Internet-like brain hierarchical network model: Alzheimer's disease study as an example

Area of Science:

• Neuroscience
• Network Science
• Computational Biology

Background:

• Hierarchical structure is a key feature of complex networks, including brain networks.
• Previous research has primarily focused on temporal scales, with limited investigation into spatial hierarchical organization of brain networks.
• The application of spatial hierarchical analysis in brain networks requires further exploration.

Purpose of the Study:

• To propose a novel Internet-like brain hierarchical network (IBHN) model for analyzing spatial hierarchical organization in brain networks.
• To apply the IBHN model to a case-control study of Alzheimer's disease (AD) to assess its utility.
• To investigate alterations in functional connectivity at different hierarchical levels in AD patients.

Main Methods:

• Developed the Internet-like brain hierarchical network (IBHN) model, partitioning brain networks into Brain-WAN, Brain-MAN, and Brain-LAN levels.
• Employed a multivariate analysis method to assess overall functional connectivity between brain networks at the same hierarchical level.
• Applied the IBHN model to a dataset of 64 AD patients and 75 healthy controls.

Main Results:

• The IBHN model identified significantly enhanced functional connectivity at the Brain-WAN level in AD patients (P<0.05).
• Reduced functional connectivity was observed at the Brain-LAN level in AD patients (P=0.004).
• These findings suggest that altered hierarchical functional connectivity patterns can serve as multi-dimensional biomarkers for AD diagnosis.

Conclusions:

• The proposed IBHN model effectively demonstrates altered hierarchical functional connectivity in Alzheimer's disease.
• The study provides insights into AD pathophysiology through a multi-level analysis of brain network organization.
• The IBHN model offers a novel perspective for exploring the functional organization of complex brain networks.