John Porrill1, Paul Dean, James V Stone
1Department of Psychology, The University of Sheffield, Sheffield S10 2UR, UK. j.porrill@sheffield.ac.uk
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This study presents a novel recurrent decorrelation control architecture for motor learning, demonstrating its convergence and advantages for modular control. The model learns without requiring motor error, offering a new perspective on cerebellar function.
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