Human movements with or without vision exhibit timing (i.e. speed and duration) and variability characteristics which are not well captured by existing computational models. Here, we introduce a stochastic optimal feedforward-feedback control (SFFC) model that can predict the nominal timing and trial-by-trial variability of self-paced arm reaching movements carried out with or without online visual feedback of the hand. In SFFC, movement timing results from the minimization of the intrinsic factors of effort and variance due to constant and signal-dependent motor noise, and movement variability depends on the integration of visual feedback. Reaching arm movements data are used to examine the effect of online vision on movement timing and variability, and test the model. This modelling suggests that the central nervous system predicts the effects of sensorimotor noise to generate an optimal feedforward motor command, and triggers optimal feedback corrections to task-related errors based on the available limb state estimate.
Sleep benefits the consolidation of motor skills learned by physical practice, mainly through periodic thalamocortical sleep spindle activity. However, motor skills can be learned without overt movement, either through motor imagery or action observation. Here, we investigated whether sleep spindle activity also supports the consolidation of non-physically learned movements. Forty-five electroencephalographic sleep recordings were collected during a daytime nap after motor sequence learning by physical practice, motor imagery or action observation. Our findings revealed that irrespective of the modality of practice, spindles tend to cluster in trains on a low-frequency time scale of about 50 seconds, and during which spindles iterate every 3-4 seconds. However, despite this apparent modality-unspecific temporal organization of sleep spindles, different behavioral outcomes were elicited. We show that a daytime nap offers an early sleep window that promotes the retention of the learned motor skill following PP and MI practice, and its generalizability towards the transfer of skill from one effector to another after AO practice. Altogether, we demonstrated that the temporal cluster-based organization of sleep spindles may be a general mechanism for effective memory reprocessing.
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