Academic literature on the topic 'Réseaux de connectivité du cerveau'
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Journal articles on the topic "Réseaux de connectivité du cerveau"
Gay, Ayla. "De l’apprentissage à la mémoire : Similitudes avec la topologie des réseaux sociaux." Cortica 2, no. 2 (September 19, 2023): 151–56. http://dx.doi.org/10.26034/cortica.2023.3772.
Full textGasnier, M., C. Gaudeau, A. H. Clair, A. Pelissolo, L. Mallet, and K. N’Diaye. "Connectivité fonctionnelle des réseaux cortico-striataux chez des patients atteints de trouble obsessionnel compulsif de vérification : étude du « resting state » en IRM fonctionnelle." European Psychiatry 29, S3 (November 2014): 545–46. http://dx.doi.org/10.1016/j.eurpsy.2014.09.330.
Full textHilal, Fahd, Jérôme Jeanblanc, and Mickaël Naassila. "Intérêt et mécanismes d’action de la kétamine dans le traitement de l’addiction à l’alcool – Revue des études cliniques et précliniques." Biologie Aujourd’hui 217, no. 3-4 (2023): 161–82. http://dx.doi.org/10.1051/jbio/2023028.
Full textBoussac, Mathilde, and Emeline Descamps. "Changement de connectivité fonctionnelle cérébrale après une session de réflexologie plantaire lors d’un essai contrôlé randomisé." Hegel N° 4, no. 4 (January 18, 2024): 295–305. http://dx.doi.org/10.3917/heg.134.0295.
Full textCorredor, David, Anais Vallet, Maëlle Riou, Francis Eustache, and Bérengère Guillery-Girard. "Les sciences des réseaux appliquées à l’étude du Trouble de Stress Post-Traumatique." Biologie Aujourd’hui 217, no. 1-2 (2023): 79–87. http://dx.doi.org/10.1051/jbio/2023020.
Full textCLAUZEL, Céline, Christophe EGGERT, Simon TARABON, Lili PASQUET, Gilles VUIDEL, Marion BAILLEUL, Claude MIAUD, and Claire GODET. "Analyser la connectivité de la trame turquoise : définition, caractérisation et enjeux opérationnels." Sciences Eaux & Territoires, no. 43 (October 16, 2023): 67–71. http://dx.doi.org/10.20870/revue-set.2023.43.7642.
Full textMallet, L. "∑njeux de la πsychiatrie ℂomputationnelle." European Psychiatry 30, S2 (November 2015): S50—S51. http://dx.doi.org/10.1016/j.eurpsy.2015.09.143.
Full textCitton, Yves. "Brain Scales and the Dynamics of Images according to Gilbert Simondon." IRIS, no. 36 (June 30, 2015): 139–57. http://dx.doi.org/10.35562/iris.1608.
Full textCitton, Yves. "Brain Scales and the Dynamics of Images according to Gilbert Simondon." IRIS, no. 36 (June 30, 2015): 139–57. http://dx.doi.org/10.35562/iris.1608.
Full textWidlöcher, D. "Le cerveau humain : un ordinateur à réseaux multiples et fragiles." médecine/sciences 12, no. 6-7 (1996): 703. http://dx.doi.org/10.4267/10608/810.
Full textDissertations / Theses on the topic "Réseaux de connectivité du cerveau"
Bellec, Pierre. "Etude longitudinale des réseaux cérébraux à large échelle en IRMf : méthodes et application à l'étude de l'apprentissage moteur." Paris 11, 2006. http://www.theses.fr/2006PA112011.
Full textSkill learning in human healthy volunteers is thought to induce a reorganization of cerebral activity. Such process of cerebral plasticity involves the modulation of functional interactions within networks of spatially distributed brain regions, or large-scale networks. Various measures of connectivity exist that allow one to quantify these functional interactions using functional magnetic resonance imaging (fMRI), which enables the non-invasive, yet indirect, measure of cerebral activity. I developed a series of methods that allows to characterize the reorganization of large-scale networks in the brain when considering an fMRI longitudinal study of a single subject or group of subjects, at various stages of a learning process. First, the regions of the network involved in the execution of the task under scrutiny are built and identified from the functional data in an exploratory way, by using a competitive region growing method, which segments the gray matter into functionally homogeneous regions, then followed by a statistical classification procedure. A statistical method is then designed to assess which interactions are significantly modulated within the network during the plasticity process. This method is based on a non-parametric bootstrap technique, taking the temporal auto-correlation of fMRI time series into account, and controling the false discovery rate. These methods have been validated and evaluated on both synthetic and real datasets. Two real datasets were studied, which involved learning of a sensorimotor adaptation task and of a motor sequence task, respectively
Karkar, Slim Ismael. "Parcellisation et analyse multi-niveaux de données : Application à l’étude des réseaux de connectivité cérébrale." Strasbourg, 2011. https://publication-theses.unistra.fr/public/theses_doctorat/2011/KARKAR_Slim_Ismael_2011.pdf.
