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.
journal_name
Neural Computjournal_title
Neural computationauthors
Neltner L,Hansel D,Mato G,Meunier Cdoi
10.1162/089976600300015286subject
Has Abstractpub_date
2000-07-01 00:00:00pages
1607-41issue
7eissn
0899-7667issn
1530-888Xjournal_volume
12pub_type
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