Coordinated force production in multi-finger tasks: finger interaction and neural network modeling

Abstract

During maximal voluntary contraction (MVC) with several fingers, the following three phenomena are observed: (1) the total force produced by all the involved fingers is shared among the fingers in a specific manner (sharing); (2) the force produced by a given finger in a multi-finger task is smaller than the force generated by this finger in a single-finger task (force deficit); (3) the fingers that are not required to produce any force by instruction are involuntary activated (enslaving). We studied involuntary force production by individual fingers (enslaving effects, EE) during tasks when (an)other finger(s) of the hand generated maximal voluntary pressing force in isometric conditions. The subjects (n = 10) were instructed to press as hard as possible on the force sensors with one, two, three and four fingers acting in parallel in all possible combinations. The EE were (A) large, the slave fingers always producing a force ranging from 10.9% to 54.7% of the maximal force produced by the finger in the single-finger task; (B) nearly symmetrical; (C) larger for the neighboring fingers; and (D) non-additive. In most cases, the EE from two or three fingers were smaller than the EE from at least one finger (this phenomenon was coined occlusion). The occlusion cannot be explained only by anatomical musculo-tendinous connections. Therefore, neural factors contribute substantially to the EE. A neural network model that accounts for all the three effects has been developed. The model consists of three layers: the input layer that models a central neural drive; the hidden layer modeling transformation of the central drive into an input signal to the muscles serving several fingers simultaneously (multi-digit muscles); and the output layer representing finger force output. The output of the hidden layer is set inversely proportional to the number of fingers involved. In addition, direct connections between the input and output layers represent signals to the hand muscles serving individual fingers (uni-digit muscles). The network was validated using three different training sets. Single digit muscles contributed from 25% to 50% of the total finger force. The master matrix and the enslaving matrix were computed; they characterize the ability of a given finger to enslave other fingers and its ability to be enslaved. Overall, the neural network modeling suggests that no direct correspondence exists between neural command to an individual finger and finger force. To produce a desired finger force, a command sent to an intended finger should be scaled in accordance with the commands sent to the other fingers.

Motor variability within a multi-effector system: experimental and analytical studies of multi-finger production of quick force pulses

“…In particular, the UCM hypothesis was used to analyze covariation of force modes (hypothetical independent elemental variables that lead to force generation by individual digits, Zatsiorsky et al 1998;Scholz et al 2002;Danion et al 2003) with respect to two hypotheses:…”

Control of finger force direction in the flexion-extension plane

“…to explore the dependence of the direction of forces produced by fingers that are not required to produce force (enslaved forces; Li et al 1998aLi et al , 1998bZatsiorsky et al 1998Zatsiorsky et al , 2000 on the target direction; and 4. to establish whether there is a multi-finger synergy stabilizing the direction of the total force.…”

Hierarchies of synergies: an example of two-hand, multi-finger tasks

“…No a priori hypotheses could be formulated with respect to these comparisons. However, differences could be expected based on earlier studies that have shown effects of hand dominance on indices of finger interaction , different ability to control finger forces independently across fingers (typically, the index finger is better controlled individually as compared to the other fingers Zatsiorsky et al 1998Zatsiorsky et al , 2000, and differences in bilateral effects in symmetrical and asymmetrical two-hand tasks (Li et al 2002). Most of the cited studies used maximal force production tasks; thus one cannot readily make predictions with respect to our task of accurate sub-maximal force production.…”