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Détail de l'auteur
Auteur Ragini VERMA |
Documents disponibles écrits par cet auteur (2)
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DTI and Tractography in the Autistic Brain / Timothy P.L. ROBERTS
Titre : DTI and Tractography in the Autistic Brain Type de document : Texte imprimé et/ou numérique Auteurs : Timothy P.L. ROBERTS, Auteur ; Jeffrey I. BERMAN, Auteur ; Ragini VERMA, Auteur Année de publication : 2013 Importance : p.267-279 Langues : Anglais (eng) Index. décimale : SCI-D SCI-D - Neurosciences Résumé : Diffusion tensor imaging (DTI) and associated fiber tractography are an emerging MRI technique for studying white matter of the brain. This chapter presents an introduction to the physical and biological bases of diffusion in white matter and the development and analysis of diffusion tensor imaging. It also includes visualization of white matter fiber tracts and quantification of physical diffusion parameters, such as the mean diffusivity (MD) and fractional anisotropy (FA) that might be used to index white matter maturation. A review of the recent findings made using DTI in ASD (autism spectrum disorder) is presented, focusing on studies with large (gt;20) sample sizes. Common themes of elevated mean diffusivity and diminished fractional anisotropy emerge, especially in structures of the frontal and temporal lobes, but also in the corpus callosum. Voxel-based as well as regional connectivity approaches to extracting quantitative information from DTI are discussed along with approaches involving machine learning of pattern classifiers to distinguish ASD from TD and also identify key features (structures, regions or connections) that contribute most to that discrimination ability. Limitations of tractography based on DTI are discussed along with the emerging advance of high angular resolution diffusion imaging (HARDI) as a means to overcome DTI limitations in regions of complex white matter organization. Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=189 DTI and Tractography in the Autistic Brain [Texte imprimé et/ou numérique] / Timothy P.L. ROBERTS, Auteur ; Jeffrey I. BERMAN, Auteur ; Ragini VERMA, Auteur . - 2013 . - p.267-279.
Langues : Anglais (eng)
Index. décimale : SCI-D SCI-D - Neurosciences Résumé : Diffusion tensor imaging (DTI) and associated fiber tractography are an emerging MRI technique for studying white matter of the brain. This chapter presents an introduction to the physical and biological bases of diffusion in white matter and the development and analysis of diffusion tensor imaging. It also includes visualization of white matter fiber tracts and quantification of physical diffusion parameters, such as the mean diffusivity (MD) and fractional anisotropy (FA) that might be used to index white matter maturation. A review of the recent findings made using DTI in ASD (autism spectrum disorder) is presented, focusing on studies with large (gt;20) sample sizes. Common themes of elevated mean diffusivity and diminished fractional anisotropy emerge, especially in structures of the frontal and temporal lobes, but also in the corpus callosum. Voxel-based as well as regional connectivity approaches to extracting quantitative information from DTI are discussed along with approaches involving machine learning of pattern classifiers to distinguish ASD from TD and also identify key features (structures, regions or connections) that contribute most to that discrimination ability. Limitations of tractography based on DTI are discussed along with the emerging advance of high angular resolution diffusion imaging (HARDI) as a means to overcome DTI limitations in regions of complex white matter organization. Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=189 Exemplaires
Code-barres Cote Support Localisation Section Disponibilité aucun exemplaire Joint Analysis of Band-Specific Functional Connectivity and Signal Complexity in Autism / Yasser GHANBARI in Journal of Autism and Developmental Disorders, 45-2 (February 2015)
[article]
