Mélanie Pélégrini-Issac
University of Paris
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Publication
Featured researches published by Mélanie Pélégrini-Issac.
NeuroImage | 2006
Guillaume Marrelec; A. Krainik; Hugues Duffau; Mélanie Pélégrini-Issac; Stéphane Lehéricy; Julien Doyon; Habib Benali
Examination of functional interactions through effective connectivity requires the determination of three distinct levels of information: (1) the regions involved in the process and forming the spatial support of the network, (2) the presence or absence of interactions between each pair of regions, and (3) the directionality of the existing interactions. While many methods exist to select regions (Step 1), very little is available to complete Step 2. The two main methods developed so far, structural equation modeling (SEM) and dynamical causal modeling (DCM), usually require precise prior information to be used, while such information is sometimes lacking. Assuming that Step 1 was successfully completed, we here propose a data-driven method to deal with Step 2 and extract functional interactions from fMRI datasets through partial correlations. Partial correlation is more closely related to effective connectivity than marginal correlation and provides a convenient graphical representation for functional interactions. As an instance of brain interactivity investigation, we consider how simple hand movements are processed by the bihemispheric cortical motor network. In the proposed framework, Bayesian analysis makes it possible to estimate and test the partial statistical dependencies between regions without any prior model on the underlying functional interactions. We demonstrate the interest of this approach on real data.
Magnetic Resonance in Medicine | 2005
Saâd Jbabdi; Emmanuel Mandonnet; Hugues Duffau; Laurent Capelle; Kristin R. Swanson; Mélanie Pélégrini-Issac; Rémy Guillevin; Habib Benali
A recent computational model of brain tumor growth, developed to better describe how gliomas invade through the adjacent brain parenchyma, is based on two major elements: cell proliferation and isotropic cell diffusion. On the basis of this model, glioma growth has been simulated in a virtual brain, provided by a 3D segmented MRI atlas. However, it is commonly accepted that glial cells preferentially migrate along the direction of fiber tracts. Therefore, in this paper, the model has been improved by including anisotropic extension of gliomas. The method is based on a cell diffusion tensor derived from water diffusion tensor (as given by MRI diffusion tensor imaging). Results of simulations have been compared with two clinical examples demonstrating typical growth patterns of low‐grade gliomas centered around the insula. The shape and the kinetic evolution are better simulated with anisotropic rather than isotropic diffusion. The best fit is obtained when the anisotropy of the cell diffusion tensor is increased to greater anisotropy than the observed water diffusion tensor. The shape of the tumor is also influenced by the initial location of the tumor. Anisotropic brain tumor growth simulations provide a means to determine the initial location of a low‐grade glioma as well as its cell diffusion tensor, both of which might reflect the biological characteristics of invasion. Magn Reson Med, 2005.
NeuroImage | 2003
Harold Mouras; Serge Stoléru; Jacques Bittoun; Dominique Glutron; Mélanie Pélégrini-Issac; Anne-Lise Paradis; Yves Burnod
The brain plays a central role in sexual motivation. To identify cerebral areas whose activation was correlated with sexual desire, eight healthy male volunteers were studied with functional magnetic resonance imaging (fMRI). Visual stimuli were sexually stimulating photographs (S condition) and emotionally neutral photographs (N condition). Subjective responses pertaining to sexual desire were recorded after each condition. To image the entire brain, separate runs focused on the upper and the lower parts of the brain. Statistical Parametric Mapping was used for data analysis. Subjective ratings confirmed that sexual pictures effectively induced sexual arousal. In the S condition compared to the N condition, a group analysis conducted on the upper part of the brain demonstrated an increased signal in the parietal lobes (superior parietal lobules, left intraparietal sulcus, left inferior parietal lobule, and right postcentral gyrus), the right parietooccipital sulcus, the left superior occipital gyrus, and the precentral gyri. In addition, a decreased signal was recorded in the right posterior cingulate gyrus and the left precuneus. In individual analyses conducted on the lower part of the brain, an increased signal was found in the right and/or left middle occipital gyrus in seven subjects, and in the right and/or left fusiform gyrus in six subjects. In conclusion, fMRI allows to identify brain responses to visual sexual stimuli. Among activated regions in the S condition, parietal areas are known to be involved in attentional processes directed toward motivationally relevant stimuli, while frontal premotor areas have been implicated in motor preparation and motor imagery. Further work is needed to identify those specific features of the neural responses that distinguish sexual desire from other emotional and motivational states.
