Learning-dependent increases in sleep spindle density have been reported during nocturnal sleep immediately after the learning session. Here, we investigated experience-dependent changes in daytime sleep EEG activity after declarative learning of unrelated word pairs. At weekly intervals, 13 young male volunteers spent three 24 h sessions in the laboratory under carefully controlled homeostatic and circadian conditions. At approximately midday, subjects performed either one of two word-pair learning tasks or a matched nonlearning control task, in a counterbalanced order. The two learning lists differed in the level of concreteness of the words used, resulting in an easier and a more difficult associative encoding condition, as confirmed by performance at immediate cued recall. Subjects were then allowed to sleep for 4 h; afterward, delayed cued recall was tested. Compared with the control condition, sleep EEG spectral activity in the low spindle frequency range and the density of low-frequency sleep spindles (11.25-13.75 Hz) were both significantly increased in the left frontal cortex after the difficult but not after the easy encoding condition. Furthermore, we found positive correlations between these EEG changes during sleep and changes in memory performance between pre-nap and post-nap recall sessions. These results indicate that, like during nocturnal sleep, daytime sleep EEG oscillations including spindle activity are modified after declarative learning of word pairs. Furthermore, we demonstrate here that the nature of the learning material is a determinant factor for sleep-related alterations after declarative learning.

A schematic design of an epidermal touch panel is shown in Fig. 4A. The epidermal touch panel was built on a 1-mm-thick VHB film (3M, Maplewood, MN) so as to insulate the panel from

Italy and Belgium have been among the first western countries to face the Coronavirus disease 2019 (COVID-19) emergency, imposing a total lockdown over the entire national territories.These limitations have proven effective in slowing down the spread of the infection. However, the benefits obtained in public health have come with huge costs in terms of social, economic, and psychological well-being. In the current study, we aimed at investigating how the period of home confinement affected self-reported sleep characteristics in Italians and Belgians, with special regard to sleep timing and subjective quality. Using an online survey we collected data from 2272 participants, 1622 Italians (Mage=34.1±13.6 years, 1171 F), and 650 Belgian (Mage=43.0±16.8 years, 509 F). Participants reported their sleep pattern (e.g., bedtime, risetime) and perceived sleep quality during and, retrospectively, before the lockdown. During the lockdown, sleep timing was significantly delayed, time spent in bed increased, and sleep quality was markedly impaired in both Italians and Belgians. The most vulnerable individualsappeared to be women, subjects experiencing a more negative mood, and those perceiving the pandemic situation as highly stressful. However, the two samples differed in the subgroups most affected by the changes, possibly because of the different welfare systems of the two countries. In fact, in the Italian sample sleep quality and timing underwent significant modifications especially in unemployed participants, whereas in the Belgian sample this category was the one who suffered less from the restrictions. Considering that the novel coronavirus has spread across the whole globe, involving countries with different types of health and welfare systems, understanding which policy measures have the most effective protecting role on physical and mental health is of primary importance.

