Summary: We present two-layered neural network models with $Q(\geq 2)$-states neurons for a system with middle temporal neurons and Medial Superior Temporal (MST) neurons by using a wake-sleep algorithm proposed by Hinton et al.; we notice that the wake-sleep algorithm consists of local learning rules. We first investigate a model with binary neurons for response properties of the MST neurons to optical flows as for various types of motion. We next extend the model with binary neurons to a model with $Q(\geq 3)$-states neurons and investigate the response properties of the MST neurons for various values of $Q(\geq 3)$.We obtain better response properties for the model with $Q(\geq 3)$-states neurons than for the one with binary neurons.