arXiv subjects

Andrew Adamatzky

Publications and source records attributed to Andrew Adamatzky.

At least 55 records · Page 3Linked to original sources

arXiv2022

Reactive fungal insoles

Mycelium bound composites are promising materials for a diverse range of applications including wearables and building elements. Their functionality surpasses some of the capabilities of traditionally passive materials, such as synthetic fibres, reconstituted cellulose fibres and natural fibres. Thereby, creating novel propositions including augmented functionality (sensory) and aesthetic (personal fashion). Biomaterials can offer multiple modal sensing capability such as mechanical loading (compressive and tensile) and moisture content. To assess the sensing potential of fungal insoles we undertook laboratory experiments on electrical response of bespoke insoles made from capillary matting colonised with oyster fungi Pleurotus ostreatus to compressive stress which mimics human loading when standing and walking. We have shown changes in electrical activity with compressive loading. The results advance the development of intelligent sensing insoles which are a building block towards more generic reactive fungal wearables. Using FitzhHugh-Nagumo model we numerically illustrated how excitation wave-fronts behave in a mycelium network colonising an insole and shown that it may be possible to discern pressure points from the mycelium electrical activity.

cs.ET↗

arXiv2022

Neuropunk Revolution. Hacking Cognitive Systems towards Cyborgs 3.0

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 approaches to AI and computing in general. We present the review of the current state-of-the-art and our vision of near future development of scientific approaches and future technologies. We call the "Neuropunk revolution" the set of trends that in our view provide the necessary background for the new generation of approaches technologies to integrate the cybernetic objects with biological tissues in close loop system as well as robotic systems inspired by the biological processes again integrated with biological objects. We see bio-plausible simulations implemented by digital computers or spiking networks memristive hardware as promising bridge or middleware between digital and (neuro)biological domains.

cs.ET↗

arXiv2022

Computing with Modular Robots

Propagating patterns are used to transfer and process information in chemical and physical prototypes of unconventional computing devices. Logical values are represented by fronts of traveling diffusive, trigger or phase waves. We apply this concept of pattern based computation to develop experimental prototypes of computing circuits implemented in small modular robots. In the experimental prototypes the modular robots Cubelets are concatenated into channels and junction. The structures developed by Cubelets propagate signals in parallel and asynchronously. The approach is illustrated with a working circuit of a one-bit full adder. Complementarily a formalization of these constructions are developed across Sleptsov nets. Finally, a perspective to swarm dynamics is discussed.

cs.RO↗

arXiv2021

Language of fungi derived from electrical spiking activity

ungi exhibit oscillations of extracellular electrical potential recorded via differential electrodes inserted into a substrate colonised by mycelium or directly into sporocarps. We analysed electrical activity of ghost fungi (\emph{Omphalotus nidiformis}), Enoki fungi (\emph{Flammulina velutipes}), split gill fungi (\emph{Schizophyllum commune}) and caterpillar fungi (\emph{Cordyceps militari}). The spiking characteristics are species specific: a spike duration varies from one to 21 hours and an amplitude from 0.03~mV to 2.1mV. We found that spikes are often clustered into trains. Assuming that spikes of electrical activity are used by fungi to communicate and process information in mycelium networks, we group spikes into words and provide a linguistic and information complexity analysis of the fungal spiking activity. We demonstrate that distributions of fungal word lengths match that of human languages. We also construct algorithmic and Liz-Zempel complexity hierarchies of fungal sentences and show that species \emph{S. commune} generate most complex sentences.

