References of "Mascetti, Laura"
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See detailAltered white matter architecture in BDNF Met carriers
Ziegler, Erik ULg; Foret, Ariane; Mascetti, Laura ULg et al

in PLoS ONE (2013)

Brain-derived neurotrophic factor (BDNF) modulates the pruning of synaptically-silent axonal arbors. The Met allele of the BDNF gene is associated with a reduction in the neurotrophin's activity-dependent ... [more ▼]

Brain-derived neurotrophic factor (BDNF) modulates the pruning of synaptically-silent axonal arbors. The Met allele of the BDNF gene is associated with a reduction in the neurotrophin's activity-dependent release. We used di ffusion-weighted imaging to construct structural brain networks for 36 healthy subjects with known BDNF genotypes. Through permutation testing we discovered clear di fferences in connection strength between subjects carrying the Met allele and those homozygotic for the Val allele. We trained a Gaussian process classi fier capable of identifying the subjects' allelic group with 86% accuracy and high predictive value. In Met carriers structural connectivity was greatly increased throughout the forebrain, particularly in connections corresponding to the anterior and superior corona radiata as well as corticothalamic and corticospinal projections from the sensorimotor, premotor and prefrontal portions of the internal capsule. Interhemispheric connectivity was also increased via the corpus callosum and anterior commissure, and extremely high connectivity values were found between inferior medial frontal polar regions via the anterior forceps. We propose that the decreased availability of BDNF leads to de cifits in axonal maintenance in carriers of the Met allele, and that this produces mesoscale changes in white matter architecture. [less ▲]

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See detailConnectome-based classification of BDNF Met allele carriers
Ziegler, Erik ULg; Foret, Ariane; Mascetti, Laura ULg et al

Poster (2013, June)

Secretion of brain-derived neurotrophic factor (BDNF) is essential for synaptic plasticity in the central nervous system during neurodevelopment [Huang]. A common human non-synonymous SNIP in the BDNF ... [more ▼]

Secretion of brain-derived neurotrophic factor (BDNF) is essential for synaptic plasticity in the central nervous system during neurodevelopment [Huang]. A common human non-synonymous SNIP in the BDNF gene (Val66Met, rs6265) decreases activity-dependent BDNF release in neurons transfected with the human A allele (Met-BDNF). We reasoned that the persistent differential activity-dependent BDNF release implied by this polymorphism should also be associated with differences in adult brain structure. The study population comprised 36 healthy subjects (aged 18-25): 15 (9 male) were identified as carrying the Met allele (“Met carrier” group) and 21 (9 male) were homozygotes for the Val allele (“Val/Val” group). The groups did not vary significantly in IQ, age nor scores for a battery of psychological tests. A high-resolution T1-weighted image (sMRI), 7 unweighted (b=0) and a set of diffusion-weighted (b=1000) images using 61 non-collinear directional gradients were acquired for each subject. The processing workflow relied on several pieces of software and was developed in Python and Nipype. The sMRIs were segmented using the automated labeling of Freesurfer [Desikan] and further parcellated using the Lausanne2008 atlas into 1015 regions of interest (ROIs) [Cammoun]. DWIs were corrected for image distortions (due to eddy currents) using linear coregistration functions from FSL [Smith]. Fractional anisotropy maps were generated, and a few single-fiber (high FA) voxels were used to estimate the spherical harmonic coefficients (order 8) of the response function from the DWIs [Tournier]. Then orientation distribution functions were obtained at each voxel. Probabilistic tractography was performed throughout the whole brain using seeds from subject-specific white-matter masks and a predefined number of tracts (300,000), see Fig. 1. The tracks were affine-transformed into the subject's structural space with Dipy [Garyfallidis]. Connectome mapping was performed by considering every contact point between each tract and the outlined ROIs (unlike in [Hagmann]): the connectivity matrix was incremented every time a single fiber traversed between any two ROIs. We trained a Gaussian Process Classifier [Rasmussen] (interfaced by PRoNTo [Schrouff]) on these connectivity matrices. The accuracy and generalization ability of the classification were assessed with a leave-one-subject-out cross-validation procedure. With this linear kernel method weights were also obtained indicating the contribution to the classification output (in favor of either genotypic group) of each edge in the network. The same method was employed to discriminate features related to the subjects' gender and genotype for the ADA gene. The classifier was able to discriminate between Val/Val and Met carriers with 86.1% balanced accuracy. The predictive value for the Val/Val and Met carrier groups were 94.4% (p=0.001) and 77.8% (p=0.003), respectively. In Fig. 2 the weights obtained by the classifier are visualized as edges in the brain network. For the classifier trained to identify gender or the subjects' ADA genotype, the global accuracy reached 63.9% (n.s.) and 58.3% (n.s.) respectively. Using high-resolution connectome mapping from normal young healthy human volunteers grouped based on the Met allele of the BNDF gene, we show that the BDNF genotype of an individual can be significantly identified from his structural brain wiring. These differences appear specific to this allele; no such difference could be found for the polymorphism in the ADA gene, or even for gender. We propose that the decreased availability of BDNF leads to deficits in axonal maintenance in Met carriers, and that this produces mesoscale changes in white matter architecture. Acknowledgements: the FNRS, the ULg, the Queen Elisabeth Medical Foundation, the Léon Fredericq Foundation, the Belgian Inter-University Attraction Program, the Welbio program, and the MCITN in Neurophysics (PITN-GA-2009-238593). Cammoun L. et al. (2011), ‘Mapping the human connectome at multiple scales with diffusion spectrum MRI’, J Neuroscience Methods, 203:386–397. Desikan R.S. et al. (2006), ‘An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest’, Neuroimage, 31:968-980. Hagmann P. et al. (2008), ‘Mapping the structural core of human cerebral cortex’, PLoS Biology, 6:e159 Huang E.J., Reichardt L.F. (2001), ‘Neurotrophins: roles in neuronal development and function’, Annual Review of Neuroscience, 24:677-736. Garyfallidis E. et al. (2011), ‘Dipy - a novel software library for diffusion MR and tractography’, 17th Annual Meeting of the Organization for Human Brain Mapping. http://nipy.sourceforge.net/dipy/ Rasmussen C.E. (2006), Gaussian processes for machine learning. Schrouff J. et al. (2012), ‘PRoNTo: Pattern Recognition for Neuroimaging Toolbox’, 18th Annual Meeting of the Organization for Human Brain Mapping. http://www.mlnl.cs.ucl.ac.uk/pronto Smith S.M. et al. (2004), ‘Advances in functional and structural MR image analysis and implementation as FSL’, Neuroimage, 23 Suppl 1:S208-S219. Tournier J.D., et al. (2007), ‘Robust determination of the fibre orientation distribution in diffusion MRI: non-negativity constrained super-resolved spherical deconvolution’, Neuroimage, 35:1459-1472. [less ▲]

