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See detail"Relevance vector machine" consciousness classifier applied to cerebral metabolism of vegetative and locked-in patients.
Phillips, Christophe ULg; Bruno, Marie-Aurélie ULg; Maquet, Pierre ULg et al

in NeuroImage (2011), 56(2), 797808

The vegetative state is a devastating condition where patients awaken from their coma (i.e., open their eyes) but fail to show any behavioural sign of conscious awareness. Locked-in syndrome patients also ... [more ▼]

The vegetative state is a devastating condition where patients awaken from their coma (i.e., open their eyes) but fail to show any behavioural sign of conscious awareness. Locked-in syndrome patients also awaken from their coma and are unable to show any motor response to command (except for small eye movements or blinks) but recover full conscious awareness of self and environment. Bedside evaluation of residual cognitive function in coma survivors often is difficult because motor responses may be very limited or inconsistent. We here aimed to disentangle vegetative from "locked-in" patients by an automatic procedure based on machine learning using fluorodeoxyglucose PET data obtained in 37 healthy controls and in 13 patients in a vegetative state. Next, the trained machine was tested on brain scans obtained in 8 patients with locked-in syndrome. We used a sparse probabilistic Bayesian learning framework called "relevance vector machine" (RVM) to classify the scans. The trained RVM classifier, applied on an input scan, returns a probability value (p-value) of being in one class or the other, here being "conscious" or not. Training on the control and vegetative state groups was assessed with a leave-one-out cross-validation procedure, leading to 100% classification accuracy. When applied on the locked-in patients, all scans were classified as "conscious" with a mean p-value of .95 (min .85). In conclusion, even with this relatively limited data set, we could train a classifier distinguishing between normal consciousness (i.e., wakeful conscious awareness) and the vegetative state (i.e., wakeful unawareness). Cross-validation also indicated that the clinical classification and the one predicted by the automatic RVM classifier were in accordance. Moreover, when applied on a third group of "locked-in" consciously aware patients, they all had a strong probability of being similar to the normal controls, as expected. Therefore, RVM classification of cerebral metabolic images obtained in coma survivors could become a useful tool for the automated PET-based diagnosis of altered states of consciousness. [less ▲]

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See detailDepression alters "top-down" visual attention: a dynamic causal modeling comparison between depressed and healthy subjects.
Desseilles, Martin ULg; Schwartz, Sophie; Dang Vu, Thien Thanh ULg et al

in NeuroImage (2011), 54(2), 1662-8

Using functional magnetic resonance imaging (fMRI), we recently demonstrated that nonmedicated patients with a first episode of unipolar major depression (MDD) compared to matched controls exhibited an ... [more ▼]

Using functional magnetic resonance imaging (fMRI), we recently demonstrated that nonmedicated patients with a first episode of unipolar major depression (MDD) compared to matched controls exhibited an abnormal neural filtering of irrelevant visual information (Desseilles et al., 2009). During scanning, subjects performed a visual attention task imposing two different levels of attentional load at fixation (low or high), while task-irrelevant colored stimuli were presented in the periphery. In the present study, we focused on the visuo-attentional system and used "Dynamic Causal Modeling" (DCM) on the same dataset to assess how attention influences a network of three dynamically-interconnected brain regions (visual areas V1 and V4, and intraparietal sulcus (P), differentially in MDD patients and healthy controls. Bayesian model selection (BMS) and model space partitioning (MSP) were used to determine the best model in each population. The best model for the controls revealed that the increase of parietal activity by high attention load was selectively associated with a negative modulation of P on V4, consistent with high attention reducing the processing of irrelevant colored peripheral stimuli. The best model accounting for the data from the MDD patients showed that both low and high attention levels exerted modulatory effects on P. The present results document abnormal effective connectivity across visuo-attentional networks in MDD, which likely contributes to deficient attentional filtering of information. [less ▲]

