Abstract
To test the hypothesis that, in the context of robotic therapy designed to enhance proprioceptive feedback via a Hebbian model, integrity of both somatosensory and motor systems would be important in understanding interparticipant differences in treatment-related motor gains.MethodsIn 30 patients with chronic stroke, behavioral performance, neural injury, and neural function were quantified for somatosensory and motor systems. Patients then received a 3-week robot-based therapy targeting finger movements with enhanced proprioceptive feedback.ResultsHand function improved after treatment (Box and Blocks score increase of 2.8 blocks, p = 0.001) but with substantial variability: 9 patients showed improvement exceeding the minimal clinically important difference (6 blocks), while 8 patients (all of whom had >2-SD greater proprioception deficit compared to 25 healthy controls) showed no improvement. In terms of baseline behavioral assessments, a somatosensory measure (finger proprioception assessed robotically) best predicted treatment gains, outperforming all measures of motor behavior. When the neural basis underlying variability in treatment response was examined, somatosensory-related variables were again the strongest predictors. A multivariate model combining total sensory system injury and sensorimotor cortical connectivity (between ipsilesional primary motor and secondary somatosensory cortices) explained 56% of variance in treatment-induced hand functional gains (p = 0.002).ConclusionsMeasures related to the somatosensory network best explained interparticipant differences in treatment-related hand function gains. These results underscore the importance of baseline somatosensory integrity for improving hand function after stroke and provide insights useful for individualizing rehabilitation therapy.ClinicalTrials.gov identifier:NCT02048826.
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CITATION STYLE
Ingemanson, M. L., Rowe, J. R., Chan, V., Wolbrecht, E. T., Reinkensmeyer, D. J., & Cramer, S. C. (2019). Somatosensory system integrity explains differences in treatment response after stroke. Neurology, 92(10), E1098–E1108. https://doi.org/10.1212/WNL.0000000000007041
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