Rivalling Dynamic Adaptation of Intrinsic Neuronal Plasticity in Dual‐Mode Mott Memristor Electronic Neuron for Spiking Control

Abstract Despite the success of Mott memristors in emulating neuronal dynamics, their use in modeling intrinsic neuronal plasticity (INP) remains rare. Here, a dual‐mode Pt/V/TaO x /Pt Mott memristor is presented that achieves INP through resistance‐dependent threshold modulation, enabled by the coupling of conductive filament formation and Mott transition. Excitatory and inhibitory pulses independently modulate spiking frequency, time‐to‐first‐spike, and leaky integrate‐and‐fire behavior without altering synaptic input. Notably, the device exhibits adaptive INP responses under sustained modulation, dynamically stabilizing spiking behavior and preventing excessive excitation or inhibition. It is further demonstrated that INP can compensate for synaptic failure and help the neuron recover periodic spiking. These findings establish a compact, intrinsically plastic artificial neuron capable of self‐regulating excitability, offering a scalable solution for next‐generation neuromorphic hardware.

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Publication Details

Journal
Advanced Functional Materials
Published
2025-07-25
DOI
https://doi.org/10.1002/adfm.202508585
Citations
1
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.73
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article

Rivalling Dynamic Adaptation of Intrinsic Neuronal Plasticity in Dual‐Mode Mott Memristor Electronic Neuron for Spiking Control

Li‐Chung Shih, C. Chen, Jen‐Sue Chen, Kuan‐Ting Chen et al.
1 citations
Advanced Functional Materials
Advanced Memory and Neural Computing
0.73
article

Rivalling Dynamic Adaptation of Intrinsic Neuronal Plasticity in Dual‐Mode Mott Memristor Electronic Neuron for Spiking Control

Li‐Chung Shih, C. Chen, Jen‐Sue Chen, Kuan‐Ting Chen, Kuan‐Han Lin, S. C. Chen, Zih‐Siao Liao, Kai‐Shin Hsu
article en
1 citations

Abstract

Abstract Despite the success of Mott memristors in emulating neuronal dynamics, their use in modeling intrinsic neuronal plasticity (INP) remains rare. Here, a dual‐mode Pt/V/TaO x /Pt Mott memristor is presented that achieves INP through resistance‐dependent threshold modulation, enabled by the coupling of conductive filament formation and Mott transition. Excitatory and inhibitory pulses independently modulate spiking frequency, time‐to‐first‐spike, and leaky integrate‐and‐fire behavior without altering synaptic input. Notably, the device exhibits adaptive INP responses under sustained modulation, dynamically stabilizing spiking behavior and preventing excessive excitation or inhibition. It is further demonstrated that INP can compensate for synaptic failure and help the neuron recover periodic spiking. These findings establish a compact, intrinsically plastic artificial neuron capable of self‐regulating excitability, offering a scalable solution for next‐generation neuromorphic hardware.

Advanced Functional MaterialsVol. 35(51)
Taiwan Semiconductor Manufacturing Company (Taiwan) (TW), National Cheng Kung University (TW)
Openalex Percentile: Top 25%
Advanced Memory and Neural Computing
0.73
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Rivalling Dynamic Adaptation of Intrinsic Neuronal Plasticity in Dual‐Mode Mott Memristor Electronic Neuron for Spiking Control — Li‐Chung Shih, C. Chen, et al. · Advanced Functional Materials (2025) | TGRS Research Map | TGRS