In brief

The artificial neuron detects dopamine using an electrochemical sensor and releases it through hydrogel - a new technology successfully used to control a mouse leg and robotic hand.

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A deeper mind-machine connection

16 May 2023

A newly developed artificial neuron detects subtle chemical signals produced by brain cells to power advanced brain-machine interfaces.

Imagine logging into your computer, opening a web browser and surfing the internet using nothing but a thought. Brain-machine interfaces (BMIs) are signalling the dawn of a new era in human-machine collaboration where our gadgets understand and respond to biological cues.

Electrodes in BMIs pick up electrical impulses generated by brain cells which are then translated into digital commands via specialised algorithms. These commands are then registered and executed by the instrument—anything from a robotic arm to a computer game.

However, electrical impulses alone don’t capture the full breadth of communication within our brains. Neurons talk to each other using chemical transmitters, each one sending a unique message. These neurotransmitters are heavily involved in a variety of cognitive functions such as memory formation and mood regulation.

Xiaodong Chen, Scientific Director at the Institute of Materials Research & Engineering (IMRE), said that despite the necessity, classical BMIs are still unable to read biological cues provided by neurotransmitters. “There is a mismatch in communication between the nervous system and today’s BMIs which rely primarily on electrical signal inputs,” said Chen.

With this problem in mind, Chen and colleagues at Nanyang Technological University, Singapore collaborated with teams from Nanjing Medical University, Nanjing University of Posts and Telecommunications, and Fudan University in China to build a new-and-improved BMI with an ultrasensitive carbon-based electrochemical sensor capable of detecting dopamine with unprecedented accuracy: the first artificial neuron.

Housed on a chip the size of a fingernail, the artificial neuron was tested in two lab-based simulations. “We validated the chip’s adaptive interaction with live rat neurons and the sciatic nerve in a mouse leg,” explained Chen, adding that this new technology could facilitate chemical communication with living neurons to transmit signals and activate movement.

The artificial neuron also contains a memory resistor that can dynamically adjust the strength of the output current. This feature mimics synaptic plasticity—the ability of our neuronal connections to grow stronger or weaker over time and with training. To finally relay the signal and complete the chemical communication loop, a temperature-sensitive hydrogel releases dopamine from heat produced by the resistor.

For future studies, Chen’s team aims to advance the development of chemical BMIs and pave the way for creating neurotransmitter-based neuroprosthetics and neuromorphic systems. “The vision is that artificial neuron networks can work like biological systems for cyborg construction, consciousness control and neuromorphic computing,” concluded Chen.

The A*STAR-affiliated researchers contributing to this research are from the Institute of Materials Research & Engineering (IMRE).

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Wang, T., Wang, M., Wang, J., Yang, L., Ren, X., et al. A chemically mediated artificial neuron. Nature electronics 5, 586 - 595 (2022)| article

About the Researcher

Xiaodong Chen is the Scientific Director at the Institute of Materials Research and Engineering, A*STAR. He is also the President’s Chair Professor in Materials Science and Engineering, Professor of Chemistry and Medicine at Nanyang Technological University, Singapore (NTU). Chen also serves as the Director of the Innovative Centre for Flexible Devices (iFLEX) at NTU, the Director of Max Planck – NTU Joint Lab for Artificial Senses and the Deputy Director of the Singapore Hybrid-Integrated Next-Generation μ-Electronics (SHINE) Centre. His research interests include mechano-materials science, senses digitalisation, flexible electronics technology and cyber-human interfaces. Chen is the Editor-in-Chief of ACS Nano and an editorial advisory board member for more than 15 international journals. He has also received prestigious accolades for his exceptional scientific contributions, including the Singapore President’s Science Award and the Friedrich Wilhelm Bessel Research Award.

This article was made for A*STAR Research by Wildtype Media Group