AI
20 Feb

Multi-scale Network Neuroscience

February 20, 2026 In-person
1:00 PM 3:30 PM
School of Data Science, 1919 Ivy Road, Room 205
Richard Betzel from University of Minnesota. Talk on February 20, 2026 begins at 1 p.m. until 2 p.m. To be held in the School of Data Science, Room 205.

Connectomes are comprehensive maps of the wiring within nervous systems, representing connections from the cellular and synaptic level (on the nanometer scale) to large-scale brain areas (on the centimeter scale). Network neuroscience focuses on modeling and analyzing these connectomes. While the primary goal of network neuroscience—understanding the principles of connectome organization and its impact on brain function—remains consistent across different scales, specific scientific questions often require examining particular spatial levels. For instance, exploring the relationship between clinical outcomes and connectome organization in humans currently requires analysis at the areal level. In my talk, I will present several ongoing research projects from my lab that span multiple scales of network neuroscience. These include nanoscale connectome analyses from model organisms such as C. elegans, Drosophila, and zebrafish, as well as large-scale functional MRI studies. I will conclude with a discussion of key open questions and challenges in the field, along with potential directions for advancing the discipline. 

Dr. Rick Betzel studied physics at Oberlin College, earned a PhD in psychological and brain sciences at Indiana University, Bloomington with Dr. Olaf Sporns and completed a postdoc at the University of Pennsylvania with Dr. Dani Bassett. In 2018, he founded the Brain Networks and Behavior Lab at Indiana University. In 2024 Dr. Betzel moved his lab to the University of Minnesota, Twin Cities where he is currently an associate professor in the Department of Neuroscience and Scientific Director at the Masonic Institute for the Developing Brain and Center for Developmental Neuroimaging. Dr. Betzel's current research focuses on applications of network science to brain data with the overarching aim of understanding how the architecture of biological neural networks helps to support brain function and behavior in health and disease. 

Research / Artificial Intelligence / Neuroscience / Health and Medicine