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Place Cells and Spatial Navigation based on 2d Visual Feature Extraction, Path Integration,
 

Summary: Place Cells and Spatial Navigation based on
2d Visual Feature Extraction, Path Integration,
and Reinforcement Learning
A. Arleo
F. Smeraldi S. Hug W. Gerstner
Centre for Neuro-Mimetic Systems, MANTRA
Swiss Federal Institute of Technology Lausanne,
CH-1015 Lausanne EPFL, Switzerland
Abstract
We model hippocampal place cells and head-direction cells by combin-
ing allothetic (visual) and idiothetic (proprioceptive) stimuli. Visual in-
put, provided by a video camera on a miniature robot, is preprocessed by
a set of Gabor filters on 31 nodes of a log-polar retinotopic graph. Unsu-
pervised Hebbian learning is employed to incrementally build a popula-
tion of localized overlapping place fields. Place cells serve as basis func-
tions for reinforcement learning. Experimental results for goal-oriented
navigation of a mobile robot are presented.
1 Introduction
In order to achieve spatial learning, both animals and artificial agents need to autonomously
locate themselves based on available sensory information. Neurophysiological findings

  

Source: Arleo, Angelo - Laboratory of Neurobiology of Adaptive Processes, Université Pierre-et-Marie-Curie, Paris 6

 

Collections: Biology and Medicine