Name
Abstract | ||
|---|---|---|
We show that synchronization in networks of spiking neurons reflects a particular computation on the inputs: magnitude-invariant pattern detection. By analyzing a population of mutually coupled integrate-and-fire neurons, we find that the amount of synchronization reflects the number of components which match the input weights, where the similarity threshold is set by the strength of coupling among the neurons. Possible implications for cortical information processing are discussed. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1016/S0925-2312(02)00396-X | Neurocomputing |
Keywords | Field | DocType |
Computation with synchronization,Magnitude-invariant pattern detection,Pulse-coupled neurons,Information processing | Magnitude (mathematics),Population,Synchronization,Coupling,Information processing,Pattern recognition,Computer science,Synchronizing,Artificial intelligence,Invariant (mathematics),Machine learning,Computation | Journal |
Volume | Issue | ISSN |
44 | 1-4 | 0925-2312 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rolf D. Henkel | 1 | 26 | 4.00 |
| Udo Ernst | 2 | 13 | 3.99 |
| Klaus Pawelzik | 3 | 509 | 107.71 |