How Weight Affects the Perceived Spacing between the Thumb and Fingers during Grasping

Proprioception: a new look at an old concept

Proprioception, which can be defined as the awareness of the mechanical and spatial state of the body and its musculoskeletal parts, is critical to motor actions and contributes to our sense of body ownership. To date, clinical proprioceptive tests have focused on a person's ability to detect, discriminate or match limb positions or movements, and reveal that the strength of the relationship between deficits in proprioception and physical function varies widely. Unfortunately, these tests fail to assess higher-level proprioceptive abilities. In this Perspective, we propose that to understand fully the link between proprioception and function, we need to look beyond traditional clinical tests of proprioception. Specifically, we present a novel framework for human proprioception assessment that is divided into two categories: low-level and high-level proprioceptive judgments. Low-level judgments are those made in a single frame of reference and are the types of judgments made in traditional proprioceptive tests (i.e. detect, discriminate or match). High-level proprioceptive abilities involve proprioceptive judgments made in a different frame of reference. For example, when a person indicates where their hand is located in space. This framework acknowledges that proprioception is complex and multifaceted, and that tests of proprioception should not be viewed as interchangeable, but rather as complimentary. Crucially, it provides structure to the way researchers and clinicians can approach proprioception and its assessment. We hope this Perspective serves as the catalyst for discussion and new lines of investigation.

A meta-analysis of the size-weight and material-weight illusions

The current study comprises the first systematic meta-analysis of weight illusions. We obtained descriptive data from studies in which subjective heaviness estimates were made for pairs or groups of objects that had the same mass and different volumes (size-weight illusion; SWI) or different apparent material properties (material-weight illusion; MWI). Using these data, we calculated mean effect sizes to represent illusion strength. Other study details, including stimulus mass, volume, density, and degree of visual and somatosensory access to the stimuli were also recorded to quantify the contribution of these variables to effect sizes for the SWI. The results indicate that the SWI has a larger mean effect size than the MWI and that the former is consistent in strength when information about stimulus size is gained through somatosensory channels, regardless of visual access. The SWI is weaker when only the visual system provides size information. Effect sizes for the SWI were larger when there was a greater difference in volume across the stimuli. There was also a positive correlation between SWI strength and the difference in physical density across the different experimental stimuli, even after controlling for volume differences. Together, we argue that these findings provide support for theories of weight illusions that are based on conceptual expectancies as well as those that are based on bottom-up processing of physical density. We further propose that these processes, which have been considered dichotomously in the past, may not be mutually exclusive from each other and could both contribute to our perception of weight when we handle objects in everyday life.

Stability of perception of the hand's aperture in a grasp

KEY POINTS

How we judge the location of our body parts can be affected by a range of factors that change how our brain interprets proprioceptive signals. We examined the effect of several such factors on how we perceive an object's width and the spacing between our thumb and fingers when grasping. Grasp-related perceptions were slightly wider when using all digits, in line with our tendency to grasp larger objects with the entire hand. Surprisingly, these perceptions were not affected by the frames of reference for judgements (object width versus grasp aperture), whether the object was grasped actively or passively, or the strength of the grasp. These results show that the brain maintains a largely stable representation of the hand when grasping stationary objects. This stability may underpin our dexterity when grasping a vast array of objects.

ABSTRACT

Various factors can alter how the brain interprets proprioceptive signals, leading to errors in how we perceive our body and execute motor tasks. This study determined the effect of critical factors on hand-based perceptions. In Experiment 1, 20 participants grasped without lifting an unseen 6.5 cm-wide object with two grasp configurations: thumb and all fingers, and thumb and index finger. Participants reported perceived grasp aperture (body reference frame) or perceived object width (external reference frame) using visual charts. In Experiment 2, 20 participants grasped the object with three grasp intensities (1, 5 and 15% maximal grasp force) actively or passively and reported perceived grasp aperture. A follow-up experiment addressed whether results from Experiment 2 were influenced by the external force applied during passive grasp. Overall, there was a mean difference of 0.38 cm (95% confidence interval (CI), 0.12 to 0.63) between the two grasp configurations (all digits compared to thumb and index finger). Perceived object width compared to perceived grasp aperture differed by only -0.04 cm (95% CI, -0.30 to 0.21). There was no real effect of grasp intensity on perceived grasp aperture (-0.01 cm; 95% CI, -0.03 to 0.01) or grasp type (active versus passive; 0.18 cm; 95% CI, -0.19 to 0.55). Overall, grasp-related perceptions are slightly wider when using all digits, in line with our tendency to grasp larger objects with the entire hand. The other factors - frame of reference, grasp intensity and grasp type - had no meaningful effect on these perceptions. These results provide evidence that the brain maintains a largely stable representation of the hand.

Linear Integration of Tactile and Non-tactile Inputs Mediates Estimation of Fingertip Relative Position

While skin, joints and muscles receptors alone provide lower level information about individual variables (e.g., exerted limb force and limb displacement), the distance between limb endpoints (i.e., relative position) has to be extracted from high level integration of somatosensory and motor signals. In particular, estimation of fingertip relative position likely involves more complex sensorimotor transformations than those underlying hand or arm position sense: the brain has to estimate where each fingertip is relative to the hand and where fingertips are relative to each other. It has been demonstrated that during grasping, feedback of digit position drives rapid adjustments of fingers force control. However, it has been shown that estimation of fingertips' relative position can be biased by digit forces. These findings raise the question of how the brain combines concurrent tactile (i.e., cutaneous mechanoreceptors afferents induced by skin pressure and stretch) and non-tactile (i.e., both descending motor command and joint/muscle receptors signals associated to muscle contraction) digit force-related inputs for fingertip distance estimation. Here we addressed this question by quantifying the contribution of tactile and non-tactile force-related inputs for the estimation of fingertip relative position. We asked subjects to match fingertip vertical distance relying only on either tactile or non-tactile inputs from the thumb and index fingertip, and compared their performance with the condition where both types of inputs were combined. We found that (a) the bias in the estimation of fingertip distance persisted when tactile inputs and non-tactile force-related signals were presented in isolation; (b) tactile signals contributed the most to the estimation of fingertip distance; (c) linear summation of the matching errors relying only on either tactile or non-tactile inputs was comparable to the matching error when both inputs were simultaneously available. These findings reveal a greater role of tactile signals for sensing fingertip distance and suggest a linear integration mechanism with non-tactile inputs for the estimation of fingertip relative position.