cs.ET↗

arXiv2021

Logics in fungal mycelium networks

The living mycelium networks are capable of efficient sensorial fusion over very large areas and distributed decision making. The information processing in the mycelium networks is implemented via propagation of electrical and chemical signals en pair with morphological changes in the mycelium structure. These information processing mechanisms are manifested in experimental laboratory findings that show that the mycelium networks exhibit rich dynamics of neuron-like spiking behaviour and a wide range of non-linear electrical properties. On an example of a single real colony of \emph{Aspergillus niger}, we demonstrate that the non-linear transformation of electrical signals and trains of extracellular voltage spikes can be used to implement logical gates and circuits. The approaches adopted include numerical modelling of excitation propagation on the mycelium network, representation of the mycelium network as a resistive and capacitive (RC) network and an experimental laboratory study on mining logical circuits in mycelium bound composites.

cs.ET↗

arXiv2021

Fungal electronics

Fungal electronics is a family of living electronic devices made of mycelium bound composites or pure mycelium. Fungal electronic devices are capable of changing their impedance and generating spikes of electrical potential in response to external control parameters. Fungal electronics can be embedded into fungal materials and wearables or used as stand alone sensing and computing devices.

cs.ET↗

arXiv2021

On Wave-Based Majority Gates with Cellular Automata

We demonstrate a discrete implementation of a wave-based majority gate in a chaotic Life-like cellular automaton. The gate functions via controlling of patterns' propagation into stationary channels. The gate presented is realisable in many living and non-living substrates that show wave-like activity of its space-time dynamics or pattern propagation. In the gate a symmetric pattern represents a binary value 0 while a non-symmetric pattern represents a binary value 1. Origination of the patterns and their symmetry type are encoded by the particle reactions at the beginning of computation. The patterns propagate in channels of the gate and compete for the space at the intersection of the channels. We implement 3-inputs majority gates using a W topology showing additional implementations of 5-inputs majority gates and one tree (cascade) majority gate.

cs.ET↗

arXiv2021

Mining logical circuits in fungi

Living substrates are capable for nontrivial mappings of electrical signals due to the substrate nonlinear electrical characteristics. This property can be used to realise Boolean functions. Input logical values are represented by amplitude or frequency of electrical stimuli. Output logical values are decoded from electrical responses of living substrates. We demonstrate how logical circuits can be implemented in mycelium bound composites. The mycelium bound composites (fungal materials) are getting growing recognition as building, packaging, decoration and clothing materials. Presently the fungal materials are passive. To make the fungal materials adaptive, i.e. sensing and computing, we should embed logical circuits into them. We demonstrate experimental laboratory prototypes of many-input Boolean functions implemented in fungal materials from oyster fungi \emph{P. ostreatus}. We characterise complexity of the functions discovered via complexity of the space-time configurations of one-dimensional cellular automata governed by the functions. We show that the mycelium bound composites can implement representative functions from all classes of cellular automata complexity including the computationally universal. The results presented will make an impact in the field of unconventional computing, experimental demonstration of purposeful computing with fungi, and in the field of intelligent materials, as the prototypes of computing mycelium bound composites.

cs.ET↗

arXiv2021

Generating Boolean Functions on Totalistic Automata Networks

We consider the problem of studying the simulation capabilities of the dynamics of arbitrary networks of finite states machines. In these models, each node of the network takes two states 0 (passive) and 1 (active). The states of the nodes are updated in parallel following a local totalistic rule, i.e., depending only on the sum of active states. Four families of totalistic rules are considered: linear or matrix defined rules (a node takes state 1 if each of its neighbours is in state 1), threshold rules (a node takes state 1 if the sum of its neighbours exceed a threshold), isolated rules (a node takes state 1 if the sum of its neighbours equals to some single number) and interval rule (a node takes state 1 if the sum of its neighbours belong to some discrete interval). We focus in studying the simulation capabilities of the dynamics of each of the latter classes. In particular, we show that totalistic automata networks governed by matrix defined rules can only implement constant functions and other matrix defined functions. In addition, we show that t by threshold rules can generate any monotone Boolean functions. Finally, we show that networks driven by isolated and the interval rules exhibit a very rich spectrum of boolean functions as they can, in fact, implement any arbitrary Boolean functions. We complement this results by studying experimentally the set of different Boolean functions generated by totalistic rules on random graphs.

