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Generative Models of Brain Networks (DSI-SRP)

Posted by on Thursday, August 1, 2019 in Completed Research, DSI-SRP, Engineering, School of Engineering.

This DSI-SRP fellowship funded Evan Rothchild to work in the laboratory of Professor Mikail Rubinov in the Department of Biomedical Engineering during the summer of 2019. Evan graduated in 2020 with a major in Biomedical Engineering.

The project funded by this fellowship aimed to understand how brain networks promises to help us better understand the principles of brain organization. Unbiased sampling of brain networks with pre-specified constraints is an important component of this study. Network sampling generates surrogate data and allows to test new results against null hypotheses. This project used machine learning methods to generate surrogate data sets with several combinations of constraints. There were two primary goals for this project. The first goal was to investigate the use of neural network type algorithms to create null models. The second was to use these null models to observe properties that emerge as a result of the pre-specified constraints. This project served as Evan’s Biomedical Engineering Honors Thesis. Evan worked on this project throughout his senior year at Vanderbilt. As part of this project, Evan successfully generated network null models with several combination of constraints. The algorithm he developed has potential to be a new, faster and more flexible way to generate brain-network null models.

In addition to receiving support through a DSI-SRP fellowship, this project was supported and facilitated by the DSI Data Science Team through their regular summer workshops and demo sessions.

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