Events Calendar

YINS Summer Seminar: Mehraveh Salehi

YINS Summer Seminar: Mehraveh Salehi

Event time: 
Wednesday, June 20, 2018 - 12:00pm
Yale Institute for Network Science See map
17 Hillhouse Avenue, 3rd floor
New Haven, CT 06511
Event description: 

“A submodular approach to the individualized human brain parcellation in multiple scales”

Speaker: Mehraveh Salehi

Summary: Recent studies on functional neuroimaging (e.g., fMRI) attempt to model the brain as a network. A conventional functional connectivity approach for defining nodes in the network is grouping similar voxels together, a method known as functional parcellation. The majority of previous work on human brain parcellation employs a group-level analysis by collapsing data from the entire population. While these methods hold great potential for improving our understanding of the brain functional organization, they ignore the large amount of inter-individual variability and uniqueness in connectivity. This is particularly relevant for patient studies or even developmental studies where a single functional atlas may not be appropriate for all individuals or conditions. In this talk, I will first present a recently developed individualized parcellation technique that utilizes submodular maximization of an exemplar-based utility function. Then, I will cover the predictive models that can estimate biological and cognitive characteristics of individuals (including sex and IQ) as well as their brain’s mental state, solely based on the features extracted from these individualized parcellations. Compared to traditional group-level parcellations, our submodular approach yields significant improvement in the predictive power of such models. This is a joint work with Amin Karbasi from Yale Institute of Network Science (YINS), Dustin Scheinost, and R. Todd Constable from Yale Magnetic Resonance Research Center (MRRC).

Speaker Bio: Mehraveh Salehi is a Ph.D. candidate in Electrical Engineering department at Yale University. She earned her Bachelor degree in Electrical Engineering from Sharif University of Technology, Tehran, Iran. Her research lies at the intersection of statistical machine learning and computational neuroscience. She is interested in developing models that relate human behavior to individual brain connectivity patterns using optimization and machine learning techniques. She has received a number of awards including the Young Scientist Award from the International Conference on Medical Image Computing and Computer Assisted Intervention 2017 (MICCAI), and the best poster award from the BioImaging Sciences Retreat 2018. She is also the recipient of Tananbaum Fellowship, Advanced Graduate Leadership Program (AGLP) Fellowship, and CRA-Women Graduate Fellowship.