Synergies at the level of motor units in single-finger and multi-finger tasks

Shirin Madarshahian, Mark L. Latash

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

We explored the organization of motor units recorded in the flexor digitorum superficialis into stable groups (MU-modes) and force-stabilizing synergies in spaces of MU-modes. Young, healthy participants performed one-finger and three-finger accurate cyclical force production tasks. Two wireless sensor arrays (Trigno Galileo, Delsys, Inc.) were placed over the proximal and distal portions of the muscle for surface recording and identification of motor unit action potentials. Principal component analysis with Varimax rotation and factor extraction was used to identify MU-modes. The framework of the uncontrolled manifold hypothesis was used to analyze inter-cycle variance in the space of MU-modes and compute the index of force-stabilizing synergy. Multiple linear regression between the first MU-mode in the three-finger task and the first MU-modes in the three single-finger tasks showed no differences between the data recorded by the two electrodes suggesting that MU-modes were unlikely to be synonymous with muscle compartments. Multi-MU-mode synergies stabilizing task force were documented across all tasks. In contrast, there were no force-stabilizing synergies in the three-finger task analyzed in the space of individual finger forces. Our results confirm the synergic organization of motor units in single-finger tasks and, for the first time, expand this result to multi-finger tasks. We offer an interpretation of the findings within the theoretical scheme of control with spatial referent coordinates expanded to the analysis of individual motor units. The results confirm trade-offs between synergies at different hierarchical levels and expand this notion to intra-muscle synergies.

Original languageEnglish (US)
Pages (from-to)2905-2923
Number of pages19
JournalExperimental Brain Research
Volume239
Issue number9
DOIs
StatePublished - Sep 2021

All Science Journal Classification (ASJC) codes

  • Neuroscience(all)

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