Analysis of reflex modulation with a biologically realistic neural network.

Arno H.A. Stienen, Alfred C. Schouten*, Jasper Schuurmans, Frans C.T. van der Helm

*Corresponding author for this work

    Research output: Contribution to journalArticleAcademicpeer-review

    19 Citations (Scopus)
    13 Downloads (Pure)

    Abstract

    In this study, a neuromusculoskeletal model was built to give insight into the mechanisms behind the modulation of reflexive feedback strength as experimentally identified in the human shoulder joint. The model is an integration of a biologically realistic neural network consisting of motoneurons and interneurons, modeling 12 populations of spinal neurons, and a one degree-of-freedom musculoskeletal model, including proprioceptors. The model could mimic the findings of human postural experiments, using presynaptic inhibition of the Ia afferents to modulate the feedback gains. In a pathological case, disabling one specific neural connection between the inhibitory interneurons and the motoneurons could mimic the experimental findings in complex regional pain syndrome patients. It is concluded that the model is a valuable tool to gain insight into the spinal contributions to human motor control. Applications lay in the fields of human motor control and neurological disorders, where hypotheses on motor dysfunction can be tested, like spasticity, clonus, and tremor.
    Original languageEnglish
    Pages (from-to)333-348
    Number of pages16
    JournalJournal of computational neuroscience
    Volume23
    DOIs
    Publication statusPublished - 2007

    Keywords

    • Spinal reflexes
    • Biological neural network
    • Human motor control
    • Neuromusculoskeletal model
    • Complex regional pain syndrome

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