Structural Analysis on STDP Neural Networks Using Complex Network Theory
Synaptic plasticity is one of essential and central functions for the memory, the learning, and the development of the brains. Triggered by recent physiological experiments, the basic mechanisms of the spike-timing-dependent plasticity (STDP) have been widely analyzed in model studies. In this paper, we analyze complex structures in neural networks evolved by the STDP. In particular, we introduce the complex network theory to analyze spatiotemporal network structures constructed through the STDP. As a result, we show that nonrandom structures emerge in the neural network through the STDP.
KeywordsSynaptic Plasticity Degree Distribution Characteristic Path Length Spatiotemporal Structure Surrogate Network
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