4 papers
Diffusion learning reveals viable parameter manifolds and compensation geometry in biological dynamical systems
Ruilin Zhang, Louis Tao, Zhuo-Cheng Xiao
Models of complex systems often have many parameters, yet are constrained by far fewer experimentally accessible observables: similar activity can emerge from coordinated parameter…
Resolving the Blow-Up: A Time-Dilated Numerical Framework for Multiple Firing Events in Mean-Field Neuronal Networks
Xu'an Dou, Louis Tao, Zhe Xue +1
In large-scale excitatory neuronal networks, rapid synchronization manifests as {multiple firing events (MFEs)}, mathematically characterized by a finite-time blow-up of the neuron…
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…