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.

Functionalizing the Electrical Properties of Kombucha Zoogleal Mats for Biosensing Applications.

Kombucha is a type of tea that is fermented using yeast and bacteria. During this process, a film made of cellulose is produced. This film has unique properties such as biodegradability, flexibility, shape conformability, and ability to self-grow as well as be produced across customized scales. In our previous studies, we demonstrated that Kombucha mats exhibit electrical activity represented by spikes of the electrical potential. We propose using microbial fermentation as a method for in situ functionalization to modulate the electroactive nature of Kombucha cellulose mats, where graphene and zeolite were used for the functionalization. We subjected the pure and functionalized Kombucha mats to mechanical stimulation by applying different weights and geometries. Our experiments demonstrated that Kombucha mats functionalized with graphene and zeolite exhibit memfractive properties and respond to load by producing distinctive spiking patterns. Our findings present incredible opportunities for the in situ development of functionalized hybrid materials with sensing, computing, and memory capabilities. These materials can self-assemble and self-grow after they fuse their living and synthetic components. This study contributes to an emergent area of research on bioelectronic sensing and hybrid living materials, opening up exciting opportunities for use in smart wearables, diagnostics, health monitoring, and energy harvesting applications.

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.

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.

Exploring discrete space-time models for information transfer: Analogies from mycelial networks to the cosmic web.

Fungal mycelium networks are large scale biological networks along which nutrients, metabolites flow. Recently, we discovered a rich spectrum of electrical activity in mycelium networks, including action-potential spikes and trains of spikes. Reasoning by analogy with animals and plants, where travelling patterns of electrical activity perform integrative and communicative mechanisms, we speculated that waves of electrical activity transfer information in mycelium networks. Using a new discrete space-time model with emergent radial spanning-tree topology, hypothetically comparable mycelial morphology and physically comparable information transfer, we provide physical arguments for the use of such a model, and by considering growing mycelium network by analogy with growing network of matter in the cosmic web, we develop mathematical models and theoretical concepts to characterise the parameters of the information transfer.

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.

Logical circuits in colloids.

Colloid-based computing devices offer remarkable fault tolerance and adaptability to varying environmental conditions due to their amorphous structure. An intriguing observation is that a colloidal suspension of ZnO nanoparticles in dimethylsulfoxide (DMSO) exhibits reconfiguration when exposed to electrical stimulation and produces spikes of electrical potential in response. This study presents a novel laboratory prototype of a ZnO colloidal computer, showcasing its capability to implement various Boolean functions featuring two, four and eight inputs. During our experiments, we input binary strings into the colloid mixture, where a logical 'True' state is represented by an impulse of an electrical potential. In contrast, the absence of the electrical impulse denotes a logical 'False' state. The electrical responses of the colloid mixture are recorded, allowing us to extract truth tables from the recordings. Through this methodological approach, we demonstrate the successful implementation of a wide range of logical functions using colloidal mixtures. We provide detailed distributions of the logical functions discovered and offer speculation on the potential impacts of our findings on future and emerging unconventional computing technologies. This research highlights the exciting possibilities of colloid-based computing and paves the way for further advancements.

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.

On Transducing Properties of Kombucha-Proteinoid Complexes.

We investigate the information processing capacities of kombucha-proteinoid proto-brains, focusing on the transducing properties through accommodation spiking, tonic bursting spiking, and optical and acoustic stimulation. We explore self-organization, adaptability, and emergent phenomena in this unconventional proto-architecture. By constructing kombucha-proteinoid networks exposed to diverse audio stimuli, we analyze nonlinear dynamics using time series analysis. Assessing information representation in the presence of extreme noise, we examine the system's resilience. Our results illustrate intricate pathways resulting from the interplay between the synthetic biological substrate and bio-inspired stimulation. The kombucha-proteinoid proto-brains consistently map complex stimuli to distinct activation levels, showcasing their adaptability and potential for information processing without the need for external shaping circuits.

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.

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.

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.

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.

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.

Proteinoid Microspheres as Protoneural Networks.

Proteinoids, also known as thermal proteins, possess a fascinating ability to generate microspheres that exhibit electrical spikes resembling the action potentials of neurons. These spiking microspheres, referred to as protoneurons, hold the potential to assemble into proto-nanobrains. In our study, we investigate the feasibility of utilizing a promising electrochemical technique called differential pulse voltammetry (DPV) to interface with proteinoid nanobrains. We evaluate DPV's suitability by examining critical parameters such as selectivity, sensitivity, and linearity of the electrochemical responses. The research systematically explores the influence of various operational factors, including pulse width, pulse amplitude, scan rate, and scan time. Encouragingly, our findings indicate that DPV exhibits significant potential as an efficient electrochemical interface for proteinoid nanobrains. This technology opens up new avenues for developing artificial neural networks with broad applications across diverse fields of research.

Learning in ensembles of proteinoid microspheres.

Proteinoids are thermal proteins which form microspheres in water in the presence of salt. Ensembles of proteinoid microspheres exhibit passive nonlinear electrical properties and active neuron-like spiking of electrical potential. We propose that various neuromorphic computing architectures can be prototyped from the proteinoid microspheres. A key feature of a neuromorphic system is a learning. Through the use of optical and resistance measurements, we study mechanisms of learning in ensembles of proteinoid microspheres. We analyse 16 types of proteinoids study and their intrinsic morphology and electrical properties. We demonstrate that proteinoids can learn, memorize and habituate, making them a promising candidate for novel computing.

Logical gates in ensembles of proteinoid microspheres.

Proteinoids are thermal proteins which swell into microspheres in aqueous solution. Ensembles of proteinoids produce electrical spiking activity similar to that of neurons. We introduce a novel method for implementing logical gates in the ensembles of proteinoid microspheres using chronoamperometry. Chronoamperometry is a technique that involves applying a voltage pulse to proteinoid microspheres and measuring their current response. We have observed that proteinoids exhibit distinct current patterns that align with various logical outputs. We identify four types of logical gates: AND, OR, XOR, and NAND. These gates are determined by the current response of proteinoid microspheres. Additionally, we demonstrate that proteinoid microspheres have the ability to modify their current response over time, which is influenced by their previous exposure to voltage. This indicates that they possess a capacity for learning and are capable of adapting to their environment. Our research showcases the ability of proteinoid microspheres to perform logical operations and computations through their inherent electrical properties.

Light induced spiking of proteinoids.

Proteinoids, or thermal proteins, are produced by heating amino acids to their melting point and initiating polymerisation to produce polymeric chains. In aqueous solutions proteinoids swell into hollow microspheres. These microspheres produce endogenous burst of electrical potential spikes and change patterns of their electrical activity in response to illumination. We report results on a detailed investigation on the effects of white cold light on the spiking of proteinoids. We study how different types and intensities of light determine proteinoids' spiking amplitude, period, and pattern. The results of this study will be utilised to evaluate proteinoids for their potential as optical sensors and their application in unconventional computing.

No ultrasounds detected from fungi when dehydrated.

Many organisms (including certain plant species) can be observed to emit sounds, potentially signifying threat alerts. Sensitivity to such sounds and vibrations may also play an important role in the lives of fungi. In this work, we explore the potential of ultrasound activity in dehydrating fungi, and discover that several species of fungi do not emit sounds (detectable with conventional instrumentation) in the frequency range of 10kHz to 210kHz upon dehydration. Over 5 terabytes of ultrasound recordings were collected and analysed. We conjecture that fungi interact via non-sound means, such as electrical or chemical.