References of "Maquet, Pierre"
     in
Bookmark and Share    
Full Text
Peer Reviewed
See detailExploration of the mechanisms underlying the ISPC effect: Evidence from behavioral and neuroimaging data
Grandjean, Julien; D'Ostilio, Kevin ULg; Fias, Wim et al

in Neuropsychologia (2013), 51

The item-specific proportion congruent (ISPC) effect in a Stroop task – the observation of reduced interference for color words mostly presented in an incongruent color – has attracted growing interest ... [more ▼]

The item-specific proportion congruent (ISPC) effect in a Stroop task – the observation of reduced interference for color words mostly presented in an incongruent color – has attracted growing interest since the original study by Jacoby (2003). Two mechanisms have been proposed to explain the effect: associative learning of contingencies and item-specific control through word reading modulation. Both interpretations have received empirical support from behavioral data. Therefore, the aim of this study was to investigate the responsible mechanisms of the ISPC effect with the classic two-item sets design using fMRI. Results showed that the ISPC effect is associated with increased activity in the anterior cingulate (ACC), dorsolateral prefrontal (DLPFC), and inferior and superior parietal cortex. Importantly, behavioral and fMRI analyses specifically addressing the respective contribution of associative learning and item-specific control mechanisms brought support for the contingency learning account of the ISPC effect. Results are discussed in reference to task and procedure characteristics that may influence the extent to which item-specific control and/or contingency learning contribute to the ISPC effect. [less ▲]

Detailed reference viewed: 33 (6 ULg)
Peer Reviewed
See detailIncrease in cortico-thalamo-cortical connectivity during human sleep slow wave activity
Kussé, Caroline ULg; Lehembre, Rémy; Foret, Ariane et al

Poster (2012, October 27)

Detailed reference viewed: 13 (1 ULg)
Peer Reviewed
See detailDifference in neural correlates of discrimination during sleep deprivation in PER3 homozygous
Shaffii-Le Bourdiec, Anahita; Muto, Vincenzo ULg; Jaspar, Mathieu ULg et al

Poster (2012, September 07)

Detailed reference viewed: 43 (10 ULg)
Peer Reviewed
See detailIncrease in cortico-thalamo-cortical connectivity during human sleep slow wave activity
Kussé, Caroline ULg; Lehembre, Rémy; Foret, Ariane et al

Poster (2012, September 05)

Detailed reference viewed: 15 (1 ULg)
Peer Reviewed
See detailIncrease in cortico-thalamo-cortical connectivity during human sleep slow wave activity
Kussé, Caroline ULg; Lehembre, Rémy; Foret, Ariane et al

Poster (2012, September 04)

Detailed reference viewed: 11 (1 ULg)
Full Text
Peer Reviewed
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 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 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 . Some individuals are very vulnerable to the negative effects of sleep loss and circadian misalignment, whereas others are resilient. These individuals differences can be readily explained within the conceptual framework of the circadian and homeostatic regulation of performance but also by individual genetic differences and notably the PERIOD3 gene polymorphism. 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. [less ▲]

Detailed reference viewed: 157 (38 ULg)
Full Text
Peer Reviewed
See detailInfluence of sleep homeostasis and circadian rhythm on waking EEG oscillations during a constant routine
Muto, Vincenzo ULg; Jaspar, Mathieu ULg; Meyer, C et al

in Journal of Sleep Research (2012, September)

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 ... [more ▼]

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, thus more homeostatically-driven, while alpha activity undergoes a clear circadian modulation. 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 (PER3 5/5) were reported to generate more slow wave activity during NREM sleep and theta activity during wakefulness, relative to individuals with the shorter allele (PER3 4/4). However, the phase and amplitude of circadian markers do not differ between these genotypes. 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. [less ▲]

