References of "Phillips, Christophe"
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See detailThe neural bases of proactive and reactive control processes in normal aging
Manard, Marine ULg; François, Sarah ULg; Phillips, Christophe ULg et al

in Behavioural Brain Research (in press)

Introduction. Research on cognitive control suggests an age-related decline in proactive control abilities (anticipatory control), whereas reactive control (following conflict detection) seems to remain ... [more ▼]

Introduction. Research on cognitive control suggests an age-related decline in proactive control abilities (anticipatory control), whereas reactive control (following conflict detection) seems to remain intact. As proactive and reactive control abilities are associated with specific brain networks, this study investigated age-related effects on the neural substrates associated with each kind of control. Methods. In an event-related fMRI study, a modified version of the Stroop task was administered to groups of 20 young and 20 older healthy adults. Based on the theory of dual mechanisms of control, the Stroop task has been built to induce proactive or reactive control depending on task context. Results. Behavioral results (p < .05) indicated faster processing of interfering items in the mostly incongruent (MI) than the mostly congruent (MC) context in both young and older participants. fMRI results showed that reactive control is associated with increased activity in left frontal areas for older participants. For proactive control, decreased activity in the bilateral anterior cingulate cortex was associated with more activity in the right middle frontal gyrus in the older than the younger group. Conclusion. These observations support the hypothesis that aging affects the neural networks associated with reactive and proactive cognitive control differentially. These age-related changes are very similar to those observed in young adults with low dopamine availability, suggesting that a general mechanism (prefrontal dopamine availability) may modulate brain networks associated with various kinds of cognitive control. [less ▲]

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See detailAge-related differences in the dynamics of cortical excitability and cognitive inhibition during prolongedwakefulness
Gaggioni, Giulia ULg; Chelllappa, S.; Ly, J. et al

Conference (2016, September)

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See detailCircadian dynamics in measures of cortical excitation and inhibition balance
Chellappa, Sarah; Gaggioni, Giulia ULg; LY, Julien ULg et al

in Scientific Reports (2016), 6:33661

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See detailLocal modulation of human brain responses by circadian rhythmicity and sleep debt
Muto, Vincenzo ULg; Jaspar, Mathieu ULg; Meyer, Christelle et al

in Science (2016), 351(6300),

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See detailSleep deprivation affects brain global cortical responsivenes
Gaggioni, Giulia ULg; Chellappa, S; Ly, J et al

Conference (2016, June 15)

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See detailSeasonal variation in human COGNITIVE brain responses
Meyer, Christelle; Muto, Vincenzo ULg; Jaspar, Mathieu ULg et al

Poster (2016, June)

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See detailThe influence of COMT single nucleotide polymorphism (rs4680) on the neural substrates of working memory representations maintenance in healthy aging
Manard, Marine ULg; François, Sarah ULg; Bahri, Mohamed Ali ULg et al

Poster (2016, May 10)

The COMT val108/158met polymorphism was associated to the dopaminergic modulation in the brain, and therefore stimulated research on its influence for cognitive functioning and particularly working memory ... [more ▼]

The COMT val108/158met polymorphism was associated to the dopaminergic modulation in the brain, and therefore stimulated research on its influence for cognitive functioning and particularly working memory. First, a general advantage of carrying the met allele was reported. However, many studies used tasks that did not allow efficiently assessing the contribution of manipulation and maintenance processes in working memory, leading to divergent results, in both young and older populations, resulting in debates about the exact phenotypic effect of the COMT polymorphism. Using fMRI, this study was designed to assess the potential effect of the COMT polymorphism on age-related differences in working memory representations maintenance abilities (Sternberg paradigm). Partial Least Squares method was used to determine the brain-behavior correlations at low, intermediate, and high cognitive demands among young and older groups, homozygous for the val or for the met allele. First, young val/val showed some disadvantages at brain and behavioral level compared to their m/m counterparts. However, in older adults subgroups, the m/m participants tended to show greater age-related difference (when compared to younger adults with similar genotype), suggesting an advantage in carrying the val allele when dopamine signaling is not at optimal efficiency (optimal: young/middle adulthood vs suboptimal: childhood or older ages). These results will be discussed in regard to compensating theories and dopaminergic models accounting for the potential effect of COMT polymorphism on stability/flexibility abilities. [less ▲]

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See detailDecoding intracranial EEG data with multiple kernel learning method
Schrouff, Jessica ULg; Mourao-Miranda, Janaina; Phillips, Christophe ULg et al

in Journal of Neuroscience Methods (2016), 261

Machine learning models have been successfully applied to neuroimaging data to make predictions about behavioral and cognitive states of interest. While these multivariate methods have greatly advanced ... [more ▼]

