Learning multi-finger synergies: an uncontrolled manifold analysis

We used the uncontrolled manifold (UCM) approach to study the synergy formation during learning an unusual multi-finger task. The subjects produced accurate force ramps with challenging sets of four fingers (two per hand). We tested hypotheses on stabilization of the contributions of subsets of effe...

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Published inExperimental brain research Vol. 157; no. 3; pp. 336 - 350
Main Authors Kang, Ning, Shinohara, Minoru, Zatsiorsky, Vladimir M, Latash, Mark L
Format Journal Article
LanguageEnglish
Published Germany Springer Nature B.V 01.08.2004
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Abstract We used the uncontrolled manifold (UCM) approach to study the synergy formation during learning an unusual multi-finger task. The subjects produced accurate force ramps with challenging sets of four fingers (two per hand). We tested hypotheses on stabilization of the contributions of subsets of effectors to the task force ( F(TASK)) and to the moment in the frontal plane (force-stabilization and moment-stabilization, respectively). Force signals were used to compute magnitudes of hypothetical independent signals, modes. The variance of the mode magnitudes across repetitions of the task was partitioned into two components, within the UCM ( V(UCM)), which did not affect the average value of a selected performance variable (force or moment), and orthogonal to the UCM ( V(ORT)), which affected the variable. Prior to practice, subjects showed high error indices and failed to show stabilization of each hand's contribution to F(TASK) ( V(ORT)> or = V(UCM)), while the pronation-supination moment was stabilized by the fingers of each hand ( V(ORT)< V(UCM)). The total forces produced by each of the two hands showed negative covariation across trials, which supported the force-stabilization hypothesis but not moment-stabilization hypothesis. Both force-stabilization and moment-stabilization hypotheses were supported by analysis of mode magnitudes to all eight fingers. Over 2 days of practice, the performance of the subjects improved considerably. This was accompanied by the emergence of within-a-hand force-stabilization for each of the two hands without deterioration of moment-stabilization. Quantitatively better within-a-hand force-stabilization was seen in male subjects as compared to females throughout the course of the experiment. Force-stabilization by all eight fingers improved quantitatively with practice. Practice also resulted in higher finger forces in maximal force production (MVC) trials and higher forces produced by unintended fingers in single-finger MVC trials (higher enslaving). We conclude that the UCM approach allows quantifying changes in the coordination of effectors during practice, and offers insights into the microstructure of this coordination with respect to different performance variables and different subsets of effectors. The approach can be used to test whether new synergies emerge in the process of practice.
AbstractList We used the uncontrolled manifold (UCM) approach to study the synergy formation during learning an unusual multi-finger task. The subjects produced accurate force ramps with challenging sets of four fingers (two per hand). We tested hypotheses on stabilization of the contributions of subsets of effectors to the task force (F sub(TASK)) and to the moment in the frontal plane (force-stabilization and moment-stabilization, respectively). Force signals were used to compute magnitudes of hypothetical independent signals, modes. The variance of the mode magnitudes across repetitions of the task was partitioned into two components, within the UCM (V sub(UCM)), which did not affect the average value of a selected performance variable (force or moment), and orthogonal to the UCM (V sub(ORT)), which affected the variable. Prior to practice, subjects showed high error indices and failed to show stabilization of each hand's contribution to F sub(TASK) (V sub(ORT) V sub(UCM)), while the pronation-supination moment was stabilized by the fingers of each hand (V sub(ORT)< V sub(UCM)). The total forces produced by each of the two hands showed negative covariation across trials, which supported the force-stabilization hypothesis but not moment-stabilization hypothesis. Both force-stabilization and moment-stabilization hypotheses were supported by analysis of mode magnitudes to all eight fingers. Over 2 days of practice, the performance of the subjects improved considerably. This was accompanied by the emergence of within-a-hand force-stabilization for each of the two hands without deterioration of moment-stabilization. Quantitatively better within-a-hand force-stabilization was seen in male subjects as compared to females throughout the course of the experiment. Force-stabilization by all eight fingers improved quantitatively with practice. Practice also resulted in higher finger forces in maximal force production (MVC) trials and higher forces produced by unintended fingers in single-finger MVC trials (higher enslaving). We conclude that the UCM approach allows quantifying changes in the coordination of effectors during practice, and offers insights into the microstructure of this coordination with respect to different performance variables and different subsets of effectors. The approach can be used to test whether new synergies emerge in the process of practice.
