Feedback-Feedforward Dynamics Shape De Novo Motor Learning
Avraham, C.; Mawase, F.
Show abstract
Humans excel at adjusting movements and acquiring new skills through feedback corrections and predictive control, yet how these feedback-feedforward computations evolve in the motor system remains unclear. We investigated this process by examining how humans learned a novel, continuous visuomotor mirror reversal (MR) tracking task over multiple days. Using a frequency-dependent system-identification approach and responses to cursor perturbations, we dissociated feedback-driven corrections from predictive feedforward adjustments. Our findings reveal two distinct learning pathways: early learning relies on rapid, corrective feedback at lower frequencies, while feedforward control gradually emerges at higher frequencies, compensating for feedback limitations. These findings suggest that motor learning involves a dynamic interplay between feedback and feedforward control, providing mechanistic insights into sensorimotor learning, with implications for optimizing motor skill acquisition and neurorehabilitation strategies.
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