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

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.

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.