Electrical and Computer Engineering
Johns Hopkins University

“Generative Models to Decode Brain Pathology”

Abstract: Clinical neuroscience is a field with all the difficulties that come from high dimensional data, and none of the advantages that fuel modern-day breakthroughs in computer vision, automated speech recognition, and health informatics. It is a field of unavoidably small datasets, due to the costly acquisitions and environmental confounds, massive patient variability, and an arguable lack of ground truth information. My lab tackles these challenges by combining analytical tools from signal processing and machine learning with hypothesis-driven insights about the brain.

This talk will highlight three ongoing projects in my lab that span a range of methodologies and clinical applications. First, I will develop a joint optimization framework to predict clinical severity from resting-state fMRI data. Our model is based on two coupled terms: a generative non-negative matrix factorization and a discriminative linear regression. This project is part of our larger effort to better characterize heterogeneous patient cohorts. Next, I will describe a spatio-temporal model to track the spread of epileptic seizures from EEG data. Unlike conventional approaches, our model relies on a latent network structure that captures the hidden state of each EEG channel; the latent variables are complemented by an intuitive likelihood model for the observed neuroimaging measures. This project takes the first steps toward noninvasive seizure localization. Finally, I will highlight a very recent initiative in my lab to manipulate emotional cues in human speech. Our long-term goal is to create a naturalistic therapy for autism.

Biography: Archana Venkataraman is a John C. Malone Assistant Professor in the Department of Electrical and Computer Engineering at Johns Hopkins University. She directs the Neural Systems Analysis Laboratory and is a core faculty member of the Malone Center for Engineering in Healthcare. Dr. Venkataraman’s research lies at the intersection of multimodal integration, network modeling and clinical neuroscience. Her work has yielded novel insights in to debilitating neurological disorders, such as autism, schizophrenia and epilepsy, with the long-term goal of improving patient care. Dr. Venkataraman completed her B.S., M.Eng. and Ph.D. in Electrical Engineering at MIT in 2006, 2007 and 2012, respectively. She is a recipient of the CHDI Grant on network models for Huntington’s Disease, the MIT Lincoln Lab campus collaboration award, the NIH Advanced Multimodal Neuroimaging Training Grant, the National Defense Science and Engineering Graduate Fellowship, the Siebel Scholarship and the MIT Provost Presidential Fellowship.

Host: Xian Du, Dept of Mechanical and Industrial Engineering