Challenges in the Visualization of Bioelectric Fields for Cardiac and Neural Research

The visualization of bioelectric fields has been an ongoing challenge to cardiac and neural researchers. Bioelectrical field data are heterogeneous and their interpretation often requires simultaneous interrogation of anatomical information with measured or simulated scalar, vector, and tensor fields. They may be volumetric or constrained to (obscuring) surfaces; and are usually time-dependent. To fully understand the spatiotemporal dynamics of the pathology under study, it is often necessary to integrate diverse formation across multiple scales, and to quantify and visualize the uncertainty associated with the data. Unfortunately, few visualization approaches are catered to the needs, conventions, and language of the applications, leading to a lack of widespread standards and use. Addressing these visualization challenges has potentially far-reaching benefits to both the understanding and diagnosis of a number of diseases.

The 90-minute spotlight session includes a single 30-minute plenary talk given by a domain scientist with experience in cardiac and neural analysis and visualization to outline the challenges facing the field. The plenary talk will be followed by three 15-minute talks from specialists from across the country who will outline their specific applications and visualization challenges.

Participants and Intended Audience

This application spotlight targets researchers in visualization and bioengineering.

Dr. Rob S. MacLeod - SCI Institute, University of Utah

Rob MacLeod was trained in physics, electrical engineering, and physiology & biophysics and is a full professor of Bioengineering and Internal Medicine (Cardiology) at the University of Utah. He is a co-founder and Associate Director of the Scientific Computing and Imaging (SCI) Institute and holds a similar position at the Nora Eccles Harrison Cardiovascular Research and Training Institute (CVRTI). He also co-founded the Consortium for ECG Imaging. He is Vice Chair and Director of the Undergraduate program in Biomedical Engineering. His research interests include computational electrocardiography with special interest in simulating bioelectric fields, e.g., from cardiac defibrillation and neuromodulation, and exploring new approaches for electrocardiographic imaging (ECGI) He also uses experimental investigation and clinical approaches to improve management of ventricular and atrial arrhythmias and acute myocardial ischemia. For his research, he uses a broad range of techniques including scientific computing, imaging, image and signal processing, and visualization.

Dr. Sumientra Rampersad - Northeastern University

Sumientra Rampersad is a Research Assistant Professor of Electrical and Computer Engineering at Northeastern University in Boston. She was trained in biochemistry, biophysics, neuroscience and biomedical engineering, and received a PhD in Medical Sciences. Her main research goals are to better understand the working mechanisms behind noninvasive brain stimulation in humans and to improve its application. For her research, she uses finite element simulations with detailed human head models, and experiments with healthy volunteers, for which she uses cognitive tests, transcranial magnetic stimulation (TMS) and electroencephalography (EEG) to measure stimulation effects. She focuses on transcranial current stimulation (tCS), including direct (tDCS), alternating (tACS) and temporal interference (tTIS) stimulation, but her research projects include TMS, electrocortigraphy (ECoG) and stereoelectroencephalography (SEEG). She is especially interested in bridging the gap between models and experiments in noninvasive brain stimulation through model-based experiments that have the potential to improve experimental outcomes as well as modeling techniques.

Dr. Andrew Janson - Vanderbilt University

Andrew Janson was trained in biomedical engineering and computer science and is a post-doctoral research fellow at the Vanderbilt University Institute of Imaging Science (VUIIS). His research interests include computational neuroscience and surgical interventions (e.g. deep brain stimulation and tissue resection) for the treatment of neurological disorders, such as traumatic brain injury and epilepsy. The focus of his work is to improve surgical decision making and to guide long-term patient management through the use and visualization of bioelectric field simulations integrated with functional and structural magnetic resonance imaging. He investigates novel surgical targets and image-based biomarkers to adapt surgical interventions on a patient-specific basis to improve the chances of providing a successful therapy that improves patient quality of life.

Tentative Schedule