Date: Friday, September 30, 2022

Time: 11:00 a.m.

Virtual: View meeting instructions below

Speaker: Richard Betzel

Speaker’s Title: Assistant Professor, Psychological and Brain Sciences, Indiana University Bloomington

Seminar Title: Edge-centric connectomics 

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.

Biosketch: Undergraduate in Physics at Oberlin College, Ohio. PhD at Indiana University in psychological and brain sciences/cognitive science with Olaf Sporns. Postdoc at University Pennsylvania in Bioengineering with Danielle Bassett. Started the “brain networks and behavior lab” at Indiana University in 2018. Our aim is to characterize the architecture of macro-scale brain networks and understand its roles in cognition/disease/development.

Twitter: @richardfbetzel 
Website: https://www.brainnetworkslab.com/

Recommended Article:

• Zamani Esfahlani, F., Jo, Y., Faskowitz, J., Byrge, L., Kennedy, D. P., Sporns, O., & Betzel, R. F. (2020). High-amplitude cofluctuations in cortical activity drive functional connectivity. Proceedings of the National Academy of Sciences, 117(45), 28393-28401. Link to Paper
• Faskowitz, J., Esfahlani, F. Z., Jo, Y., Sporns, O., & Betzel, R. F. (2020). Edge-centric functional network representations of human cerebral cortex reveal overlapping system-level architecture. Nature neuroscience, 23(12), 1644-1654. Link to Paper

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