Flexible modularity in the human brain: How network architecture reconfigures over time

Area of Science:

• Neuroscience
• Network Science
• Computational Biology

Background:

• Human brain networks feature modular organization with densely interconnected subsystems and sparser between-module connections.
• Brain modularity is dynamic, reconfiguring across timescales from seconds (cognition) to years (development, aging), and is altered in neuropathology.
• Inconsistent empirical findings arise because similar global modularity values can result from different underlying network reorganizations.

Purpose of the Study:

• To synthesize evidence across cognition, learning, and lifespan research to reframe modularity change.
• To propose a unifying framework for understanding flexible modularity as a repertoire of timescale-dependent reconfiguration modes.
• To demonstrate the applicability of this framework to neuropathological conditions.

Main Methods:

• Systematic synthesis of empirical findings from cognitive, learning, lifespan, and neuropathology research.
• Development of a conceptual framework categorizing modularity changes into distinct reconfiguration modes.
• Relating these modes to biological mechanisms and constraints.

Main Results:

• Brain modularity change is best understood as a repertoire of timescale-dependent reconfiguration modes, not a single scalar property.
• Key reconfiguration modes include transient integration, selective decoupling and stabilization, and slow long-term rebalancing.
• This framework extends to neuropathology, where damage and compensatory reorganization utilize the same reconfiguration modes.

Conclusions:

• Flexible modularity, understood through timescale-dependent reconfiguration modes, is a core principle of adaptive brain organization.
• This unifying framework resolves apparent inconsistencies in empirical findings across different domains.
• The framework provides a novel perspective for interpreting brain dynamics in health and disease.