title: Age-related changes in optimality and motor variability: an example of multifinger redundant tasks.
abstract: We used two methods, analytical inverse optimization (ANIO) and uncontrolled manifold (UCM) analysis of synergies, to explore age-related changes in finger coordination during accurate force and moment of force production tasks. The two methods address two aspects of the control of redundant systems: Finding an optimal solution (an optimal sharing pattern) and using variable solutions across trials (covarying finger forces) that are equally able to solve the task. Young and elderly subjects produced accurate combinations of total force and moment by pressing with the four fingers of the dominant hand on individual force sensors. In session-1, single trials covered a broad range of force-moment combinations. Principal component (PC) analysis showed that the first two PCs explained about 90% and 75% of finger force variance for the young and elderly groups, respectively. The magnitudes of the loading coefficients in the PCs suggested that the young subjects used mechanical advantage to produce moment while elderly subjects did not (confirmed by analysis of moments produced by individual digits). A co-contraction index was computed reflecting the magnitude of moment produced by fingers acting against the required direction of the total moment. This index was significantly higher in the young group. The ANIO approach yielded a quadratic cost function with linear terms. In the elderly group, the contribution of the forces produced by the middle and ring fingers to the cost function value was much smaller than in the young group. The angle between the plane of experimental observations and the plane of optimal solutions (D-angle), was very small (about 1.5°) in the young group and significantly larger (about 5°) in the elderly group. In session-2, four force-moment combinations were used with multiple trials at each. Covariation among finger forces (multifinger synergies) stabilizing total force, total moment, and both was seen in both groups with larger synergy indices in the young group. Multiple regression analysis has shown that, at higher force magnitudes, the synergy indices defined with the UCM method were significantly related to the percent of variance accounted by the first two PCs and to the D-angle computed using the ANIO method. We interpret the results as pointing at a transition with age from synergic control to element-based control (back-to-elements hypothesis). Optimization and analysis of synergies are complementary approaches that focus on two aspects of multidigit coordination, sharing and covariation, respectively.
authors.affiliation: Department of Kinesiology, The Pennsylvania State University, Rec.Hall-268N, University Park, PA 16802, USA.
authors.forename: Jaebum
authors.initials: J
authors.lastname: Park
authors.forename: Yao
authors.initials: Y
authors.lastname: Sun
authors.forename: Vladimir M
authors.initials: VM
authors.lastname: Zatsiorsky
authors.forename: Mark L
authors.initials: ML
authors.lastname: Latash
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000502:physiology*; D005260:Female; D005385:Fingers / Q000502:physiology*; D006801:Humans; D008297:Male; D009048:Motor Skills / Q000502:physiology; D025341:Principal Component Analysis / Q000379:methods; D011597:Psychomotor Performance / Q000502:physiology*