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Information transmission across a dynamic synapse
Mark Goldman
Department of Brain and Cognitive Sciences
Massachusetts Institute of Technology
Many hippocampal and neocortical synapses appear to be surprisingly
unreliable, with only a small fraction of presynaptic action potentials
successfully triggering vesicle release. Previous work (Goldman et al.,
1999) has shown that synaptic depression may remove the correlations and
associated redundancy present in realistic spike trains, and has
suggested that this removal of correlations may increase the information
carried per vesicle release.
Here we calculate the information transmitted across a depressing
synapse. Information calculations on time scales typical of spike train
correlations are numerically intractable. We overcome this difficulty by
performing an analytic calculation. Our results show that synaptic
dynamics, regardless of their form, generally increase the information
transmitted across a stochastic synapse. This increase in information
may occur even when the dynamics introduce correlations, and hence
redundancy, into the train of synaptic transmissions. However, our
results suggest that the increase in information transmission is
greatest when the form of the dynamics is matched to that of the spike
train correlations.