Encoding of task regularities links grid-like signals to human timing behavior

Abstract

Grid cells have been proposed to encode task regularities that allow predicting future states. Entorhinal grid-like signals might therefore mirror behavioral biases associated with relying on task regularities, like regression-to-the-mean biases in time estimation. Here, we tested this proposal using functional magnetic resonance imaging and a rapid timing task in humans. Indeed, trial-wise entorhinal activity reflected task accuracy and the degree to which interval estimates regressed towards the mean of all tested intervals. Grid-like signals were observed exclusively for the interval closest to the mean, which was explained by differences in temporal grid stability across intervals. Finally, both behavioral and entorhinal results were explained by a Bayesian observer model that assumes the integration of current-trial sensory evidence with prior expectations. Together, we find that entorhinal activity and grid-like signals reflect behavioral performance in a timing task, supporting the proposed role of grid cells in encoding task structure for predictive processing.