title: Anticipatory control of motion-to-force transitions with the fingertips adapts optimally to task difficulty.
abstract: Moving our fingertips toward objects to produce well-directed forces immediately upon contact is fundamental to dexterous manipulation. This apparently simple motion-to-force transition in fact involves a time-critical, predictive switch in control strategy. Given that dexterous manipulation must accommodate multiple mechanical conditions, we investigated whether and how this transition adapts to task difficulty. Eight adults (19-39 yr) produced ramps of isometric vertical fingertip force against a rigid surface immediately following a tapping motion. By changing target surface friction and size, we defined an easier (sandpaper, 11 mm diam) versus a more difficult (polished steel, 5 mm diam) task. As in prior work, we assembled fine-wire electromyograms from all seven muscles of the index finger into a seven-dimensional vector defining the full muscle coordination pattern-and quantified its temporal evolution as its alignment with a reference coordination pattern vector for steady-state force production. As predicted by numerical optimizations to neuromuscular delays, our empirical and sigmoidal nonlinear regression analyses show that the coordination pattern transitions begin sooner for the more difficult tasks than for the easier tasks ( approximately 120 ms, P < 0.02, and approximately 115 ms, P < 0.015, respectively) and that the coordination pattern transition in alignment is well represented by a sigmoidal trend (R;2 > 0.7 in most cases). Importantly, the force vector following contact had smaller directional error (P < 0.02) for the more difficult task even though the transition in coordination pattern was less stereotypical and uniform than for the easier task. These adaptations of transition strategy to task difficulty are compatible with an optimization to counteract neuromuscular delays and noise to enable this fundamental element of dexterous manipulation.
authors.affiliation: Sibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, New York, USA.
authors.forename: Flor A
authors.initials: FA
authors.lastname: Cianchetti
authors.forename: Francisco J
authors.initials: FJ
authors.lastname: Valero-Cuevas
mesh_terms: D000328:Adult; D004576:Electromyography; D005385:Fingers / Q000502:physiology*; D006801:Humans; D009043:Motor Activity / Q000502:physiology*; D018482:Muscle, Skeletal / Q000502:physiology; D017711:Nonlinear Dynamics; D011597:Psychomotor Performance / Q000502:physiology*; D012044:Regression Analysis; D013647:Task Performance and Analysis; D013997:Time Factors; D055815:Young Adult