Modeling grid fields instead of modeling grid cells : An effective model at the macroscopic level and its relationship with the underlying microscopic neural system
| Autor: | Sophie Rosay, Simon Nikolaus Weber, Marcello Mulas |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
0301 basic medicine
Sensory Receptor Cells Computer science Cognitive Neuroscience Models Neurological Pattern formation Action Potentials Topology 03 medical and health sciences Cellular and Molecular Neuroscience 0302 clinical medicine Medial entorhinal cortex Animals Entorhinal Cortex Computer Simulation Orientation Spatial Quantitative Biology::Neurons and Cognition Grid cell Grid Sensory Systems 030104 developmental biology Salient Physical space Theory of computation Neural Networks Computer Merge (version control) 030217 neurology & neurosurgery |
| Zdroj: | Journal of computational neuroscience. 47(1) |
| ISSN: | 1573-6873 |
| Popis: | A neuron's firing correlates are defined as the features of the external world to which its activity is correlated. In many parts of the brain, neurons have quite simple such firing correlates. A striking example are grid cells in the rodent medial entorhinal cortex: their activity correlates with the animal's position in space, defining 'grid fields' arranged with a remarkable periodicity. Here, we show that the organization and evolution of grid fields relate very simply to physical space. To do so, we use an effective model and consider grid fields as point objects (particles) moving around in space under the influence of forces. We reproduce several observations on the geometry of grid patterns. This particle-like behavior is particularly salient in a recent experiment in which two separate grid patterns merge. We discuss pattern formation in the light of known results from physics of two-dimensional colloidal systems. Notably, we study the limitations of the widely used 'gridness score' and show how physics of 2d systems could be a source of inspiration, both for data analysis and computational modeling. Finally, we draw the relationship between our 'macroscopic' model for grid fields and existing 'microscopic' models of grid cell activity and discuss how a description at the level of grid fields allows to put constraints on the underlying grid cell network. |
| Databáze: | OpenAIRE |
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