Fig. 4: RSC exhibits stable attractor dynamics sufficient for computing hypothesis-dependent landmark identity.
From: Spatial reasoning via recurrent neural dynamics in mouse retrosplenial cortex
a, Top, to study hypothesis encoding and its impact without sensory or motor confounds, we used trials with matched egocentric paths just before and after the second landmark (‘a’ or ‘b’) encounter. One example session is shown. Bottom, 3D neural state space trajectories (isomap); RSC latent states do not correspond directly to those of the ANN. b, RSC encodes the difference between LM1a and LM1b, and between subsequent LM2 states, as in the ANN (Fig. 2e and Extended Data Fig. 5). Blue, within-group and grey, across-group distances in neural state space. Horizontal lines, mean; boxes, 95% CIs (bootstrap). State can also be decoded from raw spike rates (Extended Data Fig. 9j). c, Neural dynamics in RSC are smooth across trials: pairwise distances between per trial spike counts in a 750 ms window before LM2 onset remain correlated with later windows; line, median; shading, CIs (bootstrap). d, RSC activity preceding the second landmark encounter predicts correct/incorrect port choice (horizontal line, mean; gray shaded box, 95% CI from bootstrap, cross-validated regression trees). e, Decoding of hypothesis states and position from RSC using ANNs to illustrate the evolution of neural activity in the task-relevant space (see b, c and d and Fig. 1e,f, Extended Data Fig. 9 statistics). f, Schematic of potential computational mechanisms. Left, if RSC encodes only current spatial and sensorimotor states and no hypotheses beyond landmark count (LM1a or LM2b, derived from seeing the first landmark and self-motion integration that lead to identifying the second landmark as ‘a’ or ‘b’), an external disambiguating input is needed. Right, because task-specific hypotheses arising from the learned relative position of the landmarks are encoded (this figure), and activity follows stable attractor dynamics (Fig. 3), ambiguous visual inputs can drive the neural activity to different positions, disambiguating landmark identity in RSC analogously to the ANN.
