We present a neural architecture capable to control syn-ergistically a flexible robotic model of the human vertebral column toward balance and upward posture. The neural controller is composed of non-linear oscillators that control each vertebre of the column constructed on the principle of tensegrity. They play the role of the central pattern generators in the spinal cords to generate rhythmical patterns and to be entrained to the resonant modes of the tensegrity system. After exploration of the different coordination regimes for different coupling parameters, the top-down controller is able to dynamically select, amplify or inhibit each motor synergy for upward postural balance even with respect to external perturbations. 2 Introduction Animal's musculo-skeletal system is based on a complex network of muscles, bones, nerves, tissues and soft-bodies, which are hard to replicate accurately in robots and to control. The animal's biomechanics are however well-ordered so that the neural control done in the spinal cords can fit its organization and generate the dynamical grouping of the muscles for compliant motion. The hierarchical organization of the motor control a.k.a. the motor synergies has been suggested to diminish the curse of dimensionality of control as enounced by Bernstein. Therefore, the design principles of both the body structure and of the neural model are complementary and have to be considered jointly in order to generate complex motion dynamics. Considering the body, the musculo-skeletal system is always soft and elastic and positioned in a stable or neutral posture. This property is specific to tensile structures, which most biological systems possess as attribute. Eventhough the redundancy and nonlinearity within such dynamical system might be considered as an obstacle for control, the symmetries of the overall structure and the many resonant modes generated can serve to reduce the dimensionality of the control problem. For instance, the control and discovery of the motor synergies may be easier to find by applying synchronization and resonance to these resonant modes. In previous works, we presented a framework based on feedback resonance of chaotic controllers to excite the passive dynam-Figure 1: Vertebral column robot. This tensegrity-based robot is compliant and lightweight , mounted with springs in opposition. The motors are mounted in pairs to produce co-contractions. An IMU is placed at the top of the structure for feedback. ics of several robotic devices and to tune them dynamically to their resonant modes. The control was done indirectly through the coupling parameters between the robot and the oscillators per se. By doing so, we decreased significantly the dimensionality of the control space. We suggested that the coupling parameters are playing the role of the neuro-modulators in the spinal cords, which dynamically trigger the different motor synergies [1]. As our aim is of integrating the structure and the control , we expand our framework to the control of a dorsal spine robot based on tensegrity, see Fig. 1. The homepage of the project is given at 1 with videos of the vertebral column in different configurations. After exploration and cat-egorization of its resonant modes and of its behavioral patterns within the parameters space for different coupling values , we control the spinal cord robot to return back to its rhythmical modes or to its postural configuration based on external feedback perturbations received.