Exploring scoring methods for research studies: Accuracy and variability of visual and automated sleep scoring.

Sleep studies face new challenges in terms of data, objectives and metrics. This requires reappraising the adequacy of existing analysis methods, including scoring methods. Visual and automatic sleep scoring of healthy individuals were compared in terms of reliability (i.e., accuracy and stability) to find a scoring method capable of giving access to the actual data variability without adding exogenous variability. A first dataset (DS1, four recordings) scored by six experts plus an autoscoring algorithm was used to characterize inter-scoring variability. A second dataset (DS2, 88 recordings) scored a few weeks later was used to explore intra-expert variability. Percentage agreements and Conger's kappa were derived from epoch-by-epoch comparisons on pairwise and consensus scorings. On DS1 the number of epochs of agreement decreased when the number of experts increased, ranging from 86% (pairwise) to 69% (all experts). Adding autoscoring to visual scorings changed the kappa value from 0.81 to 0.79. Agreement between expert consensus and autoscoring was 93%. On DS2 the hypothesis of intra-expert variability was supported by a systematic decrease in kappa scores between autoscoring used as reference and each single expert between datasets (.75-.70). Although visual scoring induces inter- and intra-expert variability, autoscoring methods can cope with intra-scorer variability, making them a sensible option to reduce exogenous variability and give access to the endogenous variability in the data.

Human fronto-parietal response scattering subserves vigilance at night.

Lack of sleep has a considerable impact on vigilance: we perform worse, we make more errors, particularly at night, when we should be sleeping. Measures of brain functional connectivity suggest that decrease in vigilance during sleep loss is associated with an impaired cross-talk within the fronto-parietal cortex. However, fronto-parietal effective connectivity, which is more closely related to the causal cross-talk between brain regions, remains unexplored during prolonged wakefulness. In addition, no study has simultaneously investigated brain effective connectivity and wake-related changes in vigilance, preventing the concurrent incorporation of the two aspects. Here, we used electroencephalography (EEG) to record responses evoked by Transcranial Magnetic Stimulation (TMS) applied over the frontal lobe in 23 healthy young men (18-30 yr.), while they simultaneously performed a vigilance task, during 8 sessions spread over 29 h of sustained wakefulness. We assessed Response Scattering (ReSc), an estimate of effective connectivity, as the propagation of TMS-evoked EEG responses over the fronto-parietal cortex. Results disclose a significant change in fronto-parietal ReSc with time spent awake. When focusing on the night-time period, when one should be sleeping, participants with lower fronto-parietal ReSc performed worse on the vigilance task. Conversely, no association was detected during the well-rested, daytime period. Night-time fronto-parietal ReSc also correlated with objective EEG measures of sleepiness and alertness. These changes were not accompanied by variations in fronto-parietal response complexity. These results suggest that decreased brain response propagation within the fronto-parietal cortex is associated to increased vigilance failure during night-time prolonged wakefulness. This study reveals a novel facet of the detrimental effect on brain function of extended night-time waking hours, which is increasingly common in our societies.

A finite-element reciprocity solution for EEG forward modeling with realistic individual head models.

We present a finite element modeling (FEM) implementation for solving the forward problem in electroencephalography (EEG). The solution is based on Helmholtz's principle of reciprocity which allows for dramatically reduced computational time when constructing the leadfield matrix. The approach was validated using a 4-shell spherical model and shown to perform comparably with two current state-of-the-art alternatives (OpenMEEG for boundary element modeling and SimBio for finite element modeling). We applied the method to real human brain MRI data and created a model with five tissue types: white matter, gray matter, cerebrospinal fluid, skull, and scalp. By calculating conductivity tensors from diffusion-weighted MR images, we also demonstrate one of the main benefits of FEM: the ability to include anisotropic conductivities within the head model. Root-mean square deviation between the standard leadfield and the leadfield including white-matter anisotropy showed that ignoring the directional conductivity of white matter fiber tracts leads to orientation-specific errors in the forward model. Realistic head models are necessary for precise source localization in individuals. Our approach is fast, accurate, open-source and freely available online.

Increased cortical excitability but stable effective connectivity index during attentional lapses.

