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Electronically Reconfigurable Memristive Neuron Capable of Operating in Both Excitation and Inhibition Modes.

Lingxiang Hu1, Zongxiao Li1, Jiale Shao1

  • 1Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, China.

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|August 14, 2024
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Researchers developed a novel bi-mode memristive neuron that mimics both excitatory and inhibitory functions, enhancing artificial neuron capabilities for advanced neuromorphic systems.

Keywords:
Artificial neuronFilamentary mechanismMemristorNeuromorphic computingThreshold switching

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Area of Science:

  • Materials Science
  • Neuroscience
  • Computer Engineering

Background:

  • Threshold switching (TS) memristors are key components for artificial neurons in neuromorphic computing.
  • Current memristive neurons primarily exhibit excitatory behavior, lacking biological plausibility due to the absence of an inhibitory mode.
  • This limitation hinders the synergistic processing of both excitatory and inhibitory signals essential for complex neural functions.

Purpose of the Study:

  • To propose and demonstrate a novel memristive neuron capable of operating in both excitation and inhibition modes.
  • To overcome the limitations of single-mode memristive neurons for more biologically plausible artificial neural networks.
  • To enable the development of advanced neuromorphic systems with enhanced processing capabilities.

Main Methods:

  • Utilized bipolar threshold switching (TS) behavior in memristors to achieve tunable threshold voltages via polarity-controlled voltages.
  • Engineered a memristive device capable of reversible threshold voltage tuning, enabling bi-mode neuronal operation.
  • Developed a self-adaptive neuromorphic vision sensor utilizing the proposed bi-mode neurons.

Main Results:

  • Demonstrated a novel memristive neuron functioning in both excitatory and inhibitory modes.
  • Successfully mimicked neuronal activities like all-or-nothing behavior and tunable firing probability under diverse stimuli.
  • The developed neuromorphic vision sensor showed effective object recognition across varied lighting conditions.

Conclusions:

  • The proposed bi-mode memristive neuron offers a versatile platform for creating neuromorphic systems with richer functionality.
  • This advancement addresses the need for biologically plausible artificial neurons capable of processing both excitatory and inhibitory signals.
  • The bi-mode neuron technology paves the way for more sophisticated and adaptive neuromorphic computing applications.