Full textOver the last decade, functional MRI has emerged as a widely used tool for mapping functions of the brain. More recently, it has been used for identifying networks of cerebral connectivity that represent the interactions between different brain areas. In this context, a recent strategy is based on a preliminary parcellation of the brain into functional regions, and then identifying functional networks from a measurement of interactions between each area. The first part of this thesis describes a novel approach for parcellation that produces regions that are homogeneous at several levels. These regions are shown to be consistent with the anatomical landmarks of the processed subjects. In the second part, we propose a new family of statistics to identify significant networks of functional connectivity. This approach enables the detection of small, strongly-connected networks as well as larger networks that involve weaker interactions. Finally, within a classification framework, we developed a group-level study, producing networks that synthesize characteristics of functional networks across the population under study
Bertrand, Perrine. "Étude en IRM des modifications des connectivités cérébrales anatomique et fonctionnelle en fonction de l'âge chez le sujet sain." Toulouse 3, 2012. http://thesesups.ups-tlse.fr/2021/.
Full textOur study was focused on the changes of anatomical and functional brain connectivity during aging. We acquired for each participant (47 male subjects, healthy, aged from 20 to 65) several MRI imaging (Philips 3T MRI): an anatomical sequence (T1 weighted image), a sequence of diffusion imaging in 32 directions and three sequences of functional imaging (at rest, during a motor task and an attentional). The anatomical image allows us to assess the brain atrophy and calculate the cortical thickness. With the diffusion tensor imaging (DTI) we have extracted fractional anisotropy and mean diffusivity and we have realized tractography. We used different software as SPM8 (Statistical Parametric Mapping), MATLAB (The MathWorks, Inc. ) and Statistica (Statsoft). We have analyzed the functional connectivity with the 3 sequences of fMRI using methods of Independent Component Analysis, and methods based on statistical analysis of networks (Network Based Statistics). Functional imaging has showed the role played by the Angular Gyrus (including many modifications on connections), and changes occurring in the Default-Mode Network and the Working Memory (decreases in the frontal lobe). Furthermore, we have demonstrated a decrease in fiber orientation in the anterior part of the Corpus Callosum, and in the cerebellum. Due to the study of anatomical connectivity, we have defined a set of sub-networks that resist structurally with age. Our contribution will allow a better characterization of the effect of normal aging on brain connectivity. Besides, benefits of this study may be useful for the comprehension of neurodegenerative diseases such as Alzheimer and Parkinson
Skeif, Hanadi. "Connectivité fonctionnelle des réseaux neuronaux intégratifs du système limbique étudiée en IRM fonctionnelle d'activation par stimuli olfactifs." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLS537/document.
Full textThe precise mechanisms at the origin of the depression are not yet elucidated. The advent of functional neuroimaging techniques such as functional magnetic resonance imaging (fMRI) has provided a powerful tool not only for defining the neurobiological circuits disturbed in depression, but also for better understanding the contribution of each region. The objectives of this work were to highlight: (i) the clusters involved in the hedonic evaluation of the smell (ii) the functional brain abnormalities underlying the olfactory deficits in the major depressive episode (MDE) and (iii) the modulations of these abnormalities following antidepressant treatment. Thirty-eight depressive patients and thirty healthy subjects were selected to perform a fMRI examination with three tasks: recognizing three smells which are the spearmint, sandalwood and wine lees. Based on our study, we can conclude that depressed patients have functional abnormalities in the thalamus, this region may be considered as a good marker for the prognosis of depression. In addition, fMRI could be a good tool to evaluate the treatment performance of antidepressant treatment
Obando, Forero Catalina. "Statistical graph models of temporal brain networks." Electronic Thesis or Diss., Sorbonne université, 2018. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2018SORUS454.pdf.
