References of "Phillips, Christophe"
     in
Bookmark and Share    
Full Text
Peer Reviewed
See detailEmbedding Anatomical or Functional Knowledge in Whole-Brain Multiple Kernel Learning Models
Schrouff, Jessica ULiege; Monteiro, Joao M.; Portugal, Liana et al

in Neuroinformatics (2018)

Pattern recognition models have been increasingly applied to neuroimaging data over the last two decades. These applications have ranged from cognitive neuroscience to clinical problems. A common ... [more ▼]

Pattern recognition models have been increasingly applied to neuroimaging data over the last two decades. These applications have ranged from cognitive neuroscience to clinical problems. A common limitation of these approaches is that they do not incorporate previous knowledge about the brain structure and function into the models. Previous knowledge can be embedded into pattern recognition models by imposing a grouping structure based on anatomically or functionally defined brain regions. In this work, we present a novel approach that uses group sparsity to model the whole brain multivariate pattern as a combination of regional patterns. More specifically, we use a sparse version of Multiple Kernel Learning (MKL) to simultaneously learn the contribution of each brain region, previously defined by an atlas, to the decision function. Our application of MKL provides two beneficial features: (1) it can lead to improved overall generalisation performance when the grouping structure imposed by the atlas is consistent with the data; (2) it can identify a subset of relevant brain regions for the predictive model. In order to investigate the effect of the grouping in the proposed MKL approach we compared the results of three different atlases using three different datasets. The method has been implemented in the new version of the open-source Pattern Recognition for Neuroimaging Toolbox (PRoNTo). [less ▲]

Detailed reference viewed: 26 (0 ULiège)
Full Text
Peer Reviewed
See detailHuman brain patterns underlying vigilant attention: impact of sleep debt, circadian phase and attentional engagement
Maire, Micheline; Reichert, Carolin Franziska; Gabel, Virginie et al

in Scientific Reports (2018), 8(1), 970

Detailed reference viewed: 20 (1 ULiège)
Full Text
Peer Reviewed
See detailThe dorsal attention network reflects both encoding load and top-down control during working memory
Majerus, Steve ULiege; Péters, Frédéric; Bouffier, Marion ULiege et al

in Journal of Cognitive Neuroscience (2018), 30

Detailed reference viewed: 17 (1 ULiège)
Full Text
Peer Reviewed
See detailCognitive brain responses during circadian wake-promotion: evidence for sleep- pressure-dependent hypothalamic activations
Reichert, Carolin Franziska; Maire, Micheline; Gabel, Virginie et al

in Scientific Reports (2017), 7(1),

Detailed reference viewed: 25 (0 ULiège)
Peer Reviewed
See detailMean and variance of Dynamic Functional Connectivity in Parkinson’s Disease
Baquero Duarte, Katherine Andrea ULiege; Guldenmund, Pieter; Rouillard, Maud ULiege et al

Poster (2017, June 29)

Detailed reference viewed: 38 (8 ULiège)
Full Text
Peer Reviewed
See detailTree Ensemble Methods and Parcelling to Identify Brain Areas Related to Alzheimer’s Disease
Wehenkel, Marie ULiege; Bastin, Christine ULiege; Phillips, Christophe ULiege et al

in 2017 International Workshop on Pattern Recognition in Neuroimaging (PRNI), proceedings (2017, June)

Detailed reference viewed: 47 (14 ULiège)
Full Text
See detailUnifying lesion masking and tissue probability maps for improved segmentation and normalization
Phillips, Christophe ULiege; LOMMERS, Emilie ULiege; Pernet, Cyril

Poster (2017, June)

Nowadays “Unified Segmentation” (US) is the usual approach to warp brain images into a standard reference space, i.e. perform spatial normalization, and derive posterior probability maps of the brain ... [more ▼]

