LSMs are a type of spiking neural network. LSMs are sparse neural networks with activations replaced as threshold levels. The LSM models the behavior of the following: an input layer with randomly connected reservoir of neurons that add activations over the timesteps and fire after a threshold. The pattern involved with time varying inputs is called a spatio-temporal pattern (spiking neurons). Lastly, an output layer interprets the pattern and uses it for classification. LSMs are used for speech recognition or computer vision.