Figure S4.

In Mouse dCA1, Representational Similarity between Activity Patterns for Xn and Yn in Set 1 Is Not Explained by Spatial Trajectory, Related to Figures 3, 4, 5, and 6

In mice: (A-D) Overlaid trajectory for an example mouse during visual cues (Yn) and auditory cues (Xn). Blue indicates the start of the trajectory and red indicates the end of the trajectory. Left hand panels: complete trajectories during the cue. Right hand panels: trajectories filtered by the “decision point” of the mouse, as applied in Figures 3, 4, 5, and 6. The “decision point” of the mouse is defined as the time point where the speed of the mouse was below 5cm/s prior to visiting the outcome area on that trial (see STAR Methods). Filtering the trial data by the decision point eliminated time periods where the mouse was at or near the dispenser, thus controlling for spatial confounds in set 1. (A) Trajectories during visual cue Y1 from set 1. (B) Trajectories during visual cue Y2 from set 2. (C) Trajectories during auditory cues Xn from set 1 and 2 for correctly inferred trials. (D) Trajectories during auditory cues Xn from set 1 and 2 for incorrectly inferred trials. (E) Schematic showing birds-eye view of the open field used for the example mouse shown in A-D. (F) The average representational similarity matrices (RSMs) across recording days for spatial trajectories during cues Xn and Yn, after filtering by the decision point and dividing the data by performance in the inference test. Rank-transformed and scaled between [0 to 1] for visualization purposes. (G-H) The average representational similarity for ‘within set’ versus ‘between set’ spatial trajectories across cues Xn and Yn, after filtering by the decision point and splitting by performance in the inference test. The group mean was compared against a null distribution generated by permuting the identity labels assigned to the auditory cues Xn. (G) Across both set 1 and 2, spatial trajectories during the auditory cues Xn significantly predicted the trajectories for the associated visual cue Yn, ([within set XnYn correlation] – [between set XnYn correlation], ‘correct inference’ p = 0.014, ‘incorrect inference’ p = 0.687). (H) Across set 1 alone, spatial trajectories during the auditory cues Xn did not significantly predict the trajectories for the associated visual cue Yn, ([within XnYn correlation] – [between XnYn correlation], ‘correct inference’ p = 0.957, ‘incorrect inference’ p = 0.151). (I) Across set 1 alone, the single-unit activity in neurons recorded from dCA1 during auditory cues Xn significantly predicted the activity patterns for the associated visual cue Yn during correct but not incorrect inference ([within set XnYn correlation] – [between set XnYn correlation]). The group mean was compared against a null distribution generated by permuting the identity labels assigned to the auditory cues Xn (‘correct inference’ p = 0.002, ‘incorrect inference’ p = 0.865). Given the absence of significant spatial correlations for set 1 shown in H, this result shows that during correct inference, dCA1 ensemble activity predicted the associated cue Yn over and above the spatial location of the animal.