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IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 20, NO. 7, JULY 2009 1135 Learning of SpatioTemporal Codes
 

Summary: IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 20, NO. 7, JULY 2009 1135
Learning of Spatio­Temporal Codes
in a Coupled Oscillator System
Gábor Orosz, Peter Ashwin, and Stuart Townley
Abstract--In this paper, we consider a learning strategy that
allows one to transmit information between two coupled phase
oscillator systems (called teaching and learning systems) via fre-
quency adaptation. The dynamics of these systems can be modeled
with reference to a number of partially synchronized cluster
states and transitions between them. Forcing the teaching system
by steady but spatially nonhomogeneous inputs produces cyclic
sequences of transitions between the cluster states, that is, infor-
mation about inputs is encoded via a "winnerless competition"
process into spatio­temporal codes. The large variety of codes
can be learned by the learning system that adapts its frequencies
to those of the teaching system. We visualize the dynamics using
"weighted order parameters (WOPs)" that are analogous to "local
field potentials" in neural systems. Since spatio­temporal coding
is a mechanism that appears in olfactory systems, the developed
learning rules may help to extract information from these neural

  

Source: Awtar, Shorya - Department of Mechanical Engineering, University of Michigan

 

Collections: Engineering