The vertebrate central nervous system is organized in modules that independently execute sophisticated tasks. Such modules are flexibly controlled and operate with a considerable degree of autonomy. One example is locomotion generated by spinal central pattern generator networks (CPGs) that shape the detailed motor output. The level of activity is controlled from brainstem locomotor command centers, which in turn, are under the control of the basal ganglia. By using a biophysically detailed, full-scale computational model of the lamprey CPG (10,000 neurons) and its brainstem/forebrain control, we demonstrate general control principles that can adapt the network to different demands. Forward or backward locomotion and steering can be flexibly controlled by local synaptic effects limited to only the very rostral part of the network. Variability in response properties within each neuronal population is an essential feature and assures a constant phase delay along the cord for different locomotor speeds.basal ganglia ͉ brainstem ͉ computational model ͉ lamprey ͉ spinal CPG V ertebrate behavior depends on different sets of neuronal networks specialized to coordinate different motor tasks like locomotion, breathing, and the expression of emotions (1-5). The activity of these networks is governed by brainstem command centers that are, in turn, under the control of the basal ganglia (1, 2). Although the critical role of these networks is well established, their intrinsic mode of operation has, for the most part, remained enigmatic. The lamprey nervous system provides one of the few examples in which detailed knowledge is available, not only of the different types of the participating neurons, but also their membrane properties and synaptic connectivity, particularly with regard to the spinal network (6, 7). Even with this knowledge at hand, it is very difficult, if not impossible, to establish, without the help of modeling, whether the experimental data available are actually sufficient to account for the dynamic operation of the networkand enable exploration of the particular role of different cellular and synaptic components to make predictions of their functional role. To achieve this, we report here a biophysically realistic model of the locomotor network and its control from the brain. The spinal network is composed of excitatory and inhibitory model neurons that, in considerable detail, behave as their biological counterparts. It proved to be important to introduce within each pool of model neurons the known biological variability in neuronal size and membrane properties. Thanks to recent developments in computer technology, we have been able to make a full-scale model of the network with 100 model neurons per segment, each of the Hodgkin-Huxley type-altogether 10,000 neurons connected via 760,000 synapses in the 100 segments. We represent the brainstem command system, as well as the forebrain control from the basal ganglia with an additional 3,500 neurons. Simulations limited to subsamples of neurons have previou...