Adaptive Biomimetic Neuronal Circuit System Based on Myelin Sheath Function

Xiaosong Li, Jingru Sun, Wenjing Ma, Yichuang Sun, Chunhua Wang, Jiliang Zhang

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Brain-inspired neuromorphic computing architectures
are receiving significant attention in the consumer electronics
field owing to their low power consumption, high computational
capacity, and strong adaptability, where highly biomimetic
circuit design is at the core of neuromorphic network research.
Myelin sheaths are crucial cellular components in building stable
circuits in biological neurons, capable of adaptively adjusting the
conduction speed of neural signals. However, current research on
neuronal circuits relies on simplified mathematical models and
overlooks the adaptive functionality of myelin sheaths. This paper
is based on the dynamic mechanism of myelination, utilizing
physical devices such as memristors and voltage-controlled variable
capacitors to simulate the physiological functions of myelin
sheaths, and other organelles. Furthermore, adaptive biomimetic
neuronal circuit system (ABNCS) is constructed by connecting
various devices according to the physiological structure of neurons.
PSpice simulations show that the ABNCS can adjust its
parameters autonomously as the number of action potentials
(APs) increase, which modifies the neuron’s activation criteria
and firing rate. Through circuit experiments, PSpice simulations
were further validated. Implementing myelin sheath functions in
the neuronal circuit improves adaptability and reduces power
consumption, and when combined with artificial synapses to
construct neural networks, can form more stable neural circuits.
Original languageEnglish
Number of pages1
JournalIEEE Transactions on Consumer Electronics
Early online date25 Jan 2024
Publication statusE-pub ahead of print - 25 Jan 2024


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