We used the uncontrolled manifold (UCM) approach to study the synergy formation during learning an unusual multi-finger task. The subjects produced accurate force ramps with challenging sets of four fingers (two per hand). We tested hypotheses on stabilization of the contributions of subsets of effectors to the task force (F TASK) and to the moment in the frontal plane (force-stabilization and moment-stabilization, respectively). Force signals were used to compute magnitudes of hypothetical independent signals, modes. The variance of the mode magnitudes across repetitions of the task was partitioned into two components, within the UCM (V UCM), which did not affect the average value of a selected performance variable (force or moment), and orthogonal to the UCM (V ORT), which affected the variable. Prior to practice, subjects showed high error indices and failed to show stabilization of each hand’s contribution to F TASK (V ORT≥V UCM), while the pronation-supination moment was stabilized by the fingers of each hand (V ORT<V UCM). The total forces produced by each of the two hands showed negative covariation across trials, which supported the force-stabilization hypothesis but not moment-stabilization hypothesis. Both force-stabilization and moment-stabilization hypotheses were supported by analysis of mode magnitudes to all eight fingers. Over 2 days of practice, the performance of the subjects improved considerably. This was accompanied by the emergence of within-a-hand force-stabilization for each of the two hands without deterioration of moment-stabilization. Quantitatively better within-a-hand force-stabilization was seen in male subjects as compared to females throughout the course of the experiment. Force-stabilization by all eight fingers improved quantitatively with practice. Practice also resulted in higher finger forces in maximal force production (MVC) trials and higher forces produced by unintended fingers in single-finger MVC trials (higher enslaving). We conclude that the UCM approach allows quantifying changes in the coordination of effectors during practice, and offers insights into the microstructure of this coordination with respect to different performance variables and different subsets of effectors. The approach can be used to test whether new synergies emerge in the process of practice.
We used the uncontrolled manifold (UCM) approach to study the synergy formation during learning an unusual multi-finger task. The subjects produced accurate force ramps with challenging sets of four fingers (two per hand). We tested hypotheses on stabilization of the contributions of subsets of effectors to the task force (<F<<TASK<) and to the moment in the frontal plane (force-stabilization and moment-stabilization, respectively). Force signals were used to compute magnitudes of hypothetical independent signals, modes. The variance of the mode magnitudes across repetitions of the task was partitioned into two components, within the UCM (<V<<UCM<), which did not affect the average value of a selected performance variable (force or moment), and orthogonal to the UCM (<V<<ORT<), which affected the variable. Prior to practice, subjects showed high error indices and failed to show stabilization of each hand's contribution to <F<<TASK< (<V<<ORT or =<V<<UCM<), while the pronation-supination moment was stabilized by the fingers of each hand (<V<<ORT<<<V<<UCM<). The total forces produced by each of the two hands showed negative covariation across trials, which supported the force-stabilization hypothesis but not moment-stabilization hypothesis. Both force-stabilization and moment-stabilization hypotheses were supported by analysis of mode magnitudes to all eight fingers. Over 2 days of practice, the performance of the subjects improved considerably. This was accompanied by the emergence of within-a-hand force-stabilization for each of the two hands without deterioration of moment-stabilization. Quantitatively better within-a-hand force-stabilization was seen in male subjects as compared to females throughout the course of the experiment. Force-stabilization by all eight fingers improved quantitatively with practice. Practice also resulted in higher finger forces in maximal force production (MVC) trials and higher forces produced by unintended fingers in single-finger MVC trials (higher enslaving). We conclude that the UCM approach allows quantifying changes in the coordination of effectors during practice, and offers insights into the microstructure of this coordination with respect to different performance variables and different subsets of effectors. The approach can be used to test whether new synergies emerge in the process of practice.