Modern lifestyle curtails sleep and increases nighttime work and leisure activities. This has a deleterious impact on vigilance and attention, exacerbating chances of committing attentional lapses, with potential dramatic outcomes. Here, we investigated the brain signature of attentional lapses and assessed whether cortical excitability and brain response propagation were modified during lapses and whether these modifications changed with aging. We compared electroencephalogram (EEG) responses to transcranial magnetic stimulation (TMS) during lapse and no-lapse periods while performing a continuous attentional/vigilance task at night, after usual bedtime. Data were collected in healthy younger (N = 12; 18-30 years) and older individuals (N = 12; 50-70 years) of both sexes. The amplitude and slope of the first component of the TMS-evoked potential were larger during lapses. In contrast, TMS response scattering over the cortical surface, as well as EEG response complexity, did not significantly vary between lapse and no-lapse periods. Importantly, despite qualitative differences, age did not significantly affect any of the TMS-EEG measures. These results demonstrate that attentional lapses are associated with a transient increase of cortical excitability. This initial change is not associated with detectable changes in subsequent effective connectivity-as indexed by response propagation-and are not markedly different between younger and older adults. These findings could contribute to develop models aimed to predicting and preventing lapses in real-life situations.

Changes in EEG permutation entropy in the evening and in the transition from wake to sleep.

Quantifying the complexity of the EEG signal during prolonged wakefulness and during sleep is gaining interest as an additional mean to characterize the mechanisms associated with sleep and wakefulness regulation. Here, we characterized how EEG complexity, as indexed by Multiscale Permutation Entropy (MSPE), changed progressively in the evening prior to light off and during the transition from wakefulness to sleep. We further explored whether MSPE was able to discriminate between wakefulness and sleep around sleep onset and whether MSPE changes were correlated with spectral measures of the EEG related to sleep need during concomitant wakefulness (theta power-Ptheta: 4-8 Hz). To address these questions, we took advantage of large datasets of several hundred of ambulatory EEG recordings of individual of both sexes aged 25-101 years. Results show that MSPE significantly decreases before light off (i.e. before sleep time) and in the transition from wakefulness to sleep onset. Furthermore, MSPE allows for an excellent discrimination between pre-sleep wakefulness and early sleep. Finally, we show that MSPE is correlated with concomitant Ptheta. Yet, the direction of the latter correlation changed from before light-off to the transition to sleep. Given the association between EEG complexity and consciousness, MSPE may track efficiently putative changes in consciousness preceding sleep onset. An MSPE stands as a comprehensive measure that is not limited to a given frequency band and reflects a progressive change brain state associated with sleep and wakefulness regulation. It may be an effective mean to detect when the brain is in a state close to sleep onset.

Time course of cortical response complexity during extended wakefulness and its differential association with vigilance in young and older individuals.

Characterization of the complexity of electroencephalogram (EEG) responses has provided important insights in cognitive function as well as in the brain bases of consciousness and vigilance. Whether brain response complexity changes during prolonged wakefulness and sleep deprivation -when vigilance level considerably varies- is not fully elucidated yet. In the present study, we repeatedly assessed EEG responses to transcranial magnetic stimulation (TMS) over 34 h of sleep deprivation under constant routine conditions in healthy younger (N = 13; 5 women; 18-30 y) and older (N = 12; 6 women; 50-70 y) individuals, while they were performing a vigilance task. Response complexity was computed both at the global (all scalp sensors) and local (sensors surrounding TMS hotspot) levels using the Lempel-Ziv algorithm. Response complexity was significantly higher in the older compared to the young volunteers over the entire protocol. Global complexity response significantly changed with time spent awake, with an increasing trend from the beginning to the middle of the biological night, followed by a decreasing trend from the middle of the biological night to the following afternoon. An unexpected different link between vigilance performance and brain response complexity was detected across age groups: higher response complexity was associated with lower performance in the older group, particularly in the morning sessions. These findings show that cortical activity complexity changes with vigilance variation, as experienced during sleep deprivation and circadian misalignment, in two age groups, with no evident time course difference across age-groups. Aside from classical linear EEG analyses, computation of Lempel-Ziv complexity provides additional insights on the neurophysiology of the processes associated with vigilance and their modifications throughout ageing.

Steady-State Pupil Size Varies with Circadian Phase and Sleep Homeostasis in Healthy Young Men.

