Proto-neural networks from thermal proteins.

Proteinoids are synthetic polymers that have structural similarities to natural proteins, and their formation is achieved through the application of heat to amino acid combinations in a dehydrated environment. The thermal proteins, initially synthesised by Sidney Fox during the 1960s, has the ability to undergo self-assembly, resulting in the formation of microspheres that resemble cells. These microspheres have fascinating biomimetic characteristics. In recent studies, substantial advancements have been made in elucidating the electrical signalling phenomena shown by proteinoids, hence showcasing their promising prospects in the field of neuro-inspired computing. This study demonstrates the advancement of experimental prototypes that employ proteinoids in the construction of fundamental neural network structures. The article provides an overview of significant achievements in proteinoid systems, such as the demonstration of electrical excitability, emulation of synaptic functions, capabilities in pattern recognition, and adaptability of network structures. This study examines the similarities and differences between proteinoid networks and spontaneous neural computation. We examine the persistent challenges associated with deciphering the underlying mechanisms of emergent proteinoid-based intelligence. Additionally, we explore the potential for developing bio-inspired computing systems using synthetic thermal proteins in forthcoming times. The results of this study offer a theoretical foundation for the advancement of adaptive, self-assembling electronic systems that operate using artificial bio-neural principles.

Electrical Signaling Beyond Neurons.

Neural action potentials (APs) are difficult to interpret as signal encoders and/or computational primitives. Their relationships with stimuli and behaviors are obscured by the staggering complexity of nervous systems themselves. We can reduce this complexity by observing that "simpler" neuron-less organisms also transduce stimuli into transient electrical pulses that affect their behaviors. Without a complicated nervous system, APs are often easier to understand as signal/response mechanisms. We review examples of nonneural stimulus transductions in domains of life largely neglected by theoretical neuroscience: bacteria, protozoans, plants, fungi, and neuron-less animals. We report properties of those electrical signals-for example, amplitudes, durations, ionic bases, refractory periods, and, particularly, their ecological purposes. We compare those properties with those of neurons to infer the tasks and selection pressures that neurons satisfy. Throughout the tree of life, nonneural stimulus transductions time behavioral responses to environmental changes. Nonneural organisms represent the presence or absence of a stimulus with the presence or absence of an electrical signal. Their transductions usually exhibit high sensitivity and specificity to a stimulus, but are often slow compared to neurons. Neurons appear to be sacrificing the specificity of their stimulus transductions for sensitivity and speed. We interpret cellular stimulus transductions as a cell's assertion that it detected something important at that moment in time. In particular, we consider neural APs as fast but noisy detection assertions. We infer that a principal goal of nervous systems is to detect extremely weak signals from noisy sensory spikes under enormous time pressure. We discuss neural computation proposals that address this goal by casting neurons as devices that implement online, analog, probabilistic computations with their membrane potentials. Those proposals imply a measurable relationship between afferent neural spiking statistics and efferent neural membrane electrophysiology.

Thermosensory Spiking Activity of Proteinoid Microspheres Cross-Linked by Actin Filaments.

Actin, found in all eukaryotic cells as globular (G) or filamentous (F) actin, undergoes polymerization, with G-actin units changing shape to become F-actin. Thermal proteins, or proteinoids, are created by heating amino acids (160-200 °C), forming polymeric chains. These proteinoids can swell in an aqueous solution at around 50 °C, producing hollow microspheres filled with a solution, exhibiting voltage spikes. Our research explores the signaling properties of proteinoids, actin filaments, and hybrid networks combining actin and proteinoids. Proteinoids replicate brain excitation dynamics despite lacking specific membranes or ion channels. We investigate enhancing conductivity and spiking by using pure actin, yielding improved coordination in networks compared with individual filaments or proteinoids. Temperature changes (20 short-peptide supramolecular C to 80 °C) regulate conduction states, demonstrating external control over emergent excitability in protobrain systems. Adding actin to proteinoids reduces spike timing variability, providing a more uniform feature distribution. These findings support theoretical models proposing cytoskeletal matrices for functional specification in synthetic protocell brains, promoting stable interaction complexity. The study concludes that life-like signal encoding can emerge spontaneously within biological polymer scaffolds, incorporating abiotic chemistry.

