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Liebermann, D. G., Biess, A., Friedman, J., Gielen, C. C. A. M., & Flash, T. (2006). Intrinsic joint kinematic planning. I: reassessing the Listing's law constraint in the control of three-dimensional arm movements. Exp Brain Res, 171(2), 139–154.
Abstract: This study tested the validity of the assumption that intrinsic kinematic constraints, such as Listing's law, can account for the geometric features of three-dimensional arm movements. In principle, if the arm joints follow a Listing's constraint, the hand paths may be predicted. Four individuals performed 'extended arm', 'radial', 'frontal plane', and 'random mixed' movements to visual targets to test Listing's law assumption. Three-dimensional rotation vectors of the upper arm and forearm were calculated from three-dimensional marker data. Data fitting techniques were used to test Donders' and Listing's laws. The coefficient values obtained from fitting rotation vectors to the surfaces described by a second-order equation were analyzed. The results showed that the coefficients that represent curvature and twist of the surfaces were often not significantly different from zero, particularly not during randomly mixed and extended arm movements. These coefficients for forearm rotations were larger compared to those for the upper arm segment rotations. The mean thickness of the rotation surfaces ranged between approximately 1.7 degrees and 4.7 degrees for the rotation vectors of the upper arm segment and approximately 2.6 degrees and 7.5 degrees for those of the forearm. During frontal plane movements, forearm rotations showed large twist scores while upper arm segment rotations showed large curvatures, although the thickness of the surfaces remained low. The curvatures, but not the thicknesses of the surfaces, were larger for large versus small amplitude radial movements. In conclusion, when examining the surfaces obtained for the different movement types, the rotation vectors may lie within manifolds that are anywhere between curved or twisted manifolds. However, a two-dimensional thick surface may roughly represent a global arm constraint. Our findings suggest that Listing's law is implemented for some types of arm movement, such as pointing to targets with the extended arm and during radial reaching movements.
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Friedman, J., & Korman, M. (2012). Kinematic Strategies Underlying Improvement in the Acquisition of a Sequential Finger Task with Self-Generated vs. Cued Repetition Training. PLoS One, 7(12), e52063.
Abstract: Many motor skills, such as typing, consist of articulating simple movements into novel sequences that are executed faster and smoother with practice. Dynamics of re-organization of these movement sequences with multi-session training and its dependence on the amount of self-regulation of pace during training is not yet fully understood. In this study, participants practiced a sequence of key presses. Training sessions consisted of either externally (Cued) or self-initiated (Uncued) training. Long-term improvements in performance speed were mainly due to reducing gaps between finger movements in both groups, but Uncued training induced higher gains. The underlying kinematic strategies producing these changes and the representation of the trained sequence differed significantly across subjects, although net gains in speed were similar. The differences in long-term memory due to the type of training and the variation in strategies between subjects, suggest that the different neural mechanisms may subserve the improvements observed in overall performance.
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Noy, L., Alon, U., & Friedman, J. (2015). Corrective jitter motion shows similar individual frequencies for the arm and the finger. Exp Brain Res, 233(4), 1307–1320.
Abstract: A characteristic of visuomotor tracking of non-regular oscillating stimuli are high-frequency jittery corrective motions, oscillating around the tracked stimuli. However, the properties of these corrective jitter responses are not well understood. For example, does the jitter response show an idiosyncratic signature? What is the relationship between stimuli properties and jitter properties? Is the jitter response similar across effectors with different inertial properties? To answer these questions, we measured participants' jitter frequencies in two tracking tasks in the arm and the finger. Thirty participants tracked the same set of eleven non-regular oscillating stimuli, vertically moving on a screen, once with forward-backward arm movements (holding a tablet stylus) and once with upward-downward index finger movements (with a motion tracker attached). Participants' jitter frequencies and tracking errors varied systematically as a function of stimuli frequency and amplitude. Additionally, there were clear individual differences in average jitter frequencies between participants, ranging from 0.7 to 1.15 Hz, similar to values reported previously. A comparison of individual jitter frequencies in the two tasks showed a strong correlation between participants' jitter frequencies in the finger and the arm, despite the very different inertial properties of the two effectors. This result suggests that the corrective jitter response stems from common neural processes.
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Zopf, R., Friedman, J., & Williams, M. A. (2015). The plausibility of visual information for hand ownership modulates multisensory synchrony perception. Experimental Brain Research, 233(8), 2311–2321.
Abstract: We are frequently changing the position of our bodies and body parts within complex environments. How does the brain keep track of one’s own body? Current models of body ownership state that visual body ownership cues such as viewed object form and orientation are combined with multisensory information to correctly identify one’s own body, estimate its current location and evoke an experience of body ownership. Within this framework, it may be possible that the brain relies on a separate perceptual analysis of body ownership cues (e.g. form, orientation, multisensory synchrony). Alternatively, these cues may interact in earlier stages of perceptual processing—visually derived body form and orientation cues may, for example, directly modulate temporal synchrony perception. The aim of the present study was to distinguish between these two alternatives. We employed a virtual hand set-up and psychophysical methods. In a two-interval force-choice task, participants were asked to detect temporal delays between executed index finger movements and observed movements. We found that body-specifying cues interact in perceptual processing. Specifically, we show that plausible visual information (both form and orientation) for one’s own body led to significantly better detection performance for small multisensory asynchronies compared to implausible visual information. We suggest that this perceptual modulation when visual information plausible for one’s own body is present is a consequence of body-specific sensory predictions.
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Raveh, E., Portnoy, S., & Friedman, J. (2018). Adding vibrotactile feedback to a myoelectric-controlled hand improves performance when online visual feedback is disturbed. Hum Mov Sci, 58, 32–40.
Abstract: We investigated whether adding vibrotactile feedback to a myoelectric-controlled hand, when visual feedback is disturbed, can improve performance during a functional test. For this purpose, able-bodied subjects, activating a myoelectric-controlled hand attached to their right hand performed the modified Box & Blocks test, grasping and manipulating wooden blocks over a partition. This was performed in 3 conditions, using a repeated-measures design: in full light, in a dark room where visual feedback was disturbed and no auditory feedback – one time with the addition of tactile feedback provided during object grasping and manipulation, and one time without any tactile feedback. The average time needed to transfer one block was measured, and an infrared camera was used to give information on the number of grasping errors during performance of the test. Our results show that when vibrotactile feedback was provided, performance time was reduced significantly, compared with when no vibrotactile feedback was available. Furthermore, the accuracy of grasping and manipulation was improved, reflected by significantly fewer errors during test performance. In conclusion, adding vibrotactile feedback to a myoelectric-controlled hand has positive effects on functional performance when visual feedback is disturbed. This may have applications to current myoelectric-controlled hands, as adding tactile feedback may help prosthesis users to improve their functional ability during daily life activities in different environments, particularly when limited visual feedback is available or desirable.
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