Network control theory uncovers aberrant connectome controllability in trigeminal neuralgia.

Background: Trigeminal neuralgia (TN) involves complex neural network alterations beyond the trigeminal system. Network Control Theory (NCT) offers a novel framework to quantify how brain network architecture constrains neural dynamics. This study investigated structural network controllability in TN to elucidate disease-specific alterations in brain network control properties.

Methods: Eighty-two TN patients and 42 healthy controls (HCs) underwent diffusion tensor imaging. Structural connectomes were constructed using deterministic tractography and parcellated with the Brainnetome atlas. Average controllability (AC), reflecting the ease of driving networks toward accessible states, and modal controllability (MC), indicating the capacity for difficult state transitions, were calculated at whole-brain, network, and regional levels. Age-related effects on controllability were examined.

Results: TN patients demonstrated significantly reduced whole-brain AC (P = 0.009) and increased MC (P = 0.009) compared to HCs. Network-level analyses revealed decreased AC and increased MC in the dorsal attention network (P = 0.018) and default mode network (P = 0.009), with reduced AC in subcortical regions (P = 0.041). No regional differences survived False Discovery Rate correction. Notably, controllability metrics correlated significantly with age in TN patients across multiple networks, whereas HCs showed no age-related correlations. Neither pain laterality nor neurovascular compression influenced controllability patterns.

Conclusions: TN is characterized by aberrant network controllability, manifesting as reduced efficiency in routine state transitions and increased energy requirements for network control. The unique age-controllability relationship in TN suggests disease-specific alterations in network dynamics distinct from normal aging. These findings establish NCT as a valuable framework for understanding TN pathophysiology and highlight the disorder's network-level rather than focal nature.