Abstract

In the mammalian brain, allocentric (Earth-referenced) head direction, called azimuth, is encoded by head direction (HD) cells, which fire according to the facing direction of the animal’s head. On a horizontal surface, rotations of the head around the dorsoventral (D-V) axis, called yaw, correspond to changes in azimuth and elicit appropriate updating of the HD “compass” signal to enable large-scale navigation. However, if the animal moves through three-dimensional (3D) space then there is no longer a simple relationship between yaw rotations and azimuth changes, and so processing of 3D rotations is needed. Construction of a global 3D compass would require complex integration of 3D rotations, and also a large neuronal population, most neurons of which would be silent most of the time since animals rarely sample all available 3D orientations. We propose that, instead, the HD system treats the 3D space as a set of interrelated 2D surfaces. It could do this by updating activity according to both yaw rotations around the D-V axis and rotations of the D-V axis around the gravity-defined vertical axis. We present preliminary data to suggest that this rule operates when rats move between walls of opposing orientations. This dual-axis rule, which we show is straightforward to implement using the classic one-dimensional “attractor” architecture, allows consistent representation of azimuth even in volumetric space and thus may be a general feature of mammalian directional computations even for animals that swim or fly.NEW & NOTEWORTHY Maintaining a sense of direction is complicated when moving in three-dimensional (3D) space. Head direction cells, which update the direction sense based on head rotations, may accommodate 3D movement by processing both rotations of the head around the axis of the animal’s body and rotations of the head/body around gravity. With modeling we show that this dual-axis rule works in principle, and we present preliminary data to support its operation in rats.

Highlights

  • The neural circuitry supporting navigation has been intensely studied for several decades, and attention is turning to how navigation processes operate in the complex three-dimensional (3D) real world

  • The dual-axis rule is graphically depicted in Fig. 5 for an imaginary rat walking on a hemisphere, showing how the head turn and the D-V axis turn are extracted for each timestep and used to update the head direction (HD) signal

  • We have suggested that the activity of HD cells as animals move over a 3D surface may be organized by a dual-axis updating rule, in which firing directions are updated not just by

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Summary

Introduction

The neural circuitry supporting navigation has been intensely studied for several decades, and attention is turning to how navigation processes operate in the complex three-dimensional (3D) real world. A core feature of navigation is computation of Earth-referenced head direction, or azimuth, and in mammals this faculty is supported by the head direction (HD) neurons (Taube 2007; Taube et al 1990a, 1990b), the firing of which is azimuth sensitive. The activity of the neurons is updated by changes in head direction (i.e., yaw): a simple “transfer function” describes the movement of activity through the HD cell network so that a given head turn moves activity around the ring attractor by the appropriate amount. This means that HD cell activity always reflects the animal’s current azimuth: on a horizontal surface, yaw corresponds linearly to azimuth change

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