Organic memristive devices
Organic memristive devices
Research foundation
Research foundation
NeuroCompute.cloud is grounded in long-term research on organic memristors, synapse-like devices, STDP learning, reservoir computing and neurorehabilitation-related neural modeling.
Research categories
Synaptic plasticity and STDP
Synaptic plasticity and STDP
Reservoir computing
Reservoir computing
Associative learning
Associative learning
Spinal cord / CPG modeling
Spinal cord / CPG modeling
Bio-signal and rehabilitation dynamics
Bio-signal and rehabilitation dynamics
Energy efficiency in neuromorphic systems
Energy efficiency in neuromorphic systems
Printed and flexible organic devices
Printed and flexible organic devices
Selected research articles
Printed and flexible organic devicesBiomimetics, 2026
Printed Organic Memristive Device on Rigid and Flexible Supports for Neuromorphic Applications
Victor Erokhin and co-authors
A recent article on printed organic memristive devices on rigid and flexible supports for neuromorphic applications.
Why this matters for NeuroCompute.cloud: It supports NeuroCompute.cloud’s direction toward remotely accessible organic memristive hardware, including flexible and wearable-relevant device platforms.
Read the articleEnergy efficiency in neuromorphic systemsIEEE Access, 2026
Critical Analysis of Energy Consumption in Neuro-Computational Systems
Ivan Kipelkin, Ilija Kamenko, Jovan Ivošević, Alina Fedorova, Grigory Zharkov, Jovana Maricic, Stojanka Bratic, Nebojša Pilipović, Natasa Samardzic, Staniša Dautović, Milovan Medojević, Branimir Bajac, Jordi Vallverdú, Dragiša Žunić, Francesco Restuccia, Vincenzo Alessio, Francesco Longo, Giovanni Merlino, Dario Bruneo, Salvatore Distefano, Alexander Toschev, Alexey Mikhaylov, Victor Erokhin, Max Talanov
A unified benchmark of energy consumption per synaptic event across GPUs, NPUs, FPGAs, digital spiking processors, memristive devices, and biological reference ranges.
Why this matters for NeuroCompute.cloud: It frames why specialized low-energy computing substrates matter for selected workloads rather than as universal GPU replacements.
Read the articleOrganic memristive devicesMaterials Today Chemistry, 2026
Printing Polyaniline Based Organic Memristive Devices for Neuromorphic Computing Applications
Silvia Battistoni, Anna N. Matsukatova, Rocco Carcione, Luciano Ferrucci, Matteo Parmeggiani, Matteo Cocuzza, Simone Luigi Marasso, Andrey V. Emelyanov, Vyacheslav A. Demin, Victor Erokhin
A study of printable polyaniline-based organic memristive devices and their potential as scalable, adaptable hardware elements for neuromorphic computing applications.
Why this matters for NeuroCompute.cloud: It supports the transition from device research to scalable experimental hardware modules.
Read the articleReservoir computingAdvanced Intelligent Systems, 2023
Combination of Organic-Based Reservoir Computing and Spiking Neuromorphic Systems for a Robust and Efficient Pattern Classification
Anna N. Matsukatova, Nikita V. Prudnikov, Vsevolod A. Kulagin, Silvia Battistoni, Anton A. Minnekhanov, Andrey D. Trofimov, Aleksandr A. Nesmelov, Sergey A. Zavyalov, Yulia N. Malakhova, Matteo Parmeggiani, Alberto Ballesio, Simone Luigi Marasso, Sergey N. Chvalun, Vyacheslav A. Demin, Andrey V. Emelyanov, Victor Erokhin
A fully organic system combining volatile polyaniline reservoir computing with a nonvolatile parylene-memristor spiking readout layer for robust spatiotemporal pattern classification.
Why this matters for NeuroCompute.cloud: It points toward cloud modules for temporal biosignals, sensor data and low-complexity classification.
Read the articleSpinal cord / CPG modelingFrontiers in Neuroscience, 2023
Memristive Circuit-Based Model of Central Pattern Generator to Reproduce Spinal Neuronal Activity in Walking Pattern
Dinar N. Masaev, Alina A. Suleimanova, Nikita V. Prudnikov, Mariia V. Serenko, Andrey V. Emelyanov, Vyacheslav A. Demin, Igor A. Lavrov, Max O. Talanov, Victor V. Erokhin
A self-learning memristive circuit model that uses biologically plausible spike-timing-dependent plasticity to reproduce spinal neuronal activity associated with walking patterns.
Why this matters for NeuroCompute.cloud: It is directly connected to the initial Spinal Cord Twin / CPG cloud module.
Read the articleOrganic memristive devicesBioNanoScience, 2020
Memristive Devices for Neuromorphic Applications: Comparative Analysis
Victor Erokhin
A comparative review of organic and inorganic memristive devices for neuromorphic applications, including memory-processing integration, sensors, oscillators, bio-mimicking circuits, and living-system coupling.
Why this matters for NeuroCompute.cloud: It explains the device-level foundation behind specialized memristive compute layers.
Read the articleAssociative learningJournal of Physics D: Applied Physics, 2020
Associative STDP-Like Learning of Neuromorphic Circuits Based on Polyaniline Memristive Microdevices
Nikita V. Prudnikov, Dmitry A. Lapkin, Andrey V. Emelyanov, Anton A. Minnekhanov, Yulia N. Malakhova, Sergey N. Chvalun, Vyacheslav A. Demin, Victor V. Erokhin
An experimental demonstration of improved STDP timescales and unsupervised associative learning in a simple spiking neural network built with polyaniline memristive microdevices.
Why this matters for NeuroCompute.cloud: It supports future associative learning and STDP demonstration modules.
Read the articleSynaptic plasticity and STDPBioNanoScience, 2011
Material Memristive Device Circuits with Synaptic Plasticity: Learning and Memory
Victor Erokhin, Tatiana Berzina, Paolo Camorani, Anteo Smerieri, Dimitris Vavoulis, Jianfeng Feng, Marco P. Fontana
An experimental demonstration of organic memristive device circuits showing adaptive behavior inspired by synaptic plasticity and learning in a biological neural reference system.
Why this matters for NeuroCompute.cloud: It is part of the scientific basis for hardware learning modules.
Read the articleReady to test memristive hardware without building a lab?
Join the waitlist for early access to Spinal Cord Twin / CPG and STDP Learning modules, or talk to us about a research pilot or vertical application.