Fall 2023

Abstract 

This presentation will discuss the strengths and weaknesses of the two most common laws of muscle mechanics: 1) the isometric force-length relationship; and 2) the force velocity relationship. Muscle mechanics data from animals during in vivo locomotion will be used to demonstrate the limitations associated with applying these laws to dynamics animal movement. Dynamic alternatives to the traditional quasi-static laws will be motivated by experimental data, and a general framework for how to develop new laws for dynamic muscle mechanics will be discussed.

Abstract 

Muscle contraction is a multiscale process.  During contraction, trillions of myosin molecules perform nanometer steps and generate picoNewton forces, powering muscle contraction over meters and force generation of Newtons.  Relating measurements at one scale to another is challenging, since interactions occuring at one scale cause emergent behaviors at larger scales.  Mathematical modeling provides a powerful tool to bridge scales and to take account of these emergent behaviors.  I will discuss some work we have done to build and validate multiscale muscle models in collaboration with several experimental groups.  First, I'll discuss a model we developed of myosin's interaction with actin that quantitatively describes observations of one, ten, and a hundred myosin molecules interacting with actin.  Then I'll describe how, by writing this model as a coupled system of partial differential equations (PDEs), we explained how mutations in myosin can improve jumping performance in fruit flies.  Second, I'll discuss a model we developed to describe myosin's calcium-dependent interaction with actin and the regulatory proteins troponin and tropomyosin (regulated thin filaments), and how we experimentally tested and validated the model with measurements of one, ten, and a hundred molecules interacting with regulated thin filaments at variable calcium.  I'll explain how another group used our model to understand the molecular mechanism of a heart drug in phase III clinical trials.  Finally, I'll describe a PDE model we developed to describe step stretch and ramp shortening experiments with muscle cells and show how fitting the model to our measurements allowed us to infer molecular-scale properties.  I'll then show how the model predicts our measurements of one, ten or a hundred myosin molecules interacting with actin, providing a self-consistent description of molecular to cellular measurements.  

Abstract 

Many airplanes can, or nearly can, glide stably without control. So it seems natural that the first successful powered flight followed from mastery of gliding. Many bicycles can, or nearly can, balance themselves when in motion. Bicycle design seems to have evolved to have this feature. Also, we can make toys and ‘robots’ that, like a stable glider or coasting bicycle, stably walk without motors or control in a remarkably human-like way. Again, it thus seems to make sense to use `passive-dynamics’ (uncontrolled dynamics) as a core for developing the control of walking robots and to gain understanding of the control of walking people. 

That's what I used to think. But, so far, this passive approach has not led to robust walking robots. And when looked at more carefully, the airplane and bicycle motivations are not as suggestive as they seemed. What about human evolution? Unlike what would be indicated by the passive-dynamic paradigm, we  didn’t evolve dynamic bodies and then learn to control them. Rather, people had elaborate control systems way back when we were fish and even when we were worms with no skeletons. 

Now, instead of thinking of good powered walking as passive walking with a small amount of control added, I think of good powered walking, human or robotic, as highly controlled, while optimized mostly for avoiding falls and, secondarily, for minimal actuator use.  However,  if control is paramount, why is it that uncontrolled passive-dynamic walkers walk so much like humans? It seems that energy optimal, yet robust, control, which is perhaps a proxy for the evolutionary development of human coordination, arrives at solutions that have some features in common with passive-dynamics. Such optimized control, when well done, has most of the motor effort, always at the ready, titrated out. Thus, highly controlled systems can deceptively-look almost “passive”.

Spring 2024

Abstract 

Animals move with economy and speed, successfully navigating complex environments. Most animals are also robustly maneuverable and stable. Studies of terrestrial locomotion in running avian bipeds and mammalian quadrupeds reveal neuromuscular and biomechanical capabilities for stability and economy of movement. Mechanical properties of muscles, as actuators, provide intrinsic stabilization in addition to effective power generation. Perturbation studies of running animals indicate that passive-dynamics likely underlie effective stabilization, supplemented by neuromuscular feedback control. Studies of bird flight and visuomotor control for flight navigation through cluttered aerial environments reveal how birds control head and body movements to guide their flight path.

Abstract 

Why do humans move the way they do and how do they do it so well? In this multi-part talk, we first describe a number of studies over the years showing that many aspects of human movement can be predicted, at least approximately, by optimizing the total energy cost for the task – not just in familiar steady-state straight-line locomotion tasks, but also in unfamiliar tasks, discrete and transient locomotion with starting and stopping, locomotion involving overground gait transitions (switches between walking and running), non-straight-line walking with turning or avoiding obstacles, walking with external assistance, etc. Next, we show how human recovery from perturbations during walking and running are well described by simple control strategies, explaining how people can locomote despite uncertainty and other unexpected changes. Finally, we will describe our recent work on improving metabolic cost models, so that they may eventually be applied to understand complex locomotor tasks.

Abstract 

From fossils to the forest: Modelling ape locomotor evolution using wild chimpanzees A signature adaptation of living hominoids (apes and humans) is the ability to maintain a vertical torso - ‘orthogrady’. In living apes, orthogrady allows differential use of fore- and hindlimbs and thus a range of 'versatile' arboreal behaviors, such as vertical climbing and suspension. It is hypothesized that apes evolved such versatility for feeding on fruit from terminal branches in forest canopies. However, Morotopithecus, a 21-million-year old ape from Uganda, and the oldest to exhibit orthogrady, consumed leaves and lived in grassy woodlands. To better understand the relationship between feeding postures, food type and canopy location, we collected focal follow data from 103 wild chimpanzees from Kibale Forest, Uganda, yielding 8498 arboreal feeding observations. Using a Generalized Linear Mixed Model, we found that chimpanzees are ~two times more likely to use versatile postures when feeding on leaves compared to fruit, strengthening the paleontologically-derived hypothesis that foraging for leaves may have influenced the evolution of hominoid positional behavioral versatility. Orthogrady also occurs during vertical ascent and descent to and from the trees to feed, and during bipedalism. Thus we will also discuss the use of opportunistically collected video of wild chimpanzees to explore the evolution of these behaviors.