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Kapur, S., Friedman, J., Zatsiorsky, V. M., & Latash, M. L. (2010). Finger interaction in a three-dimensional pressing task. Experimental Brain Research, 203(1), 101–118.
Abstract: Accurate control of forces produced by the fingers is essential for performing object manipulation. This study examines the indices of finger interaction when accurate time profiles of force are produced in different directions, while using one of the fingers or all four fingers of the hand. We hypothesized that patterns of unintended force production among shear force components may involve features not observed in the earlier studies of vertical force production. In particular, we expected to see unintended forces generated by non-task fingers not in the
direction on the instructed force but in the opposite direction as well as substantial force production in directions orthogonal to the instructed direction. We also tested a hypothesis that multi-finger synergies, quantified using the framework of the uncontrolled manifold hypothesis, will help reduce across-trials variance of both total force magnitude and direction. Young, healthy subjects were required to produce accurate ramps of force in five different directions by
pressing on force sensors with the fingers of the right (dominant) hand. The index finger induced the smallest unintended forces in non-task fingers. The little finger showed the smallest unintended forces when it was a non-task finger. Task fingers showed substantial force production in directions orthogonal to the intended force direction. During four-finger tasks, individual force vectors typically pointed off the task direction, with these deviations nearly
perfectly matched to produce a resultant force in the task direction. Multi-finger synergy indices reflected strong co-variation in the space of finger modes (commands to fingers) that reduced variability of the total force magnitude and direction across trials. The synergy indices increased in magnitude over the first 30% of the trial time and then stayed at a nearly constant level. The synergy index for stabilization of total force magnitude was higher for shear force components as compared to the downward pressing force component. The results suggest complex interactions between enslaving and synergic force adjustments, possibly reflecting the experience with everyday prehensile tasks. For the first time, the data document multi-finger synergies stabilizing both shear force magnitude and force vector direction. These synergies may play a major role in
stabilizing the hand action during object manipulation.
Frenkel-Toledo, S., Bentin, S., Perry, A., Liebermann, D. G., & Soroker, N. (2013). Dynamics of the EEG Power in the Frequency and Spatial Domains During Observation and Execution of Manual Movements. Brain Res, 1509, 43–57.
Abstract: Mu suppression is the attenuation of EEG power in the alpha frequency range (8-12Hz) while executing or observing a motor action. Whereas typically observed at central scalp sites, there are diverging reports about the extent of the attenuation over the cortical mantle, its exact frequency range and the specificity of this phenomenon. We investigated the modulation of EEG oscillations in frequency-bands from 4 to 12Hz at frontal, central, parietal and occipital sites during the execution of manual movements and during observation of similar actions from allocentric (i.e., facing the actor) and egocentric (i.e., seeing the actor from behind) viewpoints. Suppression was determined relative to observation of a non-biological movement. Action observation elicited greater suppression in the lower (8-10Hz) compared to the higher mu range (10-12Hz), and greater suppression in the entire 4-12Hz range at frontal and central sites compared to parietal and occipital sites. In addition, suppression tended to be greater during observation of a motor action from allocentric compared to egocentric viewpoints. During execution of movement, suppression of the EEG occurred primarily in the higher alpha range and was absent at occipital sites. In the theta range (4-8Hz), the EEG amplitude was suppressed during action observation and execution. The results suggest a functional distinction between modulation of mu and alpha rhythms, and between the higher and lower ranges of the mu rhythms. The activity of the presumed human mirror neuron system seems primarily evident in the lower mu range and in the theta range.
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.
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.
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.