Motor-cognitive integrated rehabilitation has proved effectiveness in patients with central nervous system disorders, including stroke. However, the dynamic interactions among brain regions that underlie these benefits are not well understood, and quantitative characterization of network-level interaction effects related to motor-cognitive function is essential for understanding and optimizing rehabilitation interventions. This paper presents a brain functional connectivity analysis method based on optimal-transport subnetworks to extract explainable motor-cognitive neural features from EEG signals. First, the experimental paradigm of grip force control with and without visual feedback was designed, during which EEG and grip force data were recorded simultaneously. Then, the functional connectivity matrix was constructed based on phase locking values and the most critical node connections were selected by the Kruskal algorithm, producing the optimal transport subnetwork with a refined network representation. Further, intra-and inter-ROI connectivity strength features were extracted by combining the optimal subnetwork with sliding task windows, enabling analysis of the grip force control mechanism and quantification of the dynamic changes of brain functional connectivity across different task stages. Fifteen subjects were recruited in the experiment, and the results demonstrated that visual feedback significantly enhanced specific intra-and inter-regional functional connectivity, with distinct enhancement patterns at different stages. In the preparation stage, high-frequency signals enhanced the connectivity within the prefrontal cognitive area. In the initiation stage, low-frequency oscillations enhanced coupling among the occipital visual cortex, central motor area and somatosensory association cortex. In the stable stage, low and high frequency signals jointly orchestrated connectivity between cognitive and motor areas to sustain continuous and stable grip control. Thus, this paper has established an explainable method to characterize brain region interaction and extract interpretable features, providing a technical tool and quantitative evidence for motor-cognitive integrated rehabilitation.