Full textThe emerging area of complex networks has led to a paradigm shift in neuroscience. Connectomes estimated from neuroimaging techniques such as electroencephalography (EEG), magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) results in an abstract representation of the brain as a graph, which has allowed a major breakthrough in the understanding of topological and physiological properties of healthy brains in a compact and objective way. However, state of the art approaches often ignore the uncertainty and temporal nature of functional connectivity data. Most of the available methods in the literature have been developed to characterize functional brain networks as static graphs composed of nodes (brain regions) and links (FC intensity) by network metrics. As a consequence, complex networks theory has been mainly applied to cross-sectional studies referring to a single point in time and the resulting characterization ultimately represents an average across spatiotemporal neural phenomena. Here, we implemented statistical methods to model and simulate temporal brain networks. We used graph models that allow to simultaneously study how different network properties influence the emergent topology observed in functional connectivity brain networks. We successfully identified fundamental local connectivity mechanisms that govern properties of brain networks. We proposed a temporal adaptation of such fundamental connectivity mechanisms to model and simulate physiological brain network dynamic changes. Specifically, we exploited the temporal metrics to build informative temporal models of recovery of patients after stroke
Treserras, Sébastien. "Études sur la connectivité cérébrale : aspects méthodologiques et applications au cerveau au repos, à la motricité et à la lecture." Toulouse 3, 2008. http://thesesups.ups-tlse.fr/1244/.
Full textThe cerebral connectivity implemented in functional neuroimagery, allows to better understand the relations between cortical areas. Two approaches may be used to study these relations: functional and effective connectivity. The present thesis deals about both theory of these methods and theirs applications to various cognitive situations using fMRI. Functional connectivity was chosen to study modification of cerebral activity during the transition from the resting to an activated state. We showed that two networks (resting state network and motor system network) that were independent during the resting state happened to be connected during a movement readiness state. This result suggests that default-mode network plays a role triggering the cognitive network dedicated to perform the task (motor). Effective connectivity was used to describe influences among brain regions. We applied structural equation modeling (SEM) on two different studies: one focused on motor learning and the other on the reading skill. For the first one, we showed that different learning strategies correspond to different modulation of connexions between solicited areas; for the second one we demonstrated that the linguistic load of presented items wad correlated with the connexion weight between Broca area and the left superior parietal lobule. As well as methodologic aspect, this thesis work confirms the potential of an cerebral connectivity analysis in functional neuroimagery studies
Guillon, Jérémy. "Multilayer Approach to Brain Connectivity in Alzheimer’s Disease." Electronic Thesis or Diss., Sorbonne université, 2018. http://www.theses.fr/2018SORUS305.
Full textAlzheimer’s disease causes alterations of the brain networks structure and function that can be modelized by a brain connectivity analyse. We proposed a multi-layer approach to analyse multi-frequency and multimodal brain networks built from magnetoencephalographic (MEG) recordings, functional (fMRI) or diffusion-weighted magnetic resonance imaging (DWI). Main results showed the existence of previously undefined type of hubs that are inter-frequency hubs; identified thanks to their multi-participation coefficient (MPC) computed from a brain connectivity network with a multi-frequency multiplex topology. These hubs are impacted by Alzheimer’s disease, which reduces their naturally high ability to integrate information propagating through different frequency bands. We also generalized the concept of core-periphery structure to multilayer networks to be able to apply it to a multimodal brain connectivity model that combines structural and functional networks in a single multiplex topology. Hence, we could identify, from a systemic point of view, the most important regions at the scale of the entire brain and study their alteration in patients with Alzheimer’s disease. Therefore, this thesis expose how multilayer networks applied to brain connectivity can help in understanding neurodegenerative diseases such as Alzheimer’s disease
Malherbe, Caroline. "Imagerie des faisceaux de fibres et des réseaux fonctionnels du cerveau : application à l'étude du syndrome de Gilles de la Tourette." Phd thesis, Université Paris Sud - Paris XI, 2012. http://tel.archives-ouvertes.fr/tel-00980572.
Full textRoquet, Daniel. "Etude et application de la connectivité fonctionnelle cérébrale chez le sujet sain et dans la pathologie." Thesis, Strasbourg, 2014. http://www.theses.fr/2014STRAJ100/document.
