Brain Network Dynamics and Multiscale Modelling of Neurodegenerative Disorders: A Review

TL;DR

This review discusses the challenges and advances in multiscale brain network modelling for neurodegenerative disorders, emphasizing the role of data-driven methods and the importance of understanding disease mechanisms for therapy development.

Contribution

It provides a comprehensive overview of current modelling techniques, highlighting the integration of multiscale models and data-driven approaches in understanding NDDs like AD and PD.

Findings

Large-scale brain network models elucidate disease mechanisms.

Data-driven approaches improve model validation.

Multiscale models offer insights into therapeutic targets.

Abstract

It is essential to understand the complex structure of the human brain to develop new treatment approaches for neurodegenerative disorders (NDDs). This review paper comprehensively discusses the challenges associated with modelling the complex brain networks and dynamic processes involved in NDDs, particularly Alzheimer's disease (AD), Parkinson's disease (PD), and cortical spreading depression (CSD). We investigate how the brain's biological processes and associated multiphysics interact and how this influences the structure and functionality of the brain. We review the literature on brain network models and dynamic processes, highlighting the need for sophisticated mathematical and statistical modelling techniques. Specifically, we go through large-scale brain network models relevant to AD and PD, highlighting the pathological mechanisms and potential therapeutic strategies investigated in the literature. Additionally, we investigate the propagation of CSD in the brain and its implications for neurological disorders. Furthermore, we discuss how data-driven approaches and artificial neural networks refine and validate models related to NDDs. Overall, this review underscores the significance of coupled multiscale models in deciphering disease mechanisms, offering potential avenues for therapeutic development and advancing our understanding of pathological brain dynamics.