"Avatar", a Modified Ex vivo Work Loop Experiments Using In vivo Strain and Activation

Movement behaviors are emergent features of dynamic systems that result from muscle force production and work output. The interplay between neural and mechanical systems occurs at all levels of biological organization concurrently, from the tuning of leg muscle properties while running to the dynamics of the limbs interacting with the ground. Understanding the conditions under which animals shift their neural control strategies toward intrinsic muscle mechanics ('preflexes') in the control hierarchy would allow muscle models to predict in vivo muscle force and work more accurately. To understand in vivo muscle mechanics, ex vivo investigation of muscle force and work under dynamically varying strain and loading conditions similar to in vivo locomotion is required. In vivo strain trajectories typically exhibit abrupt changes (i.e., strain and velocity transients) that arise from interactions among neural activation, musculoskeletal kinematics, and loads applied by the environment. The principal goal of our "avatar" technique is to investigate how muscles function during abrupt changes in strain rate and loading when the contribution of intrinsic mechanical properties to muscle force production may be highest. In the "avatar" technique, the traditional work-loop approach is modified using measured in vivo strain trajectories and electromyographic (EMG) signals from animals during dynamic movements to drive ex vivo muscles through multiple stretch-shortening cycles. This approach is similar to the work-loop technique, except that in vivo strain trajectories are scaled appropriately and imposed on ex vivo mouse muscles attached to a servo motor. This technique allows one to: (1) emulate in vivo strain, activation, stride frequency, and work-loop patterns; (2) vary these patterns to match in vivo force responses most accurately; and (3) vary specific features of strain and/or activation in controlled combinations to test mechanistic hypotheses.