SnNb 2 O 6 -Based Capacitive Memristive Synapses with Intrinsic LIF Dynamics for Neuromorphic Epilepsy Detection

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Authors: Xiang Zhang, Lin Ge, Siyuan Li, Hao Sun, Fengxia Yang, Zhi Zhan, Xiaofei Dong, Jianbiao Chen, Xuqiang Zhang, Jiangtao Chen, Yun Zhao, Yan Li
Cited by: 4
References: 57

Abstract

-based capacitive memristor is presented, which emulates a biosynaptic neuron through an LIF-type excitatory postsynaptic current (EPSC) for epileptic seizure monitoring. The device functions with stable coupled bipolar switching and capacitive response under both DC and pulsed operation over 500 consecutive cycles; in particular, single-pulse stimulus triggers a highly reproducible LIF-type three-stage EPSC feature. Various stimulation protocols enable diverse synaptic behaviors, and the device response can transition from transient to persistent states by tuning readout-delay. Mechanistic analysis attributes the capacitive memristor behavior to the coupling effect between interfacial polarization/displacement current and dynamic Schottky barrier modulation. By employing measured LIF-type EPSC as convolution kernels for raw electroencephalogram (EEG) signals in a lightweight one-dimensional convolutional neural network (1D-CNN), a 95.8% classification accuracy for three epilepsy-related states is achieved on the Bonn dataset. The results highlight the potential of the capacitive memristor for on-chip epileptic seizure monitoring.

Fields of Study & Subjects

Advanced Memory and Neural Computing Ferroelectric and Negative Capacitance Devices Advanced Sensor and Energy Harvesting Materials

Publication details

Journal / source
Nano Letters
Publisher
American Chemical Society (ACS)
Volume
26
Issue
2
Pages
871–879
Publication date
8 January 2026
Language
EN