High-frequency, low-energy organic event-based sensors for closed-loop neurostimulation

Yang, C.-L.; Zhao, Zifang; Wu, Han-Yan; Gao, Dace; Huang, Junda; Ji, Junpeng; Xiong, Miao; Liu, Tiefeng; Harikesh, Padinhare Cholakkal; Marks, Adam; Wang, Xin-Yi; Massetti, Matteo; Shan, Shao; Pei, Jian; McCulloch, Iain; Berggren, Magnus; Tu, Deyu; Gelinas, Jennifer N.; Khodagholy, Dion; Fabiano, Simone

doi:10.1038/s44460-025-00007-x

articleNature SensorsJan 15, 2026HYBRID OA

High-frequency, low-energy organic event-based sensors for closed-loop neurostimulation

CYC.-L. Yang ZZZifang Zhao HWHan-Yan Wu DGDace Gao JHJunda Huang

Linköping University · Cornell University · +7 more institutions

PubMed

Indexed incrossrefpubmed

Abstract

Event-based bioelectronic sensors enable real-time detection and modulation of neural activity. However, conventional silicon interfaces are rigid and energy intensive, whereas organic electrochemical neuron (OECN)-based sensors, though promising, have been limited by slow firing rates, high energy use and scalability challenges. Here we present an OECN-based sensor capable of rapid, energy-efficient neural signal detection for closed-loop neurostimulation. These event-driven sensors respond within ~1 ms and generate voltage pulses up to 1.1 kHz, covering the full bandwidth of mammalian neuronal activity (0.5-1,000 Hz) while consuming only ~40 pJ per spike. Accurate detection of hippocampal interictal…

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Topics & keywords

Topics

Keywords

Bioelectronics
Neuromodulation
Neurostimulation
Neural activity
SIGNAL (programming language)
Voltage
Energy (signal processing)
Hippocampal formation

UN Sustainable Development Goals

Affordable and clean energy

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