Performance-gated deliberation: A context-adapted strategy in which urgency is opportunity cost
Fig 5
Context-conditioned analysis of PGD and comparison to AR-RL models.
(A) Shown is the reward rate as a function of incentive strength, α. The AR-RL solution with no augmented cost (c = 0) interpolates between the wait-for-certainty strategy (brown) and the one-and-done strategy (red). We also show the slow and fast context-conditioned reward rates for the two primates (blue and orange circles) and the PGD model fitted to them (crosses). For reference, we show the mean+/-std.dev. of a forthcoming dataset of 32 humans. Reward rates for the human and non-human primates are squarely in between the best (black dashed) and uniformily random (gray) strategy. (b,c) The distribution over trials of differences in decision times between model and data, |Δtdec| = |tdec,data − tdec,model|, conditioned on slow and fast block contexts. Solid lines are for PGD. Dotted lines are for the AR-RL solution using the cost rate, c*, with the lowest mean error. The residual sum of squares (RRS) for each model/block combination is displayed. (d-g) Interpolated state-conditioned survival probabilities, P(tdec = t|Nt, t), over slow (d,f) and fast (e,g) blocks. White dotted lines show the P(tdec = t|Nt, t) = 0.5 contour. (h,i) State-conditioned decision time frequencies (cross size) from AR-RL optimal decision boundaries across different values of the cost rate, c (colored crosses) for slow (h) and fast (i) conditions. Only samples with Nt < 0 and Nt > 0, respectively, are shown. For comparison, the reflected axes shows as gray crosses the state-conditioned decision time frequencies of the data.