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See detailInfluence of noise correction on intra- and inter-subject variability of quantitative metrics in diffusion kurtosis imaging
André, Elodie ULg; Grinberg, Farida; Farrher, Ezequiel et al

in PLoS ONE (in press)

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 ... [more ▼]

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 diffusion31 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 and making valuable inferences in group analysis and longitudinal studies. [less ▲]

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See detailAutomatic artifact detection for whole-night polysomnographic sleep recordings
Coppieters't Wallant, Dorothée ULg; Chellappa, Sarah Laxhmi ULg; Gaggioni, Giulia ULg et al

Poster (2014, September 17)

Detecting of bad channels and artifacts for whole-night polysomnographic recordings is very time consuming and tedious. We therefore developed an automatic procedure to automatize this job.

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See detailBright light therapy in restless legs syndrome: a doubleblind, placebo-controlled study
Kilic-Huck, Ulker; Meyer, Christelle ULg; Ruppert, Elisabeth et al

in Journal of Sleep Research (2014, September), 23

Medications often partially alleviate the symptoms of RLS patients, emphasizing the need for finding alternative treatments. Recent studies reported an efficacy of bright light therapy (BLT) in Parkinson ... [more ▼]

Medications often partially alleviate the symptoms of RLS patients, emphasizing the need for finding alternative treatments. Recent studies reported an efficacy of bright light therapy (BLT) in Parkinson disease. RLS pathogenesis involves the dopaminergic system and light has been shown to influence the dopaminergic tone. Therefore, the objective of our study was to determine the therapeutic value of three weeks of BLT on RLS symptoms severity, sleep quality, daytime somnolence, circadian rhythms and mood. [less ▲]

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See detailPrior light history impacts on higher order cognitive brain function
Chellappa, Sarah Laxhmi ULg; Ly, Julien; Meyer, Christelle ULg et al

Conference (2014, June 17)

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See detailPrior light history impacts on cognitive brain function
Chellappa, Sarah Laxhmi ULg; Ly, Julien; Meyer, Christelle ULg et al

Conference (2014)

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See detailPrior light history impacts on higher order cognitive brain function
Chellappa, Sarah Laxhmi ULg; Ly, Julien; Meyer, Christelle ULg et al

Conference (2014)

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See detailPhotic memory for executive brain responses
Chellappa*, Sarah Laxhmi ULg; Ly*, Julien ULg; Meyer, Christelle ULg et al

in Proceedings of the National Academy of Sciences of the United States of America (2014), Epub ahead of print

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See detailModulating effect of COMT genotype on the brain regions underlying proactive control process during inhibition
Jaspar, Mathieu ULg; Genon, Sarah ULg; Muto, Vincenzo ULg et al

in Cortex : A Journal Devoted to the Study of the Nervous System & Behavior (2014), 50

Introduction. Genetic variability related to the catechol-O-methyltransferase (COMT) gene (Val158Met polymorphism) has received increasing attention as a possible modulator of cognitive control functions ... [more ▼]

Introduction. Genetic variability related to the catechol-O-methyltransferase (COMT) gene (Val158Met polymorphism) has received increasing attention as a possible modulator of cognitive control functions. Methods. In an event-related fMRI study, a modified version of the Stroop task was administered to three groups of 15 young adults according to their COMT Val158Met 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 Val158Met genotype modulation of the brain regions underlying proactive control, especially in frontal areas as suggested by Braver et al. [less ▲]

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See detailFunctional neuroimaging of human REM sleep
Meyer, Christelle ULg; Jedidi, Zayd ULg; Muto, Vincenzo ULg et al

in Nofzinger, Eric; Maquet, Pierre; Thorpy, Michael J. (Eds.) Neuroimaging of sleep and sleep disorders (2013)

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See detailInfluence of sleep homeostasis and circadian rhythm on executive discriminative ability during a constant routine
Jaspar, Mathieu ULg; Meyer, Christelle ULg; Muto, Vincenzo ULg et al

Poster (2012, September)

Introduction & Objectives The human brain upholds cognitive performance throughout a waking day due to putative circadian (C) arousal signal (1) which counteracts the increase in homeostatic (H) sleep ... [more ▼]

