Interaction between decision-making and motor learning when selecting reach targets in the presence of bias and noise
Fig 6
Predictive performance of the target selection model.
A: Target choices of two typical participants. Black dots show the selected target direction on each trial. The target choices of participant D gradually became densely concentrated as trial number increased, while the target choices of participant S were relatively scattered until the end of the experiment. The blue gradient shows model-predicted probability of selecting a target if it is located in that specific direction and on that specific trial. The predicted probabilities matched nicely to the actual distribution of target choices for both participants D and S. B: Probabilistic fraction correct of the model predictions on the last 50 target choices of each participant. Boundary of gray shaded area shows the estimated upper bound on the predictive performance as a function of concentration of target choices. Blue curve was fit to all data points (using Gaussian Process Regression) under different bias angles. The mean predictive performance of the model was significantly above chance. The two typical participants D and S (see Panel A) are marked in the figure.