We used the uncontrolled manifold (UCM) approach to study the synergy formation during learning an unusual multi-finger task. The subjects produced accurate force ramps with challenging sets of four fingers (two per hand). We tested hypotheses on stabilization of the contributions of subsets of effectors to the task force ( F(TASK)) and to the moment in the frontal plane (force-stabilization and moment-stabilization, respectively). Force signals were used to compute magnitudes of hypothetical independent signals, modes. The variance of the mode magnitudes across repetitions of the task was partitioned into two components, within the UCM ( V(UCM)), which did not affect the average value of a selected performance variable (force or moment), and orthogonal to the UCM ( V(ORT)), which affected the variable. Prior to practice, subjects showed high error indices and failed to show stabilization of each hand's contribution to F(TASK) ( V(ORT)> or = V(UCM)), while the pronation-supination moment was stabilized by the fingers of each hand ( V(ORT)< V(UCM)). The total forces produced by each of the two hands showed negative covariation across trials, which supported the force-stabilization hypothesis but not moment-stabilization hypothesis. Both force-stabilization and moment-stabilization hypotheses were supported by analysis of mode magnitudes to all eight fingers. Over 2 days of practice, the performance of the subjects improved considerably. This was accompanied by the emergence of within-a-hand force-stabilization for each of the two hands without deterioration of moment-stabilization. Quantitatively better within-a-hand force-stabilization was seen in male subjects as compared to females throughout the course of the experiment. Force-stabilization by all eight fingers improved quantitatively with practice. Practice also resulted in higher finger forces in maximal force production (MVC) trials and higher forces produced by unintended fingers in single-finger MVC trials (higher enslaving). We conclude that the UCM approach allows quantifying changes in the coordination of effectors during practice, and offers insights into the microstructure of this coordination with respect to different performance variables and different subsets of effectors. The approach can be used to test whether new synergies emerge in the process of practice.We used the uncontrolled manifold (UCM) approach to study the synergy formation during learning an unusual multi-finger task. The subjects produced accurate force ramps with challenging sets of four fingers (two per hand). We tested hypotheses on stabilization of the contributions of subsets of effectors to the task force ( F(TASK)) and to the moment in the frontal plane (force-stabilization and moment-stabilization, respectively). Force signals were used to compute magnitudes of hypothetical independent signals, modes. The variance of the mode magnitudes across repetitions of the task was partitioned into two components, within the UCM ( V(UCM)), which did not affect the average value of a selected performance variable (force or moment), and orthogonal to the UCM ( V(ORT)), which affected the variable. Prior to practice, subjects showed high error indices and failed to show stabilization of each hand's contribution to F(TASK) ( V(ORT)> or = V(UCM)), while the pronation-supination moment was stabilized by the fingers of each hand ( V(ORT)< V(UCM)). The total forces produced by each of the two hands showed negative covariation across trials, which supported the force-stabilization hypothesis but not moment-stabilization hypothesis. Both force-stabilization and moment-stabilization hypotheses were supported by analysis of mode magnitudes to all eight fingers. Over 2 days of practice, the performance of the subjects improved considerably. This was accompanied by the emergence of within-a-hand force-stabilization for each of the two hands without deterioration of moment-stabilization. Quantitatively better within-a-hand force-stabilization was seen in male subjects as compared to females throughout the course of the experiment. Force-stabilization by all eight fingers improved quantitatively with practice. Practice also resulted in higher finger forces in maximal force production (MVC) trials and higher forces produced by unintended fingers in single-finger MVC trials (higher enslaving). We conclude that the UCM approach allows quantifying changes in the coordination of effectors during practice, and offers insights into the microstructure of this coordination with respect to different performance variables and different subsets of effectors. The approach can be used to test whether new synergies emerge in the process of practice.
