Up
Previous
Next
Repetition suppression, neural synchronization, and behavioral priming:
mechanisms underlying improved efficiency in networks of
spiking neurons
Stephen J. Gotts1 and
Carson C. Chow2
1Dept of Psychology and CNBC, Carnegie Mellon University
2Department of Mathematics, University of Pittsburgh
Human subjects tend to perform tasks faster and more accurately with
practice. Cognitive-level explanations of these behavioral changes
often involve some form of threshold modification to node activity or
changes in connection strengths such that representations become
active faster, at higher levels, and/or with greater precision.
However, the neural activity associated with stimulus repetition and
improved performance most often decrease rather than increase - a
phenomenon known as "repetition suppression" (Desimone, 1996). We
propose that the behavioral improvement following stimulus repetition
involves greater neural synchronization and more efficient neural
processing that arises from a reduction of activity. We show that
artificial networks of spiking neurons with "synaptic depression" (an
automatic reduction in synaptic efficacy following pre-synaptic
activity), can account for many of the empirical findings associated
with repetition suppression in humans and monkeys. Synaptic
depression leads to reductions in both the mean and variance of neural
firing rates which dynamically enhances neural synchronization. As
neurons synchronize, processing efficiency increases because fewer
spikes are required to fire post-synaptic neurons. This can improve
the rate of information transmission, allowing earlier propagation of
individual spikes throughout an entire processing pathway.