A recurrent neural network framework for flexible and adaptive decision making based on sequence learning
Fig 3
a. The psychometric curve. The model more often chooses the target supported by the accumulated evidence. The black curve is the fitting curve from the logistic regression. b. The leverage of each shape on choice revealed by the logistic regression is consistent with its assigned logLR. c. Reaction time. The bars show the distribution of reaction time, quantified by the number of observed shapes (right y-axis). Green and red indicate the left and right choices, respectively. The lines indicate the mean total logLR (left y-axis) at the decision time, grouped by reaction time. Trials with only 1 shape or more than 16 shapes comprise less than 0.1% of the total trials and are excluded from the plot. d. The leverage of the first 3, the second and third from the last, and the middle shapes on the choice. Only trials with more than 6 shapes are included in the analysis. No significant differences are found between any pair of the coefficients of shape regressors (two-tailed t-test with Bonferroni correction). The error bars in all panels indicate SE across runs. Some error bars are smaller than the data points and not visible.