Figure 4.

ACC Represents the Full State-Action Space

(A–C) Projection of the average population activity for different trial types into the low-dimensional space that captures the most variance between trial types. Trial types were defined by the eight combinations of choice, second step, and trial outcome. Letters on the trajectories indicate the trajectory start (S; 1,000 ms before choice), the choice (C), outcome (O), and trajectory end (E; 1,000 ms after outcome). (A) Three-dimensional plot showing projections onto first three principal components. (B) Projection onto PC1 and PC2, which represent second-step and choice, respectively. (C) Projection onto PC4 and PC5, which differentiate trial outcomes.

(D and E) Decoding analysis assessing how accurately ACC population activity differentiates between different locations in task’s state-action space. (D) Diagram showing the ten different locations (red dots) in the tasks state-action space used in the decoding analysis. (E) Confusion matrix showing the cross-validated probability of decoding each location given the actual location the activity was from.