Efficient Lévy walks in virtual human foraging

Efficient foraging depends on decisions that account for the costs and benefits of various activities like movement, perception, and planning. We conducted a virtual foraging experiment set in the foothills of the Himalayas to examine how time and energy are expended to forage efficiently, and how foraging changes when constrained to a home range. Two hundred players foraged the human-scale landscape with simulated energy expenditure in search of naturally distributed resources. Results showed that efficient foragers produced periods of locomotion interleaved with perception and planning that approached theoretical expectations for Lévy walks, regardless of the home-range constraint. Despite this constancy, efficient home-range foraging trajectories were less diffusive by virtue of restricting locomotive search and spending more time instead scanning the environment to plan movement and detect far-away resources. Altogether, results demonstrate that humans can forage efficiently by arranging and adjusting Lévy-distributed search activities in response to environmental and task constraints.

Pointing in depth is shaped by a natural grasping distance prior

Vision in depth is distorted. A similar distortion can be observed for pointing to visual targets in depth. It has been suggested that pointing errors in depth reflect the visual distortion. However, much research has suggested that in case visual information is not rich enough, the sensorimotor system involves prior knowledge to optimally plan movement trajectories. Here, we show that pointing in depth is guided by a prior that biases movements toward the natural grasping distance at which object manipulation is usually performed. To dissociate whether pointing is guided by distorted vision only or whether it takes into account a natural grasping distance prior, we adapted pointing movements. Participants received visual feedback about the success of their pointing once the movement was finished. We distorted the feedback to signal either that pointing was not far enough or in separate sessions that pointing was too far. Participants adapted to this artificial error by either extending or shortening their pointing movements. The generalization of pointing adaptation revealed a bias in movement planning that is inconsistent with pointing being guided only by distorted vision but with the involvement of knowledge about the natural grasping distance. Adaptation was strongest for pointing movements to a middle position that corresponds to the natural grassing distance and it was weakest for movements leading away from it. It has been demonstrated that pointing adaptation in depth changes visual perception (Volcic et al., 2013). We also wondered how effects of pointing adaptation on visual space would generalize in depth.

Can Treatment Adherence Be Improved by Using Rubin's Four Tendencies Framework to Understand a Patient's Response to Expectations

Within the context of poorer patient outcomes and rising healthcare costs, we need to better understand why many patients do not engage fully with their treatment plan. Movement away from talking about “compliance” towards “adherence” and “concordance” is evidence of a recognition that this is a two-way process. Whilst healthcare professionals expect patients to engage in treatment, equally, patients have expectations (whether positive or negative) of their treatment and their need for engagement. There is a need for an effective method that can specifically target those interventions that will provide the most benefit to individual patients and which, crucially, is easy and inexpensive to administer in everyday practice and widely applicable. Rubin's Four Tendencies model identifies a patient's “response to outer and inner expectations” as a key factor in adherence. The model therefore provides an opportunity to test such a targeted, patient-specific strategy and we present a call to action for research in this area.

Can Treatment Adherence Be Improved by Using Rubin's Four Tendencies Framework to Understand a Patient's Response to Expectations

Within the context of poorer patient outcomes and rising healthcare costs, we need to better understand why many patients do not engage fully with their treatment plan. Movement away from talking about “compliance” towards “adherence” and “concordance” is evidence of a recognition that this is a two-way process. Whilst healthcare professionals expect patients to engage in treatment, equally, patients have expectations (whether positive or negative) of their treatment and their need for engagement. There is a need for an effective method that can specifically target those interventions that will provide the most benefit to individual patients and which, crucially, is easy and inexpensive to administer in everyday practice and widely applicable. Rubin's Four Tendencies model identifies a patient's “response to outer and inner expectations” as a key factor in adherence. The model therefore provides an opportunity to test such a targeted, patient-specific strategy and we present a call to action for research in this area.