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. 2025 Aug 1;26(1):174.
doi: 10.1186/s10194-025-02122-z.

Network control theory uncovers aberrant connectome controllability in trigeminal neuralgia

Tiantian Chu  1 , Juan Peng  2 , Feng Gao  1 , Fei Xiong  3 , Ye Tu  4
Affiliations

Network control theory uncovers aberrant connectome controllability in trigeminal neuralgia

Tiantian Chu et al. J Headache Pain. .

Abstract

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.

Keywords: Brain networks; Controllability; Diffusion tensor imaging; Network control theory; Structural connectivity; Trigeminal neuralgia.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
The flowchart for the selection of participants. TN, trigeminal neuralgia; HC, healthy control; MRI, magnetic resonance imaging
Fig. 2
Fig. 2
The calculation basis of different levels of controllability. Whole-brain controllability was calculated as the mean controllability across all brain regions. Network-level controllability was defined as the mean controllability of nodes within each network. Regional-level controllability was then calculated as the value of each node
Fig. 3
Fig. 3
Differences in controllability between the TN patients and HCs. The dotted lines denote the median and quartile, and * indicates a significant difference between groups (*P < 0.05). The P values were obtained by controlling for age and sex and correcting by multiple comparisons. TN, trigeminal neuralgia; HC, healthy control; DAN, dorsal attention network; DMN, default mode network; SUB, subcortical regions
Fig. 4
Fig. 4
Associations between average controllability and age. The P values are corrected by multiple comparisons. TN, trigeminal neuralgia; HC, healthy control; VN, visual network; DAN, dorsal attention network; VAN, ventral attention network; FCN, frontoparietal control network; DMN, default mode network; SUB, subcortical regions
Fig. 5
Fig. 5
Associations between modal controllability and age. The P values are corrected by multiple comparisons. TN, trigeminal neuralgia; HC, healthy control; VN, visual network; DAN, dorsal attention network; VAN, ventral attention network; FCN, frontoparietal control network; DMN, default mode network; SUB, subcortical regions
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