Vincenzo Muto

Encoding Difficulty Promotes Postlearning Changes in Sleep Spindle Activity during Napping

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.

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.

The Impact of Visual Perceptual Learning on Sleep and Local Slow-Wave Initiation

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.

Influence of acute sleep loss on the neural correlates of alerting, orientating and executive attention components.

The Attention Network Test (ANT) is deemed to assess the alerting, orientating and executive components of human attention. Capitalizing on the opportunity to investigate three facets of attention in a single task, we used functional magnetic resonance imaging (fMRI) to assess the effect of sleep deprivation (SD) on brain responses associated with the three attentional components elicited by the ANT. Twelve healthy volunteers were scanned in two conditions 1 week apart, after a normal night of sleep (rested wakefulness, RW) or after one night of total sleep deprivation. Sleep deprivation was associated with a global increase in reaction times, which did not affect specifically any of the three attention effects. Brain responses associated with the alerting effect did not differ between RW and SD. Higher‐order attention components (orientating and conflict effects) were associated with significantly larger thalamic responses during SD than during RW. These results suggest that SD influences different components of human attention non‐selectively, through mechanisms that might either affect centrencephalic structures maintaining vigilance or ubiquitously perturb neuronal function. Compensatory responses can counter these effects transiently by recruiting thalamic responses, thereby supporting thalamocortical 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.

Concurrent Synaptic and Systems Memory Consolidation during Sleep

Memories are consolidated during sleep by two apparently antagonistic processes: (1) reinforcement of memory-specific cortical interactions and (2) homeostatic reduction in synaptic efficiency. Using fMRI, we assessed whether episodic memories are processed during sleep by either or both mechanisms, by comparing recollection before and after sleep. We probed whether LTP influences these processes by contrasting two groups of individuals prospectively recruited based on BDNF rs6265 (Val66Met) polymorphism. Between immediate retrieval and delayed testing scheduled after sleep, responses to recollection increased significantly more in Val/Val individuals than in Met carriers in parietal and occipital areas not previously engaged in retrieval, consistent with “systems-level consolidation.” Responses also increased differentially between allelic groups in regions already activated before sleep but only in proportion to slow oscillation power, in keeping with “synaptic downscaling.” Episodic memories seem processed at both synaptic and systemic levels during sleep by mechanisms involving LTP.

Spontaneous neural activity during human non-rapid eye movement sleep.

Recent neuroimaging studies characterized the neural correlates of slow waves and spindles during human non-rapid eye movement (NREM) sleep. They showed that significant activity was consistently associated with slow (> 140 μV) and delta waves (75-140 μV) during NREM sleep in several cortical areas including inferior frontal, medial prefrontal, precuneus, and posterior cingulate cortices. Unexpectedly, slow waves were also associated with transient responses in the pontine tegmentum and in the cerebellum. On the other hand, spindles were associated with a transient activity in the thalami, paralimbic areas (anterior cingulate and insular cortices), and superior temporal gyri. Moreover, slow spindles (11-13 Hz) were associated with increased activity in the superior frontal gyrus. In contrast, fast spindles (13-15 Hz) recruited a set of cortical regions involved in sensorimotor processing, as well as the mesial frontal cortex and hippocampus. These findings indicate that human NREM sleep is an active state during which brain activity is temporally organized by spontaneous oscillations (spindles and slow oscillation) in a regionally specific manner. The functional significance of these NREM sleep oscillations is currently interpreted in terms of synaptic homeostasis and memory consolidation.

Neuroimaging of dreaming: state of the art and limitations.

During the last two decades, functional neuroimaging has been used to characterize the regional brain function during sleep in humans, at the macroscopic systems level. In addition, the topography of brain activity, especially during rapid eye movement sleep, was thought to be compatible with the general features of dreams. In contrast, the neural correlates of dreams remain largely unexplored. This review examines the difficulties associated with the characterization of dream correlates. ἓν οἶδα ὅτι οὐδὲν οἶδα Σωκράτης (The only thing I know is that I know nothing) Socrates.