An electrical device that can send and receive chemical signals from neurons could be used in brain-machine interfaces
Technology
8 August 2022
Most brain-machine interfaces measure simple electrical signals in neurons to glean information about brain function. But much of the information in neural networks, like the brain, is encoded in neurotransmitters such as dopamine, chemicals that neurons use to send messages to each another.
“The brain’s native language is chemical, but current brain-machine interfaces all use an electrical language,” says Benhui Hu at Nanjing Medical University in China. “So we devised an artificial neuron to duplicate the way a real neuron communicates.”
The neuron consists of a sensor made from a graphene and carbon nanotube electrode, which can detect when dopamine is released. If enough of it is detected by the sensor, a component called a memristor triggers the release of more dopamine at the other end through a heat-activated hydrogel.
Hu and his team demonstrated that the neuron is able to both send and receive dopamine in communication with rat brain cells in a dish. It could also activate a mouse muscle through the sciatic nerve and move a robotic hand.
The 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.
“This actually has quite a lot of potential for expanding into more sophisticated learning systems. You can do a lot of new cool things here,” says Yoeri van de Burgt at Eindhoven University of Technology in the Netherlands.
While the bulkiness of the device makes it unsuitable for any current brain-machine interface applications, the fact that it can communicate two ways chemically might make it suitable for many different interfaces with the body, such as in prosthetic devices, he says.
Journal reference: Nature Electronics, DOI: 10.1038/s41928-022-00803-0
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