Extended Data Fig. 1: Task structure and behavioral data, and necessity of RSC for egocentric-allocentric computations.

(a) Schematic of task structure and timing. (b) Example trial schematic showing all possible task states (see Methods for more details). Landmarks were formed by white dots displayed on a screen which served as the floor of the arena. They were only made visible when mice crossed a distance threshold. Only one landmark was visible at a time in the final training stage. Nose-pokes were only registered after mice held their nose in the port for a randomly chosen delay period that was randomized for each visit and not known to the mouse. Incorrect port visits resulted in timeouts that were associated with a bright background across the entire arena. After each complete trial, which results in the reward state, mice are required to complete a separate task in which they need to ‘hunt’ for a series of 4 to 8 randomly placed blinking dots on the arena floor. Each dot disappears as soon as the mouse reaches it, resulting either in a new random annulus, or initialization of the next trial. The next trial begins with a new random rotation of the landmarks and rewarded port. (c) Training phases (see Methods). Mice are trained with a single landmark first, then 2 landmarks at unlimited view distance, and finally a limited view distance. (d) Top: Experimental setup for electrophysiology and real-time mouse position tracking. The arena was placed on top of a commercial flat-screen TV that was used to display visual landmarks. A motorized commutator⁴⁷ was used to reduce tether-induced torque on the mouse, and a real-time optical tracking system was used to regulate the visibility of the landmarks and to identify when the mouse reached any of the blinking dots in the dot-hunting task. Bottom: view of the arena from the top, showing a subset of the reward ports as well as the tracking camera and the motorized commutator. (e) Example excerpt of behavioral data, with state transitions. Landmark visits (black arrowheads) are defined as the point when new landmarks become visible. (f) Top: Training curves for all 4 mice. The three major training phases are indicated with shading (corresponding to panel c). Red: Proportion of time that a landmark is visible (remains 1.0 (100%) until view distance is introduced). Blue: Maximum reward port hold time for each session, the actual hold times are drawn from a uniform distribution. Black: proportion of hits / false positives (corresponds to rewards / timeouts, or proportion correct), for the 1^st port visit in each trial. Values over 1/16 indicate that mice can distinguish the correct port amongst all ports. Values over 1 indicate that mice could reliably visit the correct port among the two ports indicated by locally ambiguous landmarks without excluding any other ports by trial and error (see main text and methods). Trials with 1^st landmark visit after <20 sec are included in analysis. Grey: Proportion of trials in which mice see both landmarks, and then turn around to go back to the 1^st landmark. If this proportion was 0, it would indicate that mice always visit the 2^nd port after seeing it, which would on average lead to chance-level behavioral performance. For each individual session, significance of correct choice for the 1^st port visit among the two indicated ports was tested with a binomial fit at the 95% level (two-sided, Clopper-Pearson exact method) and is indicated with a star. If the mouse also visited a large proportion of unmarked ports, this fraction can be significant despite the overall correct rate among all 16 ports being small. Bottom: latency to reward after encountering the 2^nd landmark in seconds (blue), proportion of visits to ‘a’ and ‘b’ as fraction of all port visits (orange) and proportion correct choice between ‘a’ or ‘b’ with binomial 95% CI (binomial as described before, green). See y-axis labels for unit definitions. (g) All paths taken by the mouse in one example session, split by LM0,1,2 state (green, glue, grey). (h) 6 example trials from the same session plotted from the start of the trial to the reward delivery, same color scheme as in g. 2 of the trials include time-outs (red). (i) Retrosplenial cortex is required for integrating egocentric sensory information and hypotheses about the animal’s allocentric location, but not for visually guided navigation. To causally test the role of RSC in relating spatial hypotheses to sensory data, we used a parametric allocentric/egocentric task using the same apparatus as in the main experiment and pharmacologically inactivated RSC. Schematic of task structure: Water restricted mice had to visit the port closest to a single visual landmark for a water reward. Visits to any other port resulted in a time-out, but allowed the mice to self-correct. As in the main experiment, the landmark and rewarded port were rotated randomly after each trial, forcing mice to use only the visual landmark. (j) To make the task reliant on allocentric hypotheses, we randomly varied the eccentricity of the landmark (center of the landmark to center of the arena, as fraction of the arena radius) at the beginning of each trial. Trials with low eccentricity (left) required the mouse to find the arena center (though path integration, requiring maintenance of a self-position hypothesis or memory in absence of persistence visual cues indicating the center of the arena) and then extrapolate a straight path through the landmark to the correct rewarded port. Alternatively, mice might triangulate which port is the closest to the landmark from the periphery. These strategies all require integration of self-location hypotheses with visual landmark information. Trials with high eccentricity (right) required merely walking to the port closest to the landmark. This design allowed us to test the role of RSC in the integration of location hypotheses with egocentric visual landmark information while simultaneously determining whether simpler visually-guided navigation was also affected. (k) RSC was either 1) transiently inactivated with Muscimol, 2) sham injected with cortex buffer, or 3) not injected (see methods). Each mouse was tested in both groups, with balanced ordering. (l) Task performance (mean and 95% confidence intervals for hit rate on 1^st port visits per trial, via binomial bootstrap). Mice always performed above full chance level (1/16^th, assuming they cannot make use of the landmark). Performance was selectively reduced by RSC inactivation for low eccentricity conditions where integration of location hypotheses and visual landmarks was required. Performance in the visually guided condition was only minimally affected.