Titre : Joint Analysis of Band-Specific Functional Connectivity and Signal Complexity in Autism Type de document : Texte imprimé et/ou numérique Auteurs : Yasser GHANBARI, Auteur ; Luke BLOY, Auteur ; J. CHRISTOPHER EDGAR, Auteur ; Lisa BLASKEY, Auteur ; Ragini VERMA, Auteur ; Timothy P. L. ROBERTS, Auteur Article en page(s) : p.444-460 Langues : Anglais (eng) Mots-clés : Autism Magnetoencephalography (MEG) Resting-state Connectivity Complexity Synchronization likelihood (SL) Multi-scale entropy (MSE) Index. décimale : PER Périodiques Résumé : Examination of resting state brain activity using electrophysiological measures like complexity as well as functional connectivity is of growing interest in the study of autism spectrum disorders (ASD). The present paper jointly examined complexity and connectivity to obtain a more detailed characterization of resting state brain activity in ASD. Multi-scale entropy was computed to quantify the signal complexity, and synchronization likelihood was used to evaluate functional connectivity (FC), with node strength values providing a sensor-level measure of connectivity to facilitate comparisons with complexity. Sensor level analysis of complexity and connectivity was performed at different frequency bands computed from resting state MEG from 26 children with ASD and 22 typically developing controls (TD). Analyses revealed band-specific group differences in each measure that agreed with other functional studies in fMRI and EEG: higher complexity in TD than ASD, in frontal regions in the delta band and occipital-parietal regions in the alpha band, and lower complexity in TD than in ASD in delta (parietal regions), theta (central and temporal regions) and gamma (frontal-central boundary regions); increased short-range connectivity in ASD in the frontal lobe in the delta band and long-range connectivity in the temporal, parietal and occipital lobes in the alpha band. Finally, and perhaps most strikingly, group differences between ASD and TD in complexity and FC appear spatially complementary, such that where FC was elevated in ASD, complexity was reduced (and vice versa). The correlation of regional average complexity and connectivity node strength with symptom severity scores of ASD subjects supported the overall complementarity (with opposing sign) of connectivity and complexity measures, pointing to either diminished connectivity leading to elevated entropy due to poor inhibitory regulation or chaotic signals prohibiting effective measure of connectivity. En ligne : http://dx.doi.org/10.1007/s10803-013-1915-7 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=258
in Journal of Autism and Developmental Disorders > 45-2 (February 2015) . - p.444-460[article] Joint Analysis of Band-Specific Functional Connectivity and Signal Complexity in Autism [Texte imprimé et/ou numérique] / Yasser GHANBARI, Auteur ; Luke BLOY, Auteur ; J. CHRISTOPHER EDGAR, Auteur ; Lisa BLASKEY, Auteur ; Ragini VERMA, Auteur ; Timothy P. L. ROBERTS, Auteur . - p.444-460.
Langues : Anglais (eng)
in Journal of Autism and Developmental Disorders > 45-2 (February 2015) . - p.444-460
Mots-clés : Autism Magnetoencephalography (MEG) Resting-state Connectivity Complexity Synchronization likelihood (SL) Multi-scale entropy (MSE) Index. décimale : PER Périodiques Résumé : Examination of resting state brain activity using electrophysiological measures like complexity as well as functional connectivity is of growing interest in the study of autism spectrum disorders (ASD). The present paper jointly examined complexity and connectivity to obtain a more detailed characterization of resting state brain activity in ASD. Multi-scale entropy was computed to quantify the signal complexity, and synchronization likelihood was used to evaluate functional connectivity (FC), with node strength values providing a sensor-level measure of connectivity to facilitate comparisons with complexity. Sensor level analysis of complexity and connectivity was performed at different frequency bands computed from resting state MEG from 26 children with ASD and 22 typically developing controls (TD). Analyses revealed band-specific group differences in each measure that agreed with other functional studies in fMRI and EEG: higher complexity in TD than ASD, in frontal regions in the delta band and occipital-parietal regions in the alpha band, and lower complexity in TD than in ASD in delta (parietal regions), theta (central and temporal regions) and gamma (frontal-central boundary regions); increased short-range connectivity in ASD in the frontal lobe in the delta band and long-range connectivity in the temporal, parietal and occipital lobes in the alpha band. Finally, and perhaps most strikingly, group differences between ASD and TD in complexity and FC appear spatially complementary, such that where FC was elevated in ASD, complexity was reduced (and vice versa). The correlation of regional average complexity and connectivity node strength with symptom severity scores of ASD subjects supported the overall complementarity (with opposing sign) of connectivity and complexity measures, pointing to either diminished connectivity leading to elevated entropy due to poor inhibitory regulation or chaotic signals prohibiting effective measure of connectivity. En ligne : http://dx.doi.org/10.1007/s10803-013-1915-7 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=258