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Latash, M. L., Friedman, J., Kim, S.W., Feldman, A.G., Zatsiorsky, V.M. (2010). Prehension Synergies and Control with Referent Hand Configurations. Exp Brain Res, 202(1), 213–229.
Abstract: We used the framework of the equilibrium-point hypothesis (in its updated form based on the notion of referent configuration) to investigate the multi-digit synergies at two levels of a hypothetical hierarchy involved in prehensile actions. Synergies were analyzed at the thumb-virtual finger level (virtual finger is an imaginary digit with the mechanical action equivalent to that of the four actual fingers) and at the individual finger level. The subjects performed very quick vertical movements of a handle into a target. A load could be attached off-center to provide a pronation or supination torque. In a few trials, the handle was unexpectedly fixed to the table and the digits slipped off the sensors. In such trials, the hand stopped at a higher vertical position and rotated into pronation or supination depending on the expected torque. The aperture showed non-monotonic changes with a large, fast decrease and further increase, ending up with a smaller distance between the thumb and the fingers as compared to unperturbed trials. Multi-digit synergies were quantified using indices of co-variation between digit forces and moments of force across unperturbed trials. Prior to the lifting action, high synergy indices were observed at the individual finger level while modest indices were observed at the thumb-virtual finger level. During the lifting action, the synergies at the individual finger level disappeared while the synergy indices became higher at the thumb-virtual finger level. The results support the basic premise that, within a given task, setting a referent configuration may be described with a few referent values of variables that influence the equilibrium state, to which the system is attracted. Moreover, the referent configuration hypothesis can help interpret the data related to the trade-off between synergies at different hierarchical levels.
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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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Shaklai, S., Mimouni-Bloch, A., Levin, M., & Friedman, J. (2017). Development of finger force coordination in children. Experimental Brain Research, 235(12), 3709–3720.
Abstract: Coordination is often observed as body parts moving together. However, when producing force with multiple fingers, the optimal coordination is not to produce similar forces with each finger, but rather for each finger to correct mistakes of other fingers. In this study, we aim to determine whether and how this skill develops in children aged 4-12 years. We measured this sort of coordination using the uncontrolled manifold hypothesis (UCM). We recorded finger forces produced by 60 typically developing children aged between 4 and 12 years in a finger-pressing task. The children controlled the height of an object on a screen by the total amount of force they produced on force sensors. We found that the synergy index, a measure of the relationship between “good” and “bad” variance, increased linearly as a function of age. This improvement was achieved by a selective reduction in “bad” variance rather than an increase in “good” variance. We did not observe differences between males and females, and the synergy index was not able to predict outcomes of upper limb behavioral tests after controlling for age. As children develop between the ages of 4 and 12 years, their ability to produce negative covariation between their finger forces improves, likely related to their improved ability to perform dexterous tasks.
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Frenkel-Toledo, S., Yamanaka, J., Friedman, J., Feldman, A. G., & Levin, M. F. (2019). Referent control of anticipatory grip force during reaching in stroke: an experimental and modeling study. Exp Brain Res, 237(7), 1655–1672.
Abstract: To evaluate normal and impaired control of anticipatory grip force (GF) modulation, we compared GF production during horizontal arm movements in healthy and post-stroke subjects, and, based on a physiologically feasible dynamic model, determined referent control variables underlying the GF-arm motion coordination in each group. 63% of 13 healthy and 48% of 13 stroke subjects produced low sustained initial force (< 10 N) and increased GF prior to arm movement. Movement-related GF increases were higher during fast compared to self-paced arm extension movements only in the healthy group. Differences in the patterns of anticipatory GF increases before the arm movement onset between groups occurred during fast extension arm movement only. In the stroke group, longer delays between the onset of GF change and elbow motion were related to clinical upper limb deficits. Simulations showed that GFs could emerge from the difference between the actual and the referent hand aperture (Ra) specified by the CNS. Similarly, arm movement could result from changes in the referent elbow position (Re) and could be affected by the co-activation (C) command. A subgroup of stroke subjects, who increased GF before arm movement, could specify different patterns of the referent variables while reproducing the healthy typical pattern of GF-arm coordination. Stroke subjects, who increased GF after arm movement onset, also used different referent strategies than controls. Thus, altered anticipatory GF behavior in stroke subjects may be explained by deficits in referent control.
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Raveh, E., Friedman, J., & Portnoy, S. (2018). Evaluation of the effects of adding vibrotactile feedback to myoelectric prosthesis users on performance and visual attention in a dual-task paradigm. Clin Rehabil, 99(11), 2263–2270.
Abstract: Objective: To evaluate the effects of adding vibrotactile feedback to myoelectric prosthesis users on the performance time and visual attention in a dual-task paradigm.
Design: A repeated-measures design with a counterbalanced order of two conditions.
Setting: Laboratory setting.
Subjects: Transradial amputees using a myoelectric prosthesis with normal or corrected eyesight (N=12, median age=65 ± 13 years). Exclusion criteria were orthopedic or neurologic problems.
Interventions: Subjects performed grasping tasks with their prosthesis, while controlling a virtual car on a road with their intact hand. The dual task was performed twice: with and without vibrotactile feedback.
Main measures: Performance time of each of the grasping tasks and gaze behavior, measured by the number of times the subjects shifted their gaze toward their hand, the relative time they applied their attention to the screen, and percentage of error in the secondary task.
Results: The mean performance time was significantly shorter (P=0.024) when using vibrotactile feedback (93.2 ± 9.6 seconds) compared with the performance time measured when vibrotactile feedback was not available (107.8 ± 20.3seconds). No significant differences were found between the two conditions in the number of times the gaze shifted from the screen to the hand, in the time the subjects applied their attention to the screen, and in the time the virtual car was off-road, as a percentage of the total game time
(51.4 ± 15.7 and 50.2 ± 19.5, respectively).
Conclusion: Adding vibrotactile feedback improved performance time during grasping in a dual-task paradigm. Prosthesis users may use vibrotactile feedback to perform better during daily tasks, when multiple cognitive demands are present.
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