Complementary spatial and timing control in rhythmic arm movements.

Volitional rhythmic motor behaviors such as limb cycling and locomotion exhibit spatial and timing regularity. Such rhythmic movements are executed in the presence of exogenous visual and nonvisual cues, and previous studies have shown the pivotal role that vision plays in guiding spatial and temporal regulation. However, the influence of nonvisual information conveyed through auditory or touch sensory pathways, and its effect on control, remains poorly understood. To characterize the function of nonvisual feedback in rhythmic arm control, we designed a paddle juggling task in which volunteers bounced a ball off a rigid elastic surface to a target height in virtual reality by moving a physical handle with the right hand. Feedback was delivered at two key phases of movement: visual feedback at ball peaks only and simultaneous audio and haptic feedback at ball-paddle collisions. In contrast to previous work, we limited visual feedback to the minimum required for jugglers to assess spatial accuracy, and we independently perturbed the spatial dimensions and the timing of feedback. By separately perturbing this information, we evoked dissociable effects on spatial accuracy and timing, confirming that juggling, and potentially other rhythmic tasks, involves two complementary processes with distinct dynamics: spatial error correction and feedback timing synchronization. Moreover, we show evidence that audio and haptic feedback provide sufficient information for the brain to control the timing synchronization process by acting as a metronome-like cue that triggers hand movement. NEW & NOTEWORTHY Vision contains rich information for control of rhythmic arm movements; less is known, however, about the role of nonvisual feedback (touch and sound). Using a virtual ball bouncing task allowing independent real-time manipulation of spatial location and timing of cues, we show their dissociable roles in regulating motor behavior. We confirm that visual feedback is used to correct spatial error and provide new evidence that nonvisual event cues act to reset the timing of arm movements.

Haptic feedback enhances rhythmic motor control by reducing variability, not improving convergence rate.

Stability and performance during rhythmic motor behaviors such as locomotion are critical for survival across taxa: falling down would bode well for neither cheetah nor gazelle. Little is known about how haptic feedback, particularly during discrete events such as the heel-strike event during walking, enhances rhythmic behavior. To determine the effect of haptic cues on rhythmic motor performance, we investigated a virtual paddle juggling behavior, analogous to bouncing a table tennis ball on a paddle. Here, we show that a force impulse to the hand at the moment of ball-paddle collision categorically improves performance over visual feedback alone, not by regulating the rate of convergence to steady state (e.g., via higher gain feedback or modifying the steady-state hand motion), but rather by reducing cycle-to-cycle variability. This suggests that the timing and state cues afforded by haptic feedback decrease the nervous system's uncertainty of the state of the ball to enable more accurate control but that the feedback gain itself is unaltered. This decrease in variability leads to a substantial increase in the mean first passage time, a measure of the long-term metastability of a stochastic dynamical system. Rhythmic tasks such as locomotion and juggling involve intermittent contact with the environment (i.e., hybrid transitions), and the timing of such transitions is generally easy to sense via haptic feedback. This timing information may improve metastability, equating to less frequent falls or other failures depending on the task.

Stride-to-stride energy regulation for robust self-stability of a torque-actuated dissipative spring-mass hopper.

In this paper, we analyze the self-stability properties of planar running with a dissipative spring-mass model driven by torque actuation at the hip. We first show that a two-dimensional, approximate analytic return map for uncontrolled locomotion with this system under a fixed touchdown leg angle policy and an open-loop ramp torque profile exhibits only marginal self-stability that does not always persist for the exact system. We then propose a per-stride feedback strategy for the hip torque that explicitly compensates for damping losses, reducing the return map to a single dimension and substantially improving the robust stability of fixed points. Subsequent presentation of simulation evidence establishes that the predictions of this approximate model are consistent with the behavior of the exact plant model. We illustrate the relevance and utility of our model both through the qualitative correspondence of its predictions to biological data as well as its use in the design of a task-level running controller.

Variability in locomotor dynamics reveals the critical role of feedback in task control.

Animals vary considerably in size, shape, and physiological features across individuals, but yet achieve remarkably similar behavioral performances. We examined how animals compensate for morphophysiological variation by measuring the system dynamics of individual knifefish (Eigenmannia virescens) in a refuge tracking task. Kinematic measurements of Eigenmannia were used to generate individualized estimates of each fish's locomotor plant and controller, revealing substantial variability between fish. To test the impact of this variability on behavioral performance, these models were used to perform simulated 'brain transplants'-computationally swapping controllers and plants between individuals. We found that simulated closed-loop performance was robust to mismatch between plant and controller. This suggests that animals rely on feedback rather than precisely tuned neural controllers to compensate for morphophysiological variability.

