Conventional analysis of trial-by-trial adaptation is biased: Empirical and theoretical support using a Bayesian estimator
Fig 1
Single subject movement data with analysis of perturbation adaptation and trial-by-trial adaptation rates.
(a) Trial-by-trial angular error data for a block of 80 consecutive movements of a human subject controlling a cursor with electromyographic signals. Red points indicate the trial and magnitude of catch-trial perturbations. Data from Subject ID# 2016–127 from Shehata et al. [25]. (b) Linear regression of Errorn+1vs. Errorn for trials in a. Red line indicates line of best fit whose slope (-0.32) is defined as the perturbation adaptation rate. (c) Linear regression of ΔError vs. Error for each consecutive sequence of unperturbed trials between perturbations. The trial-by-trial adaptation rate (-1.20) is calculated as the mean of all regression coefficients.