An evolutionary approach is used to design neural control architectures for virtual sixlegged animats. Using a geometry-oriented variation of the cellular encoding scheme and syntactic constraints that reduce the size of the genetic search space, the developmental programs of straight locomotion controllers are first evolved. One such controller is then included as the first module in a larger architecture, in which a second neural module is evolved and develops connections to the first one, so as to set locomotion on or offaccording to sustained or instantaneous external control signals. Such an incremental approach should prove useful to the automatic design of relatively complex control architectures that might, in particular, implement some cognitive abilities over and above mere stimulus-response mechanisms.