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Nature Communications· 2026Q1

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

Alexandr Pak, Janna Aarse, Heng Wei Zhu, Jean‐Paul Noel et al.

Short summary

Head-fixed mice show altered head direction (HD) cell network dynamics during immobility, which are rescued by predictive signals from upcoming locomotion.

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Key points

  • Head-fixation in mice disrupts HD cell encoding and population activity, especially during immobility.
  • Attractor dynamics are altered in head-restrained mice, recapitulated by a computational model perturbing lateral connectivity.
  • HD network dynamics recover prior to locomotion onset, suggesting a predictive mechanism involving efference copy or re-afferent signals.
  • The HD network functions as a context- and state-dependent predictive estimator stabilized by forthcoming self-motion signals.

AI-generated from the title and abstract; the full text is not read.

Abstract

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.

The authors' abstract, as published at the source. Nature Communications, 2026 · DOI ↗

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Field: Cognitive Neuroscience

Cognitive NeuroscienceNeuroscience