Animals move over a range of speeds by using rhythmic networks of neurons located in the spinal cord. Here we use electrophysiology and in vivo imaging in larval zebrafish (Danio rerio) to reveal a systematic relationship between the location of a spinal neuron and the minimal swimming frequency at which the neuron is active. Ventral motor neurons and excitatory interneurons are rhythmically active at the lowest swimming frequencies, with increasingly more dorsal excitatory neurons engaged as swimming frequency rises. Inhibitory interneurons follow the opposite pattern. These inverted patterns of recruitment are independent of cell soma size among interneurons, but may be partly explained by concomitant dorso-ventral gradients in input resistance. Laser ablations of ventral, but not dorsal, excitatory interneurons perturb slow movements, supporting a behavioural role for the topography. Our results reveal an unexpected pattern of organization within zebrafish spinal cord that underlies the production of movements of varying speeds.

Neuromechanics seeks to understand how muscles, sense organs, motor pattern generators, and brain interact to produce coordinated movement, not only in complex terrain but also when confronted with unexpected perturbations. Applications of neuromechanics include ameliorating human health problems (including prosthesis design and restoration of movement following brain or spinal cord injury), as well as the design, actuation and control of mobile robots. In animals, coordinated movement emerges from the interplay among descending output from the central nervous system, sensory input from body and environment, muscle dynamics, and the emergent dynamics of the whole animal. The inevitable coupling between neural information processing and the emergent mechanical behavior of animals is a central theme of neuromechanics. Fundamentally, motor control involves a series of transformations of information, from brain and spinal cord to muscles to body, and back to brain. The control problem revolves around the specific transfer functions that describe each transformation. The transfer functions depend on the rules of organization and operation that determine the dynamic behavior of each subsystem (i.e., central processing, force generation, emergent dynamics, and sensory processing). In this review, we (1) consider the contributions of muscles, (2) sensory processing, and (3) central networks to motor control, (4) provide examples to illustrate the interplay among brain, muscles, sense organs and the environment in the control of movement, and (5) describe advances in both robotics and neuromechanics that have emerged from application of biological principles in robotic design. Taken together, these studies demonstrate that (1) intrinsic properties of muscle contribute to dynamic stability and control of movement, particularly immediately after perturbations; (2) proprioceptive feedback reinforces these intrinsic self-stabilizing properties of muscle; (3) control systems must contend with inevitable time delays that can simplify or complicate control; and (4) like most animals under a variety of circumstances, some robots use a trial and error process to tune central feedforward control to emergent body dynamics.