Spatially selective enhancement of proprioceptive acuity following motor learning

Department of Psychology, The University of Western Ontario, 1151 Richmond St., London, ON Canada.
Journal of Neurophysiology (Impact Factor: 2.89). 03/2011; 105(5):2512-21. DOI: 10.1152/jn.00949.2010
Source: PubMed


It is well recognized that the brain uses sensory information to accurately produce motor commands. Indeed, most research into the relationship between sensory and motor systems has focused on how sensory information modulates motor function. In contrast, recent studies have begun to investigate the reverse: how sensory and perceptual systems are tuned based on motor function, and specifically motor learning. In the present study we investigated changes to human proprioceptive acuity following recent motor learning. Sensitivity to small displacements of the hand was measured before and after 10 min of motor learning, during which subjects grasped the handle of a robotic arm and guided a cursor to a series of visual targets randomly located within a small workspace region. We used a novel method of assessing proprioceptive acuity that avoids active movement, interhemispheric transfer, and intermodality coordinate transformations. We found that proprioceptive acuity improved following motor learning, but only in the region of the arm's workspace explored during learning. No proprioceptive improvement was observed when motor learning was performed in a different location or when subjects passively experienced limb trajectories matched to those of subjects who actively performed motor learning. Our findings support the idea that sensory changes occur in parallel with changes to motor commands during motor learning.

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    • "Considering FM role in the analyses seems essential for obtaining more reliable results. Some other studies have suggested using passive hand movements to investigate proprioception (Darainy et al., 2013; Cressman & Henriques, 2009, 2010; Wilson et al., 2010; Ostry et al., 2010; Wong et al., 2011). However, FM role may not be ignored in this case either, as some evidence suggests FM does not require explicit movements to make prediction (e.g., performance improvement by mental practice, in the absence of explicit movements, has been described based on FMs (Yavari & Towhidkhah, 2013)). "
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    ABSTRACT: Our ability to properly move and react in different situations is largely dependent on our perception of our limbs' position. At least three sources - vision, proprioception, and internal forward models (FMs) - seem to contribute to this perception. To the best of our knowledge, the effect of each source has not been studied individually. Specifically, role of FM has been ignored in some previous studies. We hypothesized that FM has a critical role in subjects' perception which needs to be considered in the relevant studies to obtain more reliable results. Therefore, we designed an experiment with the goal of investigating FM and proprioception role in subjects' perception of their hand's position. Three groups of subjects were recruited in the study. Based on the experiment design, it was supposed that subjects in different groups relied on proprioception, FM, and both of them for estimating their unseen hand's position. Comparing the results of three groups revealed significant difference between their estimation' errors. FM provided minimum estimation error, while proprioception had a bias error in the tested region. Integrating proprioception with FM decreased this error. Integration of two Gaussian functions, fitted to the error distribution of FM and proprioception groups, was simulated and created a mean error value almost similar to the experimental observation. These results suggest that FM role needs to be considered when studying the perceived position of the limbs. This can lead to gain better insights into the mechanisms underlying the perception of our limbs' position which might have potential clinical and rehabilitation applications, e.g., in the postural control of elderly which are at high risk of falls and injury because of deterioration of their perception with age.
    Journal of Integrative Neuroscience 08/2015; 14(3):1550016. DOI:10.1142/S0219635215500168 · 0.94 Impact Factor
    • "Patients after Stroke have shown that proprioceptive acuity improves following motor learning but only in the region of the workspace explored during learning [22]. Modern neurorehabilitation is based on techniques of motor learning using advanced technologies such as robotics and virtual reality [23]. "
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    ABSTRACT: The aims of this study were to develop and evaluate reliability of a quantitative assessment tool for upper limb sense of position on the horizontal plane. We evaluated 15 healthy individuals (controls) and 9 stroke patients. A robotic device passively moved one arm of the blindfolded participant who had to actively move his/her opposite hand to the mirror location in the workspace. Upper-limb's position was evaluated by a digital camera. The position of the passive hand was compared with the active hand's 'mirror' position. Performance metrics were then computed to measure the mean absolute errors, error variability, spatial contraction/expansion, and systematic shifts. No significant differences were observed between dominant and non-dominant active arms of controls. All performance parameters of the post-stroke group differed significantly from those of controls. This tool can provide a quantitative measure of upper limb sense of position, therefore allowing detection of changes due to rehabilitation.
    Journal of Healthcare Engineering 06/2014; 5(2):145-162. DOI:10.1260/2040-2295.5.2.145 · 0.75 Impact Factor
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    • "The test procedure has been described elsewhere [11] [12] [13]. Briefly, we employed a two-alternative forced-choice paradigm to estimate the psychophysical relationship between actual and perceived position of the limb(s). "
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    ABSTRACT: Information about the position of an object that is held in both hands, such as a golf club or a tennis racquet, is transmitted to the human central nervous system from peripheral sensors in both left and right arms. How does the brain combine these two sources of information? Using a robot to move participant's passive limbs, we performed psychophysical estimates of proprioceptive function for each limb independently, and again when subjects grasped the robot handle with both arms. We compared empirical estimates of bimanual proprioception to several models from the sensory integration literature: some that propose a combination of signals from the left and right arms (such as a Bayesian maximum-likelihood estimate), and some that propose using unimanual signals alone. Our results are consistent with the hypothesis that the nervous system both has knowledge of, and uses the limb with the best proprioceptive acuity for bimanual proprioception. Surprisingly, a Bayesian model that postulates optimal combination of sensory signals could not predict empirically observed bimanual acuity. These findings suggest that while the central nervous system seems to have information about the relative sensory acuity of each limb, it uses this information in a rather rudimentary fashion, essentially ignoring information from the less reliable limb.
    Journal of Neurophysiology 12/2013; 111(6). DOI:10.1152/jn.00537.2013 · 2.89 Impact Factor
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