An organic spiking artificial neuron with excitatory and inhibitory synapses: towards soft and flexible organic neuromorphic processing

Artificial neurons are key components of neuromorphic systems, which aim to emulate the structure and functions of biological neural networks for efficient, brain-like computation. However, most artificial neurons rely on rigid, silicon-based technologies that are poorly suited for integration with soft structures, such as soft robots or biological organisms. We report the first organic spiking neuron with excitatory and inhibitory synapses, constructed from complementary organic field-effect transistors and capacitors, integrated on the same flexible substrate. The circuit emulates key neural functions including signal integration, frequency modulation, coincidence detection, and tunable synaptic weights. The synapses demonstrate excitatory and inhibitory time constants of 60 and 280 ms, respectively. The neuron exhibits linear response properties, with output firing rates in the range 0–60 Hz. We showcase the neuron’s ability to interact with the environment, by embedding it in a light-control feedback loop that adjusts luminance based on ambient light intensity.

Authors

Institutions

Publication Details

Journal
npj Flexible Electronics
Published
2026-01-22
DOI
https://doi.org/10.1038/s41528-025-00512-6
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

An organic spiking artificial neuron with excitatory and inhibitory synapses: towards soft and flexible organic neuromorphic processing

G. Indiveri, Yi Yang, Chiara Bartolozzi, Robert A. Nawrocki et al.
npj Flexible Electronics
Advanced Memory and Neural Computing
article

An organic spiking artificial neuron with excitatory and inhibitory synapses: towards soft and flexible organic neuromorphic processing

G. Indiveri, Yi Yang, Chiara Bartolozzi, Robert A. Nawrocki, Simeon A. Bamford, Mohammad Javad Hosseini
article en

Abstract

Artificial neurons are key components of neuromorphic systems, which aim to emulate the structure and functions of biological neural networks for efficient, brain-like computation. However, most artificial neurons rely on rigid, silicon-based technologies that are poorly suited for integration with soft structures, such as soft robots or biological organisms. We report the first organic spiking neuron with excitatory and inhibitory synapses, constructed from complementary organic field-effect transistors and capacitors, integrated on the same flexible substrate. The circuit emulates key neural functions including signal integration, frequency modulation, coincidence detection, and tunable synaptic weights. The synapses demonstrate excitatory and inhibitory time constants of 60 and 280 ms, respectively. The neuron exhibits linear response properties, with output firing rates in the range 0–60 Hz. We showcase the neuron’s ability to interact with the environment, by embedding it in a light-control feedback loop that adjusts luminance based on ambient light intensity.

npj Flexible ElectronicsVol. 10(1)
SIB Swiss Institute of Bioinformatics (CH), Chinese University of Hong Kong (HK), University of Zurich (CH), Purdue University West Lafayette (US), Italian Institute of Technology (IT), ETH Zurich (CH), Stanford University (US)
Purdue University, European Commission, Office of Naval Research
Openalex Percentile: Top 81%
Advanced Memory and Neural Computing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.