Pupil size informs about sympathovagal balance as well as cognitive and affective processes, and perception. It is also directly linked to phasic activity of the brainstem locus coeruleus, so that pupil measures have gained recent attention. Steady-state pupil size and its variability have been directly linked to sleep homeostasis and circadian phase, but results have been inconsistent. Here, we report robust changes in steady-state pupil size during 29 h of continuous wakefulness in healthy young men (N = 20; 18-30 years old) maintained in dim-light in strictly controlled constant routine conditions. These variations were associated with variations in motivation and sustained attention performance. Pupil size variability did not significantly change during the protocol. Yet, pupil size variability was linearly associated with subjective fatigue, sociability, and anguish. No associations were found between neither steady-state pupil size nor pupil size variability, and objective EEG measure of alertness and subjective sleepiness. Our data support therefore the notion that, compared with its variability, steady-state pupil size is strongly influenced by the concomitant changes in sleep need and circadian phase. In addition, steady-state pupil size appears to be related to motivation and attention, while its variability may be related to separate affective dimensions and subjective fatigue.

Preserved wake-dependent cortical excitability dynamics predict cognitive fitness beyond age-related brain alterations.

Age-related cognitive decline arises from alterations in brain structure as well as in sleep-wake regulation. Here, we investigated whether preserved wake-dependent regulation of cortical function could represent a positive factor for cognitive fitness in aging. We quantified cortical excitability dynamics during prolonged wakefulness as a sensitive marker of age-related alteration in sleep-wake regulation in 60 healthy older individuals (50-69 y; 42 women). Brain structural integrity was assessed with amyloid-beta- and tau-PET, and with MRI. Participants' cognition was investigated using an extensive neuropsychological task battery. We show that individuals with preserved wake-dependent cortical excitability dynamics exhibit better cognitive performance, particularly in the executive domain which is essential to successful cognitive aging. Critically, this association remained significant after accounting for brain structural integrity measures. Preserved dynamics of basic brain function during wakefulness could therefore be essential to cognitive fitness in aging, independently from age-related brain structural modifications that can ultimately lead to dementia.

Age-related decrease in cortical excitability circadian variations during sleep loss and its links with cognition.

Cortical excitability depends on sleep-wake regulation, is central to cognition, and has been implicated in age-related cognitive decline. The dynamics of cortical excitability during prolonged wakefulness in aging are unknown, however. Here, we repeatedly probed cortical excitability of the frontal cortex using transcranial magnetic stimulation and electroencephalography in 13 young and 12 older healthy participants during sleep deprivation. Although overall cortical excitability did not differ between age groups, the magnitude of cortical excitability variations during prolonged wakefulness was dampened in older individuals. This age-related dampening was associated with mitigated neurobehavioral consequences of sleep loss on executive functions. Furthermore, higher cortical excitability was potentially associated with better and lower executive performance, respectively, in older and younger adults. The dampening of cortical excitability dynamics found in older participants likely arises from a reduced impact of sleep homeostasis and circadian processes. It may reflect reduced brain adaptability underlying reduced cognitive flexibility in aging. Future research should confirm preliminary associations between cortical excitability and behavior and address whether maintaining cortical excitability dynamics can counteract age-related cognitive decline.

Automatic artifacts and arousals detection in whole-night sleep EEG recordings.

BACKGROUND: In sleep electroencephalographic (EEG) signals, artifacts and arousals marking are usually part of the processing. This visual inspection by a human expert has two main drawbacks: it is very time consuming and subjective. NEW METHOD: To detect artifacts and arousals in a reliable, systematic and reproducible automatic way, we developed an automatic detection based on time and frequency analysis with adapted thresholds derived from data themselves. RESULTS: The automatic detection performance is assessed using 5 statistic parameters, on 60 whole night sleep recordings coming from 35 healthy volunteers (male and female) aged between 19 and 26. The proposed approach proves its robustness against inter- and intra-, subjects and raters' scorings, variability. The agreement with human raters is rated overall from substantial to excellent and provides a significantly more reliable method than between human raters. COMPARISON: Existing methods detect only specific artifacts or only arousals, and/or these methods are validated on short episodes of sleep recordings, making it difficult to compare with our whole night results. CONCLUSION: The method works on a whole night recording and is fully automatic, reproducible, and reliable. Furthermore the implementation of the method will be made available online as open source code.

