Our sense of direction: progress, controversies and challenges

Abstract

In this Perspective, we evaluate current progress in understanding how the brain encodes our sense of direction, within the context of parallel work focused on how early vestibular pathways encode self-motion. In particular, we discuss how these systems work together and provide evidence that they involve common mechanisms. We first consider the classic view of the head direction cell and results of recent experiments in rodents and primates indicating that inputs to these neurons encode multimodal information during self-motion, such as proprioceptive and motor efference copy signals, including gaze-related information. We also consider the paradox that, while the head-direction network is generally assumed to generate a fixed representation of perceived directional heading, this computation would need to be dynamically updated when the relationship between voluntary motor command and its sensory consequences changes. Such situations include navigation in virtual reality and head-restricted conditions, since the natural relationship between visual and extravisual cues is altered.

Figure 1

Overview highlighting functions and projections of the two ascending vestibular pathways: (i) the anterior vestibulothalamic pathway through the nucleus prepositus and supragenual nucleus (NPH/SGN) to the HD network (blue; see Fig. 2 for details) and (ii) the posterior vestibulothalamic pathway through the ventral posterior lateral nucleus (red). PIVC, parieto-insular vestibular cortex; VN, vestibular nuclei; VPL, ventral posterior lateral thalamic nucleus.

Figure 2

Representative plots for HD cells and HD circuit. (a) Three typical HD cells are shown across three different brain areas. Peak firing rates in each cell’s preferred firing direction can range from low (top) to medium (middle) to high (bottom) across different cells. Cells with low and high peak firing rates can be observed in all brain areas. (b) Circuit diagram showing principal connections of areas containing HD, angular head velocity, place, and grid cells. The bracket shows the site of the postulated ring attractor network that generates the HD signal. Red dashed line shows point in network where lesions to brain areas below this level induce burst firing patterns in recorded ADN neurons; lesions above this level lead to the loss of the HD signal in ADN without the presence of burstiness among the recorded neurons.

Figure 3

Learning new relationships between motor commands and sensory feedback during self-motion.(a,b) A cancellation signal is sent to the vestibular nuclei when sensory feedback matches the expected sensory consequence of motor command (a), resulting in the suppression of responses to self-generated vestibular stimulation at the first central stage of processing in the vestibular nuclei (b; compare blue and green traces). (c) When the normal relationship between the motor command and resultant movement is altered for active head movements, there is an initial mismatch (red arrow) between expected and actual sensory feedback. As a result, these vestibular neurons robustly respond to self-generated vestibular stimulation (dashed red trace shows predicted response based on sensitivity to passive vestibular stimulation). Then, after a learning phase (gray box), the brain updates its model of the expected sensory consequence of the motor command (green arrow). (d) In head-fixed or head-restrained VR-based protocols there is effectively a mismatch between multisensory feedback (both vestibular and proprioceptive) and optic flow. Dynamic updating of the brain’s model of the expected sensory consequence of the motor command requires tracking the comparison of the predictive and actual sensory feedback signals.