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Author |
Friedman, Jason; SKM, Varadhan; Zatsiorsky, Vladimir M.; Latash, Mark L. |
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Title |
The sources of two components of variance: an example of multifinger cyclic force production tasks at different frequencies |
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Journal Article |
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Year |
2009 |
Publication |
Experimental Brain Research |
Abbreviated Journal |
Exp Brain Res |
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Volume |
196 |
Issue |
2 |
Pages |
263-277 |
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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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Department of Kinesiology, The Pennsylvania State University, University Park, PA 16802, USA |
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1432-1106 |
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PMID:19468721 |
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Penn State @ write.to.jason @ |
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15 |
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Author |
Noy, L.; Alon, U.; Friedman, J. |
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Title |
Corrective jitter motion shows similar individual frequencies for the arm and the finger |
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Journal Article |
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Year |
2015 |
Publication |
Experimental Brain Research |
Abbreviated Journal |
Exp Brain Res |
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Volume |
233 |
Issue |
4 |
Pages |
1307-1320 |
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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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0014-4819 |
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PMID:25630905 |
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76 |
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