A recurrent neural network framework for flexible and adaptive decision making based on sequence learning
Fig 10
Task 4: Two-step decision task.
a. The two-step task. The thick and thin lines denote the common and rare transitions, respectively. The contingencies indicated by the dashed lines are reversed across blocks. b. The switching behavior. Trials are aligned to the block switch (trial 0). The performance first drops to below the chance level but then gradually recovers. c. The probability of repeating the previous choice. The stay probabilities of the subsequent trials are higher for the CR and the RU trials than the RR and the CU trials. d. Trial history effects. The choice in the current trial is affected by the trial types in the previous trials. Solid dots indicate significant effect (Bonferroni correction, p < 0.05). e. Factors affecting the choices. ※ indicates significance (p<0.01). f. Units in the hidden layer encode the difference between the estimated Q-values of the two actions. Greys lines represent the predictions based on the units’ activities in each run, and the black line is the average across runs. g. The response difference between the two choice output units is correlated with the difference between the estimated Q-values of the two actions.