No abstract

Daily variations in the environment have shaped life on Earth, with circadian cycles identified in most living organisms. Likewise, seasons correspond to annual environmental fluctuations to which organisms have adapted. However, little is known about seasonal variations in human brain physiology. We investigated annual rhythms of brain activity in a cross-sectional study of healthy young participants. They were maintained in an environment free of seasonal cues for 4.5 d, after which brain responses were assessed using functional magnetic resonance imaging (fMRI) while they performed two different cognitive tasks. Brain responses to both tasks varied significantly across seasons, but the phase of these annual rhythms was strikingly different, speaking for a complex impact of season on human brain function. For the sustained attention task, the maximum and minimum responses were located around summer and winter solstices, respectively, whereas for the working memory task, maximum and minimum responses were observed around autumn and spring equinoxes. These findings reveal previously unappreciated process-specific seasonality in human cognitive brain function that could contribute to intraindividual cognitive changes at specific times of year and changes in affective control in vulnerable populations.aily variations in the environment have constrained life on Earth, with circadian cycles identified in most living organisms, including in human physiology and cognition (1, 2). Seasonal variations in the environment have also triggered annual adaptations that are observed in the majority of species (for a review, see ref. 1). However, seasonal variations may seem more limited in our species or they are at least less recognized (3). Seasonality has indeed been reported for several physiological aspects including blood pressure (4), cholesterol (5), or calorie intake (6), with higher levels seen in winter or fall for food intake. Recently, seasonal variation in expression levels of a large set of genes has been reported for human white blood cells and adipose tissue (7). Furthermore, seasonal variations have been observed in several behavioral dimensions with peaks occurring at different time of year depending on the variable considered: conception (winter/ spring peak) and death [winter peak (8)] or violent suicide [spring/ summer peak (9)]. Mood has been the most extensively studied aspect of human behavior, with a large portion of the general population undergoing seasonal deteriorations in mood in winter, but these do not reach clinical threshold [e.g., subsyndromal seasonal affective disorder: up to 18% in North America (10)]. Furthermore, sparse studies suggest that, in addition to mood, other cognitive brain functions show annual variations in healthy individuals, but results are not consistent (11-13).Animal research suggests that the suprachiasmatic nucleus, site of the master circadian clock, is at least one of the sites mediating annual rhythmicity (14). The well-characterized circadian genetic machinery is...

Cortical excitability depends on sleep-wake regulation, is central to cognition and hasbeen 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 thirteen young and twelve older healthy participants during sleep deprivation. While 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 neurobehavioural 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 behaviour, and address whether maintaining cortical excitability dynamics can counteract agerelated cognitive decline.

During non-rapid eye movement (NREM) sleep, a global decrease in synaptic strength associated with slow waves (SWs) would enhance signal-to-noise ratio of neural responses during subsequent wakefulness. To test this prediction, 32 human volunteers were trained to a coarse orientation discrimination task, in either the morning or evening. They were retested after 8 h of wakefulness or sleep, respectively. Performance was enhanced only after a night of sleep, in the absence of any change in the abundance of NREM SWs but in proportion to the number of SWs "initiated" in lateral occipital areas during posttraining NREM sleep. The sources of these waves overlapped with the lateral occipital complex, in which responses to the learned stimulus, as assessed by fMRI, were selectively increased the next morning. This response enhancement was proportional to rapid eye movement (REM) sleep duration. These results provide an example of local sleep in which local initiation of SWs during NREM sleep predicts later skill improvement and foreshadows locally enhanced neural signals the next day. In addition, REM sleep also promotes local learning-dependent activity, possibly by promoting synaptic plasticity.

Diffusion kurtosis imaging (DKI) is a promising extension of diffusion tensor imaging, giving new insights into the white matter microstructure and providing new biomarkers. Given the rapidly increasing number of studies, DKI has a potential to establish itself as a valuable tool in brain diagnostics. However, to become a routine procedure, DKI still needs to be improved in terms of robustness, reliability, and reproducibility. As it requires acquisitions at higher diffusion weightings, results are more affected by noise than in diffusion tensor imaging. The lack of standard procedures for post-processing, especially for noise correction, might become a significant obstacle for the use of DKI in clinical routine limiting its application. We considered two noise correction schemes accounting for the noise properties of multichannel phased-array coils, in order to improve the data quality at signal-to-noise ratio (SNR) typical for DKI. The SNR dependence of estimated DKI metrics such as mean kurtosis (MK), mean diffusivity (MD) and fractional anisotropy (FA) is investigated for these noise correction approaches in Monte Carlo simulations and in in vivo human studies. The intra-subject reproducibility is investigated in a single subject study by varying the SNR level and SNR spatial distribution. Then the impact of the noise correction on inter-subject variability is evaluated in a homogeneous sample of 25 healthy volunteers. Results show a strong impact of noise correction on the MK estimate, while the estimation of FA and MD was affected to a lesser extent. Both intra- and inter-subject SNR-related variability of the MK estimate is considerably reduced after correction for the noise bias, providing more accurate and reproducible measures. In this work, we have proposed a straightforward method that improves accuracy of DKI metrics. This should contribute to standardization of DKI applications in clinical studies making valuable inferences in group analysis and longitudinal studies.