Victor Erokhin

University of Parma | UNIPR · Department of Physics and Earth Sciences

The energy efficiency of Artificial Intelligence (AI) systems is a crucial and actual issue that may have an important impact on an ecological, economic and technological level. Spiking Neural Networks (SNNs) are strongly suggested as valid candidates able to overcome Artificial Neural Networks (ANNs) in this specific contest. In this study, the pr...

This paper provides a conceptual roadmap for the use of hormonal bioinspired models in a broad range of AI, neuroengineering, or computational systems. The functional signaling nature of hormones provides an example of a reliable multidimensional information management system that can solve parallel multitasks. Two existing examples of hormonal com...

Reservoir computing systems are promising for application in bio-inspired neuromorphic networks as they allow the considerable reduction of training energy and time costs as well as an overall system complexity. Conductive three-dimensional structures with the ability of reversible resistive switching are intensively developed to be applied in such...

Nowadays, neuromorphic systems based on memristors are considered promising approaches to the hardware realization of artificial intelligence systems with efficient information processing. However, a major bottleneck in the physical implementation of these systems is the strong dependence of their performance on the unavoidable variations (cycle‐to...

The great demand of multifunctional portable electronic products in daily life and the need of a large integration of memories with logic devices and sensors, have increased the interest in the identification of suitable materials for neuromorphic computing applications. Major innovations in this direction have been achieved by exploring materials...

This work is dedicated to the review and perspective of the new direction that we call "Neuropunk revolution" resembling the cultural phenomenon of cyberpunk. This new phenomenon has its foundations in advances in neuromorphic technologies including memristive and bio-plausible simulations, BCI, and neurointerfaces as well as unconventional approac...

This chapter presents data on the stochastic 3D neuromorphic systems, that can be realized only with organic materials. Essential elements of the system, namely, specially synthesized block-copolymers and functionalized gold nanoparticles, are considered. The method of the network fabrication is described. These systems have demonstrated the possib...

The chapter is dedicated to the conceptual description of memristive devices as key elements of neuromorphic systems. Starting from the definition of the memristor, proposed by L. Chua in 1971, a comparison of this device with other resistance switching elements (memistor and mnemotrix, in particular) is presented. A current state of the art in the...

This chapter is dedicated to neuromorphic applications of organic memristive devices. It describes adaptive systems capable to learning, based on single and multiple devices. As it is not possible to apply directly training algorithms, developed for the artificial neuron networks, to neuromorphic systems, specific approaches are discussed. Electron...

The chapter is dedicated to the description of three models, developed for the description of the memristive device functioning: phenomenological model, simplified model, and electrochemical model. Within the phenomenological model the active channel is divided into narrow stripes in the direction from source to drain and it is supposed that the re...

In this chapter logic elements with memory and artificial neuron networks, based on organic memristive devices, are discussed. It is considered practical realization and properties of AND, OR, and NOT elements with memory. In addition, it is presented practical realizations of single- and double-layer perceptrons, capable to make classification of...

This chapter is dedicated to the detailed technical description of polyaniline based organic memristive devices. Namely this memristive device is the key element of neuromorphic system which are the protagonist in this book. Main material of the device active channel is polyaniline (PANI), because it can vary its conductivity in a wide range accord...

Organic electronics has recently emerged as a promising candidate for the emulation of brain‐like functionalities, especially at the device level. Among the proposed technologies, memristive devices have gained an increasing attention due to their non‐volatile behavior which makes them suitable for the implementation of artificial neuronal networks...

In several biomedical applications, the detection of biomarkers demands high sensitivity, selectivity and easy-to-use devices. Organic electrochemical transistors (OECTs) represent a promising class of devices combining a minimal invasiveness and good signal transduction. However, OECTs lack of intrinsic selectivity that should be implemented by sp...

This paper is dedicated to the experimental study of learning properties of systems, based on polyaniline (PANI) memristive devices. Signals with different forms, amplitudes, frequencies have been used as external stimuli and it has been demonstrated their different influence over memristive device conductance. According to the obtained results, pu...

Neuromorphic systems must have at least five unavoidable features that are present in living beings. First, neuromorphic systems must perform memorizing and processing functions, using same elements. Second, it must allow data acquisition from sensors with preliminary processing and recording. Third, it must allow non-equilibrium processes, such as...