Detailed reference viewed: 198 (30 ULg)
Full Text
Peer Reviewed
See detailDecoding spontaneous brain activity from fMRI using Gaussian Processes: tracking brain reactivation
Schrouff, Jessica ULg; Kussé, Caroline ULg; Wehenkel, Louis ULg et al

in 2012 Second International Workshop on Pattern Recognition in NeuroImaging (PRNI 2012): proceedings (2012, July 03)

While Multi-Variate Pattern Analysis techniques based on machine learning have now been regularly applied to neuroimaging data, decoding brain activity is usually performed in highly controlled ... [more ▼]

While Multi-Variate Pattern Analysis techniques based on machine learning have now been regularly applied to neuroimaging data, decoding brain activity is usually performed in highly controlled experimental paradigms. In more realistic conditions, the number, sequence and duration of mental states are unpredictably generated by the individual, resulting in complex and imbalanced fMRI data sets. Moreover, in the case of spontaneous brain activity, the mental states can not be linked to any external or internal stimulation, which makes it a highly difficult condition to decode. This study tests the classification of brain activity, acquired on 14 volunteers using fMRI, during mental imagery, a condition in which the number and duration of mental events were not externally imposed but self-generated. Application of the obtained model on rest sessions allowed classifying spontaneous brain activity linked to the task which, overall, correlated with their behavioural performance to the task. [less ▲]

Detailed reference viewed: 40 (15 ULg)
Full Text
Peer Reviewed
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 ▲]

Detailed reference viewed: 131 (42 ULg)
Peer Reviewed
See detailIncrease in cortico-thalamo-cortical connectivity during human sleep slow wave activity
Kussé, Caroline ULg; Lehembre, Rémy; Foret, Ariane et al

Poster (2012, June 10)

Detailed reference viewed: 21 (2 ULg)
See detailModulating effect of COMT genotype on the brains regions underlying inhibition
Jaspar, Mathieu ULg; Grandjean, Julien ULg; SALMON, Eric ULg et al

Conference (2012, May)

Catechol-O-methyltransferase (COMT) is an important enzyme which degrades catecholamines, such dopamine, notably in the prefrontal cortex (Männistö & Kaakkola, 1999). A large number of studies reported an ... [more ▼]

Catechol-O-methyltransferase (COMT) is an important enzyme which degrades catecholamines, such dopamine, notably in the prefrontal cortex (Männistö & Kaakkola, 1999). A large number of studies reported an effect on executive functioning of COMT genotype (Barnett & al., 2007), each genotype being associated with a different COMT enzymatic activity (Weinshilboum & al., 1999). In an event-related fMRI study, a modified form of the Stroop task was administered to 45 young adults separated in three groups according to their COMT val158met genotype : 15 homozygous val/val (VV), 15 homozygous met/met (MM) and 15 heterozygotes val/met (VM). Both behavioral and fMRI results indicated the presence of a general interference effect consistent with prior reports (Nee & al., 2007). More interestingly, group comparisons indicate that this effect is associated, for a similar behavioral performance, with increased medial frontal and precentral gyrus activity in VV and VM groups by comparison with MM group. Conversely, no supplementary brain areas were observed for the comparison of the MM to the two other groups. These observations, paralleling with the lower COMT enzymatic activity and, thus, the higher cortical dopamine level in met/met individuals, confirms our expectation of a COMT Val158Met genotype modulation of the brain regions underlying inhibition efficiency. [less ▲]

Detailed reference viewed: 17 (4 ULg)
Full Text
Peer Reviewed
See detailIdentifying the default-mode component in spatial IC analyses of patients with disorders of consciousness.
Soddu, Andrea ULg; Vanhaudenhuyse, Audrey ULg; Bahri, Mohamed Ali ULg et al

in Human Brain Mapping (2012), 36

Objectives:Recent fMRI studies have shown that it is possible to reliably identify the default-mode network (DMN) in the absence of any task, by resting-state connectivity analyses in healthy volunteers ... [more ▼]