NeuroImage | 2011
Jessica Schrouff; Vincent Perlbarg; Mélanie Boly; Guillaume Marrelec; Pierre Boveroux; Audrey Vanhaudenhuyse; Marie-Aurélie Bruno; Steven Laureys; Christophe Phillips; Mélanie Pélégrini-Issac; Pierre Maquet; Habib Benali
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.
Human Brain Mapping | 2011
Arnaud Messé; Sophie Caplain; G Paradot; D Garrigue; Jf Mineo; G Soto Ares; D. Ducreux; F Vignaud; G Rozec; H Desal; Mélanie Pélégrini-Issac; Michèle Montreuil; Habib Benali; Stéphane Lehéricy
Mild traumatic brain injury (mTBI) can induce long‐term behavioral and cognitive disorders. Although the exact origin of these mTBI‐related disorders is not known, they may be the consequence of diffuse axonal injury (DAI). Here, we investigated whether MRI at the subacute stage can detect lesions that are associated with poor functional outcome in mTBI by using anatomical images (T1) and diffusion tensor imaging (DTI). Twenty‐three patients with mTBI were investigated and compared with 23 healthy volunteers. All patients underwent an MRI investigation and clinical tests between 7 and 28 days (D15) and between 3 and 4 months (M3) after injury. Patients were divided in two groups of poor outcome (PO) and good outcome (GO), based on their complaints at M3. Groupwise differences in gray matter partial volume between PO patients, GO patients and controls were analyzed using Voxel‐Based Morphometry (VBM) from T1 data at D15. Differences in microstructural architecture were investigated using Tract‐Based Spatial Statistics (TBSS) and the diffusion images obtained from DTI data at D15. Permutation‐based non‐parametric testing was used to assess cluster significance at p < 0.05, corrected for multiple comparisons. Twelve GO patients and 11 PO patients were identified on the basis of their complaints. In PO patients, gray matter partial volume was significantly lower in several cortical and subcortical regions compared with controls, but did not differ from that of GO patients. No difference in diffusion variables was found between GO and controls. PO patients showed significantly higher mean diffusivity values than both controls and GO patients in the corpus callosum, the right anterior thalamic radiations and the superior longitudinal fasciculus, the inferior longitudinal fasciculus and the fronto‐occipital fasciculus bilaterally. In conclusion, PO patients differed from GO patients by the presence of diffusion changes in long association white matter fiber tracts but not by gray matter partial volume. These results suggest that DTI at the subacute stage may be a predictive marker of poor outcome in mTBI. Hum Brain Mapp, 2011.
NeuroImage | 2007
Jean Daunizeau; Christophe Grova; Guillaume Marrelec; Jérémie Mattout; Saad Jbabdi; Mélanie Pélégrini-Issac; Jean-Marc Lina; Habib Benali
In this work, we propose a symmetrical multimodal EEG/fMRI information fusion approach dedicated to the identification of event-related bioelectric and hemodynamic responses. Unlike existing, asymmetrical EEG/fMRI data fusion algorithms, we build a joint EEG/fMRI generative model that explicitly accounts for local coupling/uncoupling of bioelectric and hemodynamic activities, which are supposed to share a common substrate. Under a dedicated assumption of spatio-temporal separability, the spatial profile of the common EEG/fMRI sources is introduced as an unknown hierarchical prior on both markers of cerebral activity. Thereby, a devoted Variational Bayesian (VB) learning scheme is derived to infer common EEG/fMRI sources from a joint EEG/fMRI dataset. This yields an estimate of the common spatial profile, which is built as a trade-off between information extracted from EEG and fMRI datasets. Furthermore, the spatial structure of the EEG/fMRI coupling/uncoupling is learned exclusively from the data. The proposed data generative model and devoted VBEM learning scheme thus provide an un-supervised well-balanced approach for the fusion of EEG/fMRI information. We first demonstrate our approach on synthetic data. Results show that, in contrast to classical EEG/fMRI fusion approach, the method proved efficient and robust regardless of the EEG/fMRI discordance level. We apply the method on EEG/fMRI recordings from a patient with epilepsy, in order to identify brain areas involved during the generation of epileptic spikes. The results are validated using intracranial EEG measurements.
