Narrow Results

We study the emergent functional neural network organized by synaptic reorganization by the spike timing dependent synaptic plasticity (STDP). We show that small-world and scale-free functional structures organized by STDP, in the case of synaptic balance, exhibit hierarchial modularity.

Hybrid synapses widely exist in the brain neural system, but how memristive and plastic chemical synapses cooperatively modulate the collective dynamics of neurons remains largely unknown. Here, we constructed self-organized networks with two heterogeneous FitzHugh–Nagumo (FHN) neurons coupled with memristive and chemical synapses, wherein the chemical synapse is modulated by the spike-timing-dependent plasticity (STDP) rule. Additionally, three kinds of network models involving excitatory–excitatory ($E$–$E)$ neurons, high excitatory–inhibitory (high $E$–$I$) neurons and low excitatory–inhibitory (low $E$–$I$) neurons were constructed. The modulation of memristive synapses on the structure and dynamics of self-organized neuronal networks is greatly dependent on model selection. Stronger coupling of memristive synapses induces consistently more stable network structure and enhanced network synchronization in the $E$–$E$ and high $E$–$I$ models but has complex effects on the low $E$–$I$ neuronal network. In contrast, increasing the closing rate of memristive synapses has little effect on the $E$–$E$ and high $E$–$I$ networks but can accelerate the self-organization process and result in more complex firing patterns and weaker synchronization in the low $E$–$I$ network. These results provide further understanding of the mechanism of the self-organized neuronal network dynamics underlying hybrid synapses and neuronal excitation.