High-frequency, low-energy organic event-based sensors for closed-loop neurostimulation
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 epileptiform discharges is demonstrated. Integrated with microelectrodes, these OECN-based sensors enable closed-loop neuromodulation by delivering real-time stimulation to suppress pathological sleep spindle oscillations in vivo. Combining biorealistic operation with ultra-low energy use, OECN-based sensors are good candidates for the next generation of implantable bioelectronics in energy-constrained environments.
Authors
- Dion Khodagholy (ORCID: https://orcid.org/0000-0003-0805-4612)
- Jennifer N. Gelinas (ORCID: https://orcid.org/0000-0002-1164-638X)
- Adam Marks (ORCID: https://orcid.org/0000-0001-9819-4349)
- Junda Huang (ORCID: https://orcid.org/0000-0001-6192-4715)
- Junpeng Ji (ORCID: https://orcid.org/0000-0002-8060-7667)
- Padinhare Cholakkal Harikesh (ORCID: https://orcid.org/0000-0002-2488-1821)
- C.-L. Yang
- Shao Shan
- Deyu Tu
- Han-Yan Wu
- Simone Fabiano
- Zifang Zhao
- Xin-Yi Wang
- Matteo Massetti
- Magnus Berggren
- Dace Gao
- Miao Xiong
- Tiefeng Liu
- Iain McCulloch
- Jian Pei
Institutions
- Linköping University (SE)
- Princeton University (US)
- University of California, Irvine (US)
- Cornell University (US)
- University of Oxford (GB)
- Beijing National Laboratory for Molecular Sciences (CN)
- Wallenberg Wood Science Center (SE)
- Irvine University (US)
- Columbia University (US)
Publication Details
- Journal
- Nature Sensors
- Published
- 2026-01-15
- DOI
- https://doi.org/10.1038/s44460-025-00007-x
- Citations
- 2
- Primary Topic
- EEG and Brain-Computer Interfaces
- Type
- article
- Field-Weighted Citation Impact
- 59.42
Funders
- European Commission
- Stiftelsen för Strategisk Forskning
- National Natural Science Foundation of China
- VINNOVA
- Linköpings Universitet
- Knut och Alice Wallenbergs Stiftelse
- Vetenskapsrådet
- Wallenberg Wood Science Center