cs.CC↗

arXiv2021

On electrical gates on fungal colony

Mycelium networks are promising substrates for designing unconventional computing devices providing rich topologies and geometries where signals propagate and interact. Fulfilling our long-term objectives of prototyping electrical analog computers from living mycelium networks, including networks hybridised with nanoparticles, we explore the possibility of implementing Boolean logical gates based on electrical properties of fungal colonies. We converted a 3D image-data stack of \emph{Aspergillus niger} fungal colony to an Euclidean graph and modelled the colony as resistive and capacitive (RC) networks, where electrical parameters of edges were functions of the edges' lengths. We found that {\sc and}, {\sc or} and {\sc and-not} gates are implementable in RC networks derived from the geometrical structure of the real fungal colony.

cs.ET↗

arXiv2021

Fungi anaesthesia

Electrical activity of fungus \emph{Pleurotus ostreatus} is characterised by slow (hours) irregular waves of baseline potential drift and fast (minutes) action potential likes spikes of the electrical potential. An exposure of the mycelium colonised substrate to a chloroform vapour lead to several fold decrease of the baseline potential waves and increase of their duration. The chloroform vapour also causes either complete cessation of spiking activity or substantial reduction of the spiking frequency. Removal of the chloroform vapour from the growth containers leads to a gradual restoration of the mycelium electrical activity.

q-bio.NC↗

arXiv2021

Towards proteinoid computers

Proteinoids -- thermal proteins -- are produced by heating amino acids to their melting point and initiation of polymerisation to produce polymeric chains. Proteinoids swell in aqueous solution into hollow microspheres. The proteinoid microspheres produce endogenous burst of electrical potential spikes and change patterns of their electrical activity in response to illumination. The microspheres can interconnect by pores and tubes and form networks with a programmable growth. We speculate on how ensembles of the proteinoid microspheres can be developed into unconventional computing devices.

cs.ET↗

arXiv2021

On stimulating fungi $Pleurotus~ostreatus$ with Cortisol

Fungi cells are capable of sensing extracellular cues through reception, transduction and response systems which allow them to communicate with their host and adapt to their environment. They display effective regulatory protein expressions which enhance and regulate their response and adaptation to a variety of triggers such as stress, hormones, light, chemicals and host factors. In our recent studies, we have shown that $Pleurotus$ oyster fungi generate electrical potential impulses in the form of spike events as a result of their exposure to environmental, mechanical and chemical triggers, demonstrating that it is possible to discern the nature of stimuli from the fungi electrical responses. Harnessing the power of fungi sensing and intelligent capabilities, we explored the communication protocols of fungi as reporters of human chemical secretions such as hormones, addressing the question if fungi can sense human signals. We exposed $Pleurotus$ oyster fungi to cortisol, directly applied to a surface of a hemp shavings substrate colonised by fungi, and recorded the electrical activity of fungi. The response of fungi to cortisol was also supplementary studied through the application of X-ray to identify changes in the fungi tissue, where receiving cortisol by the substrate can inhibit the flow of calcium and, in turn, reduce its physiological changes. This study could pave the way for future research on adaptive fungal wearables capable for detecting physiological states of humans and biosensors made of living fungi.

cs.ET↗

arXiv2021

Living mycelium composites discern weights

Fungal construction materials -- substrates colonised by mycelium -- are getting increased recognition as viable ecologically friendly alternatives to conventional building materials. A functionality of the constructions made from fungal materials would be enriched if blocks with living mycelium, known for their ability to respond to chemical, optical and tactile stimuli, were inserted. We investigate how large blocks of substrates colonised with mycelium of \emph{Ganoderma resinaceum} respond to stimulation with heavy weights. We analyse details of the electrical responses to the stimulation with weights and show that ON and OFF stimuli can be discriminated by the living mycelium composites and that a habituation to the stimulation occurs.

