To guide navigation, the nervous system integrates multisensory self-motion and landmark information. We examined how these inputs generate the representation of self-location by recording entorhinal grid, border and speed cells in mice navigating virtual environments. Manipulating the gain between the animal’s locomotion and the visual scene revealed that border cells responded to landmark cues while grid and speed cells responded to combinations of locomotion, optic flow, and landmark cues in a context-dependent manner, with optic flow becoming more influential when it was faster than expected. A network model explained these results, providing principled regimes under which grid cells remain coherent with or break away from the landmark reference frame. Moreover, during path integration-based navigation, mice estimated their position following the principles predicted by our recordings. Together, these results provide a quantitative framework for understanding how landmark and self-motion cues combine during navigation to generate spatial representations and guide behavior.

To sense the outside world, some neurons protrude across epithelia, the cellular barriers that line every surface of our bodies. To study the morphogenesis of such neurons, we examined the C. elegans amphid, in which dendrites protrude through a glial channel at the nose. During development, amphid dendrites extend by attaching to the nose via DYF-7, a type of protein typically found in epithelial apical ECM. Here, we show that amphid neurons and glia exhibit epithelial properties, including tight junctions and apical-basal polarity, and develop in a manner resembling other epithelia. We find that DYF-7 is a fibril-forming apical ECM component that promotes formation of the tube-shaped glial channel, reminiscent of roles for apical ECM in other narrow epithelial tubes. We also identify a requirement for FRM-2, a homolog of EPBL15/moe/Yurt that promotes epithelial integrity in other systems. Finally, we show that other environmentally exposed neurons share a requirement for DYF-7. Together, our results suggest that these neurons and glia can be viewed as part of an epithelium continuous with the skin, and are shaped by mechanisms shared with other epithelia.

No abstract

Medial entorhinal cortex (MEC) supports a wide range of navigational and memory related behaviors. Well-known experimental results have revealed specialized cell types in MEC — e.g. grid, border, and head-direction cells — whose highly stereo-typical response profiles are suggestive of the role they might play in supporting MEC functionality. However, the majority of MEC neurons do not exhibit stereotypical firing patterns. How should the response profiles of these more “heterogeneous” cells be described, and how do they contribute to behavior? In this work, we took a computational approach to addressing these questions. We first performed a statistical analysis that shows that heterogeneous MEC cells are just as reliable in their response patterns as the more stereotypical cell types, suggesting that they have a coherent functional role. Next, we evaluated a spectrum of candidate models in terms of their ability to describe the response profiles of both stereotypical and heterogeneous MEC cells. We found that recently developed task-optimized neural network models are substantially better than traditional grid cell-centric models at matching most MEC neuronal response profiles — including those of grid cells themselves — despite not being explicitly trained for this purpose. Specific choices of network architecture (such as gated nonlinearities and an explicit intermediate place cell representation) have an important effect on the ability of the model to generalize to novel scenarios, with the best of these models closely approaching the noise ceiling of the data itself. We then performed “in-silica” experiments on this model to address questions involving the relative functional relevance of various cell types, finding that heterogeneous cells are likely to be just as involved in downstream functional outcomes (such as path integration) as grid and border cells. Finally, inspired by recent data showing that, going beyond their spatial response selectivity, MEC cells are also responsive to non-spatial rewards, we introduce a new MEC model that performs reward-modulated path integration. We find that this unified model matches neural recordings across all variable-reward conditions. Taken together, our results point toward a conceptually principled goal-driven modeling approach for moving future experimental and computational efforts beyond overly-simplistic single-cell stereotypes.