Author Shinohara, Minoru
Kang, Ning
Zatsiorsky, Vladimir M
Latash, Mark L
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References 11713627 - Exp Brain Res. 2001 Nov;141(2):153-65
12740728 - Exp Brain Res. 2003 Jul;151(1):60-71
15136283 - J Mot Behav. 1986 Mar;18(1):17-54
11458838 - Ann N Y Acad Sci. 2001 Jun;930:315-29
11918210 - Biol Cybern. 2002 Jan;86(1):29-39
12364526 - J Neurophysiol. 2002 Oct;88(4):2035-46
2140862 - J Physiol. 1990 Feb;421:553-68
9791934 - Biol Cybern. 1998 Aug;79(2):139-50
11907686 - Exp Brain Res. 2002 Mar;143(1):11-23
14642441 - Neurosci Lett. 2003 Dec 15;353(1):72-4
12464342 - Clin Neurophysiol. 2002 Dec;113(12):2013-24
11810146 - Exp Brain Res. 2001 Dec;141(4):530-40
10382616 - Exp Brain Res. 1999 Jun;126(3):289-306
14610628 - Exp Brain Res. 2003 Dec;153(3):275-88
12567224 - Biol Cybern. 2003 Feb;88(2):91-8
12391031 - J Appl Physiol (1985). 2003 Jan;94(1):259-70
11800496 - Exerc Sport Sci Rev. 2002 Jan;30(1):26-31
9644289 - Motor Control. 1998 Jul;2(3):189-205
21227151 - Trends Cogn Sci. 1998 May 1;2(5):168-74
12021815 - Exp Brain Res. 2002 Jun;144(3):336-42
7500130 - J Neurophysiol. 1995 Sep;74(3):1037-45
12232691 - Exp Brain Res. 2002 Oct;146(3):345-55
12898101 - Exp Brain Res. 2003 Sep;152(2):173-84
9551828 - Exp Brain Res. 1998 Apr;119(3):276-86
12404008 - Nat Neurosci. 2002 Nov;5(11):1226-35
11337823 - Exerc Sport Sci Rev. 2001 Apr;29(2):54-9
9463469 - J Neurophysiol. 1998 Feb;79(2):1117-23
11889512 - Exp Brain Res. 2002 Apr;143(3):342-9
12928761 - Exp Brain Res. 2003 Nov;153(1):45-58
2275402 - Acta Physiol Scand. 1990 Sep;140(1):23-30
12478398 - Exp Brain Res. 2003 Jan;148(1):77-87
10323289 - Exp Brain Res. 1999 Apr;125(4):435-9
12012158 - Exp Brain Res. 2002 May;144(2):200-10
References_xml – reference: 11918210 - Biol Cybern. 2002 Jan;86(1):29-39
– reference: 12740728 - Exp Brain Res. 2003 Jul;151(1):60-71
– reference: 11713627 - Exp Brain Res. 2001 Nov;141(2):153-65
– reference: 11907686 - Exp Brain Res. 2002 Mar;143(1):11-23
– reference: 11810146 - Exp Brain Res. 2001 Dec;141(4):530-40
– reference: 12391031 - J Appl Physiol (1985). 2003 Jan;94(1):259-70
– reference: 9551828 - Exp Brain Res. 1998 Apr;119(3):276-86
– reference: 11800496 - Exerc Sport Sci Rev. 2002 Jan;30(1):26-31
– reference: 12928761 - Exp Brain Res. 2003 Nov;153(1):45-58
– reference: 12567224 - Biol Cybern. 2003 Feb;88(2):91-8
– reference: 9644289 - Motor Control. 1998 Jul;2(3):189-205
– reference: 2275402 - Acta Physiol Scand. 1990 Sep;140(1):23-30
– reference: 9791934 - Biol Cybern. 1998 Aug;79(2):139-50
– reference: 11889512 - Exp Brain Res. 2002 Apr;143(3):342-9
– reference: 7500130 - J Neurophysiol. 1995 Sep;74(3):1037-45
– reference: 12012158 - Exp Brain Res. 2002 May;144(2):200-10
– reference: 15136283 - J Mot Behav. 1986 Mar;18(1):17-54
– reference: 12232691 - Exp Brain Res. 2002 Oct;146(3):345-55
– reference: 11337823 - Exerc Sport Sci Rev. 2001 Apr;29(2):54-9
– reference: 9463469 - J Neurophysiol. 1998 Feb;79(2):1117-23
– reference: 12021815 - Exp Brain Res. 2002 Jun;144(3):336-42
– reference: 12404008 - Nat Neurosci. 2002 Nov;5(11):1226-35
– reference: 11458838 - Ann N Y Acad Sci. 2001 Jun;930:315-29
– reference: 2140862 - J Physiol. 1990 Feb;421:553-68
– reference: 21227151 - Trends Cogn Sci. 1998 May 1;2(5):168-74
– reference: 14610628 - Exp Brain Res. 2003 Dec;153(3):275-88
– reference: 10382616 - Exp Brain Res. 1999 Jun;126(3):289-306
– reference: 12898101 - Exp Brain Res. 2003 Sep;152(2):173-84
– reference: 10323289 - Exp Brain Res. 1999 Apr;125(4):435-9
– reference: 14642441 - Neurosci Lett. 2003 Dec 15;353(1):72-4
– reference: 12464342 - Clin Neurophysiol. 2002 Dec;113(12):2013-24
– reference: 12364526 - J Neurophysiol. 2002 Oct;88(4):2035-46
– reference: 12478398 - Exp Brain Res. 2003 Jan;148(1):77-87
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Snippet We used the uncontrolled manifold (UCM) approach to study the synergy formation during learning an unusual multi-finger task. The subjects produced accurate...
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SubjectTerms Adult
brain
Female
Fingers - physiology
Hand Strength - physiology
Hands
Humans
Hypotheses
Learning - physiology
Male
males
microstructure
Models, Neurological
Motor Skills - physiology
Movement - physiology
Muscle Contraction - physiology
Muscle, Skeletal - physiology
Physical Fitness - physiology
Posture - physiology
Sex Factors
Variables
variance
Title Learning multi-finger synergies: an uncontrolled manifold analysis
URI https://www.ncbi.nlm.nih.gov/pubmed/15042264
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