AsianFin -- A team of researchers has unveiled a new type of biohybrid robot that can crawl at different speeds in response to light stimulation, shedding light on the intrinsic link between neural signals and muscle activation. The study, recently published in Science Robotics, suggests that neurons could serve as highly promising “biological controllers” for managing complex biohybrid systems.
The research, conducted by scientists from the University of Illinois at Urbana-Champaign, Northwestern University, and other institutions, involved constructing a system that integrates skeletal muscle with motor neurons. Both components were co-cultured on a hydrogel scaffold, enabling functional integration through neuromuscular connections. These connections can be precisely controlled via wireless optogenetics, allowing researchers to remotely activate or modulate the robot’s movements.
The robot’s design features one short leg and one long leg, relying on the cyclical contraction and relaxation of muscle for locomotion. When the muscles contract, the two legs draw closer together, and when they relax, the legs separate. The greater bending of the short leg during deformation produces an asymmetric motion pattern, propelling the robot toward the long-leg side. By incorporating single or dual clusters of neural tissue, the team created different types of crawling devices and combined experimental observations with simulations to systematically analyze their mechanical behavior.
The study revealed that these biohybrid crawlers exhibit spontaneous muscle twitches while also allowing precise control of movement through external light stimulation. Some robots began crawling under optogenetic activation and continued autonomous motion for a period even after the light was removed, demonstrating persistence and memory-like neural activity.
Interestingly, when the frequency of light stimulation increased, certain robots slowed down rather than sped up, indicating that neuronal responses are not purely linear but are regulated by complex network dynamics. This behavior may relate to changes in neuronal synchrony or adjustments in the balance between excitation and inhibition.
