When people match an unseen hand to a visual or proprioceptive target, they make both variable and systematic (bias) errors. Variance is a well-established factor in behavior, but the origin and implications of bias, and its connection to variance, are poorly understood. Eighty healthy adults matched their unseen right index finger to proprioceptive (left index finger) and visual targets with no performance feedback. We asked whether matching bias was related to target modality and to the magnitude or spatial properties of matching variance. Bias errors were affected by target modality, with subjects estimating visual and proprioceptive targets 20 mm apart. We found three pieces of evidence to suggest a connection between bias and variable errors: 1) for most subjects, the target modality that yielded greater spatial bias was also estimated with greater variance; 2) magnitudes of matching bias and variance were somewhat correlated for each target modality ( R = 0.24 and 0.29); and 3) bias direction was closely related to the angle of the major axis of the confidence ellipse ( R = 0.60 and 0.63). However, whereas variance was significantly correlated with visuo-proprioceptive weighting as predicted by multisensory integration theory ( R = -0.29 and 0.27 for visual and proprioceptive variance, respectively), bias was not. In a second session, subjects improved their matching variance, but not bias, for both target modalities, indicating a difference in stability. Taken together, these results suggest bias and variance are related only in some respects, which should be considered in the study of multisensory behavior. NEW & NOTEWORTHY People matching visual or proprioceptive targets make both variable and systematic (bias) errors. Multisensory integration is thought to minimize variance, but if the less variable modality has more bias, behavioral accuracy will decrease. Our data set suggests this is unusual. However, although bias and variable errors were spatially related, they differed in both stability and correlation with multisensory weighting. This suggests the bias-variance relationship is not straightforward, and both should be considered in multisensory behavior.

Hand position can be estimated by vision and proprioception (position sense). The brain is thought to weight and integrate these percepts to form a multisensory estimate of hand position with which to guide movement. Force field adaptation, a type of cerebellum-dependent motor learning, is associated with both motor and proprioceptive changes. The cerebellum has connections with multisensory parietal regions; however, it is unknown if force adaptation is associated with changes in multisensory perception. If force adaptation affects all relevant sensory modalities similarly, the brain’s weighting of vision vs. proprioception should be maintained. Alternatively, if force perturbation is interpreted as somatosensory unreliability, vision may be up-weighted relative to proprioception. We assessed visuo-proprioceptive weighting with a perceptual estimation task before and after subjects performed straight-ahead reaches grasping a robotic manipulandum. Each subject performed one session with a clockwise or counter-clockwise velocity-dependent force field, and one session in a null field. Subjects increased their weight of vision vs. proprioception in the force field session relative to the null session, regardless of force field direction, in the straight-ahead dimension (F 1,44 = 5.13, p = 0.029). This suggests that force field adaptation is associated with an increase in the brain’s weighting of vision vs. proprioception.

Clinicians and researchers often need to measure proprioception (position sense), for example to monitor the progress of disease, to identify the cause of movement or balance problems, or to ascertain the effects of an intervention. While researchers can use sophisticated equipment to estimate proprioceptive acuity with good precision, clinicians lack this option and must rely on the subjective and imprecise methods currently available in the clinic. Here we describe a novel technique that applies psychometric adaptive staircase procedures to hand proprioception with a simple tablet-style apparatus that could easily be adapted for the clinic. We report test-retest reliability, inter-rater reliability, and construct validity of the adaptive staircase method vs. two other methods that are commonly used in clinical settings: passive motion direction discrimination (PMDD) and matching. As a first step, we focus on healthy adults. Subjects ages 18–82 had their proprioception measured with each of the three techniques, at the metacarpophalangeal joint in the second finger of the right hand. A subset completed a second session in which the measures were repeated, to assess test-retest reliability. Another subset had the measurements done by two different testers to assess inter-rater reliability. Construct validity was assessed using stepwise regression on age and activity level, and correlations calculated across the three methods. Results suggest that of the three methods, the adaptive staircase method yields the best test-retest reliability, inter-rater reliability, and construct validity. The adaptive staircase method may prove to be a valuable clinical tool where more accurate assessment of proprioception is needed.

To control hand movement, we have both vision and proprioception, or position sense. The brain is known to integrate these to reduce variance. Here we ask whether older adults integrate vision and proprioception in a way that minimizes variance as young adults do, and whether older subjects compensate for an imposed visuo-proprioceptive mismatch as young adults do. Ten healthy older adults (mean age 69) and 10 healthy younger adults (mean age 19) participated. Subjects were asked to estimate the position of visual, proprioceptive, and combined targets, with no direct vision of either hand. After a veridical baseline block, a spatial visuo-proprioceptive misalignment was gradually imposed by shifting the visual component forward from the proprioceptive component without the subject’s awareness. Older subjects were more variable than young subjects at estimating both visual and proprioceptive target positions. Older subjects tended to rely more heavily on vision than proprioception compared to younger subjects. However, the weighting of vision vs. proprioception was correlated with minimum variance predictions for both older and younger adults, suggesting that variance-minimizing mechanisms are present to some degree in older adults. Visual and proprioceptive realignment were similar for young and older subjects in the misalignment block, suggesting older subjects are able to realign as much as young subjects. These results suggest that intact multisensory processing in older adults should be explored as a potential means of mitigating degradation in individual sensory systems.