Introduction & Objectives The human brain upholds cognitive performance throughout a waking day due to putative circadian (C) arousal signal (1) which counteracts the increase in homeostatic (H) sleep pressure associated to the deterioration in brain efficiency. When wakefulness is extended into the circadian night, maintenance of cognitive performance is jeopardized (Fig.1). Some individuals are very vulnerable to the negative effects of sleep loss and circadian misalignment, whereas others are resilient (3). These individuals differences can be readily explained within the conceptual framework of the circadian and homeostatic regulation of performance (4,5) but also by individual genetic differences and notably the PERIOD3 gene polymorphism (6). In this experiment, we investigated the consequences of sleep deprivation on cognitive performance during a working memory task (3-back). Following the signal detection theory, the ability to discriminate target from non-target stimuli is estimated by d prime (d') and criterion (cr). Here we assessed whether d' and cr were modulated by the raising sleep need and the oscillatory circadian signal. We also tested whether the individual vulnerability to sleep loss predicted by the PERIOD3 gene polymorphism influences this cognitive modulation, which is also driven by the sleep/wake regulation. Materials and Methods Population: Thirty-five right-handed healthy young volunteers aged from 19 to 26 (17 females) were recruited on the basis of their PER3 polymorphism. From a sample of about 400 screened volunteers, twelve 5/5 and twenty-three 4/4 homozygotes (matched for age, gender, chronotype, IQ, and level of education at the group level) participated in this study. Study protocol: Participants wore actigraphs for three weeks before the laboratory study. The first two weeks allowed us to determine their habitual sleep/wake schedule. During the third one, a strict sleep schedule adjusted on two possible timetables (00:00-08:00 or 01:00-09:00) was imposed in order to stagger fMRI sessions. Compliance to this schedule was again checked by wrist actigraphy and sleep diaries. The laboratory study began in the evening of day 1 and ran over 5 nights (Fig. 2). During the first 2 nights (habituation and baseline), the volunteers slept according to habitual sleep/wake schedule. Participants remained awake from the morning of day 3 for 42 hours. During this period, they remained in a semi-recumbent position, under dim light conditions (5 lux, eye level), with no information on clock time, in a constant routine protocol (CR). Saliva samples was hourly collected for melatonin analysis. Every 2 hours, volunteers received calibrated isocaloric snacks, behavioral data were collected and waking EEG recorded. During CR, behavioral measures were used to assess subjective (Karolinska Sleepiness Scale, KSS) and objective alertness (psychomotor vigilance task [PVT]). Executive functioning efficiency was assessed using the 3-back (Fig. 3) and SART tasks. During fMRI, participants performed alternating blocks of 0- and 3-back task. D’ and cr (Fig. 4) were analyzed with mixed-model analysis of variance (PROC Mixed), with main factors “session” and “genotype” (PER3 4/4 & PER3 5/5). All p-values derived from r-ANOVAs were based on Huynh-Feldt's (H-F) corrected degrees of freedom (p<0.05). Exploratory analysis assessed theoretical coefficients for the homeostatic sleep pressure (derived from a quasi-linear function) and the circadian oscillation (as a 24-hour period sine wave) were utilized in a multiple regression model to predict d’ and cr performance during the CR. Before these analyses, d’ and cr have been normalized using a z-score transformation. Results. Analyses on d’ 1. MIXED MODEL : Significant effect of sessions (F(12,385) = 17.16, p < 0.0001), but no group effect (F(1,133) = 0.00, p = 0.99) or interaction (F(12,385) = 1.51, p = 0.11). 2. REGRESSION: Significant regression (R² = 0.24, F(2,440) = 69.94, p <0.0001). The two predictors are significant (homeostat: p < 0.0001 ; circadian: p < 0.0001). Analyses on cr 1. MIXED MODEL : Significant effect of sessions (F(12,385) = 4.12, p < 0.0001), but no group effect (F(1,133) = 0.00, p = 0.99) or interaction (F(12,385) = 0.75, p = 0.71). 2. REGRESSION: Significant regression (R² = 0.04, F(2,440) = 9.35 , p = 0.0001). Only one predictor was significant (homeostat: p < 0.0001 ; circadian: p = 0.96). Conclusion These preliminary results show that both sleep homeostatic pressure and circadian factors influence executive discriminative ability during sleep loss, as assessed by signal detection theory (d’). Decision criterion (cr) appears modulated only by homeostatic sleep pressure. The difference between these two parameters could be explained by the theoretical modeling of the circadian oscillation and future analyses will incorporate individual experimentally-derived homeostatic and circadian parameters. Neither discrimination ability (d’) or criterion (cr) seem sensitive measures of individual cognitive vulnerability to sleep loss predicted by PER3 polymorphism. REFERENCES (1) Aston-Jones. Sleep Med. 2005, 6(Suppl 1), S3-7. (2) Dijk & Archer. Sleep Med. Rev. 2010, 14, 151-160.(3) Van Dongen & al. Sleep. 2004, 27, 423-433. (4) Mongrain & al. J. Sleep Res. 2006, 15, 162-166. (5) Van Dongen et al. Sleep. 2007, 30, 1129-1143. (6) Groeger & al. Sleep. 2008, 31, 1159-1167. (7) Vandewalle & al. J. Neuro. 2009, 29, 7948-7956. ACKNOWLEDGEMENTS & SPONSORS Cyclotron Research Centre (CRC) ; Belgian National Funds of Scientific Research (FNRS) ; Actions de Recherches Concertées (ARC, ULg) – Fondation Médicale Reine Elisabeth (FMRE) ; Walloon Excellence in Lifesciences and Biotechnology (WELBIO) ; Wellcome Trust ; Biotechnology and Biological Sciences Research Council (BBSRC) [less ▲]

