SPS BISP Webinar: 4 October 2022, presented by Dr. Selin Aviyente

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SPS BISP Webinar: 4 October 2022, presented by Dr. Selin Aviyente

Upcoming SPS-BISP Webinar

Title: Multi-Frequency Functional Connectivity Networks of the Brain
Date: 4 October 2022
Time: 4:00 PM Eastern (New York time)
Duration: Approximately 1 Hour
Presenters: Dr. Selin Aviyente

 

Register for the Webinar

 

Abstract:

Over the past twenty years, functional connectivity of the human brain has been studied using tools from complex network theory. One such tool is community detection which  is  fundamental for uncovering the links between structure and function in complex networks. Existing network models of the brain focus on average activity within a time window of interest and a given frequency band. Therefore, they cannot capture the changes in network connectivity across time and different frequency bands. Recently, multilayer brain networks have attracted a lot of attention as they can capture the full view of  neuronal connectivity. In this talk, I will first give an overview on the construction of multilayer functional connectivity networks, where each layer corresponds to a different frequency band. I will then introduce a multilayer community detection algorithm by extending the definition of modularity to multilayer networks. The proposed approach is applied to electroencephalogram (EEG) data collected during a study of error monitoring in the human brain, where the differences between the communities formed within and across different frequency bands and response types are studied.

Biography:

Selin Aviyente

Dr. Selin Aviyente received the B.S. degree with high honors in electrical and electronics engineering from Bogazici University, Istanbul, in 1997. She received the M.S. and Ph.D. degrees, both in electrical engineering: systems, from the University of Michigan, Ann Arbor, in 1999 and 2002, respectively.

She joined the Department of Electrical and Computer Engineering (ECE) at Michigan State University in 2002, where she is currently a Professor. Since 2017, she has also been serving as the Associate Chair for Undergraduate Studies in the ECE department. Her research focuses on statistical and nonstationary signal processing, higher-order data representations, and complex network analysis with applications to neuronal signals. In particular, she has made significant contributions to the theory and application of time-frequency analysis, transform-based sparse-feature extraction and classification, and signal and information processing over networks. Apart from pursuing fundamental research to develop better and more powerful data science tools, she has also worked on using existing tools to define and solve new problems, particularly in the area of brain connectomics. Her most recent work focuses on the study of the dynamic functional networks in the brain using EEG and fMRI. She has authored more than 150 peer-reviewed journal and conference papers.

Dr. Aviyente is the recipient of a 2005 Withrow Teaching Excellence Award and a 2008 NSF CAREER Award.  She is currently serving on several technical committees of IEEE Signal Processing Society including the Signal Processing Theory and Methods and Bio-imaging and Signal Processing Technical Committees. She is an Associate Editor for IEEE Open Journal of Signal Processing and Digital Signal Processing.

 

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