References of "Phillips, Christophe"
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See detailPRoNTo: Pattern Recognition for Neuroimaging Toolbox
Schrouff, Jessica ULg; Rosa, Maria J; Rondina, Jane et al

Poster (2012, June 12)

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See detailAutomatic multiclass classification of 18FDG-PET scans for the distinction between Parkinson’s disease and atypical parkinsonian syndromes
Phillips, Christophe ULg; Schrouff, Jessica ULg; Luxen, André ULg et al

Poster (2012, June 10)

Part of the difficulty in the early diagnosis of Parkinson’s disease (PD) is in differentiating it from atypical parkinsonian disorders (APS) that have a poorer prognosis such as multiple system atrophy ... [more ▼]

Part of the difficulty in the early diagnosis of Parkinson’s disease (PD) is in differentiating it from atypical parkinsonian disorders (APS) that have a poorer prognosis such as multiple system atrophy (MSA), progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS). 18flurodeoxyglucose (FDG) positron emission tomography (PET) has been recommended for the early differentiation between PD and APS [1]. Here, 120 FDG PET scans (42, 31, 26 and 21 for the PD, MSA, PSP and CBS resp.) were acquired on average 3.5 years after symptoms onset (because the initial clinical features were outside the prevailing perception for PD) to look, without any a priori assumption, for cerebral FDG uptake patterns that discriminate either between the PD and APS classes, or between the four PD, MSA, PSP and CBS classes. The diagnostic used to label the scans was defined by clinical criteria on average 4.5 years after PET assessment. [less ▲]

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See detailAnisotropy preserving interpolation of diffusion tensors
Collard, Anne ULg; Bonnabel, Silvère; Phillips, Christophe ULg et al

Poster (2012, June)

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See detailSPM for MEG/EEG
Phillips, Christophe ULg

Scientific conference (2012, April)

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See detailAnisotropy preserving interpolation of diffusion tensors
Collard, Anne ULg; Bonnabel, Silvère; Phillips, Christophe ULg et al

Conference (2012, March)

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See detailImpact of noise correction on diffusion kurtosis estimation
André, Elodie ULg; Balteau, Evelyne ULg; Phillips, Christophe ULg et al

in Proceedings of the International Society for Magnetic Resonance in Medicine ... Scientific Meeting and Exhibition. International Society For Magnetic Resonance in Medicine. Scientific Meeting and Exhibition (2012), 20

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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

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See detailPRoNTo: Pattern Recognition for Neuroimaging Toolbox
Schrouff, Jessica ULg; Rosa, Maria Joao; Rondina, Jane et al

Software (2012)

PRoNTo (Pattern Recognition for Neuroimaging Toolbox) is a software toolbox based on pattern recognition techniques for the analysis of neuroimaging data. Statistical pattern recognition is a field within ... [more ▼]

PRoNTo (Pattern Recognition for Neuroimaging Toolbox) is a software toolbox based on pattern recognition techniques for the analysis of neuroimaging data. Statistical pattern recognition is a field within the area of machine learning which is concerned with automatic discovery of regularities in data through the use of computer algorithms, and with the use of these regularities to take actions such as classifying the data into different categories. In PRoNTo, brain scans are treated as spatial patterns and statistical learning models are used to identify statistical properties of the data that can be used to discriminate between experimental conditions or groups of subjects (classification models) or to predict a continuous measure (regression models). PRoNTo aims to facilitate the interaction between machine learning and neuroimaging communities. On one hand, the machine learning community can contribute to the toolbox with novel machine learning models. On the other hand, the toolbox provides a variety of tools for the neuroscience and clinical neuroscience communities, enabling them to ask new questions that cannot be easily investigated using existing software and analysis tools. PRoNTo is distributed for free as copyright software under the terms of the GNU General Public License as published by the Free Software Foundation. The development of the toolbox has been supported by the PASCAL Harvest framework and The Wellcome Trust. [less ▲]

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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 ▲]

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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

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See detailCircadian preference modulates the neural substrate of conflict processing across the day
Schmidt, Christina ULg; Peigneux, Philippe ULg; Leclercq, Yves ULg et al

in PLoS ONE (2012), 7(1), 29658

Human morning and evening chronotypes differ in their preferred timing for sleep and wakefulness, as well as in optimal daytime periods to cope with cognitive challenges. Recent evidence suggests that ... [more ▼]

