Structural Target Controllability of Brain Networks in Dementia

Area of Science:

• Neuroscience
• Control Theory
• Network Science

Background:

• Aberrant cognitive functioning in Alzheimer's disease (AD) is linked to large-scale neural circuit dynamics.
• Understanding neurodegenerative disease evolution requires analyzing disease trajectory changes.
• Control theory offers tools to analyze brain network dynamics, patient-level disease evolution, and treatment responses.

Purpose of the Study:

• To apply target controllability to structural brain connectivity graphs in control (CN), mild cognitive impairment (MCI), and Alzheimer's disease (AD) subjects.
• To determine graph-theoretic conditions for structural target controllability in these brain networks.
• To identify specific brain nodes that can steer network states representative of transitions between CN, MCI, and AD.

Main Methods:

• Application of target controllability to structural MRI connectivity graphs.
• Analysis of graph-theoretic necessary and sufficient conditions for controllability.
• Identification of driver nodes using local topological information and structural target controllability.

Main Results:

• Structural target controllability can be verified using only local topological information of brain networks.
• Specific brain regions (nodes) were identified as drivers capable of steering network states.
• The study demonstrates the utility of target controllability in understanding node roles in brain network trajectories relevant to dementia progression.

Conclusions:

• Target controllability provides a novel method to describe node roles in controlling brain network trajectories.
• This approach is relevant for understanding the evolution of neurodegenerative diseases like Alzheimer's.
• The findings highlight the potential of control theory in analyzing brain connectomics and disease mechanisms.