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See detailCOMT Val158Met polymorphism, verbalizing of emotion and activation of affective brain systems
Swart, M.; Bruggeman, R.; Laroi, Frank ULg et al

in NeuroImage (2011), 55

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See detailBrain functional integration decreases during propofol-induced loss of consciousness.
Schrouff, Jessica ULg; Perlbarg, Vincent; Boly, Mélanie ULg et al

in NeuroImage (2011), 57(1), 198-205

Consciousness has been related to the amount of integrated information that the brain is able to generate. In this paper, we tested the hypothesis that the loss of consciousness caused by propofol ... [more ▼]

Consciousness has been related to the amount of integrated information that the brain is able to generate. In this paper, we tested the hypothesis that the loss of consciousness caused by propofol anesthesia is associated with a significant reduction in the capacity of the brain to integrate information. To assess the functional structure of the whole brain, functional integration and partial correlations were computed from fMRI data acquired from 18 healthy volunteers during resting wakefulness and propofol-induced deep sedation. Total integration was significantly reduced from wakefulness to deep sedation in the whole brain as well as within and between its constituent networks (or systems). Integration was systematically reduced within each system (i.e., brain or networks), as well as between networks. However, the ventral attentional network maintained interactions with most other networks during deep sedation. Partial correlations further suggested that functional connectivity was particularly affected between parietal areas and frontal or temporal regions during deep sedation. Our findings suggest that the breakdown in brain integration is the neural correlate of the loss of consciousness induced by propofol. They stress the important role played by parietal and frontal areas in the generation of consciousness. [less ▲]

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See detailThe impact of blue light on non-visual brain functions changes with age
Daneault*; Vandewalle*, Gilles ULg; Hébert, M et al

in NeuroImage (2011), 56(Suppl. 1),

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See detailOptimal design of multi-subject blocked fMRI experiments.
Maus, Bärbel ULg; van Breukelen, Gerard J P; Goebel, Rainer et al

in NeuroImage (2011), 56(3), 1338-1352

The design of a multi-subject fMRI experiment needs specification of the number of subjects and scanning time per subject. For example, for a blocked design with conditions A or B, fixed block length and ... [more ▼]

The design of a multi-subject fMRI experiment needs specification of the number of subjects and scanning time per subject. For example, for a blocked design with conditions A or B, fixed block length and block order ABN, where N denotes a null block, the optimal number of cycles of ABN and the optimal number of subjects have to be determined. This paper presents a method to determine the optimal number of subjects and optimal number of cycles for a blocked design based on the A-optimality criterion and a linear cost function by which the number of cycles and the number of subjects are restricted. Estimation of individual stimulus effects and estimation of contrasts between stimulus effects are both considered. The mixed-effects model is applied and analytical results for the A-optimal number of subjects and A-optimal number of cycles are obtained under the assumption of uncorrelated errors. For correlated errors with a first-order autoregressive (AR1) error structure, numerical results are presented. Our results show how the optimal number of cycles and subjects depend on the within- to between-subject variance ratio. Our method is a new approach to determine the optimal scanning time and optimal number of subjects for a multi-subject fMRI experiment. In contrast to previous results based on power analyses, the optimal number of cycles and subjects can be described analytically and costs are considered. [less ▲]

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See detailNeural networks involved in self-judgement in young and elderly adults
Feyers, Dorothée ULg; Collette, Fabienne ULg; D'Argembeau, Arnaud ULg et al

in NeuroImage (2010)

Recent studies have shown that both young and elderly subjects activate the ventromedial prefrontal cortex (VMPFC) when they make self-referential judgements. However, the VMPFC might interact with ... [more ▼]

