What is the nature of motor adaptation to dynamic perturbations?

Abstract

When human participants repeatedly encounter a velocity-dependent force field that distorts their movement trajectories, they adapt their motor behavior to recover straight trajectories. Computational models suggest that adaptation to a force field occurs at the action selection level through changes in the mapping between goals and actions. The quantitative prediction from these models indicates that early perturbed trajectories before adaptation and late unperturbed trajectories after adaptation should have opposite curvature, i.e. one being a mirror image of the other. We tested these predictions in a human adaptation experiment and we found that the expected mirror organization was either absent or much weaker than predicted by the models. These results are incompatible with adaptation occurring at the action selection level but compatible with adaptation occurring at the goal selection level, as if adaptation corresponds to aiming toward spatially remapped targets.

The M-basis Functions and Their Application

“…Equation (13) shows that the solution of ( 1) is a linear combination of the M-basis functions scaled by the time duration (T) and boundary conditions (B).…”

“…Similar to [2], it is easy to prove that the solution to (1) is a (2n-1) th -order polynomial. Therefore, inspired by what is written above, it is possible to show that the solution of (1) can be described simply by (13) for any order of n.…”

“…Subject to knowing the boundary conditions, i.e., the values of θ and up to the (n-1) th derivative of θ at t = 0 and t = tf, we will show that the solution to (1) is a linear combination of 2n basis functions that we call M-basis functions. First, the third-order (n = 3) is discussed because (1) results in minimum jerk patterns [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16].…”