Harikesh Padinhare Cholakkal, Gao Dace, Wu Han-Yan, Yang Chi-Yuan, Tu Deyu, Fabiano Simone
Laboratory of Organic Electronics, Department of Science and Technology, Linköping University, Norrköping, Sweden.
Sci Adv. 2025 Jun 20;11(25):eadv3194. doi: 10.1126/sciadv.adv3194.
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.
在单个人工神经元中模拟复杂的神经计算,如解决线性不可分任务,一直是神经形态工程中难以实现的目标。在此,我们报告了一种树突状有机电化学神经元(d-OECN),它能够通过在单个神经元内对异或(XOR)问题(一个典型的线性不可分任务)进行分类来实现反符合检测。受人类皮层神经元通过树突状钙峰执行异或操作的启发,d-OECN利用混合离子-电子导电聚合物中的离子可调反双极性来模拟电压门控树突状钙动力学。通过将这个树突状组件与代表胞体的可调尖峰电路集成,d-OECN通过其固有的非线性激活曲线实现异或分类,其决策边界在离子和电学上均可调。此外,我们展示了d-OECN在触觉传感系统中使用异或进行边缘检测的能力,展示了其在基于事件的传感和处理方面的潜力。d-OECN复制了生物智能的关键方面,为需要复杂神经计算的下一代生物电子学和机器人技术铺平了道路。