Neural representation of value in the state-value model.

Latent states developed by the state-value model averaged across all 10 learners, after the Cue Conditioning phase (A); and how they change after Contextual Conditioning, i.e., the differences between probabilities before and after Contextual Conditioning (B); and the activity of three sample vStr neurons drawn from the experiment in [19] (C). The images in (A, B) represent the greatest value PV(r = 1|g,xy(s)) across all head-directions attributed to a given spatial position xy(s) for a given target g. Each image represents one target and its location in the plot corresponds to its location in the Y-maze. The central image represents the combined value function across all targets. It is rotationally symmetric after the rotationally symmetric reward delivered during Cue Conditioning (as some of the vStr rodent-neurons; see insets C) and becomes asymmetric during the context conditioning phase. The spatial positions xy(s) are decoded from the latent states s using an inverse of the function providing input from the grid cells.