Human morning and evening chronotypes differ in their preferred timing for sleep and wakefulness, as well as in optimal daytime periods to cope with cognitive challenges. Recent evidence suggests that these preferences are not a simple by-product of socio-professional timing constraints, but can be driven by inter-individual differences in the expression of circadian and homeostatic sleep-wake promoting signals. Chronotypes thus constitute a unique tool to access the interplay between those processes under normally entrained day-night conditions, and to investigate how they impinge onto higher cognitive control processes. Using functional magnetic resonance imaging (fMRI), we assessed the influence of chronotype and time-of-day on conflict processing-related cerebral activity throughout a normal waking day. Sixteen morning and 15 evening types were recorded at two individually adapted time points (1.5 versus 10.5 hours spent awake) while performing the Stroop paradigm. Results show that interference-related hemodynamic responses are maintained or even increased in evening types from the subjective morning to the subjective evening in a set of brain areas playing a pivotal role in successful inhibitory functioning, whereas they decreased in morning types under the same conditions. Furthermore, during the evening hours, activity in a posterior hypothalamic region putatively involved in sleep-wake regulation correlated in a chronotype-specific manner with slow wave activity at the beginning of the night, an index of accumulated homeostatic sleep pressure. These results shed light into the cerebral mechanisms underlying inter-individual differences of higher-order cognitive state maintenance under normally entrained day-night conditions. [less ▲]

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See detailThe fate of incoming stimuli during NREM sleep is determined by spindles and the phase of the slow oscillation
Schabus, M.; Dang Vu, Thien Thanh ULg; Heib, D. P. J. et al

in Frontiers in Neurology (2012), 3(40), 1-11

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See detailMetabolic activity in external and internal awareness networks in severely brain-damaged patients.
Thibaut, Aurore ULg; Bruno, Marie-Aurélie ULg; Chatelle, Camille ULg et al

in Journal of Rehabilitation Medicine (2012), 44(6), 487-94

OBJECTIVE: An extrinsic cerebral network (encompassing lateral frontoparietal cortices) related to external/sensory awareness and an intrinsic midline network related to internal/self-awareness have been ... [more ▼]

OBJECTIVE: An extrinsic cerebral network (encompassing lateral frontoparietal cortices) related to external/sensory awareness and an intrinsic midline network related to internal/self-awareness have been identified recently. This study measured brain metabolism in both networks in patients with severe brain damage. DESIGN: Prospective [18F]-fluorodeoxyglucose-positron emission tomography and Coma Recovery Scale-Revised assessments in a university hospital setting. SUBJECTS: Healthy volunteers and patients in vegetative state/unresponsive wakefulness syndrome (VS/UWS), minimally conscious state (MCS), emergence from MCS (EMCS), and locked-in syndrome (LIS). RESULTS: A total of 70 patients were included in the study: 24 VS/UWS, 28 MCS, 10 EMCS, 8 LIS and 39 age-matched controls. VS/UWS showed metabolic dysfunction in extrinsic and intrinsic networks and thalami. MCS showed dysfunction mostly in intrinsic network and thalami. EMCS showed impairment in posterior cingulate/retrosplenial cortices. LIS showed dysfunction only in infratentorial regions. Coma Recovery Scale-Revised total scores correlated with metabolic activity in both extrinsic and part of the intrinsic network and thalami. CONCLUSION: Progressive recovery of extrinsic and intrinsic awareness network activity was observed in severely brain-damaged patients, ranging from VS/UWS, MCS, EMCS to LIS. The predominance of intrinsic network impairment in MCS could reflect altered internal/self-awareness in these patients, which is difficult to quantify at the bedside. [less ▲]

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See detailItem familiarity and controlled associative retrieval in Alzheimer’s disease: An fMRI study.
Genon, Sarah ULg; Collette, Fabienne ULg; Feyers, Dorothée ULg et al

in Frontiers in Human Neuroscience (2012)

Alzheimer’s disease (AD) is characterised by altered recollection function, with impaired controlled retrieval of associations. In contrast, familiarity-based memory for individual items may sometimes be ... [more ▼]

