Muscles Reduce Neuronal Information Load: Quantification of Control Effort in Biological vs. Robotic Pointing and Walking

Abstract

It is hypothesized that the nonlinear muscle characteristic of biomechanical systems simplify control in the sense that the information the nervous system has to process is reduced through off-loading computation to the morphological structure. It has been proposed to quantify the required information with an information-entropy based approach, which evaluates the minimally required information to control a desired movement, i.e., control effort. The key idea is to compare the same movement but generated by different actuators, e.g., muscles and torque actuators, and determine which of the two morphologies requires less information to generate the same movement. In this work, for the first time, we apply this measure to numerical simulations of more complex human movements: point-to-point arm movements and walking. These models consider up to 24 control signals rendering the brute force approach of the previous implementation to search for the minimally required information futile. We therefore propose a novel algorithm based on the pattern search approach specifically designed to solve this constraint optimization problem. We apply this algorithm to numerical models, which include Hill-type muscle-tendon actuation as well as ideal torque sources acting directly on the joints. The controller for the point-to-point movements was obtained by deep reinforcement learning for muscle and torque actuators. Walking was controlled by proprioceptive neural feedback in the muscular system and a PD controller in the torque model. Results show that the neuromuscular models consistently require less information to successfully generate the movement than the torque-driven counterparts. These findings were consistent for all investigated controllers in our experiments, implying that this is a system property, not a controller property. The proposed algorithm to determine the control effort is more efficient than other standard optimization techniques and provided as open source.

Power Amplification Increases With Contraction Velocity During Stretch-Shortening Cycles of Skinned Muscle Fibers

“…The separation of XB- and non-XB structures is of primary importance to give a more detailed understanding of the potential involvement of viscoelastic elements, such as titin, working as an energy-storing spring during lengthening contractions and SSCs. This information is required for the improvement of muscle models ( Heidlauf et al, 2016 ; Tahir et al, 2018 ; Seydewitz et al, 2019 ) as well as for improved predictions by multi-body models ( Röhrle et al, 2017 ; Haeufle et al, 2020 ) concerning, e.g., movement control and efficiency of locomotion.…”

Morphological Computation Increases From Lower- to Higher-Level of Biological Motor Control Hierarchy

“…Therefore, we expect that our findings represent a fundamental concept in biology. We further expect that it extends to other movements too, e.g., locomotion, for which it is known that muscles significantly contribute to the movement generation (van Soest and Bobbert, 1993 ; Gerritsen et al, 1998 ; Daley et al, 2009 ; Haeufle et al, 2010 ; John et al, 2013 ) and allow to simplify higher-level control (Haeufle et al, 2014 , 2020 ; Ghazi-Zahedi et al, 2016 ).…”

“…Still, the results found by the ANOVA and post-hoc test match what can be seen in Figures 5, 7. Literature suggests this contribution of muscles to dynamic movements (van Soest and Bobbert, 1993;Gerritsen et al, 1998;Wagner and Blickhan, 1999;Eriten and Dankowicz, 2009;van der Krogt et al, 2009;Haeufle et al, 2010Haeufle et al, , 2012Haeufle et al, , 2020Pinter et al, 2012;John et al, 2013;Kambara et al, 2013;Bayer et al, 2017;Stollenmaier et al, 2020a). In this sense, the MC acc W quantifies the "importance" of each hierarchical level in the sense of influence on the behavior (world state evolution) of the system.…”

Giraffes and hominins: reductionist model predictions of compressive loads at the spine base for erect exponents of the animal kingdom

“…The results of the comparisons across different degrees of spine bending, which are common to the species examined, touch general evolutionary issues across all species that developed erect body parts. Namely, the degree of erectness of a species may be indicative of at least four design criteria being balanced during evolution: (1) (neural) control effort ( Haeufle et al, 2014 ) for posture and movement ( Haeufle et al, 2020 ), (2) loads of force-bearing structures, (3) metabolic energy consumption, and (4) functional capabilities of the motor apparatus. Two of these are definitely costs (control effort, metabolic energy), one may be indicative in itself of a balance of costs and basic limits of physics (mechanical loads), and one is a gain (motor capabilities).…”