El Centro de Investigación en Matemáticas A.C. (CIMAT) y el Instituto de Neurobiología de la UNAM (campus Juriquilla, Qro.) tienen el gusto de invitarlo a la XIX Reunión de Neuroimagen que se llevará a cabo en el CIMAT, Guanajuato, Gto. del 5 al 6 de Octubre del 2017.
Para la XIX Reunión de Neuroimagen se aceptarán trabajos para presentación en el formato de ponencia y carteles, que serán incluidos en las memorias electrónicas del evento.
Neuroimaging and network analysis of epilepsy and autism: integrating tissue microstructure with macrolevel connectomics
Dr. Boris Bernhardt
Montreal Neurological Institute and Hospital
Mining developmental disorders: Pinpointing origins, and understanding cascades
Dr. John Lewis
McGill University , Montréal, McConnell Brain Imaging Centre
Abstract: Efforts to differentiate individuals with some condition from typical controls have been made wherever there is data. Much of this is from adults or adolescents with a developmental disorder. But, as has been suggested, the key to understanding developmental disorders is development itself. Thus data mining in such cases must be seen as analogous to gold mining in the river of development. Findings late in development are of limited interest; we are after the motherlode. I present results from a longitudinal study of infants at high familial risk for developing autism, which attempts to pinpoint when and where in the brain the first abnormalities appear. I then relate these original abnormalities to the brain overgrowth seen in toddlers with autism, and to the under-connectivity seen in adults with autism.
Beyond Fiber Orientations : Microstructure Informed Tractography
Dr. Gabriel Girard
Signal Processing Lab, école Polytechnique Fédérale de Lausanne, Suiza
Abstract: Diffusion-weighted (DW) magnetic resonance imaging (MRI) can measure the orientation of the white matter structure of the brain, in vivo. From the voxel-wise tissue orientations, tractography algorithms can estimate white matter fascicles volume and position. Recent studies have shown that tractography algorithms can fail to recover some existing fascicles and in some cases, produce a large incidence of false positives, biasing the structural connectivity analysis. The false positive connections are largely due to complex tissue configurations of the white matter (e.g. crossing, kissing or merging). Moreover, the relationship between the tractography reconstruction and the underlying white matter microstructure characteristics remains poorly understood. Recently, tractography methods have been proposed to reduce the rate of false positives by taking full advantage of the development DW-MRI microstructure acquisition, modeling and reconstruction techniques. Those methods, called microstructure informed tractography, uses prior information on the microstructure properties of neuronal tissue to reduce ambiguities and separate fascicles in area of complex tissue configurations. Simultaneously, microstructure informed tractography allows the characterization of the white matter tissue microstructure along fascicles. Those emerging techniques are paving the way to quantitative brain structural connectivity analysis.
El Comité Organizador
Dr. Rolando Biscay, CIMAT
Dr. Jorge Bosch, INB-UNAM
Dr. Luis Concha, INB-UNAM
Dr. Ivan Cruz, CIMAT
Dr. Oscar Dalmau, CIMAT
Dr. Thalía Harmony, INB-UNAM
Dr. José Luis Marroquín, CIMAT
Dr. Alonso Ramírez, CIMAT