sensory discriminations through games and fine motor activities, use of velcro on objects, retrieving objects from a box filled with rice and exercises in graphesthesia, localization, stereognosis and kines-thesia. Movements of the hand, mental rehearsal to reinforce learning and tasks to quiet the nervous system were also used. Patients were educated regarding the potential for improvement in neural processing and the unaffected hand was constrained through wearing of a glove. Training was investigated in 21 subjects with order of sensory or motor training crossed, although no placebo intervention period was employed. Improvements in sensory discrimination, fine motor function and musculoskeletal measurements of the upper limb were reported following sensory training. Gains were hemispheric and training specific.
In summary, recent training programs with successful outcomes have included a number of common principles consistent with theories of learning and neural plasticity. These include: attention to the sensory stimulus; repetitive stimulation with and without vision; use of tasks that are challenging and motivating; focus on the hand; graded progression of tasks and feedback on accuracy and execution. A more detailed discussion of principles of training related to perceptual learning and neural plasticity follows with suggestions for their application.
Figure 16.2. Example single-subject case chart demonstrating SST effects on trained grids and untrained grids. Improvement in untrained fabric discriminations is evident only following introduction of the program designed to enhance generalization. Baseline conditions of repeated exposure to the stimuli were not sufficient to effect clinically significant improvement. The raw time-series data (x) and predicted time-series models (da « ) are shown. Higher scores represent an improvement in texture matching ability. The criterion of normality for the Grid Matching Test is 0.62 z' score (mean = 1.47) and for the Fabric Matching Test is 1.61 z' score (mean = 2.46). Statistical time-series analyses of trend and level effects (P < 0.01) confirm the training effects shown for this subject.
16.5 Principles of neural plasticity and learning as they apply to rehabilitation of sensation
Identification and application of principles to optimize perceptual learning and brain adaptation
Evidence of neural plasticity provides a strong foundation for restorative sensory retraining post-injury, both in acute and chronic phases. Review of theories of perceptual learning and the conditions under which neural plastic changes occur suggests a number of principles that have potential application in retraining somatosensations following PNS or CNS injury.
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