Alzheimer’s disease (AD) is characterised by altered recollection function, with impaired controlled retrieval of associations. In contrast, familiarity-based memory for individual items may sometimes be preserved in the early stages of the disease. This is the first study that directly examines whole brain regional activity during one core aspect of the recollection function: associative controlled episodic retrieval (CER), contrasted to item familiarity in AD patients. Cerebral activity related to associative CER and item familiarity in AD patients and healthy controls (HC) was measured with functional magnetic resonance imaging during a word-pair recognition task to which the process dissociation procedure was applied. Some patients had null CER estimates (AD–), whereas others did show some CER abilities (AD+), although significantly less than HC. In contrast, familiarity estimates were equivalent in the three groups. In AD+, as in controls, associative CER activated the inferior precuneus/posterior cingulate cortex (PCC). However, during associative CER, functional connection between this region and the hippocampus, the inferior parietal and dorsolateral prefrontal cortex (DLPFC) was significantly higher in HC than in AD+. In all three groups, item familiarity was related to activation along the intraparietal sulcus (IPS). In conclusion, whereas the preserved automatic detection of an old item (without retrieval of accurate word association) is related to parietal activation centred on the IPS, the inferior precuneus/PCC supports associative CER ability in AD patients, as in HC. However, AD patients have deficient functional connectivity during associative CER, suggesting that the residual recollection function in these patients might be impoverished by the lack of some recollection-related aspects such as autonoetic quality, episodic details and verification. [less ▲]

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See detailThe neural correlates of recollection and familiarity during aging
Angel, Lucie; Bastin, Christine ULg; Genon, Sarah ULg et al

in Frontiers in Human Neuroscience (2012)

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See detailModulation of brain activity during a Stroop inhibitory task by the kind of cognitive control required
Grandjean, Julien ULg; D'Ostilio, Kevin ULg; Phillips, Christophe ULg et al

in PLoS ONE (2012), 7(7), 41513

This study used a proportion congruency manipulation in the Stroop task in order to investigate, at the behavioral and brain substrate levels, the predictions derived from the Dual Mechanisms of Control ... [more ▼]

This study used a proportion congruency manipulation in the Stroop task in order to investigate, at the behavioral and brain substrate levels, the predictions derived from the Dual Mechanisms of Control (DMC) account of two distinct modes of cognitive control depending on the task context. Three experimental conditions were created that varied the proportion congruency: mostly incongruent (MI), mostly congruent (MC), and mostly neutral (MN) contexts. A reactive control strategy, which corresponds to transient interference resolution processes after conflict detection, was expected for the rare conflicting stimuli in the MC context, and a proactive strategy, characterized by a sustained task-relevant focus prior to the occurrence of conflict, was expected in the MI context. Results at the behavioral level supported the proactive/reactive distinction, with the replication of the classic proportion congruent effect (i.e., less interference and facilitation effects in the MI context). fMRI data only partially supported our predictions. Whereas reactive control for incongruent trials in the MC context engaged the expected fronto-parietal network including dorsolateral prefrontal cortex (DLPFC) and anterior cingulate cortex, proactive control in the MI context was not associated with any sustained lateral prefrontal cortex activations, contrary to our hypothesis. Surprisingly, incongruent trials in the MI context elicited transient activation in common with incongruent trials in the MC context, especially in DLPFC, superior parietal lobe, and insula. This lack of sustained activity in MI is discussed in reference to the possible involvement of item-specific rather than list-wide mechanisms of control in the implementation of a high task-relevant focus. [less ▲]

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See detailAttention Supports Verbal Short-Term Memory via Competition between Dorsal and Ventral Attention Networks.
Majerus, Steve ULg; Attout, Lucie ULg; D'Argembeau, Arnaud ULg et al

in Cerebral Cortex (2012), 22

Interactions between the neural correlates of short-term memory (STM) and attention have been actively studied in the visual STM domain but much less in the verbal STM domain. Here we show that the same ... [more ▼]

Interactions between the neural correlates of short-term memory (STM) and attention have been actively studied in the visual STM domain but much less in the verbal STM domain. Here we show that the same attention mechanisms that have been shown to shape the neural networks of visual STM also shape those of verbal STM. Based on previous research in visual STM, we contrasted the involvement of a dorsal attention network centered on the intraparietal sulcus supporting task-related attention and a ventral attention network centered on the temporoparietal junction supporting stimulus-related attention. We observed that, with increasing STM load, the dorsal attention network was activated while the ventral attention network was deactivated, especially during early maintenance. Importantly, activation in the ventral attention network increased in response to task-irrelevant stimuli briefly presented during the maintenance phase of the STM trials but only during low-load STM conditions, which were associated with the lowest levels of activity in the dorsal attention network during encoding and early maintenance. By demonstrating a trade-off between task-related and stimulus-related attention networks during verbal STM, this study highlights the dynamics of attentional processes involved in verbal STM. [less ▲]

