How do treadmill speed and terrain visibility influence neuromuscular control of guinea fowl locomotion?

Locomotor control mechanisms must flexibly adapt to both anticipated and unexpected terrain changes to maintain movement and avoid a fall. Recent studies revealed that ground birds alter movement in advance of overground obstacles, but not treadmill obstacles, suggesting context-dependent shifts in the use of anticipatory control. We hypothesized that differences between overground and treadmill obstacle negotiation relate to differences in visual sensory information, which influence the ability to execute anticipatory manoeuvres. We explored two possible explanations: (1) previous treadmill obstacles may have been visually imperceptible, as they were low contrast to the tread, and (2) treadmill obstacles are visible for a shorter time compared with runway obstacles, limiting time available for visuomotor adjustments. To investigate these factors, we measured electromyographic activity in eight hindlimb muscles of the guinea fowl (Numida meleagris, N=6) during treadmill locomotion at two speeds (0.7 and 1.3 m s−1) and three terrain conditions at each speed: (i) level, (ii) repeated 5 cm low-contrast obstacles (90% contrast, black/white). We hypothesized that anticipatory changes in muscle activity would be higher for (1) high-contrast obstacles and (2) the slower treadmill speed, when obstacle viewing time is longer. We found that treadmill speed significantly influenced obstacle negotiation strategy, but obstacle contrast did not. At the slower speed, we observed earlier and larger anticipatory increases in muscle activity and shifts in kinematic timing. We discuss possible visuomotor explanations for the observed context-dependent use of anticipatory strategies

The role of intrinsic muscle mechanics in the neuromuscular control of stable running in the guinea fowl

Here we investigate the interplay between intrinsic mechanical and neural factors in muscle contractile performance during running, which has been less studied than during walking. We report in vivo recordings of the gastrocnemius muscle of the guinea fowl (Numida meleagris), during the response and recovery from an unexpected drop in terrain. Previous studies on leg and joint mechanics following this perturbation suggested that distal leg extensor muscles play a key role in stabilisation. Here, we test this through direct recordings of gastrocnemius fascicle length (using sonomicrometry), muscle–tendon force (using buckle transducers), and activity (using indwelling EMG). Muscle recordings were analysed from the stride just before to the second stride following the perturbation. The gastrocnemius exhibits altered force and work output in the perturbed and first recovery strides. Muscle work correlates strongly with leg posture at the time of ground contact. When the leg is more extended in the drop step, net gastrocnemius work decreases (−5.2 J kg−1 versus control), and when the leg is more flexed in the step back up, it increases (+9.8 J kg−1 versus control). The muscle's work output is inherently stabilising because it pushes the body back toward its pre-perturbation (level running) speed and leg posture. Gastrocnemius length and force return to level running means by the second stride following the perturbation. EMG intensity differs significantly from level running only in the first recovery stride following the perturbation, not within the perturbed stride. The findings suggest that intrinsic mechanical factors contribute substantially to the initial changes in muscle force and work. The statistical results suggest that a history-dependent effect, shortening deactivation, may be an important factor in the intrinsic mechanical changes, in addition to instantaneous force–velocity and force–length effects. This finding suggests the potential need to incorporate history-dependent muscle properties into neuromechanical simulations of running, particularly if high muscle strains are involved and stability characteristics are important. Future work should test whether a Hill or modified Hill type model provides adequate prediction in such conditions. Interpreted in light of previous studies on walking, the findings support the concept of speed-dependent roles of reflex feedback.Organismic and Evolutionary Biolog

Limping following limb loss increases locomotor stability

Although many arthropods have the ability to voluntarily lose limbs, how these animals rapidly adapt to such an extreme perturbation remains poorly understood. It is thought that moving with certain gaits can enable efficient, stable locomotion; however, switching gaits requires complex information flow between and coordination of an animal's limbs. We show here that upon losing two legs, spiders can switch to a novel, more statically stable gait, or use temporal adjustments without a gait change. The resulting gaits have higher overall static stability than the gaits that would be imposed by limb loss. By decreasing the time spent in a low-stability configuration—effectively “limping” over less stable phases of the stride—spiders increased the overall stability of the less statically-stable gait with no observable reduction in speed, as compared to the intact condition. Our results shed light on how voluntary limb loss could have persisted evolutionarily among many animals, and provide bioinspired solutions for robots when they break or lose limbs

Kinetic energy fluctuation-driven locomotor transitions on potential energy landscapes of beam obstacle traversal and ground self-righting

Animals’ physical interaction with their environment, although often difficult, is effective and enables them to move robustly by using and transitioning between different modes such as running and climbing. Although robots exhibit some of these transitions, we lack a principled approach to generating and controlling them using effective physical interaction. Bridging this knowledge gap, in addition to advancing our understanding of animal locomotion, will improve robotic mobility. Recent studies of physical interaction with environment discovered that during beam obstacle traversal and ground self-righting, discoid cockroaches use and transition between diverse locomotor modes probabilistically and via multiple pathways. To traverse beams, the animal first pushes against them, but eventually pitches up due to beam restoring forces, following which it either pushes across beams (pitch mode) or rolls into the gap (roll mode). To self-right, the animal opens and pushes its wings against the ground, which pitches its body forward (metastable mode), and then rolls sideways (roll mode). Here, we seek to begin to explain these observations by integrating biological, robotic, and physics studies. We focus on pitch-to-roll and metastable-to-roll transitions of cockroaches during escape and emergency responses and feedforward-controlled robots. We discovered that across both systems, physical interaction is stochastic, with animals showing more variability. Animal and robot system states are strongly attracted to basins of their potential energy landscape, resulting in stereotyped locomotor modes. Locomotor transitions are probabilistic barrier-crossing transitions between landscape basins. Whereas the animal and robot traversed stiff beams via roll mode, they pushed across flimsy beams, suggesting that modes with easier physical interaction are more probable to occur (more favorable). Varying potential energy barriers by changing beam torsional stiffness (in the animal and robot) and kinetic energy fluctuation by changing body oscillation (in the robot) in both beam traversal and self-righting revealed that kinetic energy fluctuation comparable to the barrier facilitates probabilistic transition to the more favorable mode. Changing the system configuration (self-righting robot's wing opening) facilitates transitions by lowering the barrier. The animal's pitch-to-roll transition during beam traversal occurred even with insufficient kinetic energy fluctuation, suggesting that sensory feedback may be involved. These discoveries support the use of potential energy landscapes as a framework to understand locomotor transitions. Finally, we implemented methods for tracking and 3-D reconstruction of small animal locomotion in an existing terrain treadmill

Math Modeling of Interlimb Coordination in Cat Locomotion

Locomotion is an evolutionary adaptation that allows animals to move in 3-D space. The way that mammalian locomotion is controlled has been studied for generations. It remains unclear how the neuronal network that controls locomotion is structured and how the mammalian locomotor network keeps balance in the face of a changing environment. In this body of research, we build mathematical models of locomotion and fit our models to experimental data of walking cats to gain understanding of network connectivity and of balance control. Specifically, we test the biological plausibility of a particular connectivity of the mammalian locomotor network by matching network activity to phases of walking in different experimental conditions. We gain understanding of balance control with an inverted pendulum model that fits the center of mass oscillations during walking in different experimental conditions

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp