Topic: excitatory-inhibitory spiking networks

Network models are often designed to capture selective aspects of cortical circuits. On one end, mechanistic models such as balanced spiking networks resemble activity regimes observed in data, but are often limited to simple computations. On the other end, functional models like trained deep networks can show comparable performance and dynamical motifs, but are far removed from experimental physiology. Here, we put forth a new framework for excitatory-inhibitory spiking networks which retains key properties of both mechanistic and functional models. Based on previous studies of the geometry o