Neuromorphic Liquids, Colloids, and Gels: A Review.

Advances in flexible electronic devices and robotic software require that sensors and controllers be virtually devoid of traditional electronic components, be deformable and stretch-resistant. Liquid electronic devices that mimic biological synapses would make an ideal core component for flexible liquid circuits. This is due to their unbeatable features such as flexibility, reconfiguration, fault tolerance. To mimic synaptic functions in fluids we need to imitate dynamics and complexity similar to those that occurring in living systems. Mimicking ionic movements are considered as the simplest platform for implementation of neuromorphic in material computing systems. We overview a series of experimental laboratory prototypes where neuromorphic systems are implemented in liquids, colloids and gels.

Liquid Marble Photosensor.

A liquid marble is a liquid droplet coated by a hydrophobic powder. The liquid marble does not wet adjacent surfaces and therefore can be manipulated as a dry soft body. A Belousov-Zhabotinsky (BZ) reaction is an oscillatory chemical reaction exhibiting waves of oxidation. We demonstrate how to make a photo-sensor from BZ medium liquid marbles. We insert electrodes into a liquid marble, prepared from BZ solution and coated with polyethylene powder. The electrodes record a potential difference which oscillates due to oxidation wave-fronts crossing the electrodes. When the BZ marble is illuminated by a light source, the oxidation wave-fronts are hindered and, thus, the electrical potential recorded ceases to oscillate. We characterise several types of responses of BZ marble photosensors to various stimuli, and provide explanations of the recorded activity. BZ liquid marble photosensors may find applications in the fields of liquid electronics, soft robotics and unconventional computing.

Liquid metal droplet solves maze.

A room temperature liquid metal features a melting point around room temperature. We use liquid metal gallium due to its non-toxicity. A physical maze is a connected set of Euclidean domains separated by impassable walls. We demonstrate that a maze filled with sodium hydroxide solution is solved by a gallium droplet when direct current is applied between start and destination loci. During the maze solving the droplet stays compact due to its large surface tension, navigates along lines of the highest electrical current density due its high electrical conductivity, and goes around corners of the maze's corridors due to its high conformability. The droplet maze solver has a long life-time due to the negligible vapour tension of liquid gallium and its corrosion resistance and its operation enables computational schemes based on liquid state devices.

Neuromorphic Liquid Marbles with Aqueous Carbon Nanotube Cores.

Neuromorphic computing devices attempt to emulate features of biological nervous systems through mimicking the properties of synapses toward implementing the emergent properties of their counterparts, such as learning. Inspired by recent advances in the utilization of liquid marbles (LMs, microliter quantities of fluid coated in hydrophobic powder) for the creation of unconventional computing devices, we describe the development of LMs with neuromorphic properties through the use of copper coatings and 1.0 mg mL-1 carbon nanotube (CNT)-containing fluid cores. Experimentation was performed through sandwiching the LMs between two cup-style electrodes and stimulating them with repeated dc pulses at 3.0 V. Our results demonstrate that "entrainment" of CNT-filled copper LMs via periodic pulses can cause their electrical resistance to rapidly switch between high to low resistance profiles upon inverting the polarity of stimulation: the reduction in resistance between high and low profiles was approximately 88% after two rounds of entrainment. This effect was found to be reversible through reversion to the original stimulus polarity and was strengthened by repeated experimentation, as evidenced by a mean reduction in time to switching onset of 43%. These effects were not replicated in nanotube solutions not bound inside LMs. Our electrical characterization also reveals that nanotube-filled LMs exhibit pinched loop hysteresis IV profiles consistent with the description of memristors. We conclude by discussing the applications of this technology to the development of unconventional computing devices and the study of emergent characteristics in biological neural tissue.

Mapping outcomes of liquid marble collisions.

