IntroductionUnderstanding how artificial neural networks (ANNs) can capture biologically meaningful dynamics is a central challenge in systems neuroscience. In this work, we investigate whether spiking neural networks (SNNs) can function not only as machine-learning tools but also as biologically inspired computational analogs and tractable testbeds for studying pathological neural dynamics.MethodsWe implemented a spiking autoencoder composed of Leaky Integrate-and-Fire and Synaptic neuron model