The effects of noise on any electronic system is a crucial aspect for the delineation of the proper functioning of circuits. Different and consolidated models have been proposed for classical electronic circuital elements but the effect of noise sourcing on memristive devices still lacks a wide and rich experimental description. Despite the larger...

Organic memristive devices are of great interest nowadays due to their low costs, flexibility, and prospects of use in artificial neuromorphic systems. Polyaniline (PANI) is a conductive and electrochemically active polymer and a promising material for redox‐gated memristive devices. In this work, the electrochromic properties of PANI are utilized...

Organic Memristive Devices Organic memristive devices are crucial elements for the mimicking important synapse properties, such as memory and learning. For their larger uses in neuromorphic computation, it is necessary to improve their rate of the resistance switching and their stability. In article number 1900985, Silvia Battistoni, Victor Erokhin...

Glass filters are functionalized by deposition of polyelectrolyte molecular layers. The procedure requires the growth of sacrificial nanoparticles within these filters in order to have the possibility of the formation of continuous layer-by-layer films. After the film formation these nanoparticles were dissolved. The resulted functionalized filters...

Spiking neuromorphic networks (SNNs) are bio-inspired artificial systems capable of unsupervised learning and promising candidates to mimic biological neural systems in efficient solution of cognitive tasks. Most SNNs are based on local learning rules, such as bio-like spike-time-dependent plasticity (STDP). In this paper, we report a significantly...

Here we provide a perspective concept of neurohybrid memristive chip based on the combination of living neural networks cultivated in microfluidic/microelectrode system, metal-oxide memristive devices or arrays integrated with mixed-signal CMOS layer to control the analog memristive circuits, process the decoded information, and arrange a feedback...

Being promising elements for neuromorphic computation, memristive devices have been often described as crucial elements for the mimicking important synapse properties, such as memory and learning. Among them, Organic memristive devices (OMDs) can claim low cost fabrication processes and the easy tunability of their electrical properties. Up to now,...

Supplementary material to Manuscript “Encapsulation of vitamin B12 into nanoengineered capsules and soft matter nanosystems for targeted delivery” (Larissa A. Maiorova, Svetlana I. Erokhina, Michela Pisani, Gianni Barucca, Massimo Marcaccio, Oscar I. Koifman, Denis S. Salnikov, Olga A. Gromova, Paola Astolfi, Valentina Ricci, Victor Erokhin)

In this paper, the resistive switching and neuromorphic behaviour of memristive devices based on parylene, a polymer both low-cost and safe for the human body, is comprehensively studied. The Metal/Parylene/ITO sandwich structures were prepared by means of the standard gas phase surface polymerization method with different top active metal electrod...

Parylene is a widely used polymer possessing such advantages as low cost and safety for the human body. Recently, several studies have been conducted showing that parylene can be used as a dielectric layer of memristors — new circuit design elements that are promising for the implementation of hardware neural networks. However, the mechanism of res...

Since CMOS technology approaches its physical limits, the spotlight of computing technologies and architectures shifts to unconventional computing approaches. In this area, novel computing systems, inspired by natural and mostly nonelectronic approaches, provide also new ways of performing a wide range of computations, from simple logic gates to so...

Actin and tubulin are key structural elements of Eukaryotes’ cytoskeleton. The networks of actin filaments and tubulin microtubules are substrates for cells’ motility and mechanics, intra-cellular transport and cell-level learning. Ideas of information processing taking place on a cytoskeleton network, especially in neurons, have been proposed by S...

Functional coupling live neurons through artificial synapses is the primary requirement for their implementation as prosthetic devices or in building hybrid networks. Here, the first evidence of unidirectional, activity dependent, coupling of two live neurons in brain slices via organic memristive devices (OMD) is demonstrated. ODM is a polymeric e...

We propose a road-map to experimental implementation of cytoskeleton-based computing devices. An overall concept is described in the following. Collision-based cytoskeleton computers implement logical gates via interactions between travelling localisation (voltage solitons on AF/MT chains and AF/MT polymerisation wave fronts). Cytoskeleton networks...

Slime mould Physarum polycephalum is a large single cell capable of distributed sensing, concurrent information processing, parallel computation, and decentralised actuation. The ease of culturing and experimenting with Physarum makes this slime mould an ideal substrate for real-world implementations of unconventional sensing and computing devices....

