Online interference of declarative memory on fast and slow adaptive processes in force field motor learning

Error-based motor adaptation is currently understood as a dual-rate process involving a fast adaptive process that learns quickly but also decays rapidly and a slow process that learns slowly but has good retention. While the fast process is typically categorized as procedural learning, recent evidence suggests that it relies on the declarative memory system. To test this hypothesis, we investigated in what manner a declarative memory task interferes with two processes that supposedly underly force field adaptation in reaching. This declarative memory task, which involved learning of a list of words, was assessed through either recognition or recall, and was compared to a non-declarative, vowel counting task, using a within-subject design (n=32). We employed a Bayesian hierarchical dual-rate process model to capture the observed force compensation across trials, expecting that the parameters of the fast process would be affected by the declarative memory task. We examined the 95% highest density interval of the posterior distribution of the difference between the experimental and control condition for each parameter. While most parameters remained unaffected by the declarative memory task, the retention rate of the fast process showed a hint of reduction, suggesting a complex interplay between declarative memory and ongoing motor adaptation processes.