Locally ordered representation of 3D space in the entorhinal cortex

Ginosar, Gily; Aljadeff, Johnatan; Burak, Yoram; Sompolinsky, Haim; Las, Liora; Ulanovsky, Nachum

doi:10.1038/s41586-021-03783-x

Cited by 76 publications

(69 citation statements)

References 55 publications

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“…This study in contradiction with (Hayman et al, 2015;Casali et al, 2019) may even arise because the motion planes do not intersect FCC with a few specific angles that lead to hexagonal lattice. The mode does not explain the grid fields during volumetric navigation (Ginosar et al, 2021;Grieves et al, 2021) either. The contradictions may only be solved if a remapping mechanism exists (Finkelstein et al, 2016).…”

Section: Discussionmentioning

confidence: 91%

“…We construct an interpretive plane-dependent model of 3D grid cells. The model has two achievements: it is capable of representing both 2D and 3D space during different navigation modes and predicting the principles behind the multimodality of grid codes and degradation of grid field regularity observed in experiments (Hayman et al, 2015;Casali et al, 2019;Ginosar et al, 2021;Grieves et al, 2021). Specifically, the model interprets 3D 6-DoF motion in local cylindrical coordinate systems based on planes.…”

Section: Discussionmentioning

confidence: 99%

“…During volumetric navigation, grid fields at least preserve local order. Two latest studies on rats navigating in a cubic lattice and bats flying in a rectangular room report that the volumetric grid fields do not fit into HCP, FCC, or COL, but are more regular than a random organization of fields (RND) (Ginosar et al, 2021;Grieves et al, 2021). On the contrary, another study implies that FCC could explain the fMRI activities of the entorhinal cortex of human subjects navigating in a 3D virtual reality paradigm (Kim and Maguire, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…A perceptual error occurs due to the limitation in the sensors, cognitive errors, to name a few. The error could perturb the RNN updates and explain why grid fields lose global order in volumetric navigation reported by Grieves et al (2021) and Ginosar et al (2021). Third, the model allows switching among navigation modes categorized by plane definition, grid cell periodicity, perceptual error, etc.…”

Section: Introductionmentioning

confidence: 99%

“…However, recordings of grid cells on sloped, multilayered and volumetric environments (Hayman et al, 2011(Hayman et al, , 2015Casali et al, 2019;Kim and Maguire, 2019;Ginosar et al, 2021;Grieves et al, 2021) challenge the theoretical prediction of isotropic 3D grid fields. Hayman et al (2011) uncovered that when navigating on a pegboard and a helix, rats manifest vertically elongated grid fields; this anisotropy suggests columnar fields (COL) in 3D.…”

Section: Introductionmentioning

confidence: 99%

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A Plane-Dependent Model of 3D Grid Cells for Representing Both 2D and 3D Spaces Under Various Navigation Modes

Gong

Fukunishi

2021

Front. Comput. Neurosci.

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Grid cells are crucial in path integration and representation of the external world. The spikes of grid cells spatially form clusters called grid fields, which encode important information about allocentric positions. To decode the information, studying the spatial structures of grid fields is a key task for both experimenters and theorists. Experiments reveal that grid fields form hexagonal lattice during planar navigation, and are anisotropic beyond planar navigation. During volumetric navigation, they lose global order but possess local order. How grid cells form different field structures behind these different navigation modes remains an open theoretical question. However, to date, few models connect to the latest discoveries and explain the formation of various grid field structures. To fill in this gap, we propose an interpretive plane-dependent model of three-dimensional (3D) grid cells for representing both two-dimensional (2D) and 3D space. The model first evaluates motion with respect to planes, such as the planes animals stand on and the tangent planes of the motion manifold. Projection of the motion onto the planes leads to anisotropy, and error in the perception of planes degrades grid field regularity. A training-free recurrent neural network (RNN) then maps the processed motion information to grid fields. We verify that our model can generate regular and anisotropic grid fields, as well as grid fields with merely local order; our model is also compatible with mode switching. Furthermore, simulations predict that the degradation of grid field regularity is inversely proportional to the interval between two consecutive perceptions of planes. In conclusion, our model is one of the few pioneers that address grid field structures in a general case. Compared to the other pioneer models, our theory argues that the anisotropy and loss of global order result from the uncertain perception of planes rather than insufficient training.

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Section: Discussionmentioning

confidence: 91%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A Plane-Dependent Model of 3D Grid Cells for Representing Both 2D and 3D Spaces Under Various Navigation Modes

Gong

Fukunishi

2021

Front. Comput. Neurosci.

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Organization of projections from the entorhinal cortex to the hippocampal formation of the Egyptian fruit bat Rousettus aegyptiacus

et al. 2023

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The hippocampal formation and entorhinal cortex are crucially involved in learning and memory as well as in spatial navigation. The conservation of these structures across the entire mammalian lineage demonstrates their importance. Information on a diverse set of spatially tuned neurons has become available, but we only have a rudimentary understanding of how anatomical network structure affects functional tuning. Bats are the only order of mammals that have evolved true flight, and with this specialization comes the need to navigate and behave in a three dimensional (3D) environment. Spatial tuning of cells in the entorhinal-hippocampal network of bats has been studied for some time, but whether the reported tuning in 3D is associated with changes in the entorhinal-hippocampal network is not known. Here we investigated the entorhinal-hippocampal projections in the Egyptian fruit bat (Rousettus aegyptiacus), by injecting chemical anterograde tracers in the entorhinal cortex.Detailed analyses of the terminations of these projections in the hippocampus showed that both the medial and lateral entorhinal cortex sent projections to the molecular layer of all subfields of the hippocampal formation. Our analyses showed that the terminal distributions of entorhinal fibers in the hippocampal formation of Egyptian fruit bats-including the proximo-distal and longitudinal topography and the layer-specificity-are similar to what has been described in other mammalian species such as rodents and primates. The major difference in entorhinal-hippocampal projections that was described to date between rodents and primates is in the terminal distribution of the DG projection. We found that bats have entorhinal-DG projections that seem more like those in primates than in rodents. It is likely that the latter projection in bats is specialized to the behavioral needs of this species, including 3D flight and long-distance navigation.

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Variational log‐Gaussian point‐process methods for grid cells

Rule,

Chaudhuri‐Vayalambrone,

Krstulovic

et al. 2023

Hippocampus

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We present practical solutions to applying Gaussian‐process (GP) methods to calculate spatial statistics for grid cells in large environments. GPs are a data efficient approach to inferring neural tuning as a function of time, space, and other variables. We discuss how to design appropriate kernels for grid cells, and show that a variational Bayesian approach to log‐Gaussian Poisson models can be calculated quickly. This class of models has closed‐form expressions for the evidence lower‐bound, and can be estimated rapidly for certain parameterizations of the posterior covariance. We provide an implementation that operates in a low‐rank spatial frequency subspace for further acceleration, and demonstrate these methods on experimental data.

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Locally ordered representation of 3D space in the entorhinal cortex

Cited by 76 publications

References 55 publications

A Plane-Dependent Model of 3D Grid Cells for Representing Both 2D and 3D Spaces Under Various Navigation Modes

A Plane-Dependent Model of 3D Grid Cells for Representing Both 2D and 3D Spaces Under Various Navigation Modes

Organization of projections from the entorhinal cortex to the hippocampal formation of the Egyptian fruit bat Rousettus aegyptiacus

Variational log‐Gaussian point‐process methods for grid cells

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