Multiple processes may contribute to motor skill acquisition, but it is thought that many of these processes require sleep or the passage of long periods of time ranging from several hours to many days or weeks. Here we demonstrate that within a timescale of minutes, two distinct fast-acting processes drive motor adaptation. One process responds weakly to error but retains information well, whereas the other responds strongly but has poor retention. This two-state learning system makes the surprising prediction of spontaneous recovery (or adaptation rebound) if error feedback is clamped at zero following an adaptation-extinction training episode. We used a novel paradigm to experimentally confirm this prediction in human motor learning of reaching, and we show that the interaction between the learning processes in this simple two-state system provides a unifying explanation for several different, apparently unrelated, phenomena in motor adaptation including savings, anterograde interference, spontaneous recovery, and rapid unlearning. Our results suggest that motor adaptation depends on at least two distinct neural systems that have different sensitivity to error and retain information at different rates.

The nucleus accumbens (NAc) is involved in many reward-related behaviors. The NAc has two major components, the core and the shell. These two areas have different inputs and outputs suggesting that they contribute differentially to goal-directed behaviors. Using a discriminative stimulus (DS) task in rats and inactivating the NAc by blocking excitatory inputs with glutamate antagonists, we dissociated core and shell contributions to task performance. NAc core but not shell inactivation decreased responding to a reward predictive cue. In contrast, inactivation of either sub-region induced a general behavioral disinhibition. This reveals that the NAc actively suppresses actions inappropriate to the DS task. Importantly, selective inactivation of the shell but not core significantly increased responding to the non-rewarded cue. To determine if the different contributions of the NAc core and shell depend on the information encoded in their constituent neurons, we performed electrophysiological recording in rats performing the DS task. Although there was no firing pattern unique to either core or shell, the reward-predictive cue elicited more frequent and larger magnitude responses in the NAc core than in the shell. Conversely, more NAc shell neurons selectively responded to the non-rewarded stimulus. These quantitative differences might account for the different behavioral patterns that require either core or shell. Neurons with similar firing patterns could also have different effects on behavior due to their distinct projection targets.

SUMMARY Dopamine neurons promote learning by processing recent changes in reward values, such that reward may be maximized. However, such a flexible signal is not suitable for habitual behaviors that are sustained regardless of recent changes in reward outcome. We discovered a type of dopamine neuron in the monkey substantia nigra pars compacta (SNc) that retains past-learned reward values stably. After reward values of visual objects are learned, these neurons continue to respond differentially to the objects, even when reward is not expected. Responses are strengthened by repeated learning and are evoked upon presentation of the objects long after learning is completed. These “sustain-type” dopamine neurons are confined to the caudal-lateral SNc and project to the caudate tail, which encodes long-term value memories of visual objects and guides gaze automatically to stably valued objects. This population of dopamine neurons thus selectively promotes learning and retention of habitual behavior.

Generalization of motor learning refers to our ability to apply what has been learned in one context to other contexts. When generalization is beneficial, it is termed transfer, and when it is detrimental, it is termed interference. Insight into the mechanism of generalization may be acquired from understanding why training transfers in some contexts but not others. However, identifying relevant contextual cues has proven surprisingly difficult, perhaps because the search has mainly been for cues that are explicit. We hypothesized instead that a relevant contextual cue is an implicit memory of action with a particular body part. To test this hypothesis we considered a task in which participants learned to control motion of a cursor under visuomotor rotation in two contexts: by moving their hand through motion of their shoulder and elbow, or through motion of their wrist. Use of these contextual cues led to three observations: First, in naive participants, learning in the wrist context was much faster than in the arm context. Second, generalization was asymmetric so that arm training benefited subsequent wrist training, but not vice versa. Third, in people who had prior wrist training, generalization from the arm to the wrist was blocked. That is, prior wrist training appeared to prevent both the interference and transfer that subsequent arm training should have caused. To explain the data, we posited that the learner collected statistics of contextual history: all upper arm movements also move the hand, but occasionally we move our hands without moving the upper arm. In a Bayesian framework, history of limb segment use strongly affects parameter uncertainty, which is a measure of the covariance of the contextual cues. This simple Bayesian prior dictated a generalization pattern that largely reproduced all three findings. For motor learning, generalization depends on context, which is determined by the statistics of how we have previously used the various parts of our limbs.