedback trials, consistent with more variable performance in the absence of feedback. Overall, we found that the behavior of the ERD in iM1 was the most informative aspect concerning the accuracy of the contraction performance, and the ability to maintain a steady level of contraction. This new approach of using FSS to extract multiple orthogonal sources provides the ability to investigate both contralateral and ipsilateral nodes of the motor network without the need for additional information (e.g. electromyography). The enhanced signal-to-noise ratio provided by FSS opens the possibility of extracting complex EEG features on an individual trial basis, which is crucial for a more nuanced understanding of fine motor performance, as well as for applications in brain-computer interfacing.

Sleep disruption in children and adolescents with epilepsy: A systematic review and meta-analysis.

This systematic review and meta-analysis aims to assess and quantify putative differences in sleep architecture, sleep efficiency, sleep timing and broadly-defined sleep difficulties between children with and without epilepsy. Databases were searched systematically, and studies identified in PubMed, EMBASE, PsychINFO and Medline. The meta-analysis included 19 studies comparing a total of 901 children with epilepsy to 1470 healthy children. Relative to healthy children, children with epilepsy experienced reduced sleep time, sleeping on average 34 mins less across self-report, actigraphy, 24-h video-EEG and polysomnography measures. They had more sleep difficulties specifically in the domains of night waking, parasomnias and sleep disordered breathing. The analysis also revealed a significantly increased percentage of N2 sleep and decreased sleep efficiency in children with epilepsy compared to healthy children. These results illustrate that children with epilepsy are vulnerable to more sleep difficulties compared to healthy children. This suggests that screening for sleep difficulties should be an integral part in a diagnosis of epilepsy to ensure that clinically relevant sleep difficulties are identified and treated. Such an approach may ultimately aid in the development of treatment strategies which can contribute to improvements in both developmental and diagnostic outcomes for children with epilepsy.

Temporal organisation of the brain's intrinsic motor network: The relationship with circadian phenotype and motor performance.

BACKGROUND: Functional connectivity (FC) of the motor network (MN) is often used to investigate how intrinsic properties of the brain are associated with motor abilities and performance. In addition, the MN is a key feature in clinical work to map the recovery after stroke and aid the understanding of neurodegenerative disorders. Time of day variation and individual differences in circadian timing, however, have not yet been considered collectively when looking at FC. METHODS: A total of 33 healthy, right handed individuals (13 male, 23.1 ± 4.2 years) took part in the study. Actigraphy, sleep diaries and circadian phase markers (dim light melatonin onset and cortisol awakening response) were used to determine early (ECP, n = 13) and late (LCP, n = 20) circadian phenotype groups. Resting state functional MRI testing sessions were conducted at 14:00 h, 20:00 h and 08:00 h and preceded by a maximum voluntary contraction test for isometric grip strength to measure motor performance. RESULTS: Significant differences in FC of the MN between ECPs and LCPs were found, as well as significant variations between different times of day. A higher amplitude in diurnal variation of FC and performance was observed in LCPs compared to ECPs, with the morning being most significantly affected. Overall, lower FC was significantly associated with poorer motor performance. DISCUSSION: Our findings uncover intrinsic differences between times of day and circadian phenotype groups. This suggests that central mechanisms contribute to diurnal variation in motor performance and the functional integrity of the MN at rest influences the ability to perform in a motor task.

Neurobiological evidence of longer-term physical activity interventions on mental health outcomes and cognition in young people: A systematic review of randomised controlled trials.

OBJECTIVE: To investigate putative neurobiological mechanisms that link longer-term physical activity interventions to mental health and cognitive outcomes using randomised controlled trials in children, adolescents and young adults. DATA SOURCES: A range of medical and psychological science electronic databases were searched (MEDLINE, EMBASE, Scopus, Web of Science, PsychINFO). REVIEW METHODS: Original research studies were selected, data were extracted and quality was appraised. RESULTS: Sixteen primary papers were included, ranging from healthy and community samples to subclinical and clinical populations across a variety of age ranges and using different neurobiological measures (e.g. magnetic resonance imaging, electroencephalography, cortisol, brain-derived neurotropic factor). DISCUSSION: The majority of studies report improvement in mental health and cognition outcomes following longer-term physical activity interventions which coincide with neurobiological alterations, especially neuroimaging alterations in activation and electrophysiological parameters in frontal areas. Future research should include measures of pre-existing fitness and target those who would benefit the most from this type of intervention (e.g. those with a lower level of fitness and at risk for or with mental health problems).

Characterisation of Haemodynamic Activity in Resting State Networks by Fractal Analysis.