Full textBrain areas are functionally connected in networks, even at rest. Since such connectivity networks could be impaired in several pathologies, they could potentially serve for diagnosis and treatment. Based on four studies, spatial independent component analysis has shown sufficient sensitivity, reproducibility and specificity to produce reliable healthy as well as pathological networks at the individual level. Therefore, the network underlying auditory hallucination could define the brain areas to treat by transcranial magnetic stimulation. Among the common resting-state networks, the ones involving the posterior cingular cortex and the precuneus seem deeply altered in disorders of consciousness, and so could be used as a diagnostic tool to distinguish the locked-in syndrome from the vegetative state. We can now map, at the individual level, the functional relationships between brain areas. Further studies on the dynamic and on the level of activity of the functional connectivity networks might provide relevant information about their functions and their involvement in the pathology
Arefin, Tanzil Mahmud. "Signatures du récepteur GPR88 sur la connectivité fonctionnelle et structurelle du cerveau chez la souris : implications pour le développement de la dépendance à l’alcool." Thesis, Strasbourg, 2017. http://www.theses.fr/2017STRAJ101/document.
Full textPathological agitations of the brain and the expression or mutation of single gene affect overall brain connectivity. Here we combined mouse mutagenesis with functional and structural MRI and explored mouse whole brain connectivity maps non-invasively in response to the inactivation of Gpr88 gene. We perceived robust modifications in the default mode network which is considered a hallmark of many psychiatric conditions, followed by sensori-motor network allied to sensorimotor gating deficiency underlying hyperactivity phenotype in Gpr88-/- mice. In addition, hippocampal and dorsal striatum functional connectivity perturbations might underlie learning deficiency and weakened amygdala connectivity with cortex and striatum might suggest triggering of risk-taking behavior previously observed in these animals. Moreover, Gpr88 deletion strongly modifies the reward network leading Gpr88-/- mice vulnerable to alcohol intake. This is the first evidence of Gpr88 involvement in reshaping the mouse brain connectome. The concordance between connectivity alterations and behavior deficits posits Gpr88 as a potential target for psychiatric disorders
Books on the topic "Réseaux de connectivité du cerveau"
R, Baldwin John. Innovation et connectivité: La nature des liaisons entre les marchés et les réseaux d'innovation dans les industries de la fabrication au Canada. Ottawa, Ont: Direction des études analytiques, Statistique Canada, 2001.
Find full textHawkins, Jeff. Intelligence. Paris: CampusPress, 2005.
Find full textHorel, Stéphane. Drogues & cerveau: LSD, cocaïne, cannabis, opium, morphine, héroïne, alcool, tabac, ecstasy, tranquillisants, antidépresseurs, jeu, boulimie, sexe. Paris: Actuel/Editions du Panama, 2005.
Find full textJ, Sejnowski Terrence, ed. The computational brain. Cambridge, Mass: MIT Press, 1992.
Find full textvon, Seelen W., Shaw G. L. 1932-, Leinhos U. M, and Werner-Reimers-Stiftung, eds. Organization of neural networks: Structures and models. Weinheim, Federal Republic of Germany: VCH, 1988.
Find full textGillian, Cohen, Johnston Lolo Bob, Plunkett Kim, and Open University, eds. Exploring cognition: Damaged brains and neural networks : readings in cognitive neuropsychology and connectionist modelling. Hove: Psychology Press, 2000.
Find full textTakao, Kumazawa, Kruger Lawrence, and Mizumura Kazue, eds. The polymodal receptor: A gateway to pathological pain. Amsterdam: Elsevier, 1996.
Find full textpublier, Alexandre. Livre de Puzzle Sudoku: Un Merveilleux Livre de Puzzle Avec de Nombreux Réseaux de Sudoku du Simple Au Lourd Gros Jeux de Cerveau Sudoku Impression Pour Adultes et Adolescents,. Independently Published, 2022.
Find full textGateway to Memory: An Introduction to Neural Network Modeling of the Hippocampus and Learning (Issues in Clinical and Cognitive Neuropsychology). The MIT Press, 2000.
Find full textThe Neural Simulation Language: A System for Brain Modeling. The MIT Press, 2002.
Find full textBook chapters on the topic "Réseaux de connectivité du cerveau"
Alexandre, Frédéric. "Corps et réseau : l’exemple du cerveau." In Les réseaux, 129–39. CNRS Éditions, 2012. http://dx.doi.org/10.4000/books.editionscnrs.19303.
Full textRioux, Michèle. "Théories des firmes multinationales et des réseaux économiques transnationaux." In Mondialisation et connectivité, 301–16. Presses de l'Université du Québec, 2019. http://dx.doi.org/10.2307/j.ctvq4bz8j.24.
Full textHARSAN, Laura Adela, Laetitia DEGIORGIS, Marion SOURTY, Éléna CHABRAN, and Denis LE BIHAN. "IRM fonctionnelle." In Les enjeux de l’IRM, 109–45. ISTE Group, 2023. http://dx.doi.org/10.51926/iste.9113.ch5.
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