Nowadays “Unified Segmentation” (US) is the usual approach to warp brain images into a standard reference space, i.e. perform spatial normalization, and derive posterior probability maps of the brain tissues, typically grey and white matter (GM, WM) and CSF [1]. US only relies on a spatial deformation model and prior ‘tissue probability maps’ (TPM) of the head tissues. When dealing with data from patients with focal brain lesions, e.g. tumors or multiple sclerosis (MS) lesion, the standard US approach does not work as it cannot account for the abnormal tissue distribution. A common work around is “cost function masking” (CFM) [2,3] where the abnormal tissues are masked out using a binary mask of the lesion [6,8]. Here we extend the US approach to provide a more principled solution for brain images with focal lesions. The aim is twofold: a more accurate warping into the reference space of the healthy tissues and a more precise delineation of the lesion(s). We modify the standard TPM adding a subject-specific ‘lesion probability map’ [5,7], by 1/ estimating a preliminary spatial warping from subject to the reference space with the CFM approach, then 2/ carefully updating the TPM with a new tissue class, the lesion, defined from the smoothed warped lesion mask and deciding which healthy tissue class can be affected by the lesion. The TPM-with-lesion is then fed into the US with the patients images, see Fig. 1. This “US-with-Lesion” (USwL) approach thus accounts for the presence of focal abnormal tissues in a probabilistic way, providing posterior probability maps of the tissues, including the lesion, and spatial deformation, accounting for the lesion. We tested and evaluated our USwL approach on 2 publicly available datasets: the BRATS [4] and the ‘MS lesion segmentation challenge’ (MSchal)[8]. The BRATS data include T1 and FLAIR images of 30 patients with gliomas and their annotated tumor mask (further considered as the ground truth). A rough lesion mask was manually built from the FLAIR image using MRIcron. USwL was used to segment T1 and FLAIR images along with this approximate mask. The GM, WM and CSF tissue classes could be affected by the lesion. The posterior probability map for the lesion tissue was cleaned up (preserving the bigger clusters) and thresholded. Overall the USwL improved (p<.05) the similarity of the lesion mask to the annotated tumor, in term of voxel matching (sensitivity, specificity & Jaccard coefficient). Synthetic lesioned brains were also generated to assess the quality of the deformation for the healthy tissues, indicating the superiority (p<.05) of the USwL compared to the standard approach. The MSchal data include T1, T2 and FLAIR images of 20 patients with MS as well as the manually annotated lesion (considered as only approximate here). USwL is applied on the 3 structural images with the lesion mask provided and with the constraint that only the WM is potentially affected by the lesion (as is plausible with MS). The thresholded posterior probability map for the lesion tissue was compared to the provided lesion mask. The USwL lead to more biologically plausible lesion volumes (p<.05), in term of volume compactness [10], see Fig. 2. The similarity of the warped posterior GM maps across the 20 subjects (expressed as the root-mean square difference to the mean of the 20 subjects) was also examined. The improvement, from using CFM-US to USwL, in the between-subject GM-matching is proportional (p<.05) to the actual WM lesion volume. We provide a new tool for US that allows to include focal lesions. Over the 2 dataset considered, USwL demonstrated improved performances compared to the standard US: 1/ a more accurate warping into the reference space of the healthy tissues and 2/ simply using an approximate mask, a more precise delineation of the lesion(s). The whole code will be made available as an SPM add-on toolbox (with a batch interface) on https://github.com/CyclotronResearchCentre/USwithLesion. [less ▲]

Detailed reference viewed: 19 (3 ULiège)
Full Text
Peer Reviewed
See detailMultivariate analysis of 18F-DMFP PET data to assist the diagnosis of parkinsonism
Segovia, Fermin; Gorriz, Juan M.; Ramirez, Javier et al

in Frontiers in Neuroinformatics (2017)

Detailed reference viewed: 51 (10 ULiège)
Full Text
Peer Reviewed
See detailHow cognition affects perception: Brain activity modelling to unravel top-down dynamics
Desseilles, Martin ULiege; Phillips, Christophe ULiege

in Behavioral and Brain Sciences (2017), 39

In this commentary on Firestone & Scholl's (F&S's) article, we argue that researchers should use brain-activity modelling to investigate top-down mechanisms. Using functional brain imaging and a specific ... [more ▼]

In this commentary on Firestone & Scholl's (F&S's) article, we argue that researchers should use brain-activity modelling to investigate top-down mechanisms. Using functional brain imaging and a specific cognitive paradigm, modelling the BOLD signal provided new insight into the dynamic causalities involved in the influence of cognitions on perceptions. [less ▲]

Detailed reference viewed: 37 (6 ULiège)
Full Text
Peer Reviewed
See detailThe neural bases of proactive and reactive control processes in normal aging
Manard, Marine ULiege; François, Sarah ULiege; Phillips, Christophe ULiege et al

in Behavioural Brain Research (2017), 320

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 ▲]

Detailed reference viewed: 36 (14 ULiège)
Full Text
Peer Reviewed
See detailCerebral Activity Associated with Transient Sleep-Facilitated Reduction in Motor Memory Vulnerability to Interference
Albouy, Geneviève; King, Bradley; Schmidt, Christina ULiege et al

in Scientific Reports (2016), 6

Detailed reference viewed: 18 (4 ULiège)
Peer Reviewed
See detailAge-related differences in the dynamics of cortical excitability and cognitive inhibition during prolongedwakefulness
Gaggioni, Giulia ULiege; Chelllappa, S.; Ly, J. et al

Conference (2016, September)

Detailed reference viewed: 42 (11 ULiège)
Full Text
Peer Reviewed
See detailCircadian dynamics in measures of cortical excitation and inhibition balance
Chellappa, Sarah; Gaggioni, Giulia ULiege; LY, Julien ULiege et al

in Scientific Reports (2016), 6:33661

Detailed reference viewed: 40 (13 ULiège)
Full Text
Peer Reviewed
See detailLocal modulation of human brain responses by circadian rhythmicity and sleep debt
Muto, Vincenzo ULiege; Jaspar, Mathieu ULiege; Meyer, Christelle et al

in Science (2016), 351(6300),

Detailed reference viewed: 105 (37 ULiège)
Peer Reviewed
See detailSleep deprivation affects brain global cortical responsivenes
Gaggioni, Giulia ULiege; Chellappa, S; Ly, J et al

Conference (2016, June 15)

Detailed reference viewed: 48 (8 ULiège)
Peer Reviewed
See detailSeasonal variation in human COGNITIVE brain responses
Meyer, Christelle; Muto, Vincenzo ULiege; Jaspar, Mathieu ULiege et al

Poster (2016, June)

Detailed reference viewed: 27 (4 ULiège)