Abstract; It is thought that enormous neurons in the brain mutually communicate using their spike activities through complicated neural networks so that the brain works as a parallel information processor. From this point of view, the information processing principle of the brain is completely different from that of conventional Von Neuman-type computers. In spite of such a difference, actions in our behavior such as body movement, speech and thinking are basically conducted sequentially one by one. This raises a question of how sequential actions are generated from parallel computation of the brain. One of examples of the information processing of temporal sequences by the brain is the generation of voluntary movement. When we try to drink water in a glass on the table, we will extend our hand toward the glass, grasp it, bring it to our mouth and decline the glass to drink water. Unless we conduct all the component actions in this order, we cannot achieve the purpose of drinking water. As can be seen in this example, it is necessary for the brain to elicit motor commands for component actions in an adequate order when we wish to achieve a particular purpose. The underlying mechanism for such information processing by the brain is a long-standing target of research, known as “the serial order of motor behavior problem”. In addition, for smooth and efficient behavior, timing and magnitude of neural activity representing each component action is required. To approach these problems from the computational viewpoint, I propose a network model of basal ganglia-thalamo-cortical loops and cerebro-cerebellar loops for sequence generation and precise control of motor actions.