Modelling the Cortical Columnar Organisation for Topological State-Space Representation, and Action Planning

Authors:
Louis-Emmanuel Martinet;Benjamin Fouque;Jean-Baptiste Passot;Jean-Arcady Meyer;Angelo Arleo
Affiliations:
Université Pierre et Marie Curie - Paris 6, FRE2507, ISIR, Paris, France F-75016 and UPMC Univ Paris 6, UMR 7102, Paris, France F-75005 and CNRS, UMR 7102, Paris, France F-75005;Université Pierre et Marie Curie - Paris 6, FRE2507, ISIR, Paris, France F-75016 and UPMC Univ Paris 6, UMR 7102, Paris, France F-75005 and CNRS, UMR 7102, Paris, France F-75005;UPMC Univ Paris 6, UMR 7102, Paris, France F-75005 and CNRS, UMR 7102, Paris, France F-75005;Université Pierre et Marie Curie - Paris 6, FRE2507, ISIR, Paris, France F-75016;UPMC Univ Paris 6, UMR 7102, Paris, France F-75005 and CNRS, UMR 7102, Paris, France F-75005
Venue:
SAB '08 Proceedings of the 10th international conference on Simulation of Adaptive Behavior: From Animals to Animats
Year:
2008

Citing 8
Cited 0

An adaptive neural network: the cerebral cortex

An adaptive neural network: the cerebral cortex
Head Direction Cells and the Neural Mechanisms of Spatial Orientation (Bradford Books)

Head Direction Cells and the Neural Mechanisms of Spatial Orientation (Bradford Books)
A Hierarchy of Associations in Hippocampo-Cortical Systems: Cognitive Maps and Navigation Strategies

Neural Computation
A Model of Prefrontal Cortical Mechanisms for Goal-directed Behavior

Journal of Cognitive Neuroscience
DEA: An Architecture for Goal Planning and Classification

Neural Computation
Synergies Between Intrinsic and Synaptic Plasticity Mechanisms

Neural Computation
Map-based navigation in mobile robots

Cognitive Systems Research
Cognitive navigation based on nonuniform Gabor space sampling, unsupervised growing networks, and reinforcement learning

IEEE Transactions on Neural Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

We present a neuromimetic navigation system modelling the columnar structure of the cortex to mediate spatial learning and action planning. The model has been validated on a spatial behavioural task, namely the Tolman & Honzik's detourprotocol, which allowed us to test the ability of the system to build a topological representation of the environment, and to use it to exhibit flexible goal-directed behaviour (i.e., to predict the outcome of alternative trajectories to avoid blocked pathways). First, it is shown that the model successfully reproduces the navigation performance of rodents in terms of goal-directed path selection. Second, we report on the neural response patterns characterising the learnt columnar space representation.