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.
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.
|Reinkensmeyer, David J; Burdet, Etienne; Casadio, Maura et al. (2016) Computational neurorehabilitation: modeling plasticity and learning to predict recovery. J Neuroeng Rehabil 13:42|
|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|
|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|
|Schweighofer, Nicolas; Xiao, Yupeng; Kim, Sujin et al. (2015) Effort, success, and nonuse determine arm choice. J Neurophysiol 114:551-9|
|Martinez, Clarisa A; Wang, Chunji (2015) Structural constraints on learning in the neural network. J Neurophysiol 114:2555-7|
|Bains, Amarpreet Singh; Schweighofer, Nicolas (2014) Time-sensitive reorganization of the somatosensory cortex poststroke depends on interaction between Hebbian and homeoplasticity: a simulation study. J Neurophysiol 112:3240-50|
|Han, Cheol E; Kim, Sujin; Chen, Shuya et al. (2013) Quantifying arm nonuse in individuals poststroke. Neurorehabil Neural Repair 27:439-47|
|Schweighofer, Nicolas; Choi, Younggeun; Winstein, Carolee et al. (2012) Task-oriented rehabilitation robotics. Am J Phys Med Rehabil 91:S270-9|
|Hidaka, Yukikazu; Han, Cheol E; Wolf, Steven L et al. (2012) Use it and improve it or lose it: interactions between arm function and use in humans post-stroke. PLoS Comput Biol 8:e1002343|