Authors:
Jochen Kerdels
and
Gabriele Peters
Affiliation:
University of Hagen, Germany
Keyword(s):
Recursive Growing Neural Gas, Entorhinal Cortex, Primates, Grid-like Encoding, Grid Cell Model.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computational Intelligence
;
Computational Neuroscience
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Methodologies and Methods
;
Neural Networks
;
Neurocomputing
;
Neuroinformatics and Bioinformatics
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Self-Organization and Emergence
;
Sensor Networks
;
Signal Processing
;
Soft Computing
;
Theory and Methods
Abstract:
Several regions of the mammalian brain contain neurons that exhibit grid-like firing patterns. The most prominent example of such neurons are grid cells in the entorhinal cortex (EC) whose activity correlates with the animal's location. Correspondingly, contemporary models of grid cells interpret this firing behavior as a specialized, functional part within a system for orientation and navigation. However, Killian et al. report on neurons in the primate EC that show similar, grid-like firing patterns but encode gaze-positions in the field of view instead of locations in the environment. We hypothesized that the phenomenon of grid-like firing patterns may not be restricted to navigational tasks and may be related to a more general, underlying information processing scheme. To explore this idea, we developed a grid cell model based on the recursive growing neural gas (RGNG) algorithm that expresses this notion. Here we show that our grid cell model can -- in
contrast to established gr
id cell models -- also describe the observations of Killian et al. and we outline the general conditions under which we would expect neurons to exhibit grid-like activity patterns in response to input signals independent of a presumed, functional task of the neurons.
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