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…
Mostly-monocular responses and other visual functions in a multiscale network model of Macaque V1
Zhuo-Cheng Xiao, Kevin K. Lin, Lai-Sang Young
Visual signals from the two eyes merge gradually as they pass through the primary visual cortex (V1). Here we use a computational model of Macaque V1 to study the first stage of th…
Numerical analysis for leaky-integrate-fire networks under Euler-Maruyama
Xu'an Dou, Frank Chen, Kevin K Lin +1
Leaky integrate-and-fire (LIF) networks are standard reduced models for spike-based neural dynamics and a natural substrate for neuromorphic computation. We study time-driven Euler…
Efficient, simulation-free estimators of firing rates with Markovian surrogates
Zhongyi Wang, Louis Tao, Zhuo-Cheng Xiao
Spiking neural networks (SNNs) are powerful mathematical models that integrate the biological details of neural systems, but their complexity often makes them computationally expen…