Recognition memory for human motor learning

The Consolidation of Newly Learned Movements Depends upon the Somatosensory Cortex in Humans

Studies using magnetic brain stimulation indicate the involvement of somatosensory regions in the acquisition and retention of newly learned movements. Recent work found an impairment in motor memory when retention was tested shortly after the application of continuous theta-burst stimulation (cTBS) to the primary somatosensory cortex, compared with stimulation of the primary motor cortex or a control zone. This finding that the somatosensory cortex is involved in motor memory retention whereas the motor cortex is not, if confirmed, could alter our understanding of human motor learning. It would indicate that plasticity in sensory systems underlies newly learned movements, which is different than the commonly held view that adaptation learning involves updates to a motor controller. Here we test this idea. Participants were trained in a visuomotor adaptation task, with visual feedback gradually shifted. Following adaptation, cTBS was applied either to M1, S1, or an occipital cortex control area. Participants were tested for retention 24 h later. It was observed that S1 stimulation led to reduced retention of prior learning, compared with stimulation of M1 or the control area (with no significant difference between M1 and control). In a further control, cTBS was applied to S1 following training with unrotated feedback, in which no learning occurred. This had no effect on movement in the retention test indicating the effects of S1 stimulation on movement are learning specific. The findings are consistent with the S1 participation in the encoding of learning-related changes to movements and in the retention of human motor memory.

Working memory constraints for visuomotor retrieval strategies

Recent work has shown the fundamental role that cognitive strategies play in visuomotor adaptation. Although algorithmic strategies, such as mental rotation, are flexible and generalizable, they are computationally demanding. To avoid this computational cost, people can instead rely on memory retrieval of previously successful visuomotor solutions. However, such a strategy is likely subject to stimulus-response associations and rely heavily on working memory. In a series of five experiments, we sought to estimate the constraints in terms of capacity and precision of working memory retrieval for visuomotor adaptation. This was accomplished by leveraging different variations of visuomotor item-recognition and visuomotor rotation tasks where we associated unique rotations with specific targets in the workspace and manipulated the set size (i.e., number of rotation-target associations). Notably, from experiment 1 to 4, we found key signatures of working memory retrieval and not mental rotation. In particular, participants were less accurate and slower for larger set sizes and less recent items. Using a Bayesian latent-mixture model, we found that such decrease in performance was the result of increasing guessing behavior and less precise memories. In addition, we estimated that participants' working memory capacity was limited to two to five items, after which guessing increasingly dominated performance. Finally, in experiment 5, we showed how the constraints observed across experiments 1 to 4 can be overcome when relying on long-term memory retrieval. Our results point to the opportunity of studying other sources of memories where visuomotor solutions can be stored (e.g., episodic memories) to achieve successful adaptation.NEW & NOTEWORTHY We show that humans can adapt to feedback perturbations in different variations of the visuomotor rotation task by retrieving the successful solutions from working memory. In addition, using a Bayesian latent-mixture model, we reveal that guessing and low-precision memories are both responsible for the decrease in participants' performance as the number of solutions to memorize increases. These constraints can be overcome by relying on long-term memory retrieval resulting from extended practice with the visuomotor solutions.

The human somatosensory cortex contributes to the encoding of newly learned movements

Recent studies have indicated somatosensory cortex involvement in motor learning and retention. However, the nature of its contribution is unknown. One possibility is that the somatosensory cortex is transiently engaged during movement. Alternatively, there may be durable learning-related changes which would indicate sensory participation in the encoding of learned movements. These possibilities are dissociated by disrupting the somatosensory cortex following learning, thus targeting learning-related changes which may have occurred. If changes to the somatosensory cortex contribute to retention, which, in effect, means aspects of newly learned movements are encoded there, disruption of this area once learning is complete should lead to an impairment. Participants were trained to make movements while receiving rotated visual feedback. The primary motor cortex (M1) and the primary somatosensory cortex (S1) were targeted for continuous theta-burst stimulation, while stimulation over the occipital cortex served as a control. Retention was assessed using active movement reproduction, or recognition testing, which involved passive movements produced by a robot. Disruption of the somatosensory cortex resulted in impaired motor memory in both tests. Suppression of the motor cortex had no impact on retention as indicated by comparable retention levels in control and motor cortex conditions. The effects were learning specific. When stimulation was applied to S1 following training with unrotated feedback, movement direction, the main dependent variable, was unaltered. Thus, the somatosensory cortex is part of a circuit that contributes to retention, consistent with the idea that aspects of newly learned movements, possibly learning-updated sensory states (new sensory targets) which serve to guide movement, may be encoded there.

Proprioception-based movement goals support imitation and are disrupted in apraxia

The ability to imitate observed actions serves as an efficient method for learning novel movements and is specifically impaired (without concomitant gross motor impairments) in the neurological disorder of limb apraxia, a disorder common after left hemisphere stroke. Research with apraxic patients has advanced our understanding of how people imitate. However, the role of proprioception in imitation has been rarely assessed directly. Prior work has proposed that proprioceptively sensed body position is transformed into a visual format, supporting the attainment of a desired imitation goal represented visually (i.e., how the movement should look when performed). In contrast, we hypothesized a more direct role for proprioception: we suggest that movement goals are also represented proprioceptively (i.e., how a desired movement should feel when performed), and the ability to represent or access such proprioceptive goals is deficient in apraxia. Using a novel imitation task in which a robot cued meaningless trajectories proprioceptively or visually, we probed the role of each sensory modality. We found that patients with left hemisphere stroke were disproportionately worse than controls at imitating when cued proprioceptively versus visually. This proprioceptive versus visual disparity was associated with apraxia severity as assessed by a traditional imitation task, but could not be explained by general proprioceptive impairment or speed-accuracy trade-offs. These data suggest that successful imitation depends in part on the ability to represent movement goals in terms of how those movements should feel, and that deficits in this ability contribute to imitation impairments in patients with apraxia.

Recognition capability of one's own skilled movement is dissociated from acquisition of motor skill memory

When we have rehearsed a movement using an object, we can reproduce the movement without holding the object. However, the reproduced movement sometimes differs from the movement holding a real object, likely because movement recognition is inaccurate. In the present study, we tested whether the recognition capability was dissociated from the acquisition of motor skill memory. Twelve novices were asked to rotate two balls with their right hand as quickly as possible; they practiced the task for 29 days. To evaluate recognition capability, we calculated the difference in coordination pattern of all five digits between the ball-rotation movement and the reproduced movement without holding balls. The recognition capability did not change within the first day, but improved after one week of practice. On the other hand, performance of the ball rotation significantly improved within the first day. Since improvement of performance is likely associated with acquisition of motor skill memory, we suggest that recognition capability, which reflects the capability to cognitively access motor skill memory, was dissociated from the acquisition of motor skill memory. Therefore, recognition of one’s own skilled movement would rely on a hierarchical structure of acquisition of motor skill memory and cognitive access to that memory.