Extended Data Fig. 5: Slow drift of place fields against landmarks.

a, Example of positive drift. Top, experimental gain, G (blue), and hippocampal gain, H (yellow), for epochs 1–3 of a session in which G_final was 1.769. There is no H (yellow) in the first or last 6 laps owing to the 12-lap sliding window. Middle, spikes from one putative pyramidal cell (blue dots) in the laboratory frame. Figure format is the same as in Fig. 2. Bottom, the same spikes in the landmark frame. The unit was silent for the first 12 laps but developed a strong place field in the landmark frame, which slowly drifted in the same direction as the movement of the rat over the course of the session. b, Example of negative drift from a session in which G_final was 0. In the landmark frame, the slow drift was in the direction opposite to the direction of movement of the rat. Note that the unit was completely silent in epoch 3, because the rat was not in the place field of the unit as G reached 0. c, Drift over the entire session plotted against G_final. Each point represents an experimental session. Linear fits are shown for each individual rat (coloured lines) and for the combined data (black line; n = 55 sessions, Pearson’s r₅₃ = 0.64, P = 1.5 × 10⁻⁷). The two example sessions of a and b are marked with a circle. d, Drift rate against G_final. Although the magnitude of drift is correlated with the final experimental gain (G_final), as shown in c, a confound is present because the ramp duration in epoch 2 depends on the value of G_final (for example, for G > 1, the larger the value of G_final, the more laps are required to ramp G up to that value). It is thus possible that the correlation between the total drift and G_final is due to the differences in duration of epoch 2 (and, in some sessions, epoch 3) rather than due to different rates of drift that depend on G. To control for the effect of session duration, we calculated drift rate by dividing the total drift by the total number of laps in the landmark frame over which the drift was computed. Linear fits are shown for each individual rat (coloured lines) and for the combined data (black line; n = 55 sessions, Pearson’s r₅₃ = 0.54, P = 1.9 × 10⁻⁵). The two example sessions of a and b are marked with circles. These results show that the drift rate was related to the value of G_final.