Anticipatory Control of Motion-to-Force Transitions With the Fingertips Adapts Optimally to Task Difficulty

Abstract

Cianchetti FA, Valero-Cuevas FJ. Anticipatory control of motionto-force transitions with the fingertips adapts optimally to task difficulty. J Neurophysiol 103: 108 -116, 2010. First published November 4, 2009 doi:10.1152/jn.00233.2009. 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 sevendimensional 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 (ϳ120 ms, P Ͻ 0.02, and ϳ115 ms, P Ͻ 0.015, respectively) and that the coordination pattern transition in alignment is well represented by a sigmoidal trend (R^2 Ͼ 0.7 in most cases). Importantly, the force vector following contact had smaller directional error (P Ͻ 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.

Feasibility Theory Reconciles and Informs Alternative Approaches to Neuromuscular Control

“…Secondly, Feasibility Theory can be extended to address dynamical behavior by applying it to a sequence of slices in time. That is, a dynamical task can be equivalently analyzed as a sequence of “slices” (Anderson and Pandy, 2001 ; Cianchetti and Valero-Cuevas, 2009 ; Simpson et al, 2015 ; Trinler et al, 2018 )—where one can define a feasible activation space at each slice to determine how the nervous system must change activation patterns such that it is always implementing a valid solution (Simpson et al, 2015 ). When strung together, these individual spaces give rise to a “spatiotemporal tunnel”—the time-varying extension of the feasible activation space (Figure 8 ).…”