In the last few decades, individuals with mobility issues have seen a flurry of advancements in neuroprosthetic devices, artificial systems that seek to replace a particular sensation or lost ability. Current neuroprosthetics use electrical stimulation to activate the muscles that lack natural electrical inputs from nerves, an approach called functional electrical stimulation (FES). Despite its success, the approach has limitations, including muscle fatigue.
Now, a team of neuroscientists reported a new technique that activating muscle engineered to respond to light, which allows for more precise muscle control. Their findings, published in Science Robotics, could potentially improve neuroprosthetics.1
Researchers and clinicians alike use FES devices to help individuals with limited mobility. However, FES works opposite to how muscles are naturally activated: it triggers the large fatigue-prone nerve fibers before it brings the smaller, fatigue-resistant units online. As a result, FES quickly tires out the muscles after only a few minutes of stimulation. “It’s hard to regulate the force and you lose precision,” said Andrew Schwartz, a neuroengineer at the University of Pittsburgh who was not involved with the study.
To improve on this approach, Hugh Herr, a neuroscientist at the Massachusetts Institute of Technology (MIT) and coauthor of the study, turned to optogenetics, a technique that allows scientists to control cell activity using light.
Specifically, Herr and his team engineered a functional optogenetic stimulation (FOS) approach that uses light to activate nerves and their connected muscles. Then, the researchers put FES and FOS in a head-to-head battle to see which one was better at stimulating muscles. Researchers delivered neural stimulation to the nerves of anesthetized mice and measured the resultant force in a specific muscle. As the researchers gradually increased light stimulation with FOS, the muscle force followed suite, exhibiting a steady increase. In contrast, FES caused the muscle to quickly reach nearly 80 percent of the total force before plateauing even with low levels of electrical stimulation.
When the team extended the experiment to an hour, they found that the muscle that received electrical stimulation fatigued after 15 minutes. In contrast, the muscle activated with light sustained its force the whole time. “It’s really remarkable that we can track for an entire hour without the muscle even resting,” Herr said.
With FOS, the muscle also more reliably mirrored the different stimulation patterns supplied to the nerves, a parameter called fidelity. “You get out what you expect to get out,” said Schwartz. With FES, the muscle activity looked distorted. Schwartz hypothesized that FOS is better at mimicking the sequence of events that naturally occur during muscle stimulation, leading to improved precision and fidelity.
Due to its gradual nature, FOS is a better alternative to FES and could allow for more fine-tuned modulation of muscles when using neuroprosthetics, according to Schwartz. “You could do more dexterous movements of the fingers,” said Schwartz. “With FES, most subjects would close the whole hand together but with FOS we might be able to precisely control the fingers and the amount of force that each finger exerts.”
Both Herr and Schwartz acknowledged that as FOS relies on the expression of light-sensitive proteins, which are delivered through viruses to the body, it still faces a mountain of challenges before the technology can reach patients. Yet, Herr remains hopeful that optogenetic stimulation could be the future of neuroprosthetics. In addition to safer and more effective delivery vehicles, the researchers need to achieve long-lasting expression of the light-sensitive proteins and overcome the challenges of delivering light to the peripheral nerves to activate the nerve fibers.
“Then optogenetics will not only be a powerful scientific tool, but also a remarkably effective clinical tool,” said Herr.
- Herrera-Arcos G, et al. Closed-loop optogenetic neuromodulation enables high-fidelity fatigue-resistant muscle control. Science Robotics. 2024;9(90).
