Reward-driven changes in striatal pathway competition shape evidence evaluation in decision-making
Fig 5
DDM fits to CBGT-simulated behavior reveals pathway-specific effects on drift rate and threshold mechanisms.
A: ΔDIC scores, showing the relative goodness-of-fit of all single- and dual-parameter DDMs considered (top) and all DDM regression models considered (bottom) compared to that of the null model (all parameters held constant across conditions; see Table 2). The ΔDIC score of the best-fitting model at each stage is plotted in green. The best overall fit was provided by DDM regression model III. B: DDM schematic showing the change in v and a across low (blue), medium (cyan), and high (yellow) reward conditions, with the threshold for L and R represented as the upper and lower boundaries, respectively. C: Posterior distributions in each reward condition for a (Eq 1), estimated on each trial as a function of the average iMSN firing rate across left and right action channels (see Iall in Fig 4C), and v (Eq 2), estimated on each trial as a function of the the difference between dMSN firing rates in the left and right channels (DL − DR in Fig 4B). D: Histograms and kernel density estimates showing the CBGT-simulated and DDM-predicted RT distributions, respectively. E: Point plots showing the CBGT network’s average accuracy and RT across reward conditions overlaid on bars showing the DDM-predicted averages.