Spectral signatures of damage in hierarchical modular network models of biosystems.

• Applicant: Privatdozent Paolo Moretti, Ph.D.
• Subject Area: Statistical Physics, Nonlinear Dynamics, Complex Systems, Soft and Fluid Matter, Biological Physics
• Term: since 2017
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 394689530

Biological systems often epitomize resilient behavior. A resilient system is able to cope with perturbation and damage, preserving its normal function. The complex, multi-scale network structure of biosystems is believed to be at the origin of such ability. Unlike techno-social systems, which are characterized by a backbone of highly connected hubs that maintains system-wide connectivity despite widespread random failures, living systems display a so-called hierarchical modular network structure. The hierarchical modular organization ensures that localized damage does not affect the standard function of the network at hand, and that it does not alter its functional differentiation/segregation. In network neuroscience, differentiation is associated with healthy brain function. In biological materials science, segregation is the essential phenomenon that promotes crack arrest and enhanced resilience, for instance in tendon and bone. An exhaustive, unified theory of network resilience for biosystems endowed with a hierarchical modular organization is still lacking. This project aims at filling this gap by providing an extensive numerical study of aspects of damage and its structural effects on hierarchical network models that may be of relevance in biosystems modelling, namely in the case of computational neuroscience and biomaterial failure. Using methods of spectral graph theory, we tackle the study of how damage locally affects the network layout in hierarchical systems, and how the properties of differentiation and segregation evolve as failure approaches. We apply this methodology both to computer generated networks and to experimental data of network connectivity in specific examples of resilient biosystems, namely brain networks, with the objective of developing efficient analysis tools that can be deployed in more general contexts of damage characterization and failure prediction.

• DFG Programme: Research Grants