Machine learning models have been successfully applied to neuroimaging data to make predictions about behavioral and cognitive states of interest. While these multivariate methods have greatly advanced the field of neuroimaging, their application to electrophysiological data has been less common especially in the analysis of human intracranial electroencephalography (iEEG, also known as electrocorticography or ECoG) data, which contains a rich spectrum of signals recorded from a relatively high number of recording sites. In the present work, we introduce a novel approach to determine the contribution of different bandwidths of EEG signal in different recording sites across different experimental conditions using the Multiple Kernel Learning (MKL) method. To validate and compare the usefulness of our approach, we applied this method to an ECoG dataset that was previously analysed and published with univariate methods. Our findings proved the usefulness of the MKL method in detecting changes in the power of various frequency bands during a given task and selecting automatically the most contributory signal in the most contributory site(s) of recording. With a single computation, the contribution of each frequency band in each recording site in the estimated multivariate model can be highlighted, which then allows formulation of hypotheses that can be tested a posteriori with univariate methods if needed. [less ▲]

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See detailSeasonality in human cognitive brain responses
Meyer, Christelle ULg; Muto, Vincenzo ULg; Jaspar, Mathieu ULg et al

in Proceedings of the National Academy of Sciences of the United States of America (2016)

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See detailAutomatic artifacts and arousals detection in whole-night sleep EEG recordings
Coppieters't Wallant, Dorothe ULg; Muto, Vincenzo ULg; Gaggioni, Giulia ULg et al

in Journal of Neuroscience Methods (2016), 258

In sleep electroencephalographic (EEG) signals, artifacts and arousals marking are usually part of the processing. This visual inspection by a human expert has two main drawbacks: it is very time ... [more ▼]

In sleep electroencephalographic (EEG) signals, artifacts and arousals marking are usually part of the processing. This visual inspection by a human expert has two main drawbacks: it is very time consuming and subjective. To detect artifacts and arousals in a reliable, systematic and reproducible automatic way, we developed an automatic detection based on time and frequency analysis with adapted thresholds derived from data themselves. The automatic detection performance is assessed using 5 statistic parameters, on 60 whole night sleep recordings coming from 35 healthy volunteers (male and female) aged between 19 and 26. The proposed approach proves its robustness against inter- and intra-, subjects and raters’ scorings, variability. The agreement with human raters is rated overall from substantial to excellent and provides a significantly more reliable method than between human raters. Existing methods detect only specific artifacts or only arousals, and/or these methods are validated on short episodes of sleep recordings, making it difficult to compare with our whole night results. The method works on a whole night recording and is fully automatic, reproducible, and reliable. Furthermore the implementation of the method will be made available online as open source code. [less ▲]

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See detailCross-Modal Decoding of Neural Patterns Associated with Working Memory: Evidence for Attention-Based Accounts of Working Memory
Majerus, Steve ULg; Cowan, Nelson; Peters, Frédéric ULg et al

in Cerebral Cortex (2016), 26

Recent studies suggest common neural substrates involved in verbal and visual working memory (WM), interpreted as reflecting shared attention-based, short-term retention mechanisms. We used a machine ... [more ▼]

Recent studies suggest common neural substrates involved in verbal and visual working memory (WM), interpreted as reflecting shared attention-based, short-term retention mechanisms. We used a machine-learning approach to determine more directly the extent to which common neural patterns characterize retention in verbal WM and visual WM. Verbal WM was assessed via a standard delayed probe recognition task for letter sequences of variable length. Visual WM was assessed via a visual array WM task involving the maintenance of variable amounts of visual information in the focus of attention. We trained a classifier to distinguish neural activation patterns associated with high- and low-visual WM load and tested the ability of this classifier to predict verbal WM load (high–low) from their associated neural activation patterns, and vice versa. We observed significant between-task prediction of load effects during WM maintenance, in posterior parietal and superior frontal regions of the dorsal attention network; in contrast, between-task prediction in sensory processing cortices was restricted to the encoding stage. Furthermore, between-task prediction of load effects was strongest in those participants presenting the highest capacity for the visual WM task. This study provides novel evidence for common, attention-based neural patterns supporting verbal and visual WM. [less ▲]

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See detailPupil size dynamics during prolonged wakefulness reflects the dual interaction of sleep-homeostasis and the circadian timing system and is related to cortical excitability
Van Egroo, Maxime ULg; Cespedes-Ortiz, Cristian ULg; Ly, Julien et al

Poster (2016)

Objective. We sought to characterize daily variations in pupil size as a function of sleep need and circadian phase. We also assessed second-to-second pupil size variability during prolonged wakefulness ... [more ▼]

Objective. We sought to characterize daily variations in pupil size as a function of sleep need and circadian phase. We also assessed second-to-second pupil size variability during prolonged wakefulness. Methods. Twenty-two healthy young men (22 y.o. ± 2.6) followed a 29h sleep deprivation protocol under constant routine conditions. On twelve occasions, pupil size was recorded (90 Hz sampling rate) while fixating a dot and suppressing eye blinks. Following automatic eye blink and artefact rejection, mean pupil size and average point to point variation in pupil size data were computed. Data were realigned according to individual dim-light melatonin onset determined based on hourly saliva samples. Results. Preliminary analyses indicate that both mean pupil size and pupil size variability show a main effect of circadian phase (PROC MIXED; n = 20; F11,206 > 4.4, p < 0.001). Post hoc analyses show that mean pupil size and pupil size variability increase up to the evening wake maintenance prior to decreasing until the early morning around the putative sleep promoting zone. Conclusion. These data confirm the pupil size and pupil size variability reflect the dual interaction of sleep homeostasis and the circadian timing system. Further analyses will determine how pupil size dynamics relates to makers of brain function. [less ▲]

