, 1998, Rutledge

et al., 2009 and Shohamy et al., 2005). Thus, our contention that initial learning of a rotation occurs through adaptation but savings results from operant learning predicts that patients with PD would show a selective savings deficit in an error-based motor learning paradigm. This is exactly what has been found: Sirolimus patients with PD were able to adapt to initial rotation as well as control subjects but they did not show savings (Bédard and Sanes, 2011 and Marinelli et al., 2009). Thus, our framework of multiple learning processes can explain this otherwise puzzling result. A prediction would be that PD patients would show no difference in learning rates between Adp+Rep− and Adp+Rep+ protocols, because only adaptation would occur. Prevailing theories

of motor learning in adaptation paradigms have been fundamentally model-based: they posit that the brain maintains an explicit internal model of its environment and/or motor apparatus that is directly used for planning of movements. When faced with a perturbation, this model is updated based on movement errors and execution of subsequent movements reflects this updated model (Shadmehr et al., 2010). We wish to define adaptation as precisely this model-based mechanism for updating a control policy in response to a perturbation. Adaptation does not invariably result in better task performance. Selleck Afatinib For example, in a previous study we showed that adaptation to rotation occurs despite conflicting with explicit task goals (Mazzoni and Krakauer, 2006). In the current study, hyper- or overadaptation occurred to some targets due to unwanted generalization; this was why the steady-state predicted by the state-space model for Adp+Rep+ showed that subjects adapted past the 70° target for near targets and insufficiently adapted for far targets ( Figure 2D). Diedrichsen and colleagues also showed that force-field adaptation occurs at the aminophylline same rate with or without concomitant use-dependent learning ( Diedrichsen et al., 2010). It appears, therefore, that adaptation is “automatic”;

it is an obligate, perhaps reward-indifferent ( Mazzoni and Krakauer, 2006), cerebellar-based ( Martin et al., 1996a, Martin et al., 1996b, Smith and Shadmehr, 2005 and Tseng et al., 2007) learning process that will attempt to reduce prediction errors whenever they occur, even if this is in conflict with task goals. In spite of the fact that most behavior in error-based motor learning paradigms is well described by adaptation, we argue here that there are phenomena in perturbation paradigms that cannot be explained in terms of adaptation alone. Instead, additional learning mechanisms must be present which are model-free in the sense that they are associated with a memory for action independently of an internal model and are likely to be driven directly by task success (i.e., reward).