Magnetic Flux Sensor Based on Spiking Neurons with Josephson Junctions

Area of Science:

• Superconducting electronics
• Computational neuroscience
• Sensor technology

Background:

• Josephson junctions (JJs) are fundamental to superconducting quantum interference devices (SQUIDs), enabling sensitive magnetic flux detection.
• Existing SQUID designs include radio frequency (RF), direct current (DC), and hybrid (D-SQUID) types.
• Josephson junctions are increasingly explored for modeling biological neuron behavior.

Purpose of the Study:

• To propose and investigate a new sensory neuron circuit model.
• To utilize a direct current superconducting quantum interference device (DC SQUID) within the circuit.
• To demonstrate the model's magnetic flux sensitivity and neuronal dynamics.

Main Methods:

• Circuit design and derivation of differential equations governing system dynamics.
• Numerical simulations for experimental evaluation.
• Analysis of the relationship between external magnetic flux and neuronal dynamics.

Main Results:

• Confirmation of the magnetic-flux-sensitive neuron concept's applicability and performance.
• Demonstration of magnetic flux encoding into neuronal dynamics with a linear response section.
• Discovery of complex behaviors including intermittent chaotic spiking and plateau bursting.

Conclusions:

• The proposed DC SQUID-based neuron effectively encodes magnetic flux into dynamic neuronal activity.
• The model exhibits complex behaviors relevant to neural computation.
• This design offers a pathway for integrating superconducting circuits with spiking neural networks, despite the need for cryogenic systems.