Active and passive exploration for spatial knowledge acquisition: A meta-analysis.

Literature reported mixed evidence on whether active exploration benefits spatial knowledge acquisition over passive exploration. Active spatial learning typically involves at least physical control of one's movement or navigation decision-making, while passive participants merely observe during exploration. To quantify the effects of active exploration in learning large-scale, unfamiliar environments, we analysed previous findings with the multi-level meta-analytical model. Potential moderators were identified and examined for their contributions to the variability in effect sizes. Of the 128 effect sizes retrieved from 33 experiments, we observed a small to moderate advantage of active exploration over passive observation. Important moderators include gender composition, decision-making, types of spatial knowledge, and matched visual information. We discussed the implications of the results along with the limitations.

Enhancing touch sensibility by sensory retraining in a sensory discrimination task via haptic rendering.

Stroke survivors are commonly affected by somatosensory impairment, hampering their ability to interpret somatosensory information. Somatosensory information has been shown to critically support movement execution in healthy individuals and stroke survivors. Despite the detrimental effect of somatosensory impairments on performing activities of daily living, somatosensory training-in stark contrast to motor training-does not represent standard care in neurorehabilitation. Reasons for the neglected somatosensory treatment are the lack of high-quality research demonstrating the benefits of somatosensory interventions on stroke recovery, the unavailability of reliable quantitative assessments of sensorimotor deficits, and the labor-intensive nature of somatosensory training that relies on therapists guiding the hands of patients with motor impairments. To address this clinical need, we developed a virtual reality-based robotic texture discrimination task to assess and train touch sensibility. Our system incorporates the possibility to robotically guide the participants' hands during texture exploration (i.e., passive touch) and no-guided free texture exploration (i.e., active touch). We ran a 3-day experiment with thirty-six healthy participants who were asked to discriminate the odd texture among three visually identical textures -haptically rendered with the robotic device- following the method of constant stimuli. All participants trained with the passive and active conditions in randomized order on different days. We investigated the reliability of our system using the Intraclass Correlation Coefficient (ICC). We also evaluated the enhancement of participants' touch sensibility via somatosensory retraining and compared whether this enhancement differed between training with active vs. passive conditions. Our results showed that participants significantly improved their task performance after training. Moreover, we found that training effects were not significantly different between active and passive conditions, yet, passive exploration seemed to increase participants' perceived competence. The reliability of our system ranged from poor (in active condition) to moderate and good (in passive condition), probably due to the dependence of the ICC on the between-subject variability, which in a healthy population is usually small. Together, our virtual reality-based robotic haptic system may be a key asset for evaluating and retraining sensory loss with minimal supervision, especially for brain-injured patients who require guidance to move their hands.