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Related Concept Videos

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The structure of a crystalline solid, whether a metal or not, is best described by considering its simplest repeating unit, which is referred to as its unit cell. The unit cell consists of lattice points that represent the locations of atoms or ions. The entire structure then consists of this unit cell repeating in three dimensions. The three different types of unit cells present in the cubic lattice are illustrated in Figure 1.
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Solids in which the atoms, ions, or molecules are arranged in a definite repeating pattern are known as crystalline solids. Metals and ionic compounds typically form ordered, crystalline solids. A crystalline solid has a precise melting temperature because each atom or molecule of the same type is held in place with the same forces or energy. Amorphous solids or non-crystalline solids (or, sometimes, glasses) which lack an ordered internal structure and are randomly arranged. Substances that...
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Related Experiment Video

Updated: Nov 8, 2025

Design, Surface Treatment, Cellular Plating, and Culturing of Modular Neuronal Networks Composed of Functionally Inter-connected Circuits
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Modularization of grid cells constrained by the pyramidal patch lattice.

Tao Wang1, Fan Yang1, Ziqun Wang1

  • 1National Laboratory of Solid State Microstructures, Department of Physics, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing 210093, P. R. China.

Iscience
|April 19, 2021
PubMed
Summary

This study proposes a hexagonal lattice of pyramidal cell patches as the mechanism for grid cell spacing and orientation discretization. This model successfully reproduces experimental data on grid spacing and orientation differences between modules.

Keywords:
BiophysicsComputational bioinformaticsNeuroscience

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Area of Science:

  • Neuroscience
  • Computational Neuroscience

Background:

  • Grid cells in the brain's entorhinal cortex provide metric self-location representations.
  • Grid cells are organized into modules with discrete grid spacing scales, but the underlying mechanism is unknown.

Purpose of the Study:

  • To propose and investigate a computational model for the discretization of grid spacing and orientation in grid cells.
  • To explore the role of pyramidal cell patch lattices in generating grid cell modularity.

Main Methods:

  • A computational modeling study using a continuous attractor network model.
  • Simulating interactions between interneurons, stellate cells, and pyramidal cells with hexagonal lattices.

Main Results:

  • A hexagonal lattice of pyramidal cell patches underlies discretized grid spacing and orientation.
  • The model reproduces experimental grid spacing ratios and orientation differences between modules.
  • Identified 22 specific geometric conditions for aligning bump attractors to patch lattices.

Conclusions:

  • The hexagonal lattice of pyramidal cell patches provides a systems-level mechanism for grid cell modularity.
  • This model reveals correlations between brain microstructures and neuronal firing fields.
  • The findings offer insights into how the brain encodes spatial information.