Abstract: Spatial visualization is a core component of spatial cognition. Compared with traditional cognitive training, novel interventions that integrate physical activity with cognitive processing offer new directions for enhancing special visualization, particularly for individuals with poor spatial ability. However, there is currently a lack of behavioral and neural evidence empirically assessing the effectiveness of these interventions.
The aim of this study was to investigate the facilitative effects and neuroplasticity mechanisms of virtual reality (VR)-based motor-cognitive dual-task training on the spatial visualization ability of individuals with poor spatial ability. A two-factor mixed experimental design was adopted with four groups (VR motor-cognitive dual-task, VR motor, VR cognitive, control) and two time points (pre- and post-intervention). Using the Santa Barbara Sense of Direction Scale (SBSOD), 120 college students with poor spatial ability (SBSOD < 3) were screened and randomly assigned to one of the four groups (n = 30 each). All intervention groups underwent an 8-week training program. Spatial visualization ability was measured using a mental rotation task, while functional near-infrared spectroscopy (fNIRS) was used to record changes in prefrontal-parietal network activation before and after the intervention. A random forest machine learning model was then applied to identify the discriminative features of the neural patterns.
The key findings were as follows: (1) At the behavioral level, the VR dual-task group significantly outperformed the other three groups on post-test measurements of spatial visualization. No significant difference was observed between the two single-task training groups, but both performed significantly better than the control group. (2) At the neural level, the VR dual-task group exhibited the highest neural efficiency, with significantly lower activation levels in the left frontopolar area (L-FPA) and right primary motor cortex (R-M1) after the intervention compared with the other three groups. Those in the dual-task group also showed the greatest reduction in activation from pre- to post-test. In contrast, although the right frontopolar area showed significantly lower activation in all three intervention groups relative to the control group, no significant differences were observed among the three intervention groups. (3) The machine learning model further validated that the neural activity patterns of the VR motor-cognitive dual-task group were highly separable from those of the control group. Changes in R-M1 and L-FPA activity were the most discriminative features.
In conclusion, VR-based motor-cognitive dual-task training can significantly improve spatial visualization ability in individuals with poor spatial ability by synergistically optimizing neural efficiency in the prefrontal and motor cortices. This study provides multimodal evidence for the “body-cognition integration” theory and establishes a methodological foundation for precision intervention paradigms based on neural markers.

Key words: virtual reality, motor-cognitive dual-task training, poor spatial ability, spatial visualization, fNIRS, machine learning