References of "Maquet, Pierre"
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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 detailHierarchical clustering of brain activity during human nonrapid eye movement sleep.
Boly, Mélanie ULg; Perlbarg, V; Marrelec, G et al

in Proceedings of the National Academy of Sciences of the United States of America (2012)

Consciousness is reduced during nonrapid eye movement (NREM) sleep due to changes in brain function that are still poorly understood. Here, we tested the hypothesis that impaired consciousness during NREM ... [more ▼]

Consciousness is reduced during nonrapid eye movement (NREM) sleep due to changes in brain function that are still poorly understood. Here, we tested the hypothesis that impaired consciousness during NREM sleep is associated with an increased modularity of brain activity. Cerebral connectivity was quantified in resting-state functional magnetic resonance imaging times series acquired in 13 healthy volunteers during wakefulness and NREM sleep. The analysis revealed a modification of the hierarchical organization of large-scale networks into smaller independent modules during NREM sleep, independently from EEG markers of the slow oscillation. Such modifications in brain connectivity, possibly driven by sleep ultraslow oscillations, could hinder the brain's ability to integrate information and account for decreased consciousness during NREM sleep. [less ▲]

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See detailDecoding semi-constrained brain activity from fMRI using SVM and GP
Schrouff, Jessica ULg; Kussé, Caroline ULg; Wehenkel, Louis ULg et al

Scientific conference (2011, November 22)

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 detailLe Sommeil dans l'Etat Végétatif et de Conscience Minimale
Cologan, Victor ULg; Drouot, Xavier; Parapatics, Silvia et al

Poster (2011, November)

Présentation des résultats de l'étude du sommeil chez les patients cérébrolésés en état de conscience altéré.

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See detailHypnotic modulation of resting state fMRI default mode and extrinsic network connectivity
Demertzi, Athina ULg; Soddu, Andrea ULg; FAYMONVILLE, Marie-Elisabeth ULg et al

in Progress in Brain Research (2011), 193

Resting state fMRI (functional magnetic resonance imaging) acquisitions are characterized by low-frequency spontaneous activity in a default mode network (encompassing medial brain areas and linked to ... [more ▼]

Resting state fMRI (functional magnetic resonance imaging) acquisitions are characterized by low-frequency spontaneous activity in a default mode network (encompassing medial brain areas and linked to self-related processes) and an anticorrelated “extrinsic” system (encompassing lateral frontoparietal areas and modulated via external sensory stimulation). In order to better determine the functional contribution of these networks to conscious awareness, we here sought to transiently modulate their relationship by means of hypnosis. We used independent component analysis (ICA) on resting state fMRI acquisitions during normal wakefulness, under hypnotic state, and during a control condition of autobiographical mental imagery. As compared to mental imagery, hypnosis-induced modulation of resting state fMRI networks resulted in a reduced “extrinsic” lateral frontoparietal cortical connectivity, possibly reflecting a decreased sensory awareness. The default mode network showed an increased connectivity in bilateral angular and middle frontal gyri, whereas its posterior midline and parahippocampal structures decreased their connectivity during hypnosis, supposedly related to an altered “self” awareness and posthypnotic amnesia. In our view, fMRI resting state studies of physiological (e.g., sleep or hypnosis), pharmacological (e.g., sedation or anesthesia), and pathological modulation (e.g., coma or related states) of “intrinsic” default mode and anticorrelated “extrinsic” sensory networks, and their interaction with other cerebral networks, will further improve our understanding of the neural correlates of subjective awareness. [less ▲]

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See detailFASST- a FMRI Artefact rejection and Sleep Scoring Toolbox
Schrouff, Jessica ULg; Leclercq, Yves ULg; Noirhomme, Quentin ULg et al

Poster (2011, June 28)

We started writing the “fMRI artefact rejection and sleep scoring toolbox”, or “FASST”, to process our sleep EEG-fMRI data, that is, the simultaneous recording of electroencephalographic and functional ... [more ▼]

We started writing the “fMRI artefact rejection and sleep scoring toolbox”, or “FASST”, to process our sleep EEG-fMRI data, that is, the simultaneous recording of electroencephalographic and functional magnetic resonance imaging data acquired while a subject is asleep. FAST tackles three crucial issues typical of this kind of data: (1) data manipulation (viewing, comparing, chunking, etc.) of long continuous M/EEG recordings, (2) rejection of the fMRI-induced artefact in the EEG signal, and (3)manual sleep-scoring of the M/EEG recording. Currently, the toolbox can efficiently deal with these issues via a GUI, SPM8 batching system or handwritten script. The tools developed are, of course, also useful for other EEG applications, for example, involving simultaneous EEG-fMRI acquisition, continuous EEG eye-balling, and manipulation. Even though the toolbox was originally devised for EEG data, it will also gracefully handle MEG data without any problem. “FAST” is developed in Matlab as an add-on toolbox for SPM8 and, therefore, internally uses its SPM8-meeg data format. “FAST” is available for free, under the GNU-GPL. [less ▲]

