Electromyographic correlates of learning an internal model of reaching movements

Theoretical and psychophysical studies have suggested that humans learn to make reaching movements in novel dynamic environments by building specific internal models (IMs). Here we have found electromyographic correlates of i nternal model formation. We recorded EMG from four muscles as subjects lear ned to move a manipulandum that created systematic forces (a "force field") . We also simulated a biomechanical controller, which generated movements b ased on an adaptive IM of the inverse dynamics of the human arm and the man ipulandum. The simulation defined two metrics of muscle activation. The fir st metric measured the component of the EMG of each muscle that counteracte d the force field. We found that early in training, the field-appropriate E MG was driven by an error feedback signal. As subjects practiced, the peak of the field-appropriate EMG shifted temporally to earlier in the movement, becoming a feedforward command. The gradual temporal shift suggests that t he CNS may use the delayed error-feedback response, which was likely to hav e been generated through spinal reflex circuits, as a template to learn a p redictive feedforward response. The second metric quantified formation of t he IM through changes in the directional bias of each muscle's spatial EMG function, i.e., EMG as a function of movement direction. As subjects practi ced, co-activation decreased, and the directional bias of each muscle's EMG function gradually rotated by an amount that was specific to the field bei ng learned. This demonstrates that formation of an IM can be represented th rough rotations in the spatial tuning of muscle EMG functions. Combined wit h other recent work linking spatial tunings of EMG and motor cortical cells , these results suggest that rotations in motor cortical tuning functions c ould underlie representation of internal models in the CNS.