An object can be used in multiple contexts, each requiring different hand actions. How the central nervous system builds and maintains memory of such dexterous manipulations remains unclear. We conducted experiments in which human subjects had to learn and recall manipulations performed in two contexts, A and B. Both contexts involved lifting the same L-shaped object whose geometry cued its asymmetrical mass distribution. Correct performance required producing a torque on the vertical handle at object lift onset to prevent it from tilting. The torque direction depended on the context, i.e., object orientation, which was changed by 180° object rotation about a vertical axis. With an A1B1A2context switching paradigm, subjects learned A1in the first block of eight trials as indicated by a torque approaching the required one. However, subjects made large errors in anticipating the required torque when switching to B1immediately after A1(negative transfer), as well as when they had to recall A1when switching to A2after learning B through another block of eight lifts (retrieval interference). Classic sensorimotor learning theories attribute such interferences to multi-rate, multistate error-driven updates of internal models. However, by systematically changing the interblock break duration and within-block number of trials, our results suggest an alternative explanation underlying interference and retention of dexterous manipulation. Specifically, we identified and quantified through a novel computational model the nonlinear interaction between two sensorimotor mechanisms: a shortlived, context-independent, use-dependent sensorimotor memory and a context-sensitive, error-based learning process.
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