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• W1982319328 endingPage "2069" @default.
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• W1982319328 abstract "In a biologically plausible but computationally simplified integrate-and-fire neuronal population, it is observed that transient synchronized spikes can occur repeatedly. However, groups with different properties exhibit different periods and different patterns of synchrony. We include learning mechanisms in these models. The effects of spike-timing-dependent plasticity have been known to play a distinct role in information processing in the central nervous system for several years. In this letter, neuronal models with dynamical synapses are constructed, and we analyze the effect of STDP on collective network behavior, such as oscillatory activity, weight distribution, and spike timing precision. We comment on how information is encoded by the neuronal signaling, when synchrony groups may appear, and what could contribute to the uncertainty in decision making." @default.
• W1982319328 created "2016-06-24" @default.
• W1982319328 creator A5005142483 @default.
• W1982319328 creator A5054827707 @default.
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• W1982319328 date "2008-08-01" @default.
• W1982319328 modified "2023-09-26" @default.
• W1982319328 title "Oscillations and Spiking Pairs: Behavior of a Neuronal Model with STDP Learning" @default.
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• W1982319328 doi "https://doi.org/10.1162/neco.2008.08-06-317" @default.
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