A Grid Cell Inspired Model of Cortical Column Function

Jochen Kerdels, Gabriele Peters

2018

Abstract

The cortex of mammals has a distinct, low-level structure consisting of six horizontal layers that are vertically connected by local groups of about 80 to 100 neurons forming so-called minicolumns. A well-known and widely discussed hypothesis suggests that this regular structure may indicate that there could be a common computational principle that governs the diverse functions performed by the cortex. However, no generally accepted theory regarding such a common principle has been presented so far. In this position paper we provide a novel perspective on a possible function of cortical columns. Based on our previous efforts to model the behaviour of entorhinal grid cells we argue that a single cortical column can function as an independent, autoassociative memory cell (AMC) that utilizes a sparse distributed encoding. We demonstrate the basic operation of this AMC by a first set of preliminary simulation results.

Paper Citation

in Harvard Style

Kerdels J. and Peters G. (2018). A Grid Cell Inspired Model of Cortical Column Function. In Proceedings of the 10th International Joint Conference on Computational Intelligence (IJCCI 2018) - Volume 1: IJCCI; ISBN 978-989-758-327-8, SciTePress, pages 204-210. DOI: 10.5220/0006931502040210

in Bibtex Style

@conference{ijcci18,
author={Jochen Kerdels and Gabriele Peters},
title={A Grid Cell Inspired Model of Cortical Column Function},
booktitle={Proceedings of the 10th International Joint Conference on Computational Intelligence (IJCCI 2018) - Volume 1: IJCCI},
year={2018},
pages={204-210},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006931502040210},
isbn={978-989-758-327-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 10th International Joint Conference on Computational Intelligence (IJCCI 2018) - Volume 1: IJCCI
TI - A Grid Cell Inspired Model of Cortical Column Function
SN - 978-989-758-327-8
AU - Kerdels J.
AU - Peters G.
PY - 2018
SP - 204
EP - 210
DO - 10.5220/0006931502040210
PB - SciTePress