Finger interaction during maximal radial and ulnar deviation efforts: Experimental data and linear neural network modeling

Todd C. Pataky, Mark L. Latash, Vladimir M. Zatsiorsky

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

The purpose of this study was to characterize finger interactions during radial/ulnar deviation, including interactions with flexion movements. Subjects performed single-finger and multi-finger maximal voluntary contraction (MVC), and maximal forces and various indices of interaction among the fingers were quantified. MVCs in radial/ulnar deviation were 50-80% as strong as in flexion. Along with the 'master' fingers (i.e., those explicitly instructed to produce force), substantial force production was also observed in 'slave' fingers (i.e., those not explicitly instructed to produce force), a phenomenon termed: force 'enslaving'. In addition, a drop in MVC during multi-finger tasks as compared to single finger tasks (force 'deficit') was also observed. A previously unreported phenomenon that we term: 'preferred direction enslaving' was also apparent; both master and slave fingers produced force in the instructed direction with a non-zero perpendicular component. Due to the architectural separation of the involved muscles, preferred direction enslaving provides strong evidence that enslaving results from neural rather than biomechanical factors. A final new phenomenon: 'negative deficit', or force 'facilitation' was observed in 46.4% of the trials in 21 out of 23 subjects during multi-finger lateral efforts and was further demonstrative of extensive interconnection among neurons serving hand muscles. The data were modeled with high accuracy (∼4% mean square error) using a linear neural network with motor 'commands' as inputs and finger forces as outputs. The proposed network, equivalent to linear regression, can be used to determine the extent to which finger forces are influenced by peripheral constraints during functional prehensile activities.

Original languageEnglish (US)
Pages (from-to)301-312
Number of pages12
JournalExperimental Brain Research
Volume179
Issue number2
DOIs
StatePublished - May 2007

All Science Journal Classification (ASJC) codes

  • Neuroscience(all)

Fingerprint Dive into the research topics of 'Finger interaction during maximal radial and ulnar deviation efforts: Experimental data and linear neural network modeling'. Together they form a unique fingerprint.

Cite this