The nerve cells could potentially be implanted into patients to overcome paralysis, restore failing brain circuits, and even connect their minds to machines.
The "brain chips" tiny behave like the real thing and may one day be used to treat diseases such as Alzheimer's disease.
The first-of-its-kind achievement gives enormous scope for medical devices to alleviate medical conditions such a neuronal degeneration, spinal cord injury and paralysis, and heart failure.
Critically, the artificial neurons not only behave just like biological neurons but only need one billionth the power of a microprocessor, making them ideally suited for use in medical implants and other bio-electronic devices. "Our job is paradigm changing because it provides a robust method to reproduce the electrical properties of neurons in real detail".
The silicon chips require just 140 nanoWatts of power meaning they are well-suited for implants to treat the aforementioned diseases. That's a billionth of the power requirement of a microprocessor, which other attempts to make synthetic neurons have used.
Researchers have been trying to create artificial brain cells for decades, but have struggled.
The artificial neurons have been developed to mimic the neurons in our nervous system, crucially copying their electrical properties. Artificial neurons could fix diseased biocircuits by replicating their healthy function and responding adequately to biological feedback to restore body functions.
Heart failure can be caused by mangled neurons failing to respond to nervous system feedback and, thus, sending the wrong signals to the heart. These are the cells that receive information from the outside world (sensory neurons) and send that information around the rest of the body (association neurons), essentially telling the muscles and organs what to do (motor neurons).
The basis for the artificial versions was a set of equations that describe the way neurons talk to each other and respond to electrical stimuli. This is incredibly complicated as responses are "non-linear"- in other words, if a signal becomes twice as strong, it shouldn't necessarily elicit twice as big a reaction- it might be thrice bigger or something else. The response may be more, or less than double.
Then they designed silicon chips that accurately modeled biological ion channels, before proving that their silicon neurons precisely mimicked real, living neurons responding to a range of stimulations. These were artificially created, and shown to accurately replicate a complete range of activity compared to their biological counterparts.
"The potential is endless in terms of understanding how the brain works, because we now have the fundamental understanding and insight into the functional unit of the brain, and indeed applications, which might be to improve memory, to overcome paralysis and ameliorate disease", said Julian Paton, a co-author on the study who holds posts at the Universities of Bristol and Auckland.
Nogaret said they are now working on smart pacemakers that will use the artificial neurons to react in real-time to pressures put on the heart, in addition to stimulating the heart into action. They are also present around the heart. "For example, the respiratory neurons which we have modeled ... couple the respiratory and cardiac rhythms and are responsible for respiratory sinus arrhythmia", the authors commented. "Our accurate description of the neurobiology within a model derived from silicon physics answers this need".
"Our approach combines several breakthroughs", explains Alain Nogaret, a University of Bath researcher leading the project. "We can very accurately estimate the precise parameters that control any neurons behavior with high certainty", said Nogaret.