18 Papers
49 Citations
Ying Du is an academic researcher from East China University of Science and Technology. The author has contributed to research in topics: Spike train & Synchronization (computer science). The author has an hindex of 7, co-authored 18 publications.
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Papers
Synchronization study in ring-like and grid-like neuronal networks
TL;DR: It is demonstrated that by varying some key parameters, such as the coupling strength and the external current injection, the neuronal network will exhibit various patterns of firing synchronization, which may be instructive in understanding synchronization transitions in neuronal systems.
Oscillations and synchrony in a cortical neural network
TL;DR: Investigation of oscillations and synchronization status of two different network connectivity patterns based on Izhikevich model reveal that by varying some key parameters, such as the connection weights of neurons, the external current injection, the noise of intensity and the neuron number, this neuronal network will exhibit various collective behaviors in randomly coupled neuronal network.
Using interspike intervals to quantify noise effects on spike trains in temperature encoding neurons
Ying Du,Qishao Lu,Rubin Wang +2 more
TL;DR: It is shown that the spike trains of a cold receptor neuron are more strongly affected by noise for low temperatures than for high temperatures, and this trend is also observed in both regimes of cold receptors.
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Spatiotemporal Behavior of Small-World Neuronal Networks Using a Map-Based Model
TL;DR: The study suggests that the map-based model will give a new opportunity to reproduce the real biological network containing a large number of neurons by varying some key parameters, such as the coupling strength of neurons, connection probability and the number of nearest neighbor in small-world topology.
12
Firing pattern and synchronization property analysis in a network model of the olfactory bulb
TL;DR: A biophysically-detailed, spiking neuronal model is used to simulate the activity of olfactory bulb and it is shown that by varying some key parameters such as maximal conductances of Ks and Nap the spike train of single neuron can exhibit various firing patterns.