Learning spiking neuronal networks with artificial neural networks: neural oscillations
First-principles-based modelings have been extremely successful in providing crucial
insights and predictions for complex biological functions and phenomena. However, they …
insights and predictions for complex biological functions and phenomena. However, they …
Minimizing information loss reduces spiking neuronal networks to differential equations
J Chang, Z Li, Z Wang, L Tao, ZC Xiao - arXiv preprint arXiv:2411.14801, 2024 - arxiv.org
Spiking neuronal networks (SNNs) are widely used in computational neuroscience, from
biologically realistic modeling of local cortical networks to phenomenological modeling of …
biologically realistic modeling of local cortical networks to phenomenological modeling of …
Learning biological neuronal networks with artificial neural networks: neural oscillations
First-principles-based modelings have been extremely successful in providing crucial
insights and predictions for complex biological functions and phenomena. However, they …
insights and predictions for complex biological functions and phenomena. However, they …