What Do Synergies Do? Effects of Secondary Constraints on Multidigit Synergies in Accurate Force-Production Tasks

1 Department of Kinesiology, Pennsylvania State University, University Park, Pennsylvania; 2 Department of Physical Therapy and Biomechanics and Movement Science Program, University of Delaware, Newark, Delaware Submitted 17 September 2007; accepted in final form 23 November 2007 We used the framewo...

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Published inJournal of neurophysiology Vol. 99; no. 2; pp. 500 - 513
Main Authors Zhang, Wei, Scholz, John P, Zatsiorsky, Vladimir M, Latash, Mark L
Format Journal Article
LanguageEnglish
Published United States Am Phys Soc 01.02.2008
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ISSN0022-3077
1522-1598
DOI10.1152/jn.01029.2007

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Abstract 1 Department of Kinesiology, Pennsylvania State University, University Park, Pennsylvania; 2 Department of Physical Therapy and Biomechanics and Movement Science Program, University of Delaware, Newark, Delaware Submitted 17 September 2007; accepted in final form 23 November 2007 We used the framework of the uncontrolled manifold (UCM) hypothesis to explore changes in the structure of variability in multifinger force-production tasks when a secondary task was introduced. Healthy young subjects produced several levels of the total force by pressing with the four fingers of the hand on force sensors. The frame with the sensors rested on the table ( Stable condition) or on a narrow supporting beam ( Unstable conditions) that could be placed between different finger pairs. Most variance in the finger mode space was compatible with a fixed value of the total force across all conditions, whereas the patterns of sharing of the total force among the fingers were condition dependent. Moment of force was stabilized only in the Unstable conditions. The finger mode data were projected onto the UCM computed for the total force and subjected to principal component (PC) analysis. Two PCs accounted for >90% of the variance. The directions of the PC vectors varied across subjects in the Stable condition, whereas two "default" PCs were observed under the Unstable conditions. These observations show that different persons coordinate their fingers differently in force-production tasks. They converge on similar solutions when an additional constraint is introduced. The use of variable solutions allows avoiding a loss in accuracy of performance when the same elements get involved in another task. Our results suggest a mechanism underlying the principle of superposition suggested in a variety of human and robotic studies. Address for reprint requests and other correspondence: M. L. Latash, Rec Hall-268N, Department of Kinesiology, Pennsylvania State University, University Park, PA 16802 (E-mail: mll11{at}psu.edu )
AbstractList We used the framework of the uncontrolled manifold (UCM) hypothesis to explore changes in the structure of variability in multifinger force-production tasks when a secondary task was introduced. Healthy young subjects produced several levels of the total force by pressing with the four fingers of the hand on force sensors. The frame with the sensors rested on the table (Stable condition) or on a narrow supporting beam (Unstable conditions) that could be placed between different finger pairs. Most variance in the finger mode space was compatible with a fixed value of the total force across all conditions, whereas the patterns of sharing of the total force among the fingers were condition dependent. Moment of force was stabilized only in the Unstable conditions. The finger mode data were projected onto the UCM computed for the total force and subjected to principal component (PC) analysis. Two PCs accounted for >90% of the variance. The directions of the PC vectors varied across subjects in the Stable condition, whereas two "default" PCs were observed under the Unstable conditions. These observations show that different persons coordinate their fingers differently in force-production tasks. They converge on similar solutions when an additional constraint is introduced. The use of variable solutions allows avoiding a loss in accuracy of performance when the same elements get involved in another task. Our results suggest a mechanism underlying the principle of superposition suggested in a variety of human and robotic studies.
We used the framework of the uncontrolled manifold (UCM) hypothesis to explore changes in the structure of variability in multifinger force-production tasks when a secondary task was introduced. Healthy young subjects produced several levels of the total force by pressing with the four fingers of the hand on force sensors. The frame with the sensors rested on the table (Stable condition) or on a narrow supporting beam (Unstable conditions) that could be placed between different finger pairs. Most variance in the finger mode space was compatible with a fixed value of the total force across all conditions, whereas the patterns of sharing of the total force among the fingers were condition dependent. Moment of force was stabilized only in the Unstable conditions. The finger mode data were projected onto the UCM computed for the total force and subjected to principal component (PC) analysis. Two PCs accounted for >90% of the variance. The directions of the PC vectors varied across subjects in the Stable condition, whereas two "default" PCs were observed under the Unstable conditions. These observations show that different persons coordinate their fingers differently in force-production tasks. They converge on similar solutions when an additional constraint is introduced. The use of variable solutions allows avoiding a loss in accuracy of performance when the same elements get involved in another task. Our results suggest a mechanism underlying the principle of superposition suggested in a variety of human and robotic studies.We used the framework of the uncontrolled manifold (UCM) hypothesis to explore changes in the structure of variability in multifinger force-production tasks when a secondary task was introduced. Healthy young subjects produced several levels of the total force by pressing with the four