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See detailInfluence of sleep homeostasis and circadian rhythm on waking EEG oscillations during a constant routine
Muto, Vincenzo ULg; Meyer, Christelle ULg; Jaspar, Mathieu ULg et al

Poster (2012, September)

Introduction & Objectives Human sleep and wake EEG oscillations are modulated by complex non-additive interaction between homeostatic and circadian processes. Quantitative analysis of EEG data, during ... [more ▼]

Introduction & Objectives Human sleep and wake EEG oscillations are modulated by complex non-additive interaction between homeostatic and circadian processes. Quantitative analysis of EEG data, during extended wakefulness, indicate that its frequency-specificity is influenced by both factors, such that low-frequencies (<8Hz) increase with time spent awake (1), thus more homeostatically-driven, while alpha activity undergoes a clear circadian modulation (2). Interindividual differences in sleep-wake regulation in young volunteers are associated with the variable-number tandem-repeat (VNTR) polymorphism in the coding region of the circadian clock gene PERIOD3 (PER3). Individuals homozygous for the longer allele of PER3 (PER35/5) were reported to generate more slow wave activity during NREM sleep and theta activity during wakefulness, relative to individuals with the shorter allele (PER34/4). However, the phase and amplitude of circadian markers do not differ between these genotypes (3). Here we tested the hypothesis if fluctuations in the dynamics of waking EEG frequency-specificity are modulated by a polymorphism in the clock gene PER3, under 42h of sustained wakefulness. Materials and Methods Population. A total of 400 young men and women were recruited, from whom DNA samples and questionnaire data were collected. On the basis of their PER3 polymorphism, 35 healthy young volunteers (age: 19-26 y; 17 females) were recruited, out of which twelve were PER35/5 and twenty-three PER34/4 homozygotes, and matched by age, gender, level of education, chronotype and IQ at the group level. Study protocol. The laboratory part of this study began in the evening of day 1 until day 5 (Fig. 1). During the first 2 nights (habituation and baseline), volunteers followed one out of two possible sleep-wake schedules (00:00-08:00 or 01:00-09:00). Thereafter, participants underwent approximately 42 hours of sustained wakefulness under constant routine (CR) conditions (semi-recumbent position, dim light <5 lux, no time-of-day information), and a subsequent recovery sleep episode. EEG recordings. Continuous EEG measurements with 9 EEG channels (F3, Fz, F4, C3, Cz, C4, Pz, O1, O2) were performed throughout the CR. Waking EEG was recorded every 2-h, during a modified version of the Karolinska Drowsiness Test (KDT) (4). Data presented here pertain to the last 60-sec of KDT, during which subjects were instructed to relax, to fixate a dot displayed on a screen ca. 75cm and to try to suppress blinks. After re-referencing to mean mastoids, recordings were scored using Rechtschaffen criteria. The 1-min EEGs during the KDT were manually and visually scored for artifacts (eye blinks, body movements, and slow eye movements) offline by 2 independent observers. The absolute EEG power density was then calculated for artifact-free 2-s epochs in the frequency range of 0.5 to 20 Hz , overlapping by 1 second using the pwelch function in MATLAB (7.5.0). For data reduction, power density of artifact-free 2-s epochs was averaged over 20-s epochs. Statistics. Waking EEG delta (0.75-4.5Hz), theta (4.75-7.75Hz) and alpha (8-12.0Hz) power density computed on Central derivation (Cz) were analyzed with a mixed-model analysis of variance (PROC Mixed), with main factors “elapsed time awake” and “genotype” (PER34/4 and PER35/5), and the interaction of these two factors. All p-values derived from r-ANOVAs were based on Huynh-Feldt's (H-F) corrected degrees of freedom (p<0.05). Multiple comparisons were performed using Tukey-Kramer test. Theoretical coefficients for the homeostatic sleep pressure (derived from a quasi-linear function) and the circadian oscillation (24-hour period sine wave) were used in a multiple regression model to predict delta, theta and alpha activity during the CR. Prior to multiple regression analysis, data were normalized according to PROC Transreg, in order to derive the best normalization method for linear and non-linear datasets. Results. Delta activity Analysis of delta activity yielded a significant main effect of “elapsed time awake” (F=5.31; p < 0.0001), albeit no significant effects for “genotype” (F=0.01; p = 0.94) nor for the interaction of these factors (F=0.85; p = 0.65). The multiple regression model revealed a significant regression (R² = 0.0433 Adj. R² = 0.0404; F = 15.24; p <0.0001), for the homeostat (p < 0.0001 ) and circadian (p = 0.0006) coefficients. Theta activity Analysis of theta activity yielded a significant main effect of “elapsed time awake” (F= 12.2; p < 0.0001), although no significant effects for “genotype” (F= 0.1; p = 0.70) nor for the interaction of these factors (F= 0.67; p = 0.86). The multiple regression model revealed a significant regression (R²= 0.072 Adj. R² =0.069; F= 26.36; p <0.0001), for the homeostat (p < 0.0001 ) and circadian (p < 0.0001 ) coefficients. Alpha activity Analysis of alpha activity yielded a significant main effect of “elapsed time awake”(F=3.43; p < 0.0001), although no significant effects for “genotype” (F = 0.01; p = 0.92) nor for the interaction of these factors (F= 1.23; p = 0.22). The multiple regression model revealed a significant regression (R²=0.052; Adj. R²=0.05; F =18.63; p <0.0001), for the homeostat (p = 0.0012) and for the circadian (p < 0.0001) coefficients. Conclusion Our results indicate that fluctuations in the dynamics of waking EEG activity are modulated by the circadian and homeostatic processes, although the magnitude of these differences are not underlined by a polymorphism in the clock gene PER3. REFERENCES 1. Cajochen C, Brunner DP, Kräuchi K, Graw P, Wirz-Justice A. Power density in theta/alpha frequencies of the waking EEG progressively increases during sustained wakefulness. Sleep. 1995, 10:890-894. 2. Cajochen C, Wyatt JK, Czeisler CA, Dijk DJ.Separation of circadian and wake duration-dependent modulation of EEG activation during wakefulnessNeuroscience. 2002, 114:1047-60. 3. Viola AU, Archer SN, James LM, Groeger JA, Lo JC, Skene DJ, von Schantz M, Dijk DJ PER3 polymorphism predicts sleep structure and waking performance. Curr Biol 2007,17:613–618. 4. Gillberg M, Kecklund G, Akerstedt T. Relations between performance and subjective rating of sleepiness during a night awake. Sleep 1994, 17:236-241. ACKNOWLEDGEMENTS & SPONSORS Cyclotron Research Centre (CRC) ; Belgian National Funds of Scientific Research (FNRS) ; Actions de Recherche Concertées (ARC, ULg) – Fondation Médicale Reine Elisabeth (FMRE) ; Walloon Excellence in Lifesciences and Biotechnology (WELBIO) ; Wellcome Trust ; Biotechnology and Biological Sciences Research Council (BBSRC) [less ▲]