Recent studies have shown that both young and elderly subjects activate the ventromedial prefrontal cortex (VMPFC) when they make self-referential judgements. However, the VMPFC might interact with different brain regions during self-referencing in the two groups. In this study, based on data from Ruby et al (2009), we have explored this issue using psychophysiological interaction analyses. Young and elderly participants had to judge adjectives describing personality traits in reference to the self versus a close friend or relative (the other), taking either a first-person or a third-person perspective. The physiological factor was the VMPFC activity observed in all participants during self judgement, and the psychological factor was the self versus other referential process. The main effect of first-person perspective in both groups revealed that the VMPFC was coactivated with the left parahippocampal gyrus and the precuneus for self versus other judgments. The main effect of age showed a stronger correlation between activity in the VMPFC and the lingual gyrus in young compared to elderly subjects. Finally, in the interaction, the VMPFC was specifically co-activated with the orbitofrontal gyrus and the precentral gyrus when elderly subjects took a first-person perspective for self judgements. No significant result was observed for the interaction in young subjects. These findings show that, although the VMPFC is engaged by both young and older adults when making self-referential judgements, this brain structure interacts differently with other brain regions as a function of age and perspective. These differences might reflect a tendency by older people to engage in more emotional/social processing than younger adults when making self-referential judgements with a first-person perspective [less ▲]

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See detailImproved shimming for fMRI specifically optimizing the local BOLD sensitivity
Balteau, Evelyne ULg; Hutton, Chloe; Weiskopf, Nikolaus

in NeuroImage (2010), 49

In functional MRI, magnetic field inhomogeneities due to air-tissue susceptibility differences may lead to severe signal dropouts and geometric distortions in echo-planar images. Therefore, the ... [more ▼]

In functional MRI, magnetic field inhomogeneities due to air-tissue susceptibility differences may lead to severe signal dropouts and geometric distortions in echo-planar images. Therefore, the inhomogeneities in the field are routinely minimized by shimming prior to imaging. However in fMRI, the Blood Oxygen Level Dependent (BOLD) effect is the measure of interest, so the BOLD sensitivity (BS) should be optimized rather than the magnetic field homogeneity. The analytical expression for an estimate of the BOLD sensitivity has been recently developed, allowing for the computation of BOLD sensitivity maps from echo-planar images and field maps. This report describes a novel shimming procedure that optimizes the local BOLD sensitivity over a region of interest. The method is applied in vivo and compared to a standard global shimming procedure. A breath-holding experiment was carried out and demonstrated that the BS-based shimming significantly improved the detection of activation in a target region of interest, the medial orbitofrontal cortex. [less ▲]

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See detailSleep spindles and neural activity changes in the cortico-striatal system underlie motor sequence consolidation
Barakat, M; Carrier, J; Debas, K et al

in NeuroImage (2010), 51(Suppl. 1),

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See detailRobustness of optimal design of fMRI experiments with application of a genetic algorithm.
Maus, Bärbel ULg; van Breukelen, Gerard J P; Goebel, Rainer et al

in NeuroImage (2010), 49(3), 2433-2443

In this paper we apply the genetic algorithm developed by Kao et al. (2009) to find designs which are robust against misspecification of the error autocorrelation. Two common optimality criteria, the A ... [more ▼]

In this paper we apply the genetic algorithm developed by Kao et al. (2009) to find designs which are robust against misspecification of the error autocorrelation. Two common optimality criteria, the A-optimality criterion and the D-optimality criterion, based upon a general linear model are employed to obtain locally optimal designs for a given value of the autocorrelation. The maximin criterion is then used to obtain designs which are robust against misspecification of the autocorrelation. Furthermore, robustness depending on the choice of optimality criterion is evaluated. We show analytically and empirically that the A- and D-optimality criterion will result in different optimal designs, e.g. with different stimulus frequencies. Optimal stimulus frequency for the A-optimality criterion has been derived by Liu et al. (2004) whereas we derive here the optimal stimulus frequency for the D-optimality criterion. Conclusions about the robustness of an optimal design against misspecification of model parameters and choice of optimality criterion are drawn based upon our results. [less ▲]

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See detailEvidence for a role of sleep in forgetting of irrelevant information
Collette, Fabienne ULg; Rauchs, Géraldine; Landeau, Brigitte et al

in NeuroImage (2009, June), 47(Suppl 1), 328-

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See detailPain and non-pain processing during hypnosis: a thulium-YAG event-related fMRI study.
Vanhaudenhuyse, Audrey ULg; Boly, Mélanie ULg; Balteau, Evelyne ULg et al

in NeuroImage (2009), 47(3), 1047-54

The neural mechanisms underlying the antinociceptive effects of hypnosis still remain unclear. Using a parametric single-trial thulium-YAG laser fMRI paradigm, we assessed changes in brain activation and ... [more ▼]

