Chu Tiantian, Peng Juan, Gao Feng, Xiong Fei, Tu Ye
Department of Anesthesiology, Hubei Key Laboratory of Geriatric Anesthesia and Perioperative Brain Health, and Wuhan Clinical Research Center for Geriatric Anesthesia, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Department of Ultrasound Imaging, Renmin Hospital of Wuhan University, Wuhan, China.
J Headache Pain. 2025 Aug 1;26(1):174. doi: 10.1186/s10194-025-02122-z.
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.
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.
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.
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.
三叉神经痛（TN）涉及三叉神经系统之外复杂的神经网络改变。网络控制理论（NCT）提供了一个新颖的框架来量化脑网络结构如何约束神经动力学。本研究调查了TN患者的结构网络可控性，以阐明脑网络控制特性中疾病特异性的改变。
82例TN患者和42名健康对照者（HCs）接受了扩散张量成像。使用确定性纤维束成像构建结构连接组，并根据脑网络图谱进行分割。在全脑、网络和区域水平计算平均可控性（AC），反映将网络驱动至可达状态的难易程度，以及模态可控性（MC），表示困难状态转换的能力。研究了年龄对可控性的影响。
与HCs相比，TN患者全脑AC显著降低（P = 0.009），MC增加（P = 0.009）。网络水平分析显示，背侧注意网络（P = 0.018）和默认模式网络（P = 0.009）的AC降低，MC增加，皮质下区域AC降低（P = 0.041）。经错误发现率校正后，未发现区域差异。值得注意的是，TN患者多个网络的可控性指标与年龄显著相关，而HCs未显示与年龄相关的相关性。疼痛侧别和神经血管压迫均未影响可控性模式。
TN的特征是异常的网络可控性，表现为常规状态转换效率降低以及网络控制的能量需求增加。TN中独特的年龄-可控性关系表明网络动力学存在疾病特异性改变，不同于正常衰老。这些发现确立了NCT作为理解TN病理生理学的有价值框架，并突出了该疾病的网络水平而非局灶性本质。