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See detailMultivariate pattern analysis: brain decoding
Schrouff, Jessica ULg; Phillips, Christophe ULg

in Schnakers, Caroline; Laureys, Steven (Eds.) Coma and altered states of consciousness (2012)

Two of the most fundamental questions in the field of neurosciences are how information is represented in different brain structures, and how this information evolves over time. Various tools, such as ... [more ▼]

Two of the most fundamental questions in the field of neurosciences are how information is represented in different brain structures, and how this information evolves over time. Various tools, such as Magnetic Resonance (MRI) and Positron Emission Tomography (PET) have been developed over the last few decades to record brain activity and investigate these questions. In particular, functional MRI (fMRI) tracks changes of the Blood Oxygenation Level-Dependent (BOLD) signal, which is a good indicator of brain activity, with a spatial resolution of a few cubic millimeters and a typical temporal resolution in the order of 1 or 2 seconds. Until recently, the methods used to analyze such data focused on characterizing the individual relationship between a cognitive or perceptual state and each image voxel, i.e. following a massively univariate approach. A well-known univariate technique is Statistical Parametric Mapping (SPM) . SPM relies on the General Linear Model to detect which voxels show a statistically significant response to the (combination of) experimental conditions of interest. However, there are limitations on what can be learned about the representation of information by examining voxels in a univariate fashion. For instance, spatially distributed sets of voxels considered as non-significant by a SPM analysis of one experimental condition might still carry information about the presence or absence of that condition. Furthermore, classic voxel-based analytic techniques are agnostic of any a priori information, for example disease-specific information. They are also mainly designed to perform group-wise comparisons and would therefore be unsuitable to evaluate the state of the disease of each individual. On the other hand, Multi-Voxel Pattern Analyses (MVPA) allow an increased sensitivity to detect the presence of a particular mental representation. These multivariate methods, also known as brain decoding or mind reading, attempt to link a particular cognitive, behavioral or perceptual state to specific patterns of voxels’ activity. Application of these methods made it possible to decode the category of a seen object or the orientation of a stripped pattern seen by the subject from the brain activation of the imaged subject. Advances in pattern-classification algorithms also allowed the decoding of less-controlled conditions such as memory retrieval tasks. Advanced mathematical tools are still under development to allow the classification of more complicated experimental data sets, such as examining the content of mind wandering or detecting the state of consciousness of a patient showing no response to a command. [less ▲]

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See detailValuing One's Self: Medial Prefrontal Involvement in Epistemic and Emotive Investments in Self-views.
D'Argembeau, Arnaud ULg; Jedidi, Haroun ULg; Balteau, Evelyne ULg et al

in Cerebral Cortex (2012), 22

Recent neuroimaging research has revealed that the medial prefrontal cortex (MPFC) is consistently engaged when people form mental representations of themselves. However, the precise function of this ... [more ▼]

Recent neuroimaging research has revealed that the medial prefrontal cortex (MPFC) is consistently engaged when people form mental representations of themselves. However, the precise function of this region in self-representation is not yet fully understood. Here, we investigate whether the MPFC contributes to epistemic and emotive investments in self-views, which are essential components of the self-concept that stabilize self-views and shape how one feels about oneself. Using functional magnetic resonance imaging, we show that the level of activity in the MPFC when people think about their personal traits (by judging trait adjectives for self-descriptiveness) depends on their investments in the particular self-view under consideration, as assessed by postscan rating scales. Furthermore, different forms of investments are associated with partly distinct medial prefrontal areas: a region of the dorsal MPFC is uniquely related to the degree of certainty with which a particular self-view is held (one's epistemic investment), whereas a region of the ventral MPFC responds specifically to the importance attached to this self-view (one's emotive investment). These findings provide new insight into the role of the MPFC in self-representation and suggest that the ventral MPFC confers degrees of value upon the particular conception of the self that people construct at a given moment. [less ▲]

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