Objectives:Recent fMRI studies have shown that it is possible to reliably identify the default-mode network (DMN) in the absence of any task, by resting-state connectivity analyses in healthy volunteers. We here aimed to identify the DMN in the challenging patient population of disorders of consciousness encountered following coma. Experimental design: A spatial independent component analysis-based methodology permitted DMN assessment, decomposing connectivity in all its different sources either neuronal or artifactual. Three different selection criteria were introduced assessing anticorrelation-corrected connectivity with or without an automatic masking procedure and calculating connectivity scores encompassing both spatial and temporal properties. These three methods were validated on 10 healthy controls and applied to an independent group of 8 healthy controls and 11 severely brain-damaged patients [locked-in syndrome (n = 2), minimally conscious (n = 1), and vegetative state (n = 8)]. Principal observations: All vegetative patients showed fewer connections in the default-mode areas, when compared with controls, contrary to locked-in patients who showed near-normal connectivity. In the minimally conscious-state patient, only the two selection criteria considering both spatial and temporal properties were able to identify an intact right lateralized BOLD connectivity pattern, and metabolic PET data suggested its neuronal origin. Conclusions: When assessing resting-state connectivity in patients with disorders of consciousness, it is important to use a methodology excluding non-neuronal contributions caused by head motion, respiration, and heart rate artifacts encountered in all studied patients. Hum Brain Mapp, 2011. (c) 2011 Wiley-Liss, Inc. [less ▲]

Detailed reference viewed: 94 (5 ULg)
See detailFunctional Neuroimaging during Human Sleep
Kussé, Caroline ULg; Maquet, Pierre ULg

in Barrett, Deirdre; McNamara, Patrick (Eds.) Encyclopedia of sleep and dreams (2 volumes): the evolution, function, nature and mysteries of slumber (2012)

Detailed reference viewed: 16 (1 ULg)
Full Text
Peer Reviewed
See detailNeural Correlates of Performance Variabilty during Motor Sequence Acquisition
Albouy, Geneviève ULg; Sterpenich, V.; Vandewalle, Gilles ULg et al

in NeuroImage (2012), 60(1), 324-331

Detailed reference viewed: 68 (15 ULg)
Full Text
Peer Reviewed
See detailDecoding Semi-Constrained Brain Activity from fMRI Using Support Vector Machines and Gaussian Processes
Schrouff, Jessica ULg; Kussé, Caroline ULg; Wehenkel, Louis ULg et al

in PLoS ONE (2012), 7(4),

Predicting a particular cognitive state from a specific pattern of fMRI voxel values is still a methodological challenge. Decoding brain activity is usually performed in highly controlled experimental ... [more ▼]

Predicting a particular cognitive state from a specific pattern of fMRI voxel values is still a methodological challenge. Decoding brain activity is usually performed in highly controlled experimental paradigms characterized by a series of distinct states induced by a temporally constrained experimental design. In more realistic conditions, the number, sequence and duration of mental states are unpredictably generated by the individual, resulting in complex and imbalanced fMRI data sets. This study tests the classification of brain activity, acquired on 16 volunteers using fMRI, during mental imagery, a condition in which the number and duration of mental events were not externally imposed but self-generated. To deal with these issues, two classification techniques were considered (Support Vector Machines, SVM, and Gaussian Processes, GP), as well as different feature extraction methods (General Linear Model, GLM and SVM). These techniques were combined in order to identify the procedures leading to the highest accuracy measures. Our results showed that 12 data sets out of 16 could be significantly modeled by either SVM or GP. Model accuracies tended to be related to the degree of imbalance between classes and to task performance of the volunteers. We also conclude that the GP technique tends to be more robust than SVM to model unbalanced data sets. [less ▲]

Detailed reference viewed: 88 (22 ULg)
Full Text
Peer Reviewed
See detailInfluence of acute sleep loss on the neural correlates of alerting, orientating and executive attention components
Muto, Vincenzo ULg; Shaffii, Anahita ULg; Matarazzo, Luca et al

in Journal of Sleep Research (2012), 21(6), 648-58

Detailed reference viewed: 63 (38 ULg)