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Lattices abound in nature - from the crystal structure of minerals to the honey-comb organization of ommatidia in the compound eye of insects. Such regular arrangements provide solutions for optimally dense packings, efficient resource…

Neurons and Cognition · Quantitative Biology 2015-05-12 Alexander Mathis , Martin B. Stemmler , Andreas V. M. Herz

The spatial responses of many of the cells recorded in all layers of rodent medial entorhinal cortex (mEC) show a triangular grid pattern, and once established might be based in part on path-integration mechanisms. Grid axes are tightly…

Neurons and Cognition · Quantitative Biology 2012-03-20 Bailu Si , Emilio Kropff , Alessandro Treves

We advertise the use of tetrahedral grids constructed via the longest edge bisection algorithm for rendering volumetric data with path tracing. The key benefits of such grids is two-fold. First, they provide a highly adaptive…

Graphics · Computer Science 2025-06-16 Anis Benyoub , Jonathan Dupuy

The entorhinal-hippocampal formation is the mammalian brain's navigation system, encoding both physical and abstract spaces via grid cells. This system is well-studied in neuroscience, and its efficiency and versatility make it attractive…

Neural and Evolutionary Computing · Computer Science 2025-03-12 Sven Krausse , Emre Neftci , Friedrich T. Sommer , Alpha Renner

Grid cells in the entorhinal cortex encode the position of an animal in its environment using spatially periodic tuning curves of varying periodicity. Recent experiments established that these cells are functionally organized in discrete…

Neurons and Cognition · Quantitative Biology 2016-01-13 Noga Weiss Mosheiff , Haggai Agmon , Avraham Moriel , Yoram Burak

While many neural networks focus on layers to process information, the GAIN model uses a grid-based structure to improve biological plausibility and the dynamics of the model. The grid structure helps neurons to interact with their closest…

Neurons and Cognition · Quantitative Biology 2025-06-06 Gage K. R. Hooper

The activity of the grid cell population in the medial entorhinal cortex (MEC) of the mammalian brain forms a vector representation of the self-position of the animal. Recurrent neural networks have been proposed to explain the properties…

Neurons and Cognition · Quantitative Biology 2022-11-08 Dehong Xu , Ruiqi Gao , Wen-Hao Zhang , Xue-Xin Wei , Ying Nian Wu

Hexagonal CNN models have shown superior performance in applications such as IACT data analysis and aerial scene classification due to their better rotation symmetry and reduced anisotropy. In order to realize hexagonal processing, existing…

Computer Vision and Pattern Recognition · Computer Science 2021-01-27 Yunxiang Zhao , Qiuhong Ke , Flip Korn , Jianzhong Qi , Rui Zhang

Grid cells enable the brain to model the physical space of the world and navigate effectively via path integration, updating self-position using information from self-movement. Recent proposals suggest that the brain might use similar…

Artificial Intelligence · Computer Science 2021-02-19 Niels Leadholm , Marcus Lewis , Subutai Ahmad

In this paper we explain the strikingly regular activity of the 'grid' cells in rodent dorsal medial entorhinal cortex (dMEC) and the spatially localized activity of the hippocampal place cells in CA3 and CA1 by assuming that the…

Neurons and Cognition · Quantitative Biology 2008-04-22 Andras Lorincz , Melinda Kiszlinger , Gabor Szirtes

We introduce a novel approach to endowing neural networks with emergent, long-term, large-scale memory. Distinct from strategies that connect neural networks to external memory banks via intricately crafted controllers and hand-designed…

Machine Learning · Computer Science 2020-08-18 Tri Huynh , Michael Maire , Matthew R. Walter

Inspired by the human visual perception system, hexagonal image processing in the context of machine learning deals with the development of image processing systems that combine the advantages of evolutionary motivated structures based on…

Machine Learning · Computer Science 2024-06-11 Tobias Schlosser , Michael Friedrich , Danny Kowerko

Hyperbolic geometry has emerged as a powerful tool for modeling complex, structured data, particularly where hierarchical or tree-like relationships are present. By enabling embeddings with lower distortion, hyperbolic neural networks offer…

Machine Learning · Computer Science 2025-06-18 Pol Arévalo , Alexis Molina , Álvaro Ciudad

Place cells in the hippocampus are active when an animal visits a certain location (referred to as a place field) within an environment. Grid cells in the medial entorhinal cortex (MEC) respond at multiple locations, with firing fields that…

Neurons and Cognition · Quantitative Biology 2018-05-17 David M. Schwartz , O. Ozan Koyluoglu

This paper presents a novel algorithmic framework for the computational design, simulation, and fabrication of a hexagonal grid-based double-curvature structure with planar hexagonal panels. The journey begins with constructing a robust…

Computational Geometry · Computer Science 2025-07-23 Mehdi Gorjian , Gregory A. Luhan , Stephen M. Caffey

Research on network mechanisms and coding properties of grid cells assume that the firing rate of a grid cell in each of its fields is the same. Furthermore, proposed network models predict spatial regularities in the firing of inhibitory…

Neurons and Cognition · Quantitative Biology 2017-01-19 Benjamin Dunn , Daniel Wennberg , Ziwei Huang , Yasser Roudi

The human brain can be considered as complex networks, composed of various regions that continuously exchange their information with each other, forming the brain network graph, from which nodes and edges are extracted using resting-state…

Machine Learning · Computer Science 2025-02-19 Parnian Jalali , Mehran Safayani

Grid cells recorded in the parahippocampal formation of freely moving rodents provide a strikingly periodic representation of self-location whose underlying mechanism has been the subject of intense interest. Our previous work(1) showed…

Neurons and Cognition · Quantitative Biology 2015-12-22 Julija Krupic , Neil Burgess , John O'Keefe

Memory systems can store vastly different amounts of information despite similar hardware constraints. Here, we show that superior spatial memory emerges from a discrete stiffening of hippocampal population geometry-a transition from…

Neurons and Cognition · Quantitative Biology 2026-05-19 Prashant C. Raju

Whereas conventional state-of-the-art image processing systems of recording and output devices almost exclusively utilize square arranged methods, biological models, however, suggest an alternative, evolutionarily-based structure. Inspired…

Computer Vision and Pattern Recognition · Computer Science 2024-06-11 Tobias Schlosser , Frederik Beuth , Danny Kowerko