Highly Bionic Neurotransmitter-Communicated Neurons Following Integrate-and-Fire Dynamics

Area of Science:

• Neuroscience
• Materials Science
• Chemical Engineering

Background:

• Biological neural networks utilize reversible integrate-and-fire (I&F) dynamics for efficient, anti-interference chemical signaling.
• Current artificial neurons lack I&F mimicry, leading to potential accumulation and dysfunction in neural systems.

Purpose of the Study:

• To develop an artificial neuron that replicates the reversible I&F dynamics of biological neurons for chemical communication.
• To enable efficient and compatible neural signaling for artificial intelligence and human-machine fusion.

Main Methods:

• A supercapacitively gated artificial neuron utilizing graphene nanowall (GNW) gate electrodes was engineered.
• Electrochemical reactions on GNWs were used to mimic membrane potential accumulation and recovery, following I&F dynamics.
• Artificial chemical synapses and axon-hillock circuits were integrated to generate neural spikes.

Main Results:

• The artificial neuron successfully mimicked reversible I&F dynamics for chemical communication.
• Highly efficient signaling was achieved with acetylcholine concentrations as low as 2 × 10-10 M.
• The artificial neuron demonstrated chemical communication with both other artificial neurons and living cells.

Conclusions:

• The developed artificial neuron effectively replicates biological I&F dynamics, overcoming limitations of existing artificial neurons.
• This technology facilitates the construction of artificial neural networks compatible with biological systems.
• It holds significant potential for advancing artificial intelligence and deep human-machine integration.