A self-organizing model of the visual development of hand-centred representations

We show how hand-centred visual representations could develop in the primate posterior parietal and premotor cortices during visually guided learning in a self-organizing neural network model. The model incorporates trace learning in the feed-forward synaptic connections between successive neuronal...

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Bibliographic Details
Published in:PloS one 2013-06, Vol.8 (6), p.e66272-e66272
Main Authors: Galeazzi, Juan M, Mender, Bedeho M W, Paredes, Mariana, Tromans, James M, Evans, Benjamin D, Minini, Loredana, Stringer, Simon M
Format: Article
Language:English
Subjects:
Algorithms
Animals
Artificial neural networks
Biology
Brain - physiology
Brain research
Computer Simulation
Configurations
Experimental psychology
Eye movements
Feedback
Hand - physiology
Learning
Mathematical models
Models, Biological
Nerve Net - physiology
Neural networks
Neural Networks, Computer
Neurons
Neurosciences
Primates - physiology
Representations
Retina
Social and Behavioral Sciences
Software
Successive discrimination learning
Synapses
Visual Perception
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Summary:We show how hand-centred visual representations could develop in the primate posterior parietal and premotor cortices during visually guided learning in a self-organizing neural network model. The model incorporates trace learning in the feed-forward synaptic connections between successive neuronal layers. Trace learning encourages neurons to learn to respond to input images that tend to occur close together in time. We assume that sequences of eye movements are performed around individual scenes containing a fixed hand-object configuration. Trace learning will then encourage individual cells to learn to respond to particular hand-object configurations across different retinal locations. The plausibility of this hypothesis is demonstrated in computer simulations.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0066272