Use It and Improve It or Lose It: Interactions between Arm Function and Use in Humans Post-stroke

• Type of Material: Article
• Authors: Yukikasu Hidaka, University of Southern California; Cheol E. Han, University of Southern California; Steven L Wolf, Emory University; Carolee J. Winstein, University of Southern California; Nicolas Schweighofer, University of Southern California
• Language: English
• Date: 2012-02-01
• Publisher: Public Library of Science
• Publication Version: Final Published Version
• Copyright Statement: © 2012 Hidaka et al.
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1371/journal.pcbi.1002343
• Title of Journal or Parent Work: PLoS Computational Biology
• ISSN: 1553-734X
• Volume: 8
• Issue: 2
• Start Page: e1002343
• End Page: e1002343
• Grant/Funding Information: This work was funded in part by grant NIH RO3 HD050591-02, R01 HD065438, and R01 HD 37606 and by the National Research Foundation of Korea, Ministry of Education, Science and Technology (R32-10142).
• Keywords: NEUROREHABILITATION; Life Sciences & Biomedicine; Biochemical Research Methods; RECOVERY; Mathematical & Computational Biology; INDUCED MOVEMENT THERAPY; RANDOMIZED-TRIAL; Biochemistry & Molecular Biology; Science & Technology; PLASTICITY; STROKE; REORGANIZATION; MATHEMATICAL & COMPUTATIONAL BIOLOGY; BIOCHEMICAL RESEARCH METHODS; SELF-EFFICACY; REHABILITATION; UPPER EXTREMITY FUNCTION
• Research Categories: Health Sciences, Rehabilitation and Therapy; Computer Science; Biology, Neuroscience

Abstract

"Use it and improve it, or lose it" is one of the axioms of motor therapy after stroke. There is, however, little understanding of the interactions between arm function and use in humans post-stroke. Here, we explored putative non-linear interactions between upper extremity function and use by developing a first-order dynamical model of stroke recovery with longitudinal data from participants receiving constraint induced movement therapy (CIMT) in the EXCITE clinical trial. Using a Bayesian regression framework, we systematically compared this model with competitive models that included, or not, interactions between function and use. Model comparisons showed that the model with the predicted interactions between arm function and use was the best fitting model. Furthermore, by comparing the model parameters before and after CIMT intervention in participants receiving the intervention one year after randomization, we found that therapy increased the parameter that controls the effect of arm function on arm use. Increase in this parameter, which can be thought of as the confidence to use the arm for a given level of function, lead to increase in spontaneous use after therapy compared to before therapy.