Maria Giulia Preti
a Senior Scientist and Lecturer at the Neuro-X Institute, École Polytechnique Fédérale de Lausanne (EPFL)
Talk recording
Magnetic resonance imaging (MRI) provides rich information about brain function -from functional MRI- and structural connectomics -from diffusion MRI-, yet understanding the complex relationship between the two remains a major challenge in the field of network neuroscience. Recent advances in connectome harmonic decomposition extend classical signal processing concepts to graph domains, offering a novel perspective on this problem. In this talk, I will first introduce the methodological framework, then present my recent results in both healthy and clinical populations, and conclude with an outlook on open questions and future directions.
About the speaker
Maria Giulia Preti is a Senior Scientist and Lecturer at the Neuro-X Institute, École Polytechnique Fédérale de Lausanne (EPFL), Switzerland, and is also affiliated with the Department of Radiology and Medical Informatics at the University of Geneva, Switzerland. She received her M.S. degree in Biomedical Engineering (2009) and her Ph.D. degree in Bioengineering (2013) from Politecnico di Milano, Italy. During her Ph.D., she was a visiting student at the Massachusetts Institute of Technology and Harvard Medical School (Boston, USA), supported by a Progetto Rocca MIT-Italy Fellowship. She joined the Medical Image Processing Laboratory (EPFL) and the CIBM Center for Biomedical Imaging, Switzerland, as a post-doc in 2013, and became lecturer at University of Geneva in 2018. Her current research aims at investigating the relationship between brain function and structure by using advanced techniques of magnetic resonance imaging associated with network neuroscience and graph signal processing methods. In particular, her work involves functional MRI, functional connectivity analysis, diffusion tensor imaging and tractography, as well as the application of these methods to several clinical contexts, including epilepsy, Alzheimer's disease and mild cognitive impairment, multiple sclerosis, attention deficit hyperactivity disorder, and stroke.
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