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See detailFunctional neuroimaging of human REM sleep
Meyer, Christelle ULg; Jedidi, Zayd ULg; Muto, Vincenzo ULg et al

in Nofzinger, Eric; Maquet, Pierre; Thorpy, Michael J. (Eds.) Neuroimaging of sleep and sleep disorders (2013)

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See detailThe impact of visual perceptual learning on sleep and local slow wave initiation
Mascetti, Laura ULg; Muto, Vincenzo ULg; Matarazzo, Luca et al

in Journal of Neuroscience (2013)

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See detailNeural Correlates of Human Sleep and Sleep-Dependent Memory Processing
Meyer, Christelle ULg; Muto, Vincenzo ULg; Jaspar, Mathieu ULg et al

in Frank, Marcos (Ed.) Sleep and Brain Activity (2012)

Wakefulness and sleep are associated with distinct patterns of neural activity and neuromodulation. In humans, functional neuroimaging was used to characterize the related changes in regional brain ... [more ▼]

Wakefulness and sleep are associated with distinct patterns of neural activity and neuromodulation. In humans, functional neuroimaging was used to characterize the related changes in regional brain metabolism and hemodynamics. Recent data combining EEG and fMRI described the transient responses associated with spindles and slow waves, as well as the changes in functional integration during NREM sleep. It was also shown that regional brain activity during sleep is influenced by the experience acquired during the preceding waking period. These data are currently interpreted in the framework of two theories. First, the use-dependent increase in slow oscillation during NREM sleep is associated with local synaptic homeostasis. Second, reactivations of memory traces during NREM sleep would reorganize declarative memories in hippocampal-neocortical networks, a systems-level memory consolidation which can be hindered by sleep deprivation. Collectively, these data reveal the dynamical changes in brain activity during sleep which support normal human cognition. [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 detailSleep, memory and the hippocampus
Foret, Ariane; Mascetti, Laura ULg; Kussé, Caroline ULg et al

in Clinical Neurobiology of the Hippocampus (2012)

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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 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 detailSpontaneous neural activity during human non-rapid eye movement sleep.
Mascetti, Laura ULg; Foret, Ariane ULg; Shaffii, Anahita ULg et al

in Progress in Brain Research (2011), 193

Recent neuroimaging studies characterized the neural correlates of slow waves and spindles during human non-rapid eye movement (NREM) sleep. They showed that significant activity was consistently ... [more ▼]