Liquid marbles (LMs) have many promising roles in the ongoing development of microfluidics, microreactors, bioreactors, and unconventional computing. In many of these applications, the coalescence of two LMs is either required or actively discouraged, therefore it is important to study liquid marble collisions and establish parameters which enable the desired collision outcome. Recent reports on LM coalescence have focused on either two mobile LMs colliding, or an accelerating LM hitting a sessile LM with a backstop. A further possible scenario is the impact of a mobile LM against a non-supported static LM. This paper investigates such a collision, using high-speed videography for single-frame analysis. Multiple collisions were undertaken whilst varying the modified Weber number (We*) and offset ratios (X*). Parameter ranges of 1.0 < We* < 1.4 and 0.0 < X* < 0.1, resulted in a coalescence rate of approximately 50%. Whereas, parameter ranges X* > 0.25, and We* < 0.95 or We* > 1.55 resulted in 100% non-coalescence. Additionally, observations of LMs moving above a threshold velocity of 0.6 m s-1 have revealed a new and unusual deformation. Comparisons of the outcome of collisions whilst varying both the LM volume and the powder grain size have also been made, revealing a strong link. The results of this work provide a deeper understanding of LM coalescence, allowing improved control when designing future collision experiments.

Evaporation, Lifetime, and Robustness Studies of Liquid Marbles for Collision-Based Computing.

Liquid marbles (LMs) have recently attracted interest for use as cargo carriers in digital microfluidics and have successfully been implemented as signal carriers in collision-based unconventional computing circuits. Both application domains require LMs to roll over substantial distances and to survive a certain number of collisions without degrading. To evaluate the lifetime of LMs being subjected to movement and impact stresses, we have selected four types of coating to investigate: polytetrafluoroethylene (PTFE), ultrahigh density polyethylene (PE), Ni, and a mixture of Ni with PE (Ni-PE). Hierarchies of robustness have been constructed which showed that pure PE LMs survived the longest when stationary and in motion. Pure PTFE LMs were shown to be the least resilient to multiple impacts. The PTFE coating provided minimal protection against evaporative losses for small LM volumes (2 and 5 µL) however, larger LMs (10 µL) were shown to have good evaporative stabilities when stationary. Conversely, PE LMs showed a remarkable ability to withstand multiple impacts and were also stable when considering just passive evaporation. Hybrid Ni-PE LMs exhibited more resilience to multiple impacts compared to Ni LMs. Thus, when designing LM devices, it is paramount to determine impact pathways and select appropriate coating materials.

Computing in Verotoxin.

We develop an excitable automata model of a protein verotoxin and demonstrate that logic gates and circuits are realised in the model via interacting patterns of excitation. By sampling potential input pairs of nodes, we calculate frequencies of logic gates which occurred in the verotoxin model for various parameters of node excitation rules. We show that overall the gates can be arranged in the following hierarchy of descending frequencies: AND>OR>AND-NOT>XOR. We demonstrate realisations of one-bit half-adder and controlled-not gates and estimate memory capacity of the verotoxin molecule.

An improved Physarum polycephalum algorithm for the shortest path problem.

Shortest path is among classical problems of computer science. The problems are solved by hundreds of algorithms, silicon computing architectures and novel substrate, unconventional, computing devices. Acellular slime mould P. polycephalum is originally famous as a computing biological substrate due to its alleged ability to approximate shortest path from its inoculation site to a source of nutrients. Several algorithms were designed based on properties of the slime mould. Many of the Physarum-inspired algorithms suffer from a low converge speed. To accelerate the search of a solution and reduce a number of iterations we combined an original model of Physarum-inspired path solver with a new a parameter, called energy. We undertook a series of computational experiments on approximating shortest paths in networks with different topologies, and number of nodes varying from 15 to 2000. We found that the improved Physarum algorithm matches well with existing Physarum-inspired approaches yet outperforms them in number of iterations executed and a total running time. We also compare our algorithm with other existing algorithms, including the ant colony optimization algorithm and Dijkstra algorithm.

Evolving spiking networks with variable resistive memories.

Neuromorphic computing is a brainlike information processing paradigm that requires adaptive learning mechanisms. A spiking neuro-evolutionary system is used for this purpose; plastic resistive memories are implemented as synapses in spiking neural networks. The evolutionary design process exploits parameter self-adaptation and allows the topology and synaptic weights to be evolved for each network in an autonomous manner. Variable resistive memories are the focus of this research; each synapse has its own conductance profile which modifies the plastic behaviour of the device and may be altered during evolution. These variable resistive networks are evaluated on a noisy robotic dynamic-reward scenario against two static resistive memories and a system containing standard connections only. The results indicate that the extra behavioural degrees of freedom available to the networks incorporating variable resistive memories enable them to outperform the comparative synapse types.

