Roger Quinn, Professor, rdq@case.edu, http://biorobots.case.edu
Hillel Chiel, Professor, hjc@case.edu, https://case.edu/artsci/biology/chiellab/ Case Western Reserve University
The purpose of this workshop is to compare and contrast how neuromechanical systems in animals from different phyla allow them to perform functions essential to their survival for the purpose of modeling them and implementing them in robots. The workshop first focuses on an overview on how the frequency of movement and size of limbs can affect the control of locomotion (Dr. Gregory Sutton). The role of joint stresses and strains on control of limbed locomotion is then discussed (Dr. Matthew Tresch). A discussion of how to fit multiple parameters that are necessary for neuromechanical models provides useful guidance for others who are working in this area (Dr. Matthieu Chardon). New insights on insect walking will bridge between single neuron function and system performance of six-legged walking (Dr. Ansgar Büschges). To further understand sensory inputs to the insect leg, a mechanical model of key leg strain sensors, campaniform sensilla, has been used to gain insights (Dr. Alexander Blanke). The workshop should be of broad general interest to those studying the neural and mechanical basis of behavior and those interested in creating autonomous artificial devices inspired by animals.
This workshop will focus on how animals’ neuromechanical systems solve problems that autonomous robots must solve. Thus, it should be of broad general interest to those studying the neural and mechanical basis of behavior and those interested in creating autonomous artificial devices inspired by animals.
Gregory Sutton, Professor at Royal Society University, Department of Life Sciences, College of Science, University of Lincoln, U.K.
While biological systems generate legged locomotion in very different ways, there are two parameters, limb size and leg swing frequency, which can be used to determine the control strategy necessary to generate locomotion. We show that the fundamental physics of legged locomotion can be derived from these two parameters, and that these two parameters can then determine the fundamental control strategy necessary to generate stable locomotion. Consequently, while animals generate locomotion very differently, the fundamental physics of the movement can yield universal parameters for all legged locomotion.
Matthew Tresch, Professor, Biomedical Engineering, Neuroscience, Physical Medicine and Rehabilitation, Northwestern University
Matthieu Chardon, Research Assistant Prof, Dept of Neuroscience, Northwestern University
Neuromechanical models often rely on Hodgkin-Huxley (H-H) formulations for their neuron models. A challenge with H-H models is that many different sets of ion channel conductances can produce the same response from the model. This makes computational approaches for inferring ion channel parameters from observations of voltage data difficult or intractable. We show that by framing the inference in a Bayesian setting, which naturally allows multiple solutions, and employing a specific algorithm from the Markov chain Monte Carlo family allows us to successfully reconstruct “landscapes” or “maps” of possible parameter sets. The visualization of these solution maps (i.e., posteriors) enables physiologists to inspect and reason about the vast possibilities, sensitivities, and uncertainties of ion channel parameters. We will cover how this algorithm is being used to reverse engineer a locomotion circuit.
Ansgar Büschges, Department of Animal Physiology, Institute of Zoology, University of Cologne
Alexander Blanke, Institute of Evolutionary Biology and Animal Ecology, University of Bonn
Time schedule coming soon!