Name
Abstract | ||
|---|---|---|
Abstract Here we,analyze synaptic transmission from an information-theoretic perspective. We derive closed-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. |
Year | Venue | Keywords |
|---|---|---|
1997 | NIPS | information-theoretic perspective,synaptic transmission,signal detection,lower bound |
Field | DocType | Volume |
Detection theory,Expression (mathematics),Computer science,Upper and lower bounds,Coding (social sciences),Redundancy (engineering),Artificial intelligence,Poisson distribution,Detector,Machine learning,Estimator | Conference | 10 |
ISSN | ISBN | Citations |
Advances in Neural Information Processing Systems 10, Michael I.
Jordan, Michael J. Kearns and Sara Solla (eds.), 1997 | 0-262-10076-2 | 8 |
PageRank | References | Authors |
4.15 | 2 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Amit Manwani | 1 | 56 | 11.11 |
| Christof Koch | 2 | 7248 | 973.47 |