The neural control of accurate hand force production

Sayan Deep De, Janina M. Prado-Rico, Mark L. Latash

Research output: Contribution to journalArticlepeer-review

Abstract

We addressed the controversy on the relative role of the reciprocal and coactivation commands in the neural control of force in multi-finger tasks. Specifically, we tested the hypothesis that a mechanical variable serving as a proxy of the coactivation command will scale with force magnitude. We also explored indices of force-stabilizing synergies assessed at the level of the reciprocal and coactivation commands to the hand and to the individual fingers and at the level of finger coordination. Healthy subjects performed a ramp-and-hold isometric force production to various force magnitudes. An “inverse piano” device was used to estimate mechanical reflections of the reciprocal and coactivation commands at steady states. The uncontrolled manifold framework was used to estimate synergy indices. Mechanical reflections of both commands showed significant linear scaling with the force magnitude, stronger for the coactivation command. Over multiple repetitions, the two commands showed strong hyperbolic covariation, the strongest for the whole hand, and the weakest for the little finger. There were four-finger force-stabilizing synergies. However, the indices of two types of synergies, four-finger and reciprocal-coactivation ones, showed no significant correlation. We interpret the results as pointing at two sources of supraspinal synergies tentatively associated with subcortical circuitry and cortical mechanisms. During voluntary movements, the reciprocal command has an advantage and may be hierarchically higher than the coactivation command. During force-production tasks, changes in the coactivation command are used more consistently to fit the task. The results suggest that movement generation and force production tasks may involve qualitatively different control strategies.

Original languageEnglish (US)
Pages (from-to)359-369
Number of pages11
JournalNeuroscience
Volume580
DOIs
StatePublished - Aug 6 2025

All Science Journal Classification (ASJC) codes

  • General Neuroscience

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