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Related Experiment Video

Updated: Sep 25, 2025

Micropatterning Transmission Electron Microscopy Grids to Direct Cell Positioning within Whole-Cell Cryo-Electron Tomography Workflows

Micropatterning Transmission Electron Microscopy Grids to Direct Cell Positioning within Whole-Cell Cryo-Electron Tomography Workflows

Published on: September 13, 2021

Challenges for Place and Grid Cell Models.

Oleksandra Soldatkina¹, Francesca Schönsberg¹, Alessandro Treves^2,3

¹SISSA - Cognitive Neuroscience, Trieste, Italy.

Advances in Experimental Medicine and Biology

|April 26, 2022

Summary

This summary is machine-generated.

Computational models explore grid and place cells, key components of spatial cognition. These models address fundamental questions in how the brain navigates and represents space.

Keywords:

Associative memory Continuous attractors Dentate Gyrus Grid cells Spatial cognition

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Area of Science:

Neuroscience
Cognitive Science
Computational Modeling

Background:

Grid cells and place cells are critical neural substrates for spatial cognition and memory.
Understanding their function is essential for deciphering brain mechanisms of navigation.

Purpose of the Study:

To provide an overview of computational models of grid and place cells.
To highlight open questions in spatial cognition that these models can help address.

Main Methods:

Review of existing computational models.
Discussion of theoretical frameworks and simulations.

Main Results:

Models offer insights into the properties and interactions of grid and place cells.
Computational approaches can elucidate mechanisms underlying spatial representation and path integration.

Conclusions:

Computational models are valuable tools for advancing our understanding of spatial cognition.
Further development of these models is crucial for resolving key theoretical challenges.