People come in different shapes and sizes, but most will perform similarly well if asked to complete a task requiring fine manual dexterity ­ such as holding a pen or picking up a single grape. How can different individuals, with different sized hands and muscles, produce such similar movements? One explanation is that an individual's brain and nervous system become precisely tuned to mechanics of the body's muscles and skeleton. An alternative explanation is that brain and nervous system use a more "robust" control policy that can compensate for differences in the body by relying on feedback from the senses to guide the movements. To distinguish between these two explanations, Uyanik et al. turned to weakly electric freshwater fish known as glass knifefish. These fish seek refuge within root systems, reed grass and among other objects in the water. They swim backwards and forwards to stay hidden despite constantly changing currents. Each fish shuttles back and forth by moving a long ribbon-like fin on the underside of its body. Uyanik et al. measured the movements of the ribbon fin under controlled conditions in the laboratory, and then used the data to create computer models of the brain and body of each fish. The models of each fish's brain and body were quite different. To study how the brain interacts with the body, Uyanik et al. then conducted experiments reminiscent of those described in the story of Frankenstein and transplanted the brain from each computer model into the body of different model fish. These "brain swaps" had almost no effect on the model's simulated swimming behavior. Instead, these "Frankenfish" used sensory feedback to compensate for any mismatch between their brain and body. This suggests that, for some behaviors, an animal's brain does not need to be precisely tuned to the specific characteristics of its body. Instead, robust control of movement relies on many seemingly redundant systems that provide sensory feedback. This has implications for the field of robotics. It further suggests that when designing robots, engineers should prioritize enabling the robots to use sensory feedback to cope with unexpected events, a well-known idea in control engineering.

Body stiffness and damping depend sensitively on the timing of muscle activation in lampreys.

Unlike most manmade machines, animals move through their world using flexible bodies and appendages, which bend due to internal muscle and body forces, and also due to forces from the environment. Fishes in particular must cope with fluid dynamic forces that not only resist their overall swimming movements but also may have unsteady flow patterns, vortices, and turbulence, many of which occur more rapidly than what the nervous system can process. Has natural selection led to mechanical properties of fish bodies and their component tissues that can respond very quickly to environmental perturbations? Here, we focus on the mechanical properties of isolated muscle tissue and of the entire intact body in the silver lamprey, Ichthyomyzon unicuspis. We developed two modified work loop protocols to determine the effect of small perturbations on the whole body and on isolated segments of muscle as a function of muscle activation and phase within the swimming cycle. First, we examined how the mechanical properties of the whole lamprey body change depending on the timing of muscle activity. Relative to passive muscle, muscle activation can modulate the effective stiffness by about two-fold and modulate the effective damping by >10-fold depending on the activation phase. Next, we performed a standard work loop test on small sections of axial musculature while adding low-amplitude sinusoidal perturbations at specific frequencies. We modeled the data using a new system identification technique based on time-periodic system analysis and harmonic transfer functions (HTFs) and used the resulting models to predict muscle function under novel conditions. We found that the effective stiffness and damping of muscle varies during the swimming cycle, and that the timing of activation can alter both the magnitude and timing of peak stiffness and damping. Moreover, the response of the isolated muscle was highly nonlinear and length dependent, but the body's response was much more linear. We applied the resulting HTFs from our experiments to explore the effect of pairs of antagonistic muscles. The results suggest that when muscles work against each other as antagonists, the combined system has weaker nonlinearities than either muscle segment alone. Together, these results begin to provide an integrative understanding of how activation timing can tune the mechanical response properties of muscles, enabling fish to swim effectively in their complex and unpredictable environment.

Walking dynamics are symmetric (enough).

Many biological phenomena such as locomotion, circadian cycles and breathing are rhythmic in nature and can be modelled as rhythmic dynamical systems. Dynamical systems modelling often involves neglecting certain characteristics of a physical system as a modelling convenience. For example, human locomotion is frequently treated as symmetric about the sagittal plane. In this work, we test this assumption by examining human walking dynamics around the steady state (limit-cycle). Here, we adapt statistical cross-validation in order to examine whether there are statistically significant asymmetries and, even if so, test the consequences of assuming bilateral symmetry anyway. Indeed, we identify significant asymmetries in the dynamics of human walking, but nevertheless show that ignoring these asymmetries results in a more consistent and predictive model. In general, neglecting evident characteristics of a system can be more than a modelling convenience--it can produce a better model.