Recent neuroimaging studies characterized the neural correlates of slow waves and spindles during human non-rapid eye movement (NREM) sleep. They showed that significant activity was consistently associated with slow (> 140 muV) and delta waves (75-140 muV) during NREM sleep in several cortical areas including inferior frontal, medial prefrontal, precuneus, and posterior cingulate cortices. Unexpectedly, slow waves were also associated with transient responses in the pontine tegmentum and in the cerebellum. On the other hand, spindles were associated with a transient activity in the thalami, paralimbic areas (anterior cingulate and insular cortices), and superior temporal gyri. Moreover, slow spindles (11-13 Hz) were associated with increased activity in the superior frontal gyrus. In contrast, fast spindles (13-15 Hz) recruited a set of cortical regions involved in sensorimotor processing, as well as the mesial frontal cortex and hippocampus. These findings indicate that human NREM sleep is an active state during which brain activity is temporally organized by spontaneous oscillations (spindles and slow oscillation) in a regionally specific manner. The functional significance of these NREM sleep oscillations is currently interpreted in terms of synaptic homeostasis and memory consolidation. [less ▲]

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See detailInfluence of brain-derived neurotrophic factor val66met human polymorphism on declarative memory consolidation
Mascetti, Laura ULg; Foret, Ariane ULg; Matarazzo, Luca et al

Poster (2010, November 15)

The Brain-Derived Neurotrophic Factor (BDNF) is a neurotrophin which in the adult brain regulates long-term potentiation. In humans, valine (val) to methionine (met) substitution in the 5’ pro-region of ... [more ▼]

The Brain-Derived Neurotrophic Factor (BDNF) is a neurotrophin which in the adult brain regulates long-term potentiation. In humans, valine (val) to methionine (met) substitution in the 5’ pro-region of the BDNF protein is associated with poorer episodic memory. Neurons transfected with met-BDNF-Green Fluorescence Protein showed lower depolarization-induced secretion, while constitutive secretion is unchanged. Here, we hypothesized that the differences in BDNF release determined by this polymorphism would influence memory consolidation and that in comparison with the val/met (=val/met or met/met), val/val individuals would show higher memory performance and different brain responses during a 16h-delayed rather than immediate retrieval session. Participants encoded a series of neutral faces in the afternoon. Retrieval sessions took place one hour after the encoding session, and in the following morning, during the acquisition of functional Magnetic Resonance Imaging (fMRI) time series with a 3 Tesla Allegra scanner. During retrieval, studied faces and new ones were presented in random order. For each stimulus, the subjects indicated whether they could retrieve the encoding episode with (“Remember”), or without details (“Know”), or if they thought the item had not been presented during encoding (“New”). A repeated-measure ANOVA on discrimination index (d’) showed significant effects of group (F(1, 27)=8.65, p=0.007, n(val/val)=14, n(val/met)=15) and session (F(1, 27)=24.64, p=0.000), although the group by session interaction was not significant (F(1, 27)=1.29, p=0.267). fMRI results showed a significant genotype (val/val > val/met) by session (delayed > immediate retrieval) by memory type (Remember > Know) interaction in the right inferior occipital gyrus (x=42, y=-78, z=0, p=0.004, Z=3.77), the left inferior parietal lobule (x=-56, y=-40, z=48, p=0.013, Z=3.43), the posterior cingulate cortex (x=14, y=-42, z=42, p=0.019, Z=3.29) and the right hippocampus (x=28, y=-22, z=-22, p=0.03, Z=3.11). Val/val individuals demonstrate higher memory performance than met-carriers but the change in memory performance between immediate and delayed retests is similar in both allelic groups. In contrast, neural correlates of recollection change between sessions differently according to genotype: responses increase significantly more in val/val than in val/met individuals in brain areas involved in the retrieval, accumulation and binding of perceptual memory details during delayed, relative to immediate retest. These data suggest that activity-dependent BDNF release promotes memory consolidation during the first post-training hours. [less ▲]

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See detailInfluence of Brain-Derived Neurotrophic Factor val66met human polymorphism on declarative memory consolidation during sleep
Mascetti, Laura ULg; Foret, Ariane ULg; Matarazzo, Luca et al

Poster (2010, September 15)

Objectives The Brain-Derived Neurotrophic Factor (BDNF) is a neurotrophin which in the adult brain, regulates long-term potentiation and has been involved in the build up of the homeostatic sleep pressure ... [more ▼]

