Objective This study employed functional near-infrared spectroscopy (fNIRS) to systematically compare the effects of active movement (AM), passive movement (PM), and motor imagery (MI) on sensorimotor cortex excitability across three dimensions: spatial distribution, activation intensity, and temporal dynamics, thereby revealing distinct neural mechanisms underlying different motor therapies. Materials and methods Sixteen healthy participants performed AM, PM, and MI tasks under therapist guidance using a block design. fNIRS data covered bilateral primary motor cortex (M1), primary somatosensory cortex (S1), supplementary motor area (SMA), dorsolateral prefrontal cortex (DLPFC), and frontopolar area (FPA). Analytical metrics included: (1) Spatial features: mean Δ [HbO] during 0–30s time windows; (2) Activation intensity: generalized linear model (GLM)-fitted Δ[HbO] during 0–30s; (3) Temporal dynamics: slope values during 2–7 s and T-centroid values during 0–60s. Results Spatially, MI demonstrated the most extensive activation (bilateral DLPFC, SMA, M1, and left FPA; all p < 0.05, FDR-corrected), followed by AM (bilateral DLPFC, M1, and left FPA), while PM showed more limited activation (bilateral DLPFC, left S1, and right FPA). In activation intensity, AM exhibited significantly stronger activation than PM and MI in DLPFC channels 27 and 29 (both p < 0.05, uncorrected). Temporally, AM showed steeper slopes in left DLPFC channel 27 ( F = 10.31, p = 0.034, FDR-corrected), while MI demonstrated faster responses in right S1 and SMA (both p = 0.03, FDR-corrected), with both PM and MI responding faster than AM in left FPA ( p = 0.03, FDR-corrected). Conclusion These findings reveal therapy-specific neural mechanisms: MI broadly engages motor execution and cognitive control networks through mental simulation, AM predominantly activates motor execution networks with DLPFC dominance, and PM recruits sensory-attentional networks via external facilitation. The multidimensional neuroimaging evidence provides a foundation for personalized rehabilitation protocols.
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Xue et al. (2025) studied this question.
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