Experts believe that within a decade brain implants and sensors will be commonplace. Neurotechnology – the field that develops tools to interact directly with the nervous system – makes incredible promises and raises understandable concerns. Its progress is unstoppable and is fueled by billions of dollars from investors such as Tesla founder Elon Musk and Facebook. But neuroscience is so complex that it must move in small steps toward that future. Now there is a new focus that could prove enormously beneficial in this journey: an artificial simulation of a neuronal connection made of organic material, which will allow for a better connection with living cells.
This artificial organic neuron managed to take control of a carnivorous plant and, by sending the correct sequence of electrical impulses to its cells, make it shut down its insect-catching mechanism. Using this circuit, pulse spikes can be modulated, which represents a “significant achievement,” adding another option to the toolbox of devices capable of simulating neural functions, according to the researchers who developed it. “It will potentially allow us to build the basic components of our brain: neurons and synapses,” says Simone Fabiano, one of the authors of the article, published in Nature communications.
Carnivorous plants have been controlled in the past with electrical stimuli; the team used the process as a model because it was important to test whether artificial organic neurons were capable of biointegrating with living tissues. “Venus traps are easy to handle and were an easy choice for an initial demonstration. However, the possibility of modifying the electrophysiology of living systems via artificial neurons could be extended to other biological systems, and we are studying this with animal models,” says Fabiano, from Linköping University in Sweden.
After testing their device in this simple scenario, the researchers are now evaluating possible future uses such as brain implants and connecting humans to the Internet of Things. In the short term, it could be used “to detect, process and command a specific action,” such as moving the Venus flytrap. In the long term, there is talk of artificial neuronal connections to implement machine learning in computers. “In the future, they could connect directly with biological neural networks for brain-machine interfaces,” explains Fabiano. This is Silicon Valley’s new Holy Grail: connecting the human brain directly to computers and the Internet.
Javier DeFelipe, a neurologist at the Spanish National Research Council (CSIC), says that “they are trying to imitate what the circuits of the brain and nervous system do. But they have to do it step by step, because we don’t know exactly how they work. If you get something that can be reproduced, a small function like in this case, it is a significant progress: it is about achieving a biocompatibility closer to that of a biological cell.”
However, DeFelipe, who was not involved in the study, adds a note of caution: “Now they put an electrode in the brain and stimulate it with an electric current and you hear a voice or move a muscle, but that doesn’t imply that you understand that the entire circuit is capable of completely reconstructing it. It’s one thing to intervene in the function of this neuron in a more organic way and another to recreate all its complexity.”
The artificial neurons developed in Sweden are based on components that can transport ions and electrons, the elements that transmit the fundamental impulses of neuronal communication. They can be molded at room temperature onto plastic or paper and printed using inexpensive screen printing materials, the kind used for T-shirts. “This would be inconceivable with silicon-based electronics,” says Fabiano. These types of silicon circuits, like classic computer chips, are what researchers are trying to get around here, as they don’t integrate well with biological organisms.
“The basic components of our artificial neurons enable direct sensory fusion between neurons. This will allow us to develop systems capable of feeling, processing and acting, and as such introduce decision-making into devices. This could be used for health monitoring, in brain-machine interfaces and in robotics,” says Fabiano. The next step in the process, he explains, will be to make his devices reach the frequency and energy efficiency of real biological neurons.
According to DeFelipe, however, science is still far from the development of an artificial neuron: “We are still trying to understand how it works, this is another step in the development of these tools, which will be more suitable for the brain than those made of silicon, but one thing is the material with which the circuit is built, another thing is to make it behave like a real cell”, he says.
