Breakthrough in Artificial Neurons

Connection Between Neurons and Health Conditions

Researchers have successfully created artificial neurons that exhibit responses nearly identical to biological neurons. Conditions such as Alzheimer’s, heart failure, and sleep apnea, while seemingly unrelated, share a commonality: they stem from issues with neurons. Damage to neurons and neural circuits poses serious health risks and is linked to numerous negative outcomes. Consequently, there has been a surge in research focused on strategies to repair or replace damaged neurons.

The Role of Bioelectronic Medicine

Bioelectronic medicine, a burgeoning field, focuses on the electronic control of physiological functions, particularly to address nervous system defects. Neurons, the primary components of the nervous system, transmit information through electrical signals. The process of transmitting information via nerve impulses involves the precise excitation and inhibition of ion channels along the neuron. Researchers in bioelectronic medicine are developing ‘neuromorphic microcircuits’ that can process nerve input and react similarly to biological neurons.

Challenges in Developing Artificial Neurons

Creating artificial neurons poses significant challenges, primarily due to the unpredictability of biological neuron responses to various stimuli. However, a recent study by researchers at the University of Bath marks a significant advancement in this field. Their findings, published in Nature Communications, detail the construction of a ‘solid-state neuron’ model capable of accurately mimicking biological neuron activity.

Methodology and Findings

The researchers estimated parameters for their model and formulated equations representing “intracellular currents and membrane voltages” for the analogue solid-state neuron. By leveraging previously documented electrophysiological recordings, they estimated parameters for individual ion channels, successfully transferring the dynamics of hippocampal and respiratory neurons to a silicon chip.

Key Features of the Research

The study’s success can be attributed to three main features of their approach:

1. **Data Assimilation Process**: The researchers utilized a data assimilation process to avoid subjective criteria in their model, allowing for automated parameter estimation.

2. **Physical Hardware Model**: They developed a physical model of the hardware for the solid-state neuron, demonstrating its ability to integrate information from biological neurons.

3. **Versatility of the Model**: The solid-state neuron model’s versatility enables it to adopt various neuronal properties, such as different ion channel types, allowing it to accurately describe complex mammalian neurons.

Energy Efficiency and Future Implications

The methodology developed allows for the transfer of neuronal information from biological neurons to the solid-state models and subsequently to silicon chips. Notably, the artificial neurons created require only “one billionth the power of a microprocessor.” The researchers emphasize that these findings are particularly relevant to bioelectronic medicine, where low-power bioimplants are essential for real-time physiological feedback and therapies targeting chronic diseases reliant on repairing diseased circuits within the central nervous system.

Conclusion

The advancements in artificial neuron technology offer promising prospects for addressing chronic health conditions linked to neuronal damage, paving the way for innovative treatments in bioelectronic medicine.

References

Abu-Hassan, K., Taylor, J., Morris, P., Donati, E., Bortolotto, Z., & Indiveri, G. et al. (2019). Optimal solid state neurons. Nature Communications, 10(1). doi: 10.1038/s41467-019-13177-3
How do neurons work?. (2019). Retrieved 8 December 2019, from https://qbi.uq.edu.au/brain-basics/brain/brain-physiology/how-do-neurons-work
Medical Definition of BIOELECTRONICS. (2019). Retrieved 8 December 2019, from https://www.merriam-webster.com/medical/bioelectronics
World first as artificial neurons developed to cure chronic diseases. (2019). Retrieved 8 December 2019, from https://www.eurekalert.org/pub_releases/2019-12/uob-wfa120219.php
Image by Colin Behrens from Pixabay