Circadian dynamics in measures of cortical excitation and inhibition balance.

Several neuropsychiatric and neurological disorders have recently been characterized as dysfunctions arising from a 'final common pathway' of imbalanced excitation to inhibition within cortical networks. How the regulation of a cortical E/I ratio is affected by sleep and the circadian rhythm however, remains to be established. Here we addressed this issue through the analyses of TMS-evoked responses recorded over a 29 h sleep deprivation protocol conducted in young and healthy volunteers. Spectral analyses of TMS-evoked responses in frontal cortex revealed non-linear changes in gamma band evoked oscillations, compatible with an influence of circadian timing on inhibitory interneuron activity. In silico inferences of cell-to-cell excitatory and inhibitory connectivity and GABA/Glutamate receptor time constant based on neural mass modeling within the Dynamic causal modeling framework, further suggested excitation/inhibition balance was under a strong circadian influence. These results indicate that circadian changes in EEG spectral properties, in measure of excitatory/inhibitory connectivity and in GABA/glutamate receptor function could support the maintenance of cognitive performance during a normal waking day, but also during overnight wakefulness. More generally, these findings demonstrate a slow daily regulation of cortical excitation/inhibition balance, which depends on circadian-timing and prior sleep-wake history.

Circadian regulation of human cortical excitability.

Prolonged wakefulness alters cortical excitability, which is essential for proper brain function and cognition. However, besides prior wakefulness, brain function and cognition are also affected by circadian rhythmicity. Whether the regulation of cognition involves a circadian impact on cortical excitability is unknown. Here, we assessed cortical excitability from scalp electroencephalography (EEG) responses to transcranial magnetic stimulation in 22 participants during 29 h of wakefulness under constant conditions. Data reveal robust circadian dynamics of cortical excitability that are strongest in those individuals with highest endocrine markers of circadian amplitude. In addition, the time course of cortical excitability correlates with changes in EEG synchronization and cognitive performance. These results demonstrate that the crucial factor for cortical excitability, and basic brain function in general, is the balance between circadian rhythmicity and sleep need, rather than sleep homoeostasis alone. These findings have implications for clinical applications such as non-invasive brain stimulation in neurorehabilitation.

A nap to recap or how reward regulates hippocampal-prefrontal memory networks during daytime sleep in humans.

Sleep plays a crucial role in the consolidation of newly acquired memories. Yet, how our brain selects the noteworthy information that will be consolidated during sleep remains largely unknown. Here we show that post-learning sleep favors the selectivity of long-term consolidation: when tested three months after initial encoding, the most important (i.e., rewarded, strongly encoded) memories are better retained, and also remembered with higher subjective confidence. Our brain imaging data reveals that the functional interplay between dopaminergic reward regions, the prefrontal cortex and the hippocampus contributes to the integration of rewarded associative memories. We further show that sleep spindles strengthen memory representations based on reward values, suggesting a privileged replay of information yielding positive outcomes. These findings demonstrate that post-learning sleep determines the neural fate of motivationally-relevant memories and promotes a value-based stratification of long-term memory stores.

Neuroimaging, cognition, light and circadian rhythms.

In humans, sleep and wakefulness and the associated cognitive processes are regulated through interactions between sleep homeostasis and the circadian system. Chronic disruption of sleep and circadian rhythmicity is common in our society and there is a need for a better understanding of the brain mechanisms regulating sleep, wakefulness and associated cognitive processes. This review summarizes recent investigations which provide first neural correlates of the combined influence of sleep homeostasis and circadian rhythmicity on cognitive brain activity. Markers of interindividual variations in sleep-wake regulation, such as chronotype and polymorphisms in sleep and clock genes, are associated with changes in cognitive brain responses in subcortical and cortical areas in response to manipulations of the sleep-wake cycle. This review also includes recent data showing that cognitive brain activity is regulated by light, which is a powerful modulator of cognition and alertness and also directly impacts sleep and circadian rhythmicity. The effect of light varied with age, psychiatric status, PERIOD3 genotype and changes in sleep homeostasis and circadian phase. These data provide new insights into the contribution of demographic characteristics, the sleep-wake cycle, circadian rhythmicity and light to brain functioning.