Alzheimer’s is a neurodegenerative disease that involves a progressive death of neurons with cognitive, behavioral, and motor consequences; it is a bit like taking away the soul of the person affected, devastating not only for patients but also their families. Alzheimer’s disease remains difficult to treat, but researchers are exploring new nanotechnology solutions that might help improve the quality of life of those afflicted.

An international research team led by scientists from the British University of Bath in the U.K. has created the first artificial neurons in the laboratory, miniature devices designed to repair nerve circuits and restore lost functions. Scientists plan to use such bionic chips to treat both heart-related and neurodegenerative diseases.

According to a 2016 study by Trust Source, someone develops Alzheimer’s disease every 66 seconds. In total, analysts note that about 5.4 million adults live with this condition. It is characterized by progressive memory loss and the degradation of other cognitive functions that impair the performance of daily activities. Currently there is no cure, though there are clinical treatments that can extend the amount of time individuals are able to carry out daily activities.

The electrical properties of biological cells have long been studied to understand intracellular dynamics. The difficulty of measuring microscopic parameters that control the dynamics of ionic currents and the non-linearity of ionic conductance has so far hindered efforts to construct quantitative computational models. That makes it difficult to create neuromorphic devices able to replicate the exact response of a biological neuron.

The growing attention to implantable bioelectronics for the treatment of chronic diseases is driving technology towards low-power solid-state analog devices that accurately mimic bio-circuits.

Analog asynchronous electronics is the most promising way to integrate raw nerve stimuli instantly, regardless of the size and complexity of the system. Moreover, recent efforts to construct quantitative neuronal computational models have focused on the generalization of the Hodgkin-Huxley (HH) model to multichannel models.

The team of scientists from the University of Bath collaborated closely with colleagues from the Swiss University of Zurich, the University of Auckland, New Zealand and some of Italian researchers. Together they designed the first artificial neurons, designed to restore functions compromised by various neurodegenerative diseases, such as Alzheimer’s and Parkinson’s. The study was published in the journal Nature Communications.

“Any area where you have some degenerative disease, such as Alzheimer’s, or where the neurons stop firing properly because of age, disease, or injury, then in theory you could replace the faulty bio-circuit with a synthetic circuit,” said Alain Nogaret, a physicist who led the project at the University of Bath.

The chips the team produced are miniature devices based on silicon, modeled on biological ion channels that mimic the “work” of real neurons. The goal is to have these chips repair the damage caused by degenerative diseases, restoring the main functions of the nervous circuits. In practice, they represent connecting bridges there where a neural canal is interrupted.

These chip implants consume only 140 nanowatts, roughly a billionth of the energy required by a microprocessor. Ultra-low energy consumption is important because it means the chip can operate battery-free, relying entirely on energy harvesting.

The next goal for scientists will be to examine the less invasive and non-surgical methods to apply deep brain stimulation to make it easier for people with Alzheimer’s disease to access this treatment, making it easy to support artificial intelligence implementation.

Solid-state neurons, or rather as a stream of electrons, respond almost identically to biological neurons under stimulation by a wide range of current algorithms that simulate the brain environment. The future challenges will concern certainly the efficiency of the response, and the improvement of the model through deep learning tools. The first silicon neurons are an example of the so-called bioelectronic medicine, which with artificial materials, mimics natural circuits, and processes. Figures 1 and 2 show the study of circuit analysis and the relevant simulations published in the scientific article.

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Figure 1: Biomimetic solid-state ion channel. a) The conductance of ion species α is modulated by an activation gate and an inactivation gate. The net ionic current, Iα, is the difference between the activation current (Im) and the inactivation current (Ih). The Heaviside function, θ(), specifies that the current mirror outputs a positive current Iα when Im>Ih and 0 otherwise. b) Electrical equivalent circuit of the neuron membrane. c–g) Block diagrams of sub-circuits for (c) the gate recovery time, (d) current mirror, e) current multiplication, (f) transconductance amplification, and (g) sigmoidal activation/inactivation. Nature Communications

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Figure 2: Twin experiment with a solid-state neuron. a) Membrane voltage of a sub-threshold neuron (black line) stimulated by a current protocol mixing hyperchaotic oscillations with current steps (blue line). b) Membrane voltage predicted by the model for a different current. c) Detail of membrane voltage oscillations. d) Predicted time dependence of several state variables. e) Phase portrait of action potentials over the assimilation window. Nature Communications

The chip in question is a technological leap for the implementation of nanoelectronics in medicine. Moreover, there is the possibility of installing GPS and other control solutions for several vital parameters. All this made possible by the advantages of microelectronics and ultra-low lower solutions. The chips can activate various signals at specific times, and measure heart rate, take blood pressure, blood glucose levels, and more. In conclusion, the road to a complete cure for the worst disease of all time is becoming increasingly effective. The progress of nanoelectronics is transforming us into digital human beings, increasingly “connected”.