Crossref journal-article
MIT Press - Journals
Neural Computation (281)
Abstract

The emergence of synchrony in the activity of large, heterogeneous networks of spiking neurons is investigated. We define the robustness of synchrony by the critical disorder at which the asynchronous state becomes linearly unstable. We show that at low firing rates, synchrony is more robust in excitatory networks than in inhibitory networks, but excitatory networks cannot display any synchrony when the average firing rate becomes too high. We introduce a new regime where all inputs, external and internal, are strong and have opposite effects that cancel each other when averaged. In this regime, the robustness of synchrony is strongly enhanced, and robust synchrony can be achieved at a high firing rate in inhibitory networks. On the other hand, in excitatory networks, synchrony remains limited in frequency due to the intrinsic instability of strong recurrent excitation.

Bibliography

Neltner, L., Hansel, D., Mato, G., & Meunier, C. (2000). Synchrony in Heterogeneous Networks of Spiking Neurons. Neural Computation, 12(7), 1607–1641.

Dates
Type When
Created 23 years, 1 month ago (July 27, 2002, 7:56 a.m.)
Deposited 4 years, 5 months ago (March 12, 2021, 4:47 p.m.)
Indexed 3 weeks, 3 days ago (Aug. 12, 2025, 5:46 p.m.)
Issued 25 years, 2 months ago (July 1, 2000)
Published 25 years, 2 months ago (July 1, 2000)
Published Print 25 years, 2 months ago (July 1, 2000)
Funders 0

None

@article{Neltner_2000, title={Synchrony in Heterogeneous Networks of Spiking Neurons}, volume={12}, ISSN={1530-888X}, url={http://dx.doi.org/10.1162/089976600300015286}, DOI={10.1162/089976600300015286}, number={7}, journal={Neural Computation}, publisher={MIT Press - Journals}, author={Neltner, L. and Hansel, D. and Mato, G. and Meunier, C.}, year={2000}, month=jul, pages={1607–1641} }