Simple motor networks mimic human muscle behavior under increasing load

Scientists have developed a network of mechanical motors that mimic the molecular machinery underpinning human muscle contraction. The University of Bristol-led findings, published in the Journal of the Royal Society Interface this week, could open new possibilities for artificial muscles in robotics.

In humans, muscles work through the coordinated activity of thousands of molecular motors called actomyosins, which help make them contract. Despite this complex biochemical process, they reliably display distinctive collective behaviors.

For example, under increasing load, human muscles can recruit more motors, a bit like bringing in more working parts into action when extra strength is needed.

Building a simplified muscle model

In this study, researchers reveal that networks of simple mechanical motors can replicate the key features of actomyosin, the molecular machinery underpinning muscle contraction.

Rather than modeling these intricate molecular interactions directly, the Bristol team created a simplified system in which motors interact only through brief mechanical contact within a carefully designed geometry.

To test this theory, the researchers built an experimental tabletop model using small electric motors arranged like real muscle proteins, in an actomyosin-like configuration.

The device "self-organized" into coordinated traveling waves of motion and automatically adapted as the mechanical load increased, just like human muscles.

The physical demonstration was built using small electric motors combined with custom 3D-printed plastic components and laser-cut acrylic.

Remarkably, this minimal system reproduced the similar collective behaviors observed in the mechanics behind real muscles.

"The motors aren't 'talking' to each other directly. Each one pushes on a shared backbone structure, which changes what the others feel. Over time, that feedback causes them to fall into coordinated patterns on their own—a bit like rowers synchronizing their strokes or the classic synchronization seen in pendulum clocks," explains the study's team leader, Dr. Hermes Bloomfield-Gadêlha, Senior Lecturer in Applied Mathematics and Data Modeling at the University of Bristol.

What the findings could unlock

The findings suggest that muscle-like coordination may arise not only from biochemical processes but also from the underlying physical architecture of the system.

This insight could influence future research in both biology and engineering. In soft robotics, the principles could help engineers design adaptive artificial muscles that organize themselves naturally rather than relying on complex control systems.

"On the engineering side, we're interested in whether these ideas could help design artificial muscles or soft robotic systems that adapt automatically," added Dr. Bloomfield-Gadêlha.

"While from a biological perspective, it also raises questions about how much of muscle behavior depends on motor chemistry and how much comes from the organization of the system. Understanding that balance could help us better understand muscle health, disease, aging and conditions such as muscular dystrophy."

The project was developed in the Polymaths Lab and Soft-Robotics at Bristol, with Dr. Benjamin Warmington carrying out the work as part of his doctoral research, combining mathematical modeling with the physical build, under the supervision of Professor Jonathan Rossiter and Dr. Hermes Bloomfield-Gadêlha.

Provided by University of Bristol