[Hardware Implementation of Numerical Simulation Function of Hodgkin-Huxley Model Neurons Action Potential Based on...

Area of Science:

• Computational neuroscience
• Biomedical engineering
• Artificial intelligence hardware

Background:

• Neurons are fundamental to biological neural systems.
• The Hodgkin-Huxley (HH) model provides a realistic electrophysiological description of neurons.
• Hardware implementation of neurons offers potential advancements in spinal cord injury treatment, bionics, and AI.

Purpose of the Study:

• To achieve a hardware implementation of a single neuron based on the HH model.
• To validate the accuracy of the hardware implementation against numerical simulations.

Main Methods:

• Utilized the DSP Builder technology for hardware implementation.
• Implemented a single HH model neuron on a Field Programmable Gate Array (FPGA).
• Stimulated the FPGA-based neuron with various currents and analyzed action potential responses.

Main Results:

• The hardware implementation demonstrated high consistency with numerical simulation results.
• Action potential response characteristics of the FPGA neuron closely matched simulated data.
• Calculated a high correlation coefficient between simulation and hardware results.

Conclusions:

• The FPGA-based HH model neuron accurately reproduces neuronal electrophysiological characteristics.
• This work establishes a foundation for the hardware implementation of more complex neural networks.
• The validated hardware neuron model has implications for AI and neuro-bionic research.