Yupeng Tian, Jérémie Lefebvre, V. Kumar Murty
tlooto Summary
The analytical method developed could be potentially implemented to general input current like experimental recordings, and help in facilitating neuromorphic computation of spiking network models, navigating parameter spaces for model fitting, increasing neuronal mechanistic understandings in terms of computational properties.
Abstract
The leaky integrate-and-fire (LIF) model is one of the most widely used models in characterizing neuronal dynamics. The simplicity and brevity of LIF models allow for analytical solutions that could quickly navigate the parameter space and provide insights of the neuronal computational properties. In this work, we developed analytical
Citation format
TIAN, Yupeng; LEFEBVRE, Jérémie; MURTY, V. Kumar. Analytical firing rate from leaky integrate-and-fire models receiving non-normal inputs. Neuromorphic Computing and Engineering, 2026, 6.