Synaptic Transmission: An Information-Theoretic Perspective
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Abstract
Here we analyze synaptic transmission from an information-theoretic perspective. We derive close-form expressions for the lower-bounds on the capacity of a simple model of a cortical synapse under two explicit coding paradigms. Under the "signal estimation" paradigm, we assume the signal to be encoded in the mean firing rate of a Poisson neuron. The performance of an optimal linear estimator of the signal then provides a lower bound on the capacity for signal estimation. Under the "signal detection" paradigm, the presence or absence of the signal has to be detected. Performance of the optimal spike detector allows us to compute a lower bound on the capacity for signal detection. WE find that single synapses (for empirically measured parameter values) transmit information poorly but significant improvement can be achieved with a small amount of redundancy.
Additional Information
c1998 Massachusetts Institute of Technology. This research was supported by NSF, NIMH and the Sloan Center for Theoretical Neuroscience. We thank Fabrizio Gabbiani for illuminating discussions.Attached Files
Accepted Version - 178.pdf
Accepted Version - 178.ps
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178.pdf
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Identifiers
- Eprint ID
- 40568
- Resolver ID
- CaltechAUTHORS:20130816-103246428
Related works
- Describes
- http://arxiv.org/abs/q-bio/0309030 (URL)
Funding
- NSF
- NIMH
- Sloan Center for Theoretical Neuroscience
Dates
- Created
-
2008-01-16Created from EPrint's datestamp field
- Updated
-
2023-06-01Created from EPrint's last_modified field
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- Caltech groups
- Koch Laboratory (KLAB)