Future machine-human interfaces could potentially be created using an artificial neuron that can both release and receive dopamine in connection with real rat cells.
Neurotransmitters like dopamine play an important role in brain function, but they are only one part of neural networks. Because of this, electrical signals are usually measured in neurons to access information. However, most of what we know about neural networks comes from studies of dopamine rather than the electrical signals themselves.
Nanjing Medical University neuroscientist Benhui Hu says that the brain’s native language is chemical, but all current brain-machine interfaces use electrical languages. Therefore, he developed an artificial neuron that resembles a real one in order to communicate with it using an electrical language.
A memristor is triggered by dopamine released at one end and detects enough of it at the other end to activate a heat-activated hydrogel that releases more dopamine. A graphene and carbon nanotube electrode is used as the sensor, which can detect dopamine released by neurons.
In vitro experiments showed that Hu and his team were able to demonstrate that neurons can both send and receive dopamine in communication with rat brain cells. Additionally, they were also able to activate a mouse muscle and move a robotic hand in a dish.
An artificial neuron’s memristor can change how much dopamine is required to trigger it to release the chemical. This is similar to how neurons in the brain change how much neurotransmitter is sent between connections in response to external stimuli, a trait called plasticity that is essential for learning.
“There are a lot of exciting things you can do here,” says Yoeri van de Burgt at Eindhoven University of Technology in the Netherlands.
The bulky nature of the device makes it unfavorable for present brain-machine interface applications, but the fact that it can communicate two ways chemically might make it suitable for many different interfaces with the body, such as prosthetic devices, he says.
Journal reference: Nature Electronics, DOI: 10.1038/s41928-022-00803-0