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Pubmed for Handhelds

PUBMED FOR HANDHELDS

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  • Title: Bilateral deficit and symmetry in finger force production during two-hand multifinger tasks.
    Author: Li S, Danion F, Latash ML, Li ZM, Zatsiorsky VM.
    Journal: Exp Brain Res; 2001 Dec; 141(4):530-40. PubMed ID: 11810146.
    Abstract:
    A comprehensive study of patterns of finger forces during one-hand and two-hand multifinger maximal force production trials was performed with particular emphasis on differences between tasks involving symmetrical and asymmetrical finger groups (symmetrical and asymmetrical tasks). Twelve healthy right-handed subjects performed maximal voluntary force production tasks with different finger combinations. Force deficit (FD) for a finger group within a hand was defined as a drop in peak force in a multifinger task as compared to the sum of individual finger peak forces in single-finger tasks. FD showed a dependence on both the number of fingers within the hand and the number of fingers in the other hand. An additional drop in peak finger forces was seen in two-hand tests (bilateral deficit, BD). BD summed over two hands was independent of the number of fingers involved in the two-hand tasks, but dependent on the distribution of fingers between the two hands. BD for a hand was larger for tasks involving fewer fingers within the hand and more fingers in the other hand. It was higher for asymmetrical tasks than for symmetrical tasks. The difference between asymmetrical and symmetrical tasks was due to the different behavior of asymmetrically involved fingers. FD was larger for asymmetrical master (explicitly involved) fingers, while forces produced involuntarily by asymmetrical slave (explicitly non-involved) fingers were larger. These differences brought down the total moment produced by both hands in the frontal plane. FD and BD are phenomena of different origin whose effects sum up. The observations have led to further development of a previously proposed double-representation, mirror-image (DoReMi) hypothesis and refinement of the neural network underlying the two-hand finger interaction.
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