On Effect of Chloroform on Electrical Activity of Proteinoids.

Proteinoids, or thermal proteins, produce hollow microspheres in aqueous solutions. Ensembles of the microspheres produce endogenous spikes of electrical activity, similar to that of neurons. To make the first step toward the evaluation of the mechanisms of such electrical behaviour, we decided to expose proteinoids to chloroform. We found that while chloroform does not inhibit the electrical oscillations of proteinoids, it causes substantial changes in the patterns of electrical activity. Namely, incremental chloroform exposure strongly affects proteinoid microsphere electrical activity across multiple metrics. As chloroform levels rise, the spike potential drops from 0.9 mV under control conditions to 0.1 mV at 25 mg/mL. This progressive spike potential decrease suggests chloroform suppresses proteinoid electrical activity. The time between spikes, the interspike period, follows a similar pattern. Minimal chloroform exposure does not change the average interspike period, while higher exposures do. It drops from 23.2 min under control experiments to 3.8 min at 25 mg/mL chloroform, indicating increased frequency of the electrical activity. These findings might lead to a deeper understanding of the electrical activity of proteinoids and their potential application in the domain of bioelectronics.

Recognition of sounds by ensembles of proteinoids.

Proteinoids are artificial polymers that imitate certain characteristics of natural proteins, including self-organization, catalytic activity, and responsiveness to external stimuli. This paper examines the acoustic response properties of proteinoids microspheres when exposed to auditory stimuli. We convert sounds of English alphabet into waveforms of electrical potential, feed the waveforms into proteinoid solutions and record electrical responses of the proteinoids. We also undertake a detailed comparison of proteinoids' electrical responses (frequencies, periods, and amplitudes) with original input signals. We found that responses of proteinoids are less regular, lower dominant frequency, wider distribution of proteinoids and less skewed distribution of amplitudes compared with input signals. We found that resonant acoustic excitation of proteinoids generates unique electrical impulse patterns dependent on sound frequency and amplitude. The finding will be used in further designs of organic electronic devices, based on ensembles of proteinoids, for sound processing and speech recognition. Our findings provide the first quantitative investigation into the potential of thermal proteinoid microspheres for bio-inspired sound processing and recognition applications. Using controlled speaker excitation on proteinoid samples, we create reliable markers of productive acoustic response capacities, paving the way for future advancement.

Micro-electrode array recording of extracellular electrical potentials of liquid static surface fermented Hericium erinaceus.

Hericium erinaceus is a basidiomycetes fungus with previously uncharacterised extracellular electrophysiology. Here, we present results of recordings of the electrical potentials of fungal biofilms of this species using microelectrode arrays (MEAs). In particular, we focused on modelling the temporal and spatial progression of the low frequency (≤ 1 Hz) potentials. Culture media control studies showed that the electrical potential activity results from the growth and subsequent spiking behaviours of the mycelium extracellular matrices. An antifungal assay using nystatin suspension, 10,000 unit/mL in DPBS, provided evidence for the biological origin of electrical potentials due to targeting of the selective permeability of the cell membrane and subsequent cessation of electrical activity. Conversely, injection of L-glutamic acid increased the combined multi-channel mean firing rate from 0.04 Hz to 0.1 Hz. Analysis of bursting and spatial propagation of the extracellular signals are also presented.

Fungal skin for robots.

Advancements in mycelium technology, stemming from fungal electronics and the development of living mycelium composites and skins, have opened new avenues in the fusion of biological and artificial systems. This paper explores an experimental endeavour that successfully incorporates living, self-regenerating, and reactive Ganoderma sessile mycelium into a model cyborg figure, creating a bio-cybernetic entity. The mycelium, cultivated using established techniques, was homogeneously grown on the cyborg model's surface, demonstrating robust reactivity to various stimuli such as light exposure and touch. This innovative merger points towards the future of sustainable biomaterials and the potential integration of these materials into new and existing technologies.

On interaction of proteinoids with simulated neural networks.