The neural mechanisms underlying the antinociceptive effects of hypnosis still remain unclear. Using a parametric single-trial thulium-YAG laser fMRI paradigm, we assessed changes in brain activation and connectivity related to the hypnotic state as compared to normal wakefulness in 13 healthy volunteers. Behaviorally, a difference in subjective ratings was found between normal wakefulness and hypnotic state for both non-painful and painful intensity-matched stimuli applied to the left hand. In normal wakefulness, non-painful range stimuli activated brainstem, contralateral primary somatosensory (S1) and bilateral insular cortices. Painful stimuli activated additional areas encompassing thalamus, bilateral striatum, anterior cingulate (ACC), premotor and dorsolateral prefrontal cortices. In hypnosis, intensity-matched stimuli in both the non-painful and painful range failed to elicit any cerebral activation. The interaction analysis identified that contralateral thalamus, bilateral striatum and ACC activated more in normal wakefulness compared to hypnosis during painful versus non-painful stimulation. Finally, we demonstrated hypnosis-related increases in functional connectivity between S1 and distant anterior insular and prefrontal cortices, possibly reflecting top-down modulation. [less ▲]

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See detailAbnormal neural filtering of irrelevant visual information in depression
Desseilles, Martin ULg; Balteau, Evelyne ULg; Sterpenich, Virginie et al

in NeuroImage (2009), 45(Suppl. 1),

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See detailComputational biology — Modeling of primary blast effects on the central nervous system
Moore, David; Jérusalem, Antoine; Nyen, Michelle et al

in NeuroImage (2009), 47(Sup. 2), 10-20

Objectives Recent military conflicts in Iraq and Afghanistan have highlighted the wartime effect of traumatic brain injury. The reason for the prominence of TBI in these particular conflicts as opposed to ... [more ▼]

Objectives Recent military conflicts in Iraq and Afghanistan have highlighted the wartime effect of traumatic brain injury. The reason for the prominence of TBI in these particular conflicts as opposed to others is unclear but may result from the increased survivability of blast due to improvements in body armor. In the military context blunt, ballistic and blast effects may all contribute to CNS injury, however blast in particular, has been suggested as a primary cause of military TBI. While blast effects on some biological tissues, such as the lung, are documented in term of injury thresholds, this is not the case for the CNS. We hypothesized that using bio-fidelic models, allowing for fluid-solid interaction and basic material properties available in the literature, that a blast wave would interact with CNS tissue and cause a possible concussive effect. Methods The blast shockwave on CNS tissue was modeled using a coupled computational fluid-solid dynamic simulation. The model included a complex finite element mesh of the head and intra-cranial contents. The effects of threshold and 50% lethal blast lung injury were compared with concussive impact injury using the full head model allowing know upper and lower bounds of tissue injury to be applied using pulmonary injury as the reference tissue. Results The effects of a 50% lethal dose blast lung injury (LD50) were comparable with concussive impact injury using the DVBIC – MIT full head model. Interpretation CNS blast concussive effects were found to be similar between impact mild TBI and the blast field associated with LD50 lung blast injury sustained without personal protective equipment. With the ubiquitous use of personal protective equipment this suggests that blast concussive effects may more readily occur in personnel due to enhanced survivability in the current conflicts. [less ▲]

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See detailRejection of pulse related artefact (PRA) from continuous electroencephalographic (EEG) time series recorded during functional magnetic resonance imaging (fMRI) using constraint independent component analysis (cICA).
Leclercq, Yves ULg; Balteau, Evelyne ULg; Dang Vu, Thien Thanh ULg et al

in NeuroImage (2009), 44(3), 679-91

Rejection of the pulse related artefact (PRA) from electroencephalographic (EEG) time series recorded simultaneously with fMRI data is difficult, particularly during NREM sleep because of the similarities ... [more ▼]