Intrinsic brain activity is organized into large-scale networks displaying specific structural-functional architecture, known as resting-state networks (RSNs). RSNs reflect complex neurophysiological processes and interactions, and have a central role in distinct sensory and cognitive functions, making it crucial to understand and quantify their anatomical and functional properties. Fractal dimension (FD) provides a parsimonious way of summarizing self-similarity over different spatial and temporal scales but despite its suitability for functional magnetic resonance imaging (fMRI) signal analysis its ability to characterize and investigate RSNs is poorly understood. We used FD in a large sample of healthy participants to differentiate fMRI RSNs and examine how the FD property of RSNs is linked with their functional roles. We identified two clusters of RSNs, one mainly consisting of sensory networks (C1, including auditory, sensorimotor and visual networks) and the other more related to higher cognitive (HCN) functions (C2, including dorsal default mode network and fronto-parietal networks). These clusters were defined in a completely data-driven manner using hierarchical clustering, suggesting that quantification of Blood Oxygen Level Dependent (BOLD) signal complexity with FD is able to characterize meaningful physiological and functional variability. Understanding the mechanisms underlying functional RSNs, and developing tools to study their signal properties, is essential for assessing specific brain alterations and FD could potentially be used for the early detection and treatment of neurological disorders.

Human Circadian Phenotyping and Diurnal Performance Testing in the Real World.

In our continuously developing 'around the clock' society, there is a need to increase our understanding of how changes in biology, physiology and psychology influence our health and performance. Embedded within this challenge, is the increasing need to account for individual differences in sleep and circadian rhythms, as well as to explore the impact of time of day on performance in the real world. There are a number of ways to measure sleep and circadian rhythms from subjective questionnaire-based methods to objective sleep/wake monitoring, actigraphy and analysis of biological samples. This paper proposes a protocol that combines multiple techniques to categorize individuals into Early, Intermediate or Late circadian phenotype groups (ECPs/ICPs/LCPs) and recommends how to conduct diurnal performance testing in the field. Representative results show large differences in rest-activity patterns derived from actigraphy, circadian phase (dim light melatonin onset and peak time of cortisol awakening response) between circadian phenotypes. In addition, significant differences in diurnal performance rhythms between ECPs and LCPs emphasizes the need to account for circadian phenotype. In summary, despite the difficulties in controlling influencing factors, this protocol allows a real-world assessment of the impact of circadian phenotype on performance. This paper presents a simple method to assess circadian phenotype in the field and supports the need to consider time of day when designing performance studies.

Late Diagnosis of Narcolepsy With Cataplexy: A Novel Case of Cataplectic Facies Presenting in an Elderly Woman.

None: Cataplectic facies is an unusual feature described in children with narcolepsy and cataplexy. The typical manifestations of cataplectic facies consist of repetitive mouth opening, tongue protrusion, and ptosis. An interesting observation is that the usual emotional triggers associated with cataplexy such as laughter and joking are not always present, thus hampering diagnosis of the underlying syndrome. Cataplectic facies is thought to be a phenomenon observed in the early stages of narcolepsy type 1 and is thought to disappear by the time the patient reaches puberty. We present a unique case of an elderly woman with narcolepsy type 1 demonstrating cataplectic facies. The novel circumstances of this case highlight that facial cataplexy can present later in life, in contrast with previous descriptions that report resolution of cataplectic facies before puberty. Wider recognition of these features throughout the life course may aid in accurate diagnosis and thereby ensure swift access to appropriate treatment.

Resetting the late timing of 'night owls' has a positive impact on mental health and performance.

BACKGROUND: There is conflict between living according to our endogenous biological rhythms and our external environment, with disruptions resulting in negative consequences to health and performance. This is often documented in shift work and jet lag, but 'societal norms' (eg, typical working hours) can create profound issues for 'night owls', people whose internal biological timing predisposes them to follow an unusually late sleep-wake cycle. Night owls have also been associated with health issues, mood disturbances, poorer performance and increased mortality rates. METHODS: This study used a randomized control trial design aimed to shift the late timing of night owls to an earlier time (phase advance), using non-pharmacological, practical interventions in a real-world setting. These interventions targeted light exposure (through earlier wake up/sleep times), fixed meals times, caffeine intake and exercise. RESULTS: Overall, participants demonstrated a significant advance of ∼2 h in sleep/wake timings as measured by actigraphy and circadian phase markers (dim light melatonin onset and peak time of the cortisol awakening response), whilst having no adverse effect on sleep duration. Notably, the phase advance was accompanied by significant improvements to self-reported depression and stress, as well as improved cognitive (reaction time) and physical (grip strength) performance measures during the typical 'suboptimal' morning hours. CONCLUSIONS: Our findings propose a novel strategy for shifting clock timing towards a pattern that is more aligned to societal demands that could significantly improve elements of performance, mental health and sleep timing in the real world.