Burst Synchronization without Frequency Locking in a Completely Solvable Neural Network Model
- Creators
- Schuster, Heinz
- Koch, Christof
Abstract
The dynamic behavior of a network model consisting of all-to-all excitatory coupled binary neurons with global inhibition is studied analytically and numerically. We prove that for random input signals, the output of the network consists of synchronized bursts with apparently random intermissions of noisy activity. Our results suggest that synchronous bursts can be generated by a simple neuronal architecture which amplifies incoming coincident signals. This synchronization process is accompanied by dampened oscillations which, by themselves, however, do not play any constructive role in this and can therefore be considered to be an epiphenomenon.
Additional Information
© 1992 Morgan Kaufmann. We thank R. Douglas for stimulating discussions and for inspiring us to think about this problem. Our collaboration was supported by the Stiftung Volkswagenwerk. The research of C.K. is supported by the National Science Foundation, the James McDonnell Foundation, and the Air Force Office of Scientific Research.Attached Files
Published - 581-burst-synchronization-without-frequency-locking-in-a-completely-solvable-neural-network-model.pdf
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Additional details
- Eprint ID
- 63938
- Resolver ID
- CaltechAUTHORS:20160125-142232445
- Stiftung Volkswagenwerk
- NSF
- James McDonnell Foundation
- Air Force Office of Scientific Research (AFOSR)
- Created
-
2016-01-25Created from EPrint's datestamp field
- Updated
-
2020-03-03Created from EPrint's last_modified field
- Series Name
- Advances in Neural Information Processing Systems
- Series Volume or Issue Number
- 4