Biostatistics and Medical Informatics Seminar with Moo Chung, BMI, UW-Madison
Topological Inference and Learning for Cycles in Graphs
Friday, October 7, 2022
In this talk, we propose an efficient algorithm for the systematic identification of cycle basis using the Hodge Laplacian and persistent homology. In the vector space of cycles, we can perform regression and clustering. The method is applied to modeling human brain networks obtained from resting-state functional magnetic resonance imaging (MRI). We demonstrate the dynamic pattern of the state space in brain activity itself is a heritable trait for the first time.