A Computational Model Of Grid Cells Based On A Recursive Growing Neural Gas
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A Computational Model of Grid Cells based on a Recursive Growing Neural Gas
Author: Jochen Kerdels
language: en
Publisher: BoD – Books on Demand
Release Date: 2016-03-07
The entorhinal cortex of rat contains neurons, called "grid cells", that exhibit a very peculiar behavior. Discovered about a decade ago, the activity of these cells was found to correlate with the allocentric position of the animal by forming a regular, hexagonal lattice of firing fields across the entire environment. Due to this unusual behavior and the proximity of the entorhinal cortex to other brain regions that also contain cells with spatially correlated activity grid cells are commonly recognized as an important element of a neuronal system for navigation. Existing computational models of grid cells share this view and typically describe the behavior of grid cells as a path integration component of such a system. This work presents a new, complementary computational model of grid cells. In contrast to existing models it does not assume that grid cells are a specialized component of a navigational system. Instead, it assumes that the activity of grid cells reflects a general principle by which neurons in higher order parts of the cortex process information. The proposed model extends the growing neural gas approach by Bernd Fritzke into a recursive algorithm that describes the joint behavior of grid cells in a group as well as the processes within each individual cell. The work demonstrates that the chosen approach is able to model the characteristic behavior of grid cells and other cells, that also exhibit grid cell-like firing patterns but whose activity does not correlate with the animal's location in the environment.
Computational Intelligence
This book gathers revised and extended versions of the best papers presented at the 8th International Joint Conference on Computational Intelligence (IJCCI 2016), which was held in Porto, Portugal from 9 to 11 November 2016. The papers address three main fields of Computational Intelligence, namely: Evolutionary Computation, Fuzzy Computation, and Neural Computation. In addition to highlighting recent advances in these areas, the book offers veteran researchers new and innovative solutions, while also providing a source of information and inspiration for newcomers to the field.
Computational Intelligence
Author: Christophe Sabourin
language: en
Publisher: Springer Nature
Release Date: 2021-03-22
This present book includes a set of selected revised and extended versions of the best papers presented at the 10th International Joint Conference on Computational Intelligence (IJCCI 2018), held in Seville, Spain, from 18 to 20 September 2018, which covers four thriving fields in Computational Intelligence: Evolutionary Computation, Fuzzy Computation, Neural Computation, and Cognitive and Hybrid Systems. Besides presenting the recent advances in these areas, the book aims, on the one hand, to aggregate new and innovative solutions for confirmed researchers and, on the other hand, to provide a source of information and/or inspiration for young researchers or learners interested in the ever-increasing and current field of Computational Intelligence. This book constitutes a precious provision of knowledge for individual researchers as well as representing a valuable sustenance for collective use in academic libraries (of universities and engineering schools) relating innovative techniques in various fields of applications.