cs.ET↗

arXiv2021

Protein Structured Reservoir computing for Spike-based Pattern Recognition

Nowadays we witness a miniaturisation trend in the semiconductor industry backed up by groundbreaking discoveries and designs in nanoscale characterisation and fabrication. To facilitate the trend and produce ever smaller, faster and cheaper computing devices, the size of nanoelectronic devices is now reaching the scale of atoms or molecules - a technical goal undoubtedly demanding for novel devices. Following the trend, we explore an unconventional route of implementing a reservoir computing on a single protein molecule and introduce neuromorphic connectivity with a small-world networking property. We have chosen Izhikevich spiking neurons as elementary processors, corresponding to the atoms of verotoxin protein, and its molecule as a 'hardware' architecture of the communication networks connecting the processors. We apply on a single readout layer various training methods in a supervised fashion to investigate whether the molecular structured Reservoir Computing (RC) system is capable to deal with machine learning benchmarks. We start with the Remote Supervised Method, based on Spike-Timing-Dependent-Plasticity, and carry on with linear regression and scaled conjugate gradient back-propagation training methods. The RC network is evaluated as a proof-of-concept on the handwritten digit images from the MNIST dataset and demonstrates acceptable classification accuracy in comparison with other similar approaches.

cs.NE↗

arXiv2021

Evolutionary computational platform for the automatic discovery of nanocarriers for cancer treatment

We present the EVONANO platform for the evolution of nanomedicines with application to anti-cancer treatments. EVONANO includes a simulator to grow tumours, extract representative scenarios, and then simulate nanoparticle transport through these scenarios to predict nanoparticle distribution. The nanoparticle designs are optimised using machine learning to efficiently find the most effective anti-cancer treatments. We demonstrate our platform with two examples optimising the properties of nanoparticles and treatment to selectively kill cancer cells over a range of tumour environments.

cs.NE↗

arXiv2020

Evolving Nano Particle Cancer Treatments with Multiple Particle Types

Evolutionary algorithms have long been used for optimization problems where the appropriate size of solutions is unclear a priori. The applicability of this methodology is here investigated on the problem of designing a nano-particle (NP) based drug delivery system targeting cancer tumours. Utilizing a treatment comprising of multiple types of NPs is expected to be more effective due to the higher complexity of the treatment. This paper begins by utilizing the well-known NK model to explore the effects of fitness landscape ruggedness upon the evolution of genome length and, hence, solution complexity. The size of a novel sequence and the absence or presence of sequence deletion are also considered. Results show that whilst landscape ruggedness can alter the dynamics of the process, it does not hinder the evolution of genome length. These findings are then explored within the aforementioned real-world problem. In the first known instance, treatments with multiple types of NPs are used simultaneously, via an agent-based open source physics-based cell simulator. The results suggest that utilizing multiple types of NPs is more efficient when the solution space is explored with the evolutionary techniques under a predefined computational budget.

cs.NE↗

arXiv2020

Reactive fungal wearable

Smart wearables sense and process information from the user's body and environment and report results of their analysis as electrical signals. Conventional electronic sensors and controllers are commonly, sometimes augmented by recent advances in soft electronics. Organic electronics and bioelectronics, especially with living substrates, offer a great opportunity to incorporate parallel sensing and information processing capabilities of natural systems into future and emerging wearables. Nowadays fungi are emerging as a promising candidate to produce sustainable textiles to be used as ecofriendly biowearables. To assess the sensing potential of fungal wearables we undertook laboratory experiments on electrical response of a hemp fabric colonised by oyster fungi~\emph{Pleurotus ostreatus} to mechanical stretching and stimulation with attractants and repellents. We have shown that it is possible to discern a nature of stimuli from the fungi electrical responses. The results paved a way towards future design of intelligent sensing patches to be used in reactive fungal wearables.

cs.ET↗