Active locomotion predictively rescues head direction attractor dynamics in head-fixed mice

Abstract Head direction (HD) cells in the anterodorsal thalamic nucleus form the brain’s internal compass, and are often modeled as a ring attractor maintaining azimuth coding by leveraging continuous visual and inertial sensory input. Here, we test how the common experimental preparation of head-fixed animals alters this code. Complete head-fixation that creates vestibular conflict disrupts both unit and population encoding of head direction, while selectively constraining head-on-body movements either in real or virtual reality uniquely impairs HD population activity. More specifically, attractor dynamics are altered in head-restrained male mice during periods of immobility, and a computational model recapitulates this effect by perturbing lateral connectivity among HD neurons. These dynamics recover several hundred milliseconds prior to locomotion onset, suggesting that an efference copy or prediction of a re-afferent signal is necessary to maintain HD network activity during head restraint. More generally, the results indicate that the HD network is a context- and state-dependent predictive estimator, stabilized by forthcoming self-motion signals. The classic ring-attractor models should be revised to integrate context-dependent dynamics with prospective motor signals, offering a more complete account of how the brain’s compass remains stable across both naturalistic and constrained conditions.