A Neural Network Model of Mapping from - Signal and Data Processing -

Volume 6, Issue 2 (3-2010) JSDP 2010, 6(2): 53-62 | Back to browse issues page

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A Neural Network Model of Mapping from. JSDP 2010; 6 (2) :53-62
URL: http://jsdp.rcisp.ac.ir/article-1-737-en.html

A Neural Network Model of Mapping from

Abstract: (4215 Views)

Abstract: Medial entorhinal cortex is known to be the hub of a brain system for navigation and spatial representation. These cells increase firing frequency at multiple regions in the environment, arranged in regular triangular grids. Each cell has some properties including spacing, orientation, and phase shift of the nodes of its grid. Entorhinal cortex is commonly perceived to be the major input and output structure of hippocampal formation; grid cells are one synapse upstream of place cells in hippocampus. The problem is how single confined place fields can be generated from the repetitive activity of grid cells. In this article we have proposed an artificial neural network model based on radial basis function, which allows for the single confined place fields of hippocampal pyramidal cells to be emerged from the activities of grid cells. In order to evaluate the performance of the model, it was considered in two steps in a one-dimensional and two-dimensional environment. Simulations were done considering different characteristics of grid cells and the model demonstrated a good performance in generating single spot activity for place fields.

Keywords: Place Cell, Grid Cell, Hippocampus, Entorhinal Cortex.

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Type of Study: Research | Subject: Paper
Received: 2010/03/20 | Accepted: 2018/02/19 | Published: 2018/02/19 | ePublished: 2018/02/19

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