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See detailDecoding Directed Brain Activity in fMRI using Support Vector Machines and Gaussian Processes
Schrouff, Jessica ULg; Kussé, Caroline ULg; Wehenkel, Louis ULg et al

Poster (2011, June 26)

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 detailModulating effect of COMT genotype on the brain regions underlying inhibition
Jaspar, Mathieu ULg; Grandjean, Julien ULg; Salmon, Eric ULg et al

Poster (2011, June 26)

Introduction Catechol-O-methytransferase (COMT) is an important enzyme which degrades catecholamines, such dopamine, notably in the prefrontal cortex (Männistö & Kaakkola, 1999). Actually, a transition of ... [more ▼]

Introduction Catechol-O-methytransferase (COMT) is an important enzyme which degrades catecholamines, such dopamine, notably in the prefrontal cortex (Männistö & Kaakkola, 1999). Actually, a transition of guanine to adenine at codon 158 of the COMT gene results in a valine to methionine substitution (Lotta & al., 1995). This phenomenon leads to different COMT genotypes, each associated with a different COMT enzymatic activity (Weinshilboum, & al., 1999). A large number of studies reported an effect of COMT on executive functioning. However, most of them used multi-determined executive tasks (e.g., Barnett & al., 2007). We are interested here to determine the effect of COMT Val158Met genotype on the activity of frontal and parietal areas (Nee & al., 2007; Laird & al., 2005) underlying the specific executive process of inhibition. Methods Procedure In an event-related fMRI experiment, a modified form of the Stroop task was administered to 44 young adults (age range: 18-30) separated into three groups according to their COMT Val158Met genotype: 15 homozygous val/val (VV), 14 homozygous met/met (MM) and 15 heterozygotes val/met (VM) carriers. The Stroop task consisted in the presentation of color words printed in various ink colors (e.g the word blue written in red). Subjects were instructed to name of ink color as fast and accurately as possible by avoiding to read the word. In this version of the Stroop task, three different contexts were created (data not showed here): (1) a congruent context (MC) with a majority of facilitator items (IC), (2) a non-congruent context (MI) with mainly interfering items (II), (3) a neutral context (MN) with mainly neutral items (IN, series of %%% written in different colors). MRI acquisition, data analysis Functional MRI time series were acquired on a 3T head-only scanner operated with the standard transmit-receive quadrature head coil. Multislice T2*-weighted functional images were acquired with a gradient-echo echo-planar imaging sequence using axial slice orientation and covering the whole brain (32 slices, FoV = 220x220 mm², voxel size 3.4x3.4x3 mm³, 30% interslice gap, matrix size 64x64x32, TR = 2130 ms, TE = 40 ms, FA = 90°). Structural images were obtained using a high resolution T1-weighted sequence (3D MDEFT [Deichmann & al., (2004)] ; TR = 7.92 ms, TE = 2.4 ms, TI = 910 ms, FA = 15°, FoV = 256 x 224 x 176 mm³, 1 mm isotropic spatial resolution). Preprocessing and statistical analyses were performed with SPM8 (p<.001 uncorrected). Results Behavioral results indicated the presence of a general interference effect (II – IN items) for reaction time (F(1,41) = 292,44 ; p < 0,001) but no significant difference in interference between the three groups (F(2,41) = 0,27; p = 0,76). FMRI results revealed that interference effect [(MI_II-MI_IN) + (MC_II-MC_IN) + (MN_II-MN_IN)] observed in our three groups is mainly associated with cerebral activity in frontal and parietal areas. Moreover, group comparisons indicates that this effect is associated with increased medial frontal and precentral gyrus activity in VV and VM groups by comparison with MM group, but also in the superior temporal gyrus and in the thalamus in the VM by comparison to MM . Conversely, no supplementary brain area was observed for the comparison of the MM to the two other groups. Conclusions The fronto-parietal brain network associated with interference resolution observed here is consistent with prior reports (Nee & al., 2007; Laird & al., 2005). Moreover, results showed activity in different brain areas according to the COMT genotype. Indeed, a similar behavioral performance is associated to the recruitment of supplementary areas in the carriers of the val allele. This observation, 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 ▲]

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See detailExperience-dependent induction of hypnagogic images during daytime naps: a combined behavioral and EEG study.
Kussé, Caroline ULg; Shaffii-Le Bourdiec, Anahita; Schrouff, Jessica ULg et al

in Association for the Scientific Study of Consciousness 15, Kyoto, Japan, 9-12 June 2011 (2011, June 09)

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See detailAn easy-to-use pipeline for creating connectomes
Ziegler, Erik ULg; Foret, Ariane; Matarazzo, Luca et al

Poster (2011, June)