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See detailCircadian and homeostatic sleep pressure modulate fMRI correlates of vigilant attention
Muto, Vincenzo ULg; Jaspar, Mathieu ULg; Meyer, C et al

in Journal of Sleep Research (2016), 25(s1),

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See detailCombining feature extraction methods to assist the diagnosis of Alzheimer's disease
Segovia, Fermin; Górriz, J. M.; Ramírez, J. et al

in Current Alzheimer Research (2016), 13

Neuroimaging data as 18F-FDG PET is widely used to assist the diagnosis of Alzheimer’s disease (AD). Looking for regions with hypoperfusion/ hypometabolism, clinicians may predict or corroborate the ... [more ▼]

Neuroimaging data as 18F-FDG PET is widely used to assist the diagnosis of Alzheimer’s disease (AD). Looking for regions with hypoperfusion/ hypometabolism, clinicians may predict or corroborate the diagnosis of the patients. Modern computer aided diagnosis (CAD) systems based on the statistical analysis of whole neuroimages are more accurate than classical systems based on quantifying the uptake of some predefined regions of interests (ROIs). In addition, these new systems allow determining new ROIs and take advantage of the huge amount of information comprised in neuroimaging data. A major branch of modern CAD systems for AD is based on multivariate techniques, which analyse a neuroimage as a whole, considering not only the voxel intensities but also the relations among them. In order to deal with the vast dimensionality of the data, a number of feature extraction methods have been successfully applied. In this work, we propose a CAD system based on the combination of several feature extraction techniques. First, some commonly used feature extraction methods based on the analysis of the variance (as principal component analysis), on the factorization of the data (as non-negative matrix factorization) and on classical magnitudes (as Haralick features) were simultaneously applied to the original data. These feature sets were then combined by means of two different combination approaches: i) using a single classifier and a multiple kernel learning approach and ii) using an ensemble of classifier and selecting the final decision by majority voting. The proposed approach was evaluated using a labelled neuroimaging database along with a cross validation scheme. As conclusion, the proposed CAD system performed better than approaches using only one feature extraction technique. We also provide a fair comparison (using the same database). [less ▲]

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See detailCircadian regulation of human cortical excitability
LY, Julien ULg; Gaggioni, Giulia ULg; Chellappa, Sarah et al

in Nature Communications (2016)

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See detailSleep deprivation affects brain global cortical responsiveness
Gaggioni, Giulia ULg; Chellappa; Ly et al

Poster (2016)

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See detailCorrelation between resting state fMRI total neuronal activity and PET metabolism in healthy controls and patients with disorders of consciousness
Soddu, Andrea ULg; Gomez, Francisco; Heine, Lizette ULg et al

in Brain and Behavior (2016)

Introduction: The mildly invasive 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) is a well-established imaging technique to measure ‘resting state’ cerebral metabolism. This technique made ... [more ▼]

Introduction: The mildly invasive 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) is a well-established imaging technique to measure ‘resting state’ cerebral metabolism. This technique made it possible to assess changes in metabolic activity in clinical applications, such as the study of severe brain injury and disorders of consciousness. Objective: We assessed the possi- bility of creating functional MRI activity maps, which could estimate the rela- tive levels of activity in FDG-PET cerebral metabolic maps. If no metabolic absolute measures can be extracted, our approach may still be of clinical use in centers without access to FDG-PET. It also overcomes the problem of recogniz- ing individual networks of independent component selection in functional mag- netic resonance imaging (fMRI) resting state analysis. Methods: We extracted resting state fMRI functional connectivity maps using independent component analysis and combined only components of neuronal origin. To assess neu- ronality of components a classification based on support vector machine (SVM) was used. We compared the generated maps with the FDG-PET maps in 16 healthy controls, 11 vegetative state/unresponsive wakefulness syndrome patients and four locked-in patients. Results: The results show a significant similarity with q = 0.75  0.05 for healthy controls and q = 0.58  0.09 for vegetative state/unresponsive wakefulness syndrome patients between the FDG- PET and the fMRI based maps. FDG-PET, fMRI neuronal maps, and the conjunction analysis show decreases in frontoparietal and medial regions in vegetative patients with respect to controls. Subsequent analysis in locked-in syndrome patients produced also consistent maps with healthy controls. Conclusions: The constructed resting state fMRI functional connectivity map points toward the possibility for fMRI resting state to estimate relative levels of activity in a metabolic map. [less ▲]

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