2025-09-18 リンショーピング大学
Researchers at LiU have developed an artificial neuron that can perform a type of information processing called anticoincidence detection.
<関連情報>
- https://liu.se/en/news-item/nervceller-av-plast-blir-mer-avancerade-och-enklare
- https://www.science.org/doi/10.1126/sciadv.adv3194
- https://www.nature.com/articles/s41467-025-59587-4
アンチコインシデンス検出可能な単一有機電気化学ニューロン Single organic electrochemical neuron capable of anticoincidence detection
Padinhare Cholakkal Harikesh, Dace Gao, Han-Yan Wu, Chi-Yuan Yang, […] , and Simone Fabianoe
Science Advances Published:20 Jun 2025
DOI:https://doi.org/10.1126/sciadv.adv3194
Abstract
Emulating complex neural computations like solving linearly inseparable tasks within single artificial neurons has remained an elusive goal in neuromorphic engineering. Here, we report a dendritic organic electrochemical neuron (d-OECN) capable of achieving anticoincidence detection by classifying the exclusive-OR (XOR) problem—a quintessential linearly inseparable task—within an individual neuron. Inspired by human cortical neurons that perform XOR through dendritic calcium spikes, the d-OECN leverages ion-tunable antiambipolarity in mixed ionic-electronic conducting polymers to mimic voltage-gated dendritic calcium dynamics. By integrating this dendritic component with a tunable spiking circuit representing the soma, the d-OECN achieves XOR classification through its inherent nonlinear activation profile, with decision boundaries that are both ionically and electrically tunable. Moreover, we demonstrate the d-OECN’s ability to perform edge detection using XOR in a tactile sensing system, showcasing its potential for event-based sensing and processing. The d-OECNs, replicating key aspects of biological intelligence, pave the way for next-generation bioelectronics and robotics requiring complex neural computation.
単一トランジスタ型有機電気化学ニューロン Single-transistor organic electrochemical neurons
Junpeng Ji,Dace Gao,Han-Yan Wu,Miao Xiong,Nevena Stajkovic,Claudia Latte Bovio,Chi-Yuan Yang,Francesca Santoro,Deyu Tu & Simone Fabiano
Nature Communications Published:09 May 2025
DOI:https://doi.org/10.1038/s41467-025-59587-4
Abstract
Neuromorphic devices that mimic the energy-efficient sensing and processing capabilities of biological neurons hold significant promise for developing bioelectronic systems capable of precise sensing and adaptive stimulus-response. However, current silicon-based technologies lack biocompatibility and rely on operational principles that differ from those of biological neurons. Organic electrochemical neurons (OECNs) address these shortcomings but typically require multiple components, limiting their integration density and scalability. Here, we report a single-transistor OECN (1T–OECN) that leverages the hysteretic switching of organic electrochemical memtransistors (OECmTs) based on poly(benzimidazobenzophenanthroline). By tuning the electrolyte and driving voltage, the OECmTs switch between high- and low-resistance states, enabling action potential generation, dynamic spiking, and logic operations within a single device with dimensions comparable to biological neurons. The compact 1T–OECN design (~180 µm2 footprint) supports high–density integration, achieving over 62,500 neurons/cm2 on flexible substrates. This advancement highlights the potential for scalable, bio-inspired neuromorphic computing and seamless integration with biological systems.