Human Brain Mapping | 2003
Guillaume Marrelec; Habib Benali; Philippe Ciuciu; Mélanie Pélégrini-Issac; Jean-Baptiste Poline
In BOLD fMRI data analysis, robust and accurate estimation of the Hemodynamic Response Function (HRF) is still under investigation. Parametric methods assume the shape of the HRF to be known and constant throughout the brain, whereas non‐parametric methods mostly rely on artificially increasing the signal‐to‐noise ratio. We extend and develop a previously proposed method that makes use of basic yet relevant temporal information about the underlying physiological process of the brain BOLD response in order to infer the HRF in a Bayesian framework. A general hypothesis test is also proposed, allowing to take advantage of the knowledge gained regarding the HRF to perform activation detection. The performances of the method are then evaluated by simulation. Great improvement is shown compared to the Maximum‐Likelihood estimate in terms of estimation error, variance, and bias. Robustness of the estimators with regard to the actual noise structure or level, as well as the stimulus sequence, is also proven. Lastly, fMRI data with an event‐related paradigm are analyzed. As suspected, the regions selected from highly discriminating activation maps resulting from the method exhibit a certain inter‐regional homogeneity in term of HRF shape, as well as noticeable inter‐regional differences. Hum. Brain Mapping 19:1–17, 2003.
Proceedings of the National Academy of Sciences of the United States of America | 2012
Mélanie Boly; Vincent Perlbarg; Guillaume Marrelec; Manuel Schabus; Steven Laureys; Julien Doyon; Mélanie Pélégrini-Issac; Pierre Maquet; Habib Benali
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 brains ability to integrate information and account for decreased consciousness during NREM sleep.
NeuroImage | 2006
V. Moulier; Harold Mouras; Mélanie Pélégrini-Issac; D. Glutron; R. Rouxel; B. Grandjean; J. Bittoun; Serge Stoléru
The objective of this study was to identify the cerebral correlates of the early phase, and of low to moderate levels, of penile tumescence using for the first time a volumetric measure of the penile response. We hypothesized that (i) regions whose response had been found correlated with circumferential penile responses in previous studies would be identified with volumetric plethysmography and (ii) that other brain regions, including the amygdalae, would be found using the more sensitive volumetric measurement. In ten healthy males, functional magnetic resonance imaging (fMRI) was used to study brain responses to sexually stimulating photographs and to various categories of control photographs. Both ratings of perceived erection and penile plethysmography demonstrated an erectile response to the presentation of sexually stimulating photographs. Regions where the BOLD signal was correlated with penile volumetric responses included the right medial prefrontal cortex, the right and left orbitofrontal cortices, the insulae, the paracentral lobules, the right ventral lateral thalamic nucleus, the right anterior cingulate cortex and regions involved in motor imagery and motor preparation (supplementary motor areas, left ventral premotor area). This study suggests that the development of low levels of penile tumescence in response to static sexual stimuli is controlled by a network of frontal, parietal, insular and cingulate cortical areas and that penile tumescence reciprocally induces activation in somatosensory regions of the brain.
Brain | 2012
Yulia Worbe; Caroline Malherbe; Andreas Hartmann; Mélanie Pélégrini-Issac; Arnaud Messé; Marie Vidailhet; Stéphane Lehéricy; Habib Benali
Gilles de la Tourette syndrome is a clinically heterogeneous disorder with poor known pathophysiology. Recent neuropathological and structural neuroimaging data pointed to the dysfunction of cortico-basal ganglia networks. Nonetheless, it is not clear how these structural changes alter the functional activity of the brain and lead to heterogeneous clinical expressions of the syndrome. The objective of this study was to evaluate global integrative state and organization of functional connections of sensori-motor, associative and limbic cortico-basal ganglia networks, which are likely involved in tics and behavioural expressions of Gilles de la Tourette syndrome. We also tested the hypothesis that specific regions and networks contribute to different symptoms. Data were acquired on 59 adult patients and 27 gender- and age-matched controls using a 3T magnetic resonance imaging scanner. Cortico-basal ganglia networks were constructed from 91 regions of interest. Functional connectivity was quantified using global integration and graph theory measures. We found a stronger functional integration (more interactions among anatomical regions) and a global functional disorganization of cortico-basal ganglia networks in patients with Gilles de la Tourette syndrome compared with controls. All networks were characterized by a shorter path length, a higher number of and stronger functional connections among the regions and by a loss of pivotal regions of information transfer (hubs). The functional abnormalities correlated to tic severity in all cortico-basal ganglia networks, namely in premotor, sensori-motor, parietal and cingulate cortices and medial thalamus. Tic complexity was correlated to functional abnormalities in sensori-motor and associative networks, namely in insula and putamen. Severity of obsessive-compulsive disorder was correlated with functional abnormalities in associative and limbic networks, namely in orbito-frontal and prefrontal dorsolateral cortices. The results suggest that the pattern of functional changes in cortico-basal ganglia networks in patients could reflect a defect in brain maturation. They also support the hypothesis that distinct regions of cortico-basal ganglia networks contribute to the clinical heterogeneity of this syndrome.