https://scholars.lib.ntu.edu.tw/handle/123456789/593648
Title: | Synchronization and Inter-Layer Interactions of Noise-Driven Neural Networks | Authors: | Anis Yuniati TE-LUN MAI Chi-Ming Chen |
Keywords: | biological neural networks; computer simulation; developing neural networks; inter-layer interactions; noise-driven synchronization; repair mechanism of neural networks; spike-timing-dependent plasticity; synchronous firing | Issue Date: | 2017 | Publisher: | Frontiers Media {SA} | Journal Volume: | 11 | Journal Issue: | 2 | Start page/Pages: | 1-12 | Source: | Frontiers in Computational Neuroscience | Abstract: | In this study, we used the Hodgkin-Huxley (HH) model of neurons to investigate the phase diagram of a developing single-layer neural network and that of a network consisting of two weakly coupled neural layers. These networks are noise driven and learn through the spike-timing-dependent plasticity (STDP) or the inverse STDP rules. We described how these networks transited from a non-synchronous background activity state (BAS) to a synchronous firing state (SFS) by varying the network connectivity and the learning efficacy. In particular, we studied the interaction between a SFS layer and a BAS layer, and investigated how synchronous firing dynamics was induced in the BAS layer. We further investigated the effect of the inter-layer interaction on a BAS to SFS repair mechanism by considering three types of neuron positioning (random, grid, and lognormal distributions) and two types of inter-layer connections (random and preferential connections). Among these scenarios, we concluded that the repair mechanism has the largest effect for a network with the lognormal neuron positioning and the preferential inter-layer connections. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/593648 | ISSN: | 1662-5188 | DOI: | 10.3389/fncom.2017.00002 |
Appears in Collections: | 生命科學系 |
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