Rejection of the pulse related artefact (PRA) from electroencephalographic (EEG) time series recorded simultaneously with fMRI data is difficult, particularly during NREM sleep because of the similarities between sleep slow waves and PRA, in both temporal and frequency domains and the need to work with non-averaged data. Here we introduce an algorithm based on constrained independent component analysis (cICA) for PRA removal. This method has several advantages: (1) automatic detection of the components corresponding to the PRA; (2) stability of the solution and (3) computational treatability. Using multichannel EEG recordings obtained in a 3 T MR scanner, with and without concomitant fMRI acquisition, we provide evidence for the sensitivity and specificity of the method in rejecting PRA in various sleep and waking conditions. [less ▲]

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See detailOptimization of blocked designs in fMRI studies
Maus, Bärbel ULg; Van Breukelen, G.J.P; Goebel, R. et al

in NeuroImage (2009), 47(Supplement 1), 125

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See detailNeural correlates mediating the consolidation of visuomotor adapted actions : A study on the role of night sleep versus the passage of daytime
Debas, Karen; Carrier, Julie; Orban, Pierre et al

in NeuroImage (2009), 45(Suppl. 1),

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See detailSelecting forward models for MEG source-reconstruction using model-evidence.
Henson, R. N.; Mattout, J.; Phillips, Christophe ULg et al

in NeuroImage (2009), 46(1), 168-76

We investigated four key aspects of forward models for distributed solutions to the MEG inverse problem: 1) the nature of the cortical mesh constraining sources (derived from an individual's MRI, or ... [more ▼]

We investigated four key aspects of forward models for distributed solutions to the MEG inverse problem: 1) the nature of the cortical mesh constraining sources (derived from an individual's MRI, or inverse-normalised from a template mesh); 2) the use of single-sphere, overlapping spheres, or Boundary Element Model (BEM) head-models; 3) the density of the cortical mesh (3000 vs. 7000 vertices); and 4) whether source orientations were constrained to be normal to that mesh. These were compared within the context of two types of spatial prior on the sources: a single prior corresponding to a standard L2-minimum-norm (MNM) inversion, or multiple sparse priors (MSP). The resulting generative models were compared using a free-energy approximation to the Bayesian model-evidence after fitting multiple epochs of responses to faces or scrambled faces. Statistical tests of the free-energy, across nine participants, showed clear superiority of MSP over MNM models; with the former reconstructing deeper sources. Furthermore, there was 1) no evidence that an individually-defined cortical mesh was superior to an inverse-normalised canonical mesh, but 2) clear evidence that a BEM was superior to spherical head-models, provided individually-defined inner skull and scalp meshes were used. Finally, for MSP models, there was evidence that the combination of 3) higher density cortical meshes and 4) dipoles constrained to be normal to the mesh was superior to lower-density or freely-oriented sources (in contrast to the MNM models, in which free-orientation was optimal). These results have practical implications for MEG source reconstruction, particularly in the context of group studies. [less ▲]

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See detailNeural Correlates of Envisioning Emotional Events in the near and Far Future
D'Argembeau, Arnaud ULg; Xue, Gui; Lu, Zhong-Lin et al

in NeuroImage (2008), 40(1), 398-407

Being able to envision emotional events that might happen in the future has a clear adaptive value. This study addressed the functional neuroanatomy of this process and investigated whether it is ... [more ▼]

Being able to envision emotional events that might happen in the future has a clear adaptive value. This study addressed the functional neuroanatomy of this process and investigated whether it is modulated by temporal distance. Participants imagined positive and negative events pertaining to the near future or far future while their brain activity was measured with fMRI. The results demonstrate that the anterior part of the ventromedial prefrontal cortex (vmPFC) was more active in envisioning emotional events in the far future than in the near future, whereas the caudate nucleus was engaged in envisioning emotional (especially positive) situations in the near future. We argue that the anterior part of the vmPFC might assign emotional values to mental representations of future events that pertain to long-term goals. On the other hand, the caudate might support more concrete simulations of action plans to achieve rewarding situations in the near future. [less ▲]

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