Self-regulation theory and research suggests that different types of mental imagery can promote goal-directed behaviors. The present study was designed to compare the efficacy of approach imagery (attainment of desired goal states) and process imagery (steps for enacting behavior) in promoting physical activity among inactive individuals. A randomized controlled trial was conducted with 182 inactive adults who received one of four interventions for generating mental images related to physical activity over a 4-week period, with Approach Imagery (approach versus neutral) and Process Imagery (process versus no process) as the intervention strategies. Participants received imagery training and practiced daily. Repeated measures ANOVAs revealed that Approach Imagery: (1) increased approach motivations for physical activity at Week 4; (2) induced greater intentions post-session, which subsequently induced more action planning at Week 4; (3) enhanced action planning when combined with process images at post-session and Week 1; and (4) facilitated more physical activity at Week 4 via action planning. These findings suggest that inducing approach orientation via mental imagery may be a convenient and low-cost technique to promote physical activity among inactive individuals.
Recent research has reached a consensus on the feasibility of motor imagery brain-computer interface (MI-BCI) for different applications, especially in stroke rehabilitation. Most MI-BCI systems rely on temporal, spectral, and spatial features of single channels to distinguish different MI patterns. However, no successful communication has been established for a completely locked-in subject. To provide more useful and informative features, it has been recommended to take into account the relationships among electroencephalographic (EEG) sensor/source signals in the form of brain connectivity as an efficient tool of neuroscience. In this review, we briefly report the challenges and limitations of conventional MI-BCIs. Brain connectivity analysis, particularly functional and effective, has been described as one of the most promising approaches for improving MI-BCI performance. An extensive literature on EEG-based MI brain connectivity analysis of healthy subjects is reviewed. We subsequently discuss the brain connectomes during left and right hand, feet, and tongue MI movements. Moreover, key components involved in brain connectivity analysis that considerably affect the results are explained. Finally, possible technical shortcomings that may have influenced the results in previous research are addressed and suggestions are provided.