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See detailReciprocal interactions between wakefulness and sleep influence global and regional brain activity
Muto, Vincenzo ULg; Mascetti, Laura ULg; Matarazzo, Luca et al

in Current Topics in Medicinal Chemistry (2011), 11(19), 2403-13

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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 detailFunctional neuroimaging of the reciprocal influences between sleep and wakefulness.
Jedidi, Zayd ULg; Rikir, Estelle ULg; Muto, Vincenzo ULg et al

in Pflugers Archiv : European journal of physiology (2011), 463(1), 103-9

The activity patterns adopted by brain neuronal populations differ dramatically between wakefulness and sleep. However, these vigilance states are not independent and they reciprocally interact. Here, we ... [more ▼]

The activity patterns adopted by brain neuronal populations differ dramatically between wakefulness and sleep. However, these vigilance states are not independent and they reciprocally interact. Here, we provide evidence that in humans, regional brain activity during wakefulness is influenced by sleep regulation, namely by the interaction between sleep homeostasis and circadian signals. We also show that, by contrast, regional brain activity during sleep is influenced by the experience acquired during the preceding waking period. These data reveal the dynamic interactions by which the succession of vigilance states support normal brain function and human cognition. [less ▲]

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See detailA systems-level approach to human REM sleep
Matarazzo, Luca; Foret, Ariane; Mascetti, Laura ULg et al

in Rapid Eye Movement Sleep: Regulation and Function (2011)

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See detailNeural Correlates of Human NREM Sleep Oscillations
Foret, Ariane ULg; Shaffii, Anahita ULg; Muto, Vincenzo ULg et al

in Hutt, Axel (Ed.) Sleep and Anesthesia (2011)

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See detailAbnormal Hypothalamic Response to Light in Seasonal Affective Disorder
Vandewalle, Gilles ULg; Hébert, M.; Beaulieu, C. et al

in Biological Psychiatry (2011), 70(10), 954-961

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See detailSleep contributes to the strengthening of some memories over others, depending on hippocampal activity at learning.
Rauchs, Géraldine; Feyers, Dorothée ULg; Landeau, Brigitte et al

in Journal of Neuroscience (2011), 31(7), 2563-2568

Memory consolidation benefits from sleep. Besides strengthening some memory traces, another crucial, albeit overlooked, function of memory is also to erase irrelevant information. Directed forgetting is ... [more ▼]

Memory consolidation benefits from sleep. Besides strengthening some memory traces, another crucial, albeit overlooked, function of memory is also to erase irrelevant information. Directed forgetting is an experimental approach consisting in presenting “to be remembered” and “to be forgotten” information, that allows selectively decreasing or increasing the strength of individual memory traces according to the instruction provided at learning. This paradigm was used in combination with fMRI to determine, in Humans, what specifically triggers at encoding sleep-dependent compared to time-dependent consolidation. Our data indicate that relevant items which subjects strived to memorize are consolidated during sleep to a greater extend than items that participants did not intend to learn. This process appears to depend on a differential activation of the hippocampus at encoding, which acts as a signal for the offline reprocessing of relevant memories during post-learning sleep episodes. [less ▲]

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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 detailIs brain activity during a Stroop inhibitory task modulated by the kind of cognitive control required?
Collette, Fabienne ULg; D'Ostilio, Kevin ULg; D'Argembeau, Arnaud ULg et al

Conference (2011)

Performance on the Stroop task is associated to a large antero-posterior cerebral network involving notably the anterior cingulate and dorsolateral prefrontal cortex. In this study, we used a mixed-BOLD ... [more ▼]

Performance on the Stroop task is associated to a large antero-posterior cerebral network involving notably the anterior cingulate and dorsolateral prefrontal cortex. In this study, we used a mixed-BOLD-fMRI design (N=25) to determine the neural substrates of inhibitory functioning in a Stroop task according to contextual information. Consequently, two task-contexts were created: (1) congruent context with a majority of facilitator items, (2) non-congruent context with mainly interfering items. Based on the dual cognitive control model, we postulated that the non-congruent blocks will involve proactive control, which is anticipatory, sustained, and involved when a large number of interfering items are successively presented. On the contrary, congruent blocks were assumed to involve reactive control, which occurs when few interfering items are presented, and just after the presentation of these items only. On this basis, we hypothesized that the kind of cognitive control modulates cerebral activity associated to inhibitory functioning. For behavioral data, we obtained faster response times for interfering items in the non-congruent vs. congruent condition, indicating proactive control specific to the congruent condition only. Functional neuro-imaging data showed an increased transient activity for interfering vs neutral items in a fronto-parietal network more important in the congruent than in the neutral condition. A similar contrast in the non-congruent condition showed no significant brain activity at the statistical threshold used. These data indicate the existence of a modulation of the cerebral areas associated to inhibitory functioning according to the kind of cognitive control necessary to perform the task. [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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