Single organic electrochemical neuron capable of anticoincidence detection.

Harikesh, Padinhare Cholakkal; Gao, Dace; Wu, Han-Yan; Yang, Chi-Yuan; Tu, Deyu; Fabiano, Simone · Sci Adv · 2025

basic_science · Level V

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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.

Medical subject headings