Share Email Print

Proceedings Paper

Determining driver nodes in dynamic signed biological networks
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Leader-follower controllability in brain networks which are affected neurodegenerative diseases can provide important biomarkers relevant for disease evolution. The brain network is viewed as a dynamic system where the nodes interact via neighbor-based Laplacian feedback rules. The network has cooperative connections between the nodes described by positive weights along with competitive connections which are described by negative connection weights. The nodes take the role of either leaders or followers, thus forming a leader-follower signed dynamic graph network. The results of this analysis can be easily generalized on unsigned brain networks. We apply the leader-follower concept to structural and functional brain networks with neurodegenerative diseases (dementia) and show that the found leaders represent important biomarkers for disease evolution. In other words, the leader nodes drive the network towards deteriorating cognitive states.

Paper Details

Date Published: 2 May 2019
PDF: 8 pages
Proc. SPIE 11020, Smart Biomedical and Physiological Sensor Technology XVI, 110200A (2 May 2019); doi: 10.1117/12.2519550
Show Author Affiliations
Amirhessam Tahmassebi, Florida State Univ. (United States)
Behshad Mohebali, Florida State Univ. (United States)
Lisa Meyer-Baese, Georgia Institute of Technology (United States)
Philip Solimine, Florida State Univ. (United States)
Katja Pinker, Florida State Univ. (United States)
Medical Univ. of Vienna (Austria)
Memorial Sloan-Kettering Cancer Ctr. (United States)
Anke Meyer-Baese, Florida State Univ. (United States)

Published in SPIE Proceedings Vol. 11020:
Smart Biomedical and Physiological Sensor Technology XVI
Brian M. Cullum; Douglas Kiehl; Eric S. McLamore, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?