Christelle Meyer

Local modulation of human brain responses by circadian rhythmicity and sleep debt

Circadian rhythms and sleep deprivation Sleep deprivation, such as that experienced because of shift work, jet lag, sleep disorders, and aging, leads to deterioration of many aspects of health. Cognition deteriorates rapidly and substantially when we stay awake through the night. To investigate the time course of brain responses during sleep loss, Muto et al. scanned volunteers repeatedly during an extended period of wakefulness (see the Perspective by Czeisler) in which circadian and homeostatic drives differentially affected local brain regions. Science, this issue p. 687; see also p. 648 Activity in different brain regions varies according to circadian rhythm and homeostatic sleep pressure. Human performance is modulated by circadian rhythmicity and homeostatic sleep pressure. Whether and how this interaction is represented at the regional brain level has not been established. We quantified changes in brain responses to a sustained-attention task during 13 functional magnetic resonance imaging sessions scheduled across the circadian cycle, during 42 hours of wakefulness and after recovery sleep, in 33 healthy participants. Cortical responses showed significant circadian rhythmicity, the phase of which varied across brain regions. Cortical responses also significantly decreased with accrued sleep debt. Subcortical areas exhibited primarily a circadian modulation that closely followed the melatonin profile. These findings expand our understanding of the mechanisms involved in maintaining cognition during the day and its deterioration during sleep deprivation and circadian misalignment.

Photic memory for executive brain responses

Significance Light is a powerful stimulant for human alertness and cognition that can be easily administered to improve performance or counteract the negative impact of sleepiness, even during the day. Here, we show that prior exposure to longer wavelength light (orange), relative to shorter wavelength (blue), enhances the subsequent impact of light on executive brain responses. These findings emphasize the importance of light for human cognitive brain function and constitute compelling evidence in favor of a cognitive role for melanopsin. This recently discovered photopigment may therefore provide a unique form of “photic memory” for human cognition and play a broader role than previously apprehended. Ultimately, these findings support the idea that the integration of light exposure over long periods of time can help optimize cognitive brain function. Light is a powerful stimulant for human alertness and cognition, presumably acting through a photoreception system that heavily relies on the photopigment melanopsin. In humans, evidence for melanopsin involvement in light-driven cognitive stimulation remains indirect, due to the difficulty to selectively isolate its contribution. Therefore, a role for melanopsin in human cognitive regulation remains to be established. Here, sixteen participants underwent consecutive and identical functional MRI recordings, during which they performed a simple auditory detection task and a more difficult auditory working memory task, while continuously exposed to the same test light (515 nm). We show that the impact of test light on executive brain responses depends on the wavelength of the light to which individuals were exposed prior to each recording. Test-light impact on executive responses in widespread prefrontal areas and in the pulvinar increased when the participants had been exposed to longer (589 nm), but not shorter (461 nm), wavelength light, more than 1 h before. This wavelength-dependent impact of prior light exposure is consistent with recent theories of the light-driven melanopsin dual states. Our results emphasize the critical role of light for cognitive brain responses and are, to date, the strongest evidence in favor of a cognitive role for melanopsin, which may confer a form of “photic memory” to human cognitive brain function.

Seasonality in human cognitive brain responses

Significance Evidence for seasonality in humans is limited. Mood probably stands as the aspect of human brain function most acknowledged as being affected by season. Yet, the present study provides compelling evidence for previously unappreciated annual variations in the cerebral activity required to sustain ongoing cognitive processes in healthy volunteers. The data further show that this annual rhythmicity is cognitive-process-specific (i.e., the phase of the rhythm changes between cognitive tasks), speaking for a complex impact of season on human brain function. Annual variations in cognitive brain function may contribute to explain intraindividual cognitive changes that could emerge at specific times of year. 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.

Modulating effect of COMT genotype on the brain regions underlying proactive control process during inhibition.

INTRODUCTION Genetic variability related to the catechol-O-methyltransferase (COMT) gene (Val(158)Met polymorphism) has received increasing attention as a possible modulator of cognitive control functions. METHODS In an event-related functional magnetic resonance imaging (fMRI) study, a modified version of the Stroop task was administered to three groups of 15 young adults according to their COMT Val(158)Met genotype [Val/Val (VV), Val/Met (VM) and Met/Met (MM)]. Based on the theory of dual mechanisms of control (Braver et al., 2007), the Stroop task has been built to induce proactive or reactive control processes according to the task context. RESULTS Behavioral results did not show any significant group differences for reaction times but Val allele carriers individuals are less accurate in the processing of incongruent items. fMRI results revealed that proactive control is specifically associated with increased activity in the anterior cingulate cortex (ACC) in carriers of the Met allele, while increased activity is observed in the middle frontal gyrus (MFG) in carriers of the Val allele. CONCLUSION These observations, in keeping with a higher cortical dopamine level in MM individuals, support the hypothesis of a COMT Val(158)Met genotype modulation of the brain regions underlying proactive control, especially in frontal areas as suggested by Braver et al.

Influence of noise correction on intra- and inter-subject variability of quantitative metrics in diffusion kurtosis imaging

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.

Neural Correlates of Human Sleep and Sleep-Dependent Memory Processing

Wakefulness and sleep are associated with distinct patterns of neural activity and neuromodulation. In humans, functional neuroimaging was used to characterize the related changes in regional brain metabolism and hemodynamics. Recent data combining EEG and fMRI described the transient responses associated with spindles and slow waves, as well as the changes in functional integration during NREM sleep. It was also shown that regional brain activity during sleep is influenced by the experience acquired during the preceding waking period. These data are currently interpreted in the framework of two theories. First, the use-dependent increase in slow oscillation during NREM sleep is associated with local synaptic homeostasis. Second, reactivations of memory traces during NREM sleep would reorganize declarative memories in hippocampal-neocortical networks, a systems-level memory consolidation that can be hindered by sleep deprivation. Collectively, these data reveal the dynamic changes in brain activity during sleep that support normal human cognition.