February 3, 2023 

Dr. Kendrick Kay

Associate Professor, Department of Radiology, University of Minnesota

What is the Natural Scenes of fMRI Dataset and What is it Good for?

March 3, 2023

Dr. Morgan Barense

Professor, Department of Psychology, University of Toronto

Memory and Perception in the Medial Temporal Lobe: Cognitive Process versus Representational Content

April 7, 2023

Dr. Jessica Cantlon

Associate Professor, Department of Psychology, Carnegie Mellon University

What makes human logic unique

September 1, 2023

Dr. Richard Betzel

Associate Professor, Department of Psychology and Brain Sciences, Indiana University

Edge-centric connectomics

Abstract: Network neuroscience is built atop a network model in which cells, populations, and regions are linked to one another via anatomical or functional connections. Historically, this model has been approached from a node-centric perspective, emphasizing features of neural elements: the number of connections they make, their centrality, module affiliation, etc. However, brain networks can also be examined from an edge-centric perspective that explicitly focuses on properties of connections: their material and metabolic costs, the generative processes that govern connection formation, and their dynamics across time. In this talk, I will present results from several recent papers and highlight findings and advantages of edge-centric network perspectives compared with traditional node-centric network representations.

Watch Dr. Betzel's seminar

October 6, 2023

Dr. Gagan Wig

Associate Professor, Center for Vital Longevity, University of Texas, Dallas

Brain aging across space and time: Using network science to chart disparities in brain health & assess Alzheimer’s Disease risk & resilience

Abstract: Is aging-related cognitive decline a consequence of brain network failure? I will highlight efforts from my lab that have helped to develop and incorporate tools from network science to further our understanding of how the brain’s large-scale functional network organization changes across the lifespan. This work is revealing that functional brain network organization relates to an individual’s cognitive ability during healthy adulthood, and that brain network changes are uniquely prognostic of cognitive impairment (independent of structural atrophy and neuropathology). Our more recent observations have demonstrated that an individual’s environmental exposures exert an impact on their trajectory of brain network decline, which indicates that brain network organization can be used to measure disparities in brain health.  Finally, I will touch on our initial steps towards developing non-human animal models of aging-related brain network changes, which we are pursuing in order to bridge the human aging work with efforts in other species. Collectively, these observations are offering a new perspective towards understanding healthy and pathological aging, spotlight a path for discovering vulnerabilities of brain aging that are linked to an individual’s past and present environmental exposures, and are catalyzing the development of a novel class of precision health measures which are based on patterns of large-scale brain network organization.

Watch Dr. Wig's seminar

November 3, 2026

Dr. Marvin Chun

Richard M. Colgate Professor, Department of Psychology, Yale University

Personalized brain imaging to predict individual performance and dysfunction

Abstract: Personalized brain imaging can estimate a person’s human brain activity and relate it to their behavior and dysfunction.  From functional magnetic resonance imaging (fMRI) scans, we can estimate an individual’s fluid intelligence, ability to focus, and memory skills.  We can also diagnose dysfunction such as attention deficits and memory problems; other labs use our methods to study depression, anxiety, schizophrenia, and other clinical conditions.  As a next step, we are extending our methods to predict future improvement or decline in cognitive function.