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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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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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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Friedman, J., Latash, M. L., & Zatsiorsky, V. M. (2009). Prehension synergies: a study of digit force adjustments to the continuously varied load force exerted on a partially constrained hand-held object. Exp Brain Res, 197(1), 1–13.
Abstract: We examined how the digit forces adjust when a load force acting on a hand-held object continuously varies. The subjects were required to hold the handle still while a linearly increasing and then decreasing force was applied to the handle. The handle was constrained, such that it could only move up and down, and rotate about a horizontal axis. In addition, the moment arm of the thumb tangential force was 1.5 times the moment arm of the virtual finger (VF, an imagined finger with the mechanical action equal to that of the four fingers) force. Unlike the situation when there are equal moment arms, the experimental setup forced the subjects to choose between (a) sharing equally the increase in load force between the thumb and VF but generating a moment of tangential force, which had to be compensated by negatively co-varying the moment due to normal forces, or (b) sharing unequally the load force increase between the thumb and VF but preventing generation of a moment of tangential forces. We found that different subjects tended to use one of these two strategies. These findings suggest that the selection by the CNS of prehension synergies at the VF-thumb level with respect to the moment of force is non-obligatory and reflects individual subject preferences. This unequal sharing of the load by the tangential forces, in contrast to the previously observed equal sharing, suggests that the invariant feature of prehension may be a correlated increase in tangential forces rather than an equal increase.
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Friedman, J., SKM, V., Zatsiorsky, V. M., & Latash, M. L. (2009). The sources of two components of variance: an example of multifinger cyclic force production tasks at different frequencies. Exp Brain Res, 196(2), 263–277.
Abstract: In a multifinger cyclic force production task, the finger force variance measured across trials can be decomposed into two components, one that affects the combined force output (“bad variance”) and one that does not (“good variance”). Previous studies have found similar time patterns of “bad variance” and force rate leading to an approximately linear relationship between them. Based on this finding and a recently developed model of multifinger force production, we expected the “bad variance” during cyclic force production to increase monotonically with the rate of force change, both within a cycle and across trials at different frequencies. Alternatively, “bad variance” could show a dependence on task frequency, not on actual force derivative values. Healthy subjects were required to produce cyclic force patterns to prescribed targets by pressing on unidimensional force sensors, at a frequency set by a metronome. The task was performed with only the index finger, and with all four fingers. In the task with all four fingers, the “good variance” increased approximately linearly with an increase in the force magnitude. The “bad variance” showed within-a-cycle modulation similar to that of the force rate. However, an increase in the frequency did not lead to an increase in the “bad variance” that could be expected based on the natural relationships between action frequency and the rate of force change modulation. The results have been interpreted in the framework of an earlier model of multifinger force production where “bad variance” is a result of variance of the timing parameter. The unexpected lack of modulation of the “bad variance” with frequency suggests a drop in variance of the timing parameter with increased frequency. This mechanism may serve to maintain a constant acceptable level of variance under different conditions.
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