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• W2979308375 abstract "Message passing between components of a distributed physical system is non-instantaneous and contributes to determine the time scales of the emerging collective dynamics. In biological neuron networks this is due in part to local synaptic filtering of exchanged spikes, and in part to the distribution of the axonal transmission delays. How differently these two kinds of communication protocols affect the network dynamics is still an open issue due to the difficulties in dealing with the non-Markovian nature of synaptic transmission. Here, we develop a mean-field dimensional reduction yielding to an effective Markovian dynamics of the population density of the neuronal membrane potential, valid under the hypothesis of small fluctuations of the synaptic current. Within this limit, the resulting theory allows us to prove the formal equivalence between the two transmission mechanisms, holding for any synaptic time scale, integrate-and-fire neuron model, spike emission regimes and for different network states even when the neuron number is finite. The equivalence holds even for larger fluctuations of the synaptic input, if white noise currents are incorporated to model other possible biological features such as ionic channel stochasticity." @default.
• W2979308375 created "2019-10-18" @default.
• W2979308375 creator A5036037034 @default.
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• W2979308375 date "2019-10-08" @default.
• W2979308375 modified "2023-10-13" @default.
• W2979308375 title "Dimensional reduction in networks of non-Markovian spiking neurons: Equivalence of synaptic filtering and heterogeneous propagation delays" @default.
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• W2979308375 doi "https://doi.org/10.1371/journal.pcbi.1007404" @default.
• W2979308375 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6799936" @default.
• W2979308375 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/31593569" @default.
• W2979308375 hasPublicationYear "2019" @default.
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