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Manual therapy promotes prefrontal neural efficiency in chronic non-specific neck pain: An fNIRS-Based randomized
Qi Zhang1, Qing Liu2, Yan Huang3
1Anhui University of Chinese Medicine, Hefei, Anhui Province, 230031, China; Department of Rehabilitation Medicine, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui Province, 230031, China.
Background:
Chronic non-specific neck pain (CNP) involves central sensitization and maladaptive cortical reorganization. The central neurophysiological mechanisms underlying combined manual therapy (MT) and exercise remain poorly understood.
Objective:
To investigate the neurobiological synergy of MT and exercise on large-scale brain network restructuring and cortical adaptation in patients with CNP.
Methods:
Thirty patients with CNP were randomized to 6 weeks of MT plus exercise (combined group, n = 15) or exercise alone (n = 15), alongside 15 healthy controls. Clinical outcomes included the Visual Analogue Scale (VAS) and Neck Disability Index. Functional near-infrared spectroscopy (fNIRS) evaluated resting-state functional connectivity and task-state cortical hemodynamics.
Results:
Both groups demonstrated significant longitudinal improvements in pain and disability (e.g., VAS main time effect: F = 279.51, P < .001, ηp2 = 0.909, 95% confidence interval [2.50, 3.19]), with no significant group-by-time clinical interaction. However, neurobiological trajectories dissociated markedly. Only the combined intervention uniquely restored frontoparietal functional connectivity and induced a stimulation-preferential reduction in prefrontal activation (interaction: F = 27.19, P < .001, ηp2 = 0.493).
Conclusions:
While MT combined with exercise yields similar short-term clinical benefits as exercise alone, the combined therapy uniquely promotes prefrontal neural efficiency and restores frontoparietal network connectivity. This highlights MT's distinct central modulatory value in optimizing top-down cognitive resource allocation for CNP management.
