Network dynamics under neuronal degradation: A comparison between modular and small-world topologies

The human brain exhibits a complex organization that combines local segregation with global integration, typically characterized by modular structure and small-world topology. Structural alterations such as demyelination and neuronal loss disrupt this architecture and impair neural signal transmission. The specific contribution of network topology to the resulting functional decline, however, remains unclear. This study aims to investigate how network topology influences the resilience and functional degradation of neural systems under progressive damage.

Two network models subjected to progressive demyelination and neuronal loss are compared. One model is modular and locally organized, and the other is characterized by stronger global integration and small-world properties. The metrics analyzed here are mean firing rate, responder fraction, conditional latency, and penalized latency.

Numerical simulations reveal gradual, diffuse degradation in the small-world network and topology-dependent functional transitions in the modular network. Across damage levels, the small-world topology maintains higher temporal efficiency and neuronal recruitment, and the modular topology exhibits larger variability and sharper functional transitions.

These results indicate that the network topology modulates the pattern of functional deterioration in demyelinating processes, offering insight into the heterogeneous progression of disorders such as multiple sclerosis.