Proteinoid-neuron networks combine biological neurons with spiking proteinoid microspheres, which are generated by thermal condensation of amino acids. Complex and dynamic spiking patterns in response to varied stimuli make these networks suitable for unconventional computing. This research examines the interaction of proteinoid-neuron networks with function-generator-artificial neural networks (ANN) that may create distinct electrical waveforms. Function-generator- artificial neural network (ANN) stimulates and modulates proteinoid-neuron network spiking activity and synchronisation to encode and decode information. We employ function-generator-ANN to study proteinoid-neuron network nonlinear dynamics and chaos and optimise their performance and energy efficiency. Function-generator-ANN improves proteinoid-neuron networks' computational capacities and robustness and creates unique hybrid systems with electrical devices. We address the benefits as well as the drawbacks of employing proteinoid-neuron networks for unconventional computing with function-generator-ANN.

Memfractance of Proteinoids.

Proteinoids, or thermal proteins, are amino acid polymers formed at high temperatures by nonbiological processes. The objective of this study is to examine the memfractance characteristics of proteinoids within a supersaturated hydroxyapatite solution. The ionic solution utilized for the current-voltage (I-V) measurements possessed an ionic strength of 0.15 mol/L, a temperature of 37 °C, and a pH value of 7.4. The I-V curves exhibited distinct spikes, which are hypothesized to arise from the capacitive charging and discharging of the proteinoid-hydroxyapatite media. The experimental results demonstrated a positive correlation between the concentration of proteinoids and the observed number of spikes in the I-V curves. This observation provides evidence in favor of the hypothesis that the spikes originate from the proteinoids' capacitive characteristics. The memfractance behavior exemplifies the capacity of proteinoids to retain electrical charge within the hydrated hydroxyapatite media. Additional investigation is required in order to comprehensively identify the memcapacitive phenomena and delve into their implications for models of protocellular membranes. In a nutshell, this study provides empirical support for the existence of capacitive membrane-memfractance mechanisms in ensembles of proteinoids.

Computation Implemented by the Interaction of Chemical Reaction, Clustering, and De-Clustering of Molecules.

A chemical reaction and its reaction environment are intrinsically linked, especially within the confines of narrow cellular spaces. Traditional models of chemical reactions often use differential equations with concentration as the primary variable, neglecting the density heterogeneity in the solution and the interaction between the reaction and its environment. We model the interaction between a chemical reaction and its environment within a geometrically confined space, such as inside a cell, by representing the environment through the size of molecular clusters. In the absence of fluctuations, the interplay between cluster size changes and the activation and inactivation of molecules induces oscillations. However, in unstable environments, the system reaches a fluctuating steady state. When an enzyme is introduced to this steady state, oscillations akin to action potential spike trains emerge. We examine the behavior of these spike trains and demonstrate that they can be used to implement logic gates. We discuss the oscillations and computations that arise from the interaction between a chemical reaction and its environment, exploring their potential for contributing to chemical intelligence.

Electroactive composite biofilms integrating Kombucha, Chlorella and synthetic proteinoid Proto-Brains.

In this study, we present electroactive biofilms made from a combination of Kombucha zoogleal mats and thermal proteinoids. These biofilms have potential applications in unconventional computing and robotic skin. Proteinoids are synthesized by thermally polymerizing amino acids, resulting in the formation of synthetic protocells that display electrical signalling similar to neurons. By incorporating proteinoids into Kombucha zoogleal cellulose mats, hydrogel biofilms can be created that have the ability to efficiently transfer charges, perform sensory transduction and undergo processing. We conducted a study on the memfractance and memristance behaviours of composite biofilms, showcasing their capacity to carry out unconventional computing operations. The porous nanostructure and electroactivity of the biofilm create a biocompatible interface that can be used to record and stimulate neuronal networks. In addition to in vitro neuronal interfaces, these soft electroactive biofilms show potential as components for bioinspired robotics, smart wearables, unconventional computing devices and adaptive biorobotic systems. Kombucha-proteinoids composite films are a highly customizable material that can be synthesized to suit specific needs. These films belong to a unique category of 'living' materials, as they have the ability to support cellular systems and improve bioelectronic functionality. This makes them an exciting prospect in various applications. Ongoing efforts are currently being directed towards enhancing the compositional tuning of conductivity, signal processing and integration within hybrid bioelectronic circuits.