Objectives The Brain-Derived Neurotrophic Factor (BDNF) is a neurotrophin which in the adult brain, regulates long-term potentiation and has been involved in the build up of the homeostatic sleep pressure in rodents. In humans, valine (val) to methionine (met) substitution in the 5’ pro-region of the BDNF protein is associated with poorer episodic memory. Neurons transfected with met-BDNF-Green Fluorescence Protein showed lower depolarization-induced secretion, while constitutive secretion is unchanged. Here, we hypothesized that the differences in BDNF release determined by this polymorphism would influence sleep-dependent memory consolidation and that in comparison with the met-carriers (val/met or met/met), val/val individuals would show higher memory performance after one night of sleep rather than an immediate retrieval session. Methods Participants encoded a series of neutral faces in the afternoon. Retrieval sessions took place one hour after the encoding session, and in the following morning, after a night of polysomnographic-monitored sleep. During retrieval, studied faces and new ones were presented in random order. For each stimulus, the subjects indicated whether they could retrieve the encoding episode with (“Remember” response), or without details (“know” response), or if they thought the item had not been presented during encoding (“New” response). Results A repeated-measure ANOVA on discrimination index (d’) showed significant effects of group (F(1, 22)=4.66, p=0.042) and session (F(1, 22)=12.21, df=1, p=0.002). Although the group by session interaction was not significant (F(1, 22)=1.84, p=0.188), exploratory planned comparisons showed that at immediate retrieval, d’ was not significantly different between groups (val/val, d’ = 1.94±0.16; met-carriers, d’= 1.61±0.14; p>0.5). In contrast, during the second retest (the next day) d’ in the val/val group (d’=2.56±0.23) was significantly higher than in the met-carriers group (d’=1.88±0.21; p=0.041). Likewise, a between-session enhancement in d’ was detected only in the val/val population (p=0.003). Conclusion Val/val individuals demonstrate higher memory performance than met-carriers after a night of sleep but not at immediate retest. These data suggest that activity-dependent BDNF release promotes memory consolidation during the first post-training hours. Further analysis of the present data set will assess the respective effect of sleep and time on the BDNF-associated delayed memory enhancement. This study was supported by FNRS-FRIA, the University of Liège, and the QEMF. [less ▲]

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See detailContributions du sommeil a la consolidation mnésique
Maquet, Pierre ULg; Matarazzo; Foret, Ariane ULg et al

in Biologie Aujourd'hui (2010), 204(2), 139-143

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See detailNeuroimaging of dreaming: state of the art and limitations
Kussé, Caroline ULg; Muto, Vincenzo ULg; Mascetti, Laura ULg et al

in International Review of Neurobiology (2010)

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See detailNeuroimaging Insights into the Dreaming Brain
Desseilles, Martin ULg; Dang Vu, Thien Thanh ULg; Schabus, Manuel et al

in Dreams and Dreaming (2010)

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See detailCharacterization of spatio-temporal organization of slow waves during human NREM sleep
Schrouff, Jessica ULg; Leclercq, Yves ULg; Foret, Ariane et al

Poster (2009, December 14)

Sleep is a behavior commonly observed in a large number of animal species. However, neuroscientists still poorly understand the meaning of this loss of consciousness absolutely needed for life. In the ... [more ▼]

Sleep is a behavior commonly observed in a large number of animal species. However, neuroscientists still poorly understand the meaning of this loss of consciousness absolutely needed for life. In the present work, we established different methods to characterize the Slow Wave Sleep most recognizable patterns: the Slow Waves (SWs). Since the anatomical structure of white matter tracts that connect various brain regions is not random and thus must constraint the propagation of waves (Hagmann et al., 2008), our basic hypothesis was that large white matter bundles would bias the propagation of SW along specific patterns, which could be identified in homogeneous clusters of waves. To investigate our hypothesis, SWs were detected automatically on the three first periods of SWS using an algorithm based on Massimini et al., 2004. They were then clustered using a two steps procedure involving a hierarchical clustering based on delay maps and a k-means clustering based on the SWs potential in a given time interval around the maximum power of the SW negative peak. To compute the relevance of the final clusters, a mathematical criterion was implemented as well as a visual check. Results of the multisubjects study showed that only bad quality and small clusters could be obtained, suggesting that there is no particular organization of SWs across the night and inforcing the hypothesis that SWs are local phenomena, each one decreasing the homeostatic pressure in only one specific area. [less ▲]

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See detailSome facts about sleep relevant for Landau-Kleffner syndrome.
Mascetti, Laura ULg; Foret, Ariane ULg; Bonjean, Maxime et al

in Epilepsia (2009), 50 Suppl 7

Our understanding of the neural mechanisms of non-rapid eye movement sleep (NREM) is steadily increasing. Given the intriguing activation of paroxysmal activity during NREM sleep in patients with Landau ... [more ▼]

Our understanding of the neural mechanisms of non-rapid eye movement sleep (NREM) is steadily increasing. Given the intriguing activation of paroxysmal activity during NREM sleep in patients with Landau-Kleffner syndrome (LKS), a thorough characterization of commonalities and differences between the neural correlates of LKS paroxysms and normal sleep oscillations might provide useful information on the neural underpinning of this disorder. Especially, given the suspected role of sleep in brain plasticity, this type of information is needed to assess the link between cognitive deterioration and electroencephalography (EEG) paroxysms during sleep. [less ▲]

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