TR announcement: Analysis of the Effects of Noise on a Model for the Neural Mechanism of Short-Term Active Memory.

[J. Devin McAuley]

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Analysis of the Effects of Noise on a Model for 
the Neural Mechanism of Short-Term Active Memory.
(8 pages)

J. Devin McAuley and Joseph Stampfli
Indiana University

ABSTRACT: Zipser (1991) showed that the hidden unit activity
of a fully-recurrent neural network model, trained on a
simple memory task, matched the temporal activity patterns
of memory-associated neurons in monkeys performing delayed 
saccade or delayed match-to-sample tasks.  When noise,
simulating random fluctuations in neural firing rate, is
added to the unit activations of this model, the effect on
the memory dynamics is to slow the rate of information loss.
In this paper, we show that the dynamics of the iterated 
sigmoid function, with gain and bias parameters, is qualitatively
very similar to the "output" behavior of Zipser's multi-unit
model.  Analysis of the simpler system provides an explanation
for the effect of noise that is missing from the description
of the multi-unit model.

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J. Devin McAuley
Artificial Intelligence Laboratory
Computer Science Department
Indiana University
Bloomington, Indiana 47405
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