3 citations · 5 across the 4 of their papers we have counts for
4 papers
Finite-state Markovian surrogates for long-time neuronal state distributions and firing rates
Zhongyi Wang, Louis Tao, Zhuo-Cheng Xiao
Spiking neuronal networks connect cellular and synaptic mechanisms to collective activity, but estimating their long-time statistics often requires costly spike-by-spike simulation…
Minimizing information loss reduces spiking neuronal networks to differential equations
Jie Chang, Zhuoran Li, Zhongyi Wang +2
Spiking neuronal networks (SNNs) are widely used in computational neuroscience, from biologically realistic modeling of local cortical networks to phenomenological modeling of the…
Learning biological neuronal networks with artificial neural networks: neural oscillations
Ruilin Zhang, Zhongyi Wang, Tianyi Wu +4
First-principles-based modelings have been extremely successful in providing crucial insights and predictions for complex biological functions and phenomena. However, they can be h…
Multi-band oscillations emerge from a simple spiking network
Tianyi Wu, Yuhang Cai, Ruilin Zhang +3
In the brain, coherent neuronal activities often appear simultaneously in multiple frequency bands, e.g., as combinations of alpha (8-12 Hz), beta (12.5-30 Hz), gamma (30-120 Hz) o…