P146 Fast Visual Reorientation in Postsubicular Head-Direction Cells Conditional on Cue Visibility
Sven Krausse1,2, Emre Neftci1,2,Alpha Renner*1
1Forschungszentrum Jülich, Aachen, Germany
2RWTH Aachen, Aachen, Germany
*Email: a.renner@fz-juelich.de
Introduction
Accurate spatial navigation relies on head-direction (HD) cells, which encode orientation in allocentric coordinates, like a neural compass [1,2]. Found, e.g., in postsubiculum (PoSub) and thalamus, HD cells integrate angular velocity signals from vestibular, proprioceptive, and optic flow inputs, recalibrating via visual cues [2] to avoid drift. Reorientation speed after cue absence is key to understanding the HD system’s dynamics and for bio-inspired models.[3]reported rapid reorientation, while[4]suggested an internal gain factor modulates it, though its mechanism remains unclear. Using a new dataset [5], we examine reorientation dynamics, finding it is fast but contingent on cue visibility.
Methods
We analyzed a dataset [5] containing head tracking and PoSub spike trains from six mice. Internal HD was decoded from spikes using a Bayesian approach [5]. Mice navigated a circular platform with dim LED cues (Fig. 1a) alternating between adjacent walls in 16 trials.Trials were excluded if >20% of the first minute after a cue switch had unreliable tracking, if movement ceased for >5 s, or if HD failed to reorient. Using head tracking data, we reconstructed each mouse’s visual field (FOV = 180°) to estimate cue visibility. Reorientation speed was quantified via exponential fits (scipy.optimize.curve_fit). Time constants (τ) were constrained to 0.1–3 s, with magnitude limits of 0–90°. Aligned mean error fits (Figs. 1b,c) estimated unconstrained τ, magnitude, and no delay.
Results
In Fig. 1d, after a cue switch, decoding error decreases from 90° as HD reorients. Reorientation does not always occur immediately but around when the cue becomes visible. Comparing error aligned in time by cue switch (Fig. 1b) vs. fitted delay (1c), the latter improves alignment and yields faster τ. Fig. 1e suggests that fitted switching times can be predicted from the mouse’s FOV, but only for “reorientation” trials (blue) where the cue appeared outside the FOV. Cues appearing within the FOV may cause a conflict between reanchoring and reorientation due to the lack of a dark phase between trials. Prediction cannot be perfect as pupil orientation and blinking are unknown. Based on these preliminary results we develop a model of reorientation dynamics to capture additional effects.
Discussion
Consistent with [3], we confirm that reorientation occurs in abrupt jumps, but alignment must consider visual FOV rather than assuming omnidirectional vision. While in [3]. mice were trained to fixate cues, FOV’s role may seem trivial but is often ignored. Our findings offer a better mechanistic understanding of the gain factor that mediates reorientation speed found by [4] in thalamus, which is not yet mechanistically explained. More broadly, our results contribute to an integrative model of HD reorientation and reanchoring, advancing both neuroscientific understanding and bio-inspired navigation systems (which we plan to build in the future [6]).
Figure 1. Fig. 1 a. Arena, platform, cues and FOV b. Decoding error aligned by cue switch c. Error aligned by fitted internal HD switch d. Single trial where cue switch occurs roughly as the cue enters FOV. Difference between red and black curves is decoding error (blue). e. Estimated time until cue becomes visible vs. fitted delay. Diagonal in black, points where cue appears within FOV in grey.
Acknowledgements
This research was funded by VolkswagenStiftung [CLAM 9C854]. For this work, the data from Duszkiewicz et al. (2024) [1] was used, and we thank the authors for making this data available. We especially thank Adrian Duszkiewicz for answering our questions and providing additional advice on the data. We thank Johannes Leugering, Friedrich Sommer and Paxon Frady for their feedback.
References
[1] Rank, J. B. (1984). Head-direction cells in the deep layers of dorsal presubiculum of freely moving rats. In Soc. Neuroscience Abstr. (Vol. 10, p. 599).
[2] Taube et al. (1990).https://doi.org/10.1523/JNEUROSCI.10-02-00420.1990
[3] Zugaro et al. (2003).https://doi.org/10.1523/JNEUROSCI.23-08-03478.2003
[4] Ajabi et al. (2023).https://doi.org/10.1038/s41586-023-05813-2
[5] Duszkiewicz et al. (2024).https://doi.org/10.1038/s41593-024-01588-5
[6] Krausse et al. (2025).https://doi.org/10.48550/arXiv.2503.08608