fingers of the hand on force sensors. The frame with the sensors rested on the table (Stable condition) or on a narrow supporting beam (Unstable conditions) that could be placed between different finger pairs. Most variance in the finger mode space was compatible with a fixed value of the total force across all conditions, whereas the patterns of sharing of the total force among the fingers were condition dependent. Moment of force was stabilized only in the Unstable conditions. The finger mode data were projected onto the UCM computed for the total force and subjected to principal component (PC) analysis. Two PCs accounted for >90% of the variance. The directions of the PC vectors varied across subjects in the Stable condition, whereas two "default" PCs were observed under the Unstable conditions. These observations show that different persons coordinate their fingers differently in force-production tasks. They converge on similar solutions when an additional constraint is introduced. The use of variable solutions allows avoiding a loss in accuracy of performance when the same elements get involved in another task. Our results suggest a mechanism underlying the principle of superposition suggested in a variety of human and robotic studies.
1 Department of Kinesiology, Pennsylvania State University, University Park, Pennsylvania; 2 Department of Physical Therapy and Biomechanics and Movement Science Program, University of Delaware, Newark, Delaware Submitted 17 September 2007; accepted in final form 23 November 2007 We used the framework of the uncontrolled manifold (UCM) hypothesis to explore changes in the structure of variability in multifinger force-production tasks when a secondary task was introduced. Healthy young subjects produced several levels of the total force by pressing with the four fingers of the hand on force sensors. The frame with the sensors rested on the table ( Stable condition) or on a narrow supporting beam ( Unstable conditions) that could be placed between different finger pairs. Most variance in the finger mode space was compatible with a fixed value of the total force across all conditions, whereas the patterns of sharing of the total force among the fingers were condition dependent. Moment of force was stabilized only in the Unstable conditions. The finger mode data were projected onto the UCM computed for the total force and subjected to principal component (PC) analysis. Two PCs accounted for >90% of the variance. The directions of the PC vectors varied across subjects in the Stable condition, whereas two "default" PCs were observed under the Unstable conditions. These observations show that different persons coordinate their fingers differently in force-production tasks. They converge on similar solutions when an additional constraint is introduced. The use of variable solutions allows avoiding a loss in accuracy of performance when the same elements get involved in another task. Our results suggest a mechanism underlying the principle of superposition suggested in a variety of human and robotic studies. Address for reprint requests and other correspondence: M. L. Latash, Rec Hall-268N, Department of Kinesiology, Pennsylvania State University, University Park, PA 16802 (E-mail: mll11{at}psu.edu )
We used the framework of the uncontrolled manifold (UCM) hypothesis to explore changes in the structure of variability in multifinger force-production tasks when a secondary task was introduced. Healthy young subjects produced several levels of the total force by pressing with the four fingers of the hand on force sensors. The frame with the sensors rested on the table ( Stable condition) or on a narrow supporting beam ( Unstable conditions) that could be placed between different finger pairs. Most variance in the finger mode space was compatible with a fixed value of the total force across all conditions, whereas the patterns of sharing of the total force among the fingers were condition dependent. Moment of force was stabilized only in the Unstable conditions. The finger mode data were projected onto the UCM computed for the total force and subjected to principal component (PC) analysis. Two PCs accounted for >90% of the variance. The directions of the PC vectors varied across subjects in the Stable condition, whereas two “default” PCs were observed under the Unstable conditions. These observations show that different persons coordinate their fingers differently in force-production tasks. They converge on similar solutions when an additional constraint is introduced. The use of variable solutions allows avoiding a loss in accuracy of performance when the same elements get involved in another task. Our results suggest a mechanism underlying the principle of superposition suggested in a variety of human and robotic studies.
Author Scholz, John P
Zhang, Wei
Zatsiorsky, Vladimir M
Latash, Mark L
AuthorAffiliation 1 Department of Kinesiology, Pennsylvania State University, University Park, Pennsylvania
2 Department of Physical Therapy and Biomechanics and Movement Science Program, University of Delaware, Newark, Delaware
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Snippet 1 Department of Kinesiology, Pennsylvania State University, University Park, Pennsylvania; 2 Department of Physical Therapy and Biomechanics and Movement...
We used the framework of the uncontrolled manifold (UCM) hypothesis to explore changes in the structure of variability in multifinger force-production tasks...
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SubjectTerms Adult
Analysis of Variance
Female
Fingers - innervation
Fingers - physiology
Hand Strength - physiology
Humans
Male
Models, Biological
Movement - physiology
Postural Balance - physiology
Principal Component Analysis
Psychomotor Performance - physiology
Task Performance and Analysis
Time Factors
Title What Do Synergies Do? Effects of Secondary Constraints on Multidigit Synergies in Accurate Force-Production Tasks
URI http://jn.physiology.org/cgi/content/abstract/99/2/500
https://www.ncbi.nlm.nih.gov/pubmed/18046000
https://www.proquest.com/docview/20528875
https://www.proquest.com/docview/70296974
https://pubmed.ncbi.nlm.nih.gov/PMC2827038
Volume 99
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