A Biophysically Based Neural Model of Matching Law Behavior: Melioration by Stochastic Synapses

Mechanism of melioration and the limit for achieving perfect matching. A, For a given choice probability, the return from each target (red for A and green for B) is computed and is plotted as a function of the probability of choosing target A (in all panels). The baiting probability on target A is three times the baiting probability on target B, and the overall baiting probability is equal to 0.3. Matching happens at a choice probability (P_A = 0.782) for which the returns from the two targets are equal. At this choice probability, the total income is optimal (blue curve) showing that, in this task, matching is optimal. B, The choice probability for target A, predicted by the model (using Eq. 6) is shown in black for σ = 10%. The steady state of the model is the point at which the predicted and current choice probabilities are equal, which is given by the intersection of the black curve with the diagonal line. The location of the steady state falls short of the prediction of matching, a phenomenon called undermatching. C, For a smaller value of σ = 5%, the steady state is closer to the prediction of matching (compare B, C).