The samples were analysed without any specific preparation, just pasting them onto the double-side conductive tape. SEM images were acquired with Zeiss Supra 40-high resolution Scanning Electron Microscope using low beam energies. Microanalysis was performed using an EDX Oxford Instrument.

One of the most challenging tasks in neuromorphic applications, in the field of artificial intelligence, is the hardware realization of artificial neural networks (ANNs) which are able to learn during information processing (pattern recognition and classification, approximation, prediction, etc). In this scenario, thanks to their ability to keep th...

In this technical report we present novel results of the dopamine bio-plausible neuromodulation excitatory (eSTDP) and inhibitory (iSTDP) learning. We present the principal schematic for the neuromodulation of D1 and D2 receptors of dopamine, wiring schematic for both cases as well as the simulatory experiments results done in LTSpice.

Polyaniline (PANI) based memristive devices have emerged as promising candidates for hardware implementation of artificial synapses (the key components of neuromorphic systems) due to their high flexibility, low cost, solution processability, three-dimensional stacking capability, and biocompatibility. Here, we report on a way of the significant im...

Plants are highly intelligent organisms. They continuously make distributed processing of sensory information, concurrent decision making and parallel actuation. The plants are efficient green computers per se. Outside in nature, the plants are programmed and hardwired to perform a narrow range of tasks aimed to maximize the plants’ ecological dist...

Slime mould Physarum polycephalum develops intricate patterns of protoplasmic networks when foraging on a non-nutrient substrates. The networks are optimised for spanning larger spaces with minimum body mass and for quick transfer of nutrients and metabolites inside the slime mould's body. We hybridise the slime mould's networks with conductive pol...

A phenomenological model of the polyaniline (PANI) based memristive element's conductivity evolution during the application of varying voltages is presented in this work. The model is based on the experimental data on the conductance versus time dependencies for a set of applied voltages. The model could be used for simulation of complex artificial...

The memristive elements constructed using polymers – polyaniline (PANI) and polyethyleneoxide (PEO) – could be assembled on planar thin films or on 3D fibrous materials. The planar conductive PANI-based materials were made by Langmuir-Schaeffer (LS) method, and the 3D materials – by electrospining method which is a scalable technique. We have analy...

In this technical report we present novel results of the dopamine neuro-modulation inspired modulation of a polyaniline (PANI) memristive device excitatory learning STDP. Results presented in this work are of two experiments setup computer simulation and physical prototype experiments. We present physical prototype of inhibitory learning or iSTDP a...

In this technical report we present novel results of the dopamine neuromodulation inspired modulation of a polyaniline (PANI) memristive device excitatory learning STDP. Results presented in this work are of two experiments setup computer simulation and physical prototype experiments. We present physical prototype of inhibitory learning or iSTDP as...

Clay nanotubes are kaolinite rolled-up sheets, discovered few years ago and, up to now, mainly exploited as carriers for drug delivery. Although available in tons, biocompatible and nontoxic, they remain sophisticated and novel natural nanomaterials. The possibility to mix them with polymers, both polar and not, opens many functional biocomposites...

We explore and demonstrate the extension of the synapse-mimicking properties of memristive devices to a dysfunctional synapse as it occurs in the Alzheimer’s disease (AD) pathology. The ability of memristive devices to reproduce synapse properties such as LTP, LTD, and STDP has been already widely demonstrated, and moreover, they were used for deve...

In this paper we propose a new hardware architecture for the implementation of an artificial neuron based on organic memristive elements and operational amplifiers. This architecture is proposed as a possible solution for the integration and deployment of the cluster based bio- realistic simulation of a mammalian brain into a robotic system. Origin...

We discuss possible designs and prototypes of computing systems that could be based on morphological development of roots, interaction of roots, and analog electrical computation with plants, and plant-derived electronic components. In morphological plant processors data are represented by initial configuration of roots and configurations of source...

Bio-based/bio-inspired systems are attracting the interest of many studies even if we are far from reproducing the simplest living cell property. The concept of memory is particularly well suited for mimicking learning behavior in biosystems and in information processing systems being capable of coupling inherently memory and logic capabilities. Bi...

In this paper we present the results of simulation of exitatory Hebbian and inhibitory “sombrero” learning of a hardware architecture based on organic memristive elements and operational amplifiers implementing an artificial neuron we recently proposed. This is a first step towards the deployment on robots of a bio-plausible simulation, currently d...

