Because each patient post stroke has unique impairments and function, it is important to depart from a """"""""one size fits all"""""""" approach to rehabilitation. Although there is now evidence that motor therapy can improve function and use of the more affected limb for patients with moderate to mild impairments, change in use in the months following therapy is variable: for some patients there is an increase in use, but for others a decrease in use. Our long-term goal is to determine prospectively the dose of therapy that leads to further improvements of use after therapy for individual patients while keeping cost at reasonable levels - we call this dose critical dose. Our objective here is to investigate long-term predictions of use as a function of the dose of therapy and of the patient's neurological and behavioral characteristics. Our general hypothesis is that, for a subset of patients, there is a threshold level for arm and hand function to be achieved after therapy, such that if therapy brings function above this threshold, spontaneous use and function will reinforce each other in a virtuous circle. We formulated our hypothesis based on computational models that demonstrate such a threshold and account for existing data. We will address our general hypothesis and accomplish our objective with two aims.
Aim 1. Determine the effect of a distributed dose of therapy on immediate and long-term gains in upper extremity use.
Aim 2 : Develop a means to compute the critical dose for individual patients. With the first aim, we will test our general hypothesis and generate relevant clinical data of function and use. The data will then be used in the second aim to develop a predictive model, based on the Extended Kalman Filter, of long-term arm and hand use as a function of the dose of therapy as well as behavioral and neurological data. Our proposed work is significant because such a predictive model of stroke recovery, once subjected under future funding to clinical trials, can be used to influence policy regarding the necessary dosage of effective treatments at a reasonable cost for the growing number of persons who have survived stroke. This work will also make an important neuro- scientific contribution as we will model, and test behaviorally, the causal and adaptive linkages between the decisions to use the affected arm and recovery of motor function.

Public Health Relevance

Stroke is the leading cause of disability in the US, and about 65% of stroke survivors experience mostly unilateral long-term upper extremity functional limitations. Improving use of the more affected arm is important because difficulty in using this arm in daily tasks has been associated with reduced quality of life. Although there is now definite evidence that motor training can improve recovery of function and use for patients with moderate to mild impairments, in some cases, the gains in arm use due to therapy are small and may not be sustained. We propose here a novel evidence-based method to allow therapists to determine in advance of treatment and for individual patients, the dose of therapy that maximizes the efficacy of treatment while keeping cost at reasonable levels for each patient.

Agency
National Institute of Health (NIH)
Institute
Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
Type
Research Project (R01)
Project #
5R01HD065438-02
Application #
8210967
Study Section
Musculoskeletal Rehabilitation Sciences Study Section (MRS)
Program Officer
Shinowara, Nancy
Project Start
2011-01-10
Project End
2015-12-31
Budget Start
2012-01-01
Budget End
2012-12-31
Support Year
2
Fiscal Year
2012
Total Cost
$344,250
Indirect Cost
$131,750
Name
University of Southern California
Department
Dentistry
Type
Schools of Dentistry
DUNS #
072933393
City
Los Angeles
State
CA
Country
United States
Zip Code
90089
Kim, Sujin; Park, Hyeshin; Han, Cheol E et al. (2018) Measuring Habitual Arm Use Post-stroke With a Bilateral Time-Constrained Reaching Task. Front Neurol 9:883
Schweighofer, Nicolas; Wang, Chunji; Mottet, Denis et al. (2018) Dissociating motor learning from recovery in exoskeleton training post-stroke. J Neuroeng Rehabil 15:89
Kim, Bokkyu; Fisher, Beth E; Schweighofer, Nicolas et al. (2018) A comparison of seven different DTI-derived estimates of corticospinal tract structural characteristics in chronic stroke survivors. J Neurosci Methods 304:66-75
Park, Hyeshin; Schweighofer, Nicolas (2017) Nonlinear mixed-effects model reveals a distinction between learning and performance in intensive reach training post-stroke. J Neuroeng Rehabil 14:21
Wang, Ximing; Liu, Brent J; Martinez, Clarisa et al. (2016) Development of a novel imaging informatics-based system with an intelligent workflow engine (IWEIS) to support imaging-based clinical trials. Comput Biol Med 69:261-9
Wang, Chunji; Xiao, Yupeng; Burdet, Etienne et al. (2016) The duration of reaching movement is longer than predicted by minimum variance. J Neurophysiol 116:2342-2345
Reinkensmeyer, David J; Burdet, Etienne; Casadio, Maura et al. (2016) Computational neurorehabilitation: modeling plasticity and learning to predict recovery. J Neuroeng Rehabil 13:42
Park, Hyeshin; Kim, Sujin; Winstein, Carolee J et al. (2016) Short-Duration and Intensive Training Improves Long-Term Reaching Performance in Individuals With Chronic Stroke. Neurorehabil Neural Repair 30:551-61
Martinez, Clarisa A; Wang, Chunji (2015) Structural constraints on learning in the neural network. J Neurophysiol 114:2555-7
Schweighofer, Nicolas; Xiao, Yupeng; Kim, Sujin et al. (2015) Effort, success, and nonuse determine arm choice. J Neurophysiol 114:551-9

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