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See detailNeural Correlates of Human Sleep and Sleep-Dependent Memory Processing
Meyer, Christelle ULg; Muto, Vincenzo ULg; Jaspar, Mathieu ULg et al

in Frank, Marcos (Ed.) Sleep and Brain Activity (2012)

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 ... [more ▼]

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 which can be hindered by sleep deprivation. Collectively, these data reveal the dynamical changes in brain activity during sleep which support normal human cognition. [less ▲]

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See detailCharacterization of periodic upper limb movement disorder in a patient with restless arms syndrome.
Ruppert, Elisabeth; Cretin, Benjamin; Meyer, Christelle ULg et al

in Movement Disorders : Official Journal of the Movement Disorder Society (2012), 27(11), 1459-61

BACKGROUND: Restless legs syndrome (RLS) and the frequently associated periodic limb movements (PLM) are common neurological disorders whose pathophysiology remains elusive. We report on the case of a 40 ... [more ▼]

BACKGROUND: Restless legs syndrome (RLS) and the frequently associated periodic limb movements (PLM) are common neurological disorders whose pathophysiology remains elusive. We report on the case of a 40-year-old patient presenting with severe restlessness in the upper limbs, a poorly known variant of RLS. CASE REPORT: Video-polysomnography was performed because of the associated poor sleep quality and daytime sleepiness evocative of PLM. An electromyogram of the extensor carpi radialis muscle was added. Remarkably, our patient had movements of repeated extension of the small finger that contrasted with the extension of the hallux, characteristic for PLM. Pramipexol was an effective treatment relieving the patient's upper limbs of discomfort and ameliorating her restless sleep. CONCLUSIONS: Involvement of the upper limbs in RLS is relatively common, but restlessness may be located on the upper limbs solely. One should be aware of the upper limb variant, and that treatment by dopaminergic agonists proves to be very efficient. [less ▲]

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