A new architecture of organic memristive device is proposed with a double-layered polyelectrolyte, one of which is a biological system that alone drives the memristive behavior. In the device the Physarum polycephalum was used as living organism, the polyaniline as conducting polymer for the source-drain channel. The key choice for the device funct...

Realizing element able to mimic some features of the human brain is a challenging perspective. The concept of organic devices, based on conductive polymers, is attracting significant interest being generally bio-compatible, able to work in liquid phase, with low bias voltage ranges. Organic memri-stive devices have demonstrated the capability of mi...

The instrumental realization of neuromorphic systems may form the basis of a radically new social and economic setup, redistributing roles between humans and complex technical aggregates. The basic elements of any neuromorphic system are neurons and synapses. New memristive elements based on both organic (polymer) and inorganic materials have been...

Memristors are widely considered as promising elements for the efficient implementation of synaptic weights in artificial neural networks (ANNs) since they are resistors that keep memory of their previous conductive state. Whereas demonstrations of simple neural networks (e.g., a single-layer perceptron) based on memristors already exist, the imple...

Nowadays, the assembling of metallophthalocyanines into well structured thin films via wet-processing techniques is a topic of active research. This process is addressed in the present study devoted to Langmuir–Schaeffer (LS) films of copper tetra-(tert-butyl)-phthalocyanine. The LS films were prepared by using o-xylene as a spreading solvent and,...

Between 2009 and 2011, during restorative works at the Church of Roccapelago (province of Modena, Italy) a remote mountain village, hundreds of bodies, some of them mummified because of natural processes, were discovered in a forgotten crypt in use from the mid-16th to the 18th centuries. Mummification processes occurred unevenly, with bodies parti...

Between 2009 and 2011, during restorative works at the Church of Roccapelago (province of Modena, Italy) a remote mountain village, hundreds of bodies, some of them mummified because of natural processes, were discovered in a forgotten crypt in use from the mid-16th to the 18th centuries. Mummification processes occurred unevenly, with bodies parti...

We discuss hybrid systems where the slime mould is interfaced with organic electronics devices. We demonstrate the realisation of slime mould Schottky diode and organic electrochemical transistor . A central part of the chapter is dedicated to the integration of the Physarum into organic memristive device , an electronic element with synapse-like p...

Perceptron is an artificial neural network that can solve simple tasks such as invariant pattern recognition, linear approximation, prediction and others. We report on the hardware realization of the perceptron with the use of polyaniline-based memristive devices as the analog link weights. An error correction algorithm was used to get the perceptr...

In this present work, initial results of the growing of neuronal like cells on the memristive substrate are going to be presented. SH-SY5Y line cells where chosen for this test, thanks to their features similar to neurons and they were grown on Polyaniline (PANI) multilayer. PANI is a well known conductive polymer and it's also the active layer of...

The paper is dedicated to the hardware realization neuromorphic networks mimicking some properties of the nervous system. In particular, we will consider memristive devices-based logic gates with memory, elementary perceptron, and deterministic and stochastic networks, where memristive devices are used as electronic analogs of biological synapses.

Memristors and memristive devices represent a splendid area of research due to the unique possibilities for the realization of new types of computer hardware elements and mimicking several essential properties of the nervous system of living beings. The organic memristive device was developed as an electronic single-device analogue of the synapse,...

Physarum polycephalum is considered to be promising for the realization of unconventional computational systems. In this work, we present results of three slime mould-based systems. We have demonstrated the possibility of transporting biocompatible microparticles using attractors, repellents and a DEFLECTOR. The latter is an external tool that enab...

Three applications of molymeris materials for the unconventional computing are considered, namely, organic memristive devices, nanoengineered polymeric capsules and hybrid systems polymer - slime mold.

Organic memristive device has three important properties allowing to consider it as a key element of neuromorphic systems. First, its electrical properties are somehow similar to those of synapses. Second, it can be easily transferred into an oscillator. Third, organic nature of the devices allow to assemble them into stochastic 3D networks capable...

The electrochemical organic memristor with polyaniline active layer is a stand-alone device designed and realized for reproduction of some synapse properties in the innovative electronic circuits, such as the new field-programmable gate arrays or the neuromorphic networks capable for learning. In this work a new theoretical model of the polyanilin...