Fig. S5.

Stimulus variance captured by mnemonic and dynamic subspaces and generalizability of the dynamic subspace. (A and B) Stimulus variance captured by the dynamic subspace as a function of the training timepoint and testing point. That is, activity at the training time is used to define the dynamic subspace, and the activity at the testing time is projected into that subspace. The diagonal elements, when training time and testing time are the same, are plotted in the Fig. 3 A and B. (C and D) The relative difference in stimulus variance captured for dynamic vs. mnemonic subspaces ($V_{dyn}$ and $V_{mne}$, respectively), as a function of training time and testing time during the cue and delay epochs. That is, the value plotted is $z(t_i,t_j)=V_{dyn}(t_i,t_j)/V_{mne}(t_j)$. Red (blue) regions show where the dynamic subspace has higher (lower) stimulus variance captured than the mnemonic subspace. These results show that the dynamic subspace classifier does not generalize well, so that for off-diagonal elements when training time and testing time are separated by more than 0.5 s, the mnemonic subspace shows greater performance. This characterizes the timescales of dynamic coding. Color bars have a logarithmic scale.