Brainless but Multi-Headed: Decision Making by the Acellular Slime Mould Physarum polycephalum

Advances in Slime Mould Algorithm: A Comprehensive Survey

The slime mould algorithm (SMA) is a new swarm intelligence algorithm inspired by the oscillatory behavior of slime moulds during foraging. Numerous researchers have widely applied the SMA and its variants in various domains in the field and proved its value by conducting various literatures. In this paper, a comprehensive review of the SMA is introduced, which is based on 130 articles obtained from Google Scholar between 2022 and 2023. In this study, firstly, the SMA theory is described. Secondly, the improved SMA variants are provided and categorized according to the approach used to apply them. Finally, we also discuss the main applications domains of the SMA, such as engineering optimization, energy optimization, machine learning, network, scheduling optimization, and image segmentation. This review presents some research suggestions for researchers interested in this algorithm, such as conducting additional research on multi-objective and discrete SMAs and extending this to neural networks and extreme learning machining.

Perspectives on Principles of Cellular Behavior from the Biophysics of Protists

Cells are the fundamental unit of biological organization. Although it may be easy to think of them as little more than the simple building blocks of complex organisms such as animals, single cells are capable of behaviors of remarkable apparent sophistication. This is abundantly clear when considering the diversity of form and function among the microbial eukaryotes, the protists. How might we navigate this diversity in the search for general principles of cellular behavior? Here, we review cases in which the intensive study of protists from the perspective of cellular biophysics has driven insight into broad biological questions of morphogenesis, navigation and motility, and decision making. We argue that applying such approaches to questions of evolutionary cell biology presents rich, emerging opportunities. Integrating and expanding biophysical studies across protist diversity, exploiting the unique characteristics of each organism, will enrich our understanding of general underlying principles.

Hydrophobic Barriers for Directing Physarum polycephalum Propulsion and Navigation

Physarum polycephalum (P. polycephalum) is a unicellular protist with unique properties, such as learning and remembering in its cultured environment without a brain or central nervous system. The organism has been extensively used in morphology, taxis, and positive feedback dynamics studies. However, the lack of standardization of materials and substrate designs used in P. polycephalum studies has significantly limited conducting such studies, increasing the cost and time. In this study, we introduce a method to control the direction and migration of P. polycephalum by drawing hydrophobic lines and patterns. Our study succeeded in controlling the movement of P. polycephalum by setting a variety of hydrophobic designs such as complete barrier, single-slit barrier, taper barrier, dumbbell barrier, and one-side-opened rectangular barrier, suggesting the effectiveness of the hydrophobic barrier in regulating the propulsion and navigation of the organisms. Moreover, we demonstrated that utilizing such geometric constraints can reduce the experimental time required for toxicity testing based on P. polycephalum by more than 300%. Our techniques open new possibilities for studying the biophysical properties and behaviors of P. polycephalum, while also facilitating toxicity testing.

Bioelectric networks: the cognitive glue enabling evolutionary scaling from physiology to mind

Each of us made the remarkable journey from mere matter to mind: starting life as a quiescent oocyte ("just chemistry and physics"), and slowly, gradually, becoming an adult human with complex metacognitive processes, hopes, and dreams. In addition, even though we feel ourselves to be a unified, single Self, distinct from the emergent dynamics of termite mounds and other swarms, the reality is that all intelligence is collective intelligence: each of us consists of a huge number of cells working together to generate a coherent cognitive being with goals, preferences, and memories that belong to the whole and not to its parts. Basal cognition is the quest to understand how Mind scales-how large numbers of competent subunits can work together to become intelligences that expand the scale of their possible goals. Crucially, the remarkable trick of turning homeostatic, cell-level physiological competencies into large-scale behavioral intelligences is not limited to the electrical dynamics of the brain. Evolution was using bioelectric signaling long before neurons and muscles appeared, to solve the problem of creating and repairing complex bodies. In this Perspective, I review the deep symmetry between the intelligence of developmental morphogenesis and that of classical behavior. I describe the highly conserved mechanisms that enable the collective intelligence of cells to implement regulative embryogenesis, regeneration, and cancer suppression. I sketch the story of an evolutionary pivot that repurposed the algorithms and cellular machinery that enable navigation of morphospace into the behavioral navigation of the 3D world which we so readily recognize as intelligence. Understanding the bioelectric dynamics that underlie construction of complex bodies and brains provides an essential path to understanding the natural evolution, and bioengineered design, of diverse intelligences within and beyond the phylogenetic history of Earth.

Wargaming cancer: a strategy for future precision oncology?

Development of drug resistance is a mounting problem in precision oncology, demanding a rethink of treatment strategy. Here, we apply concepts from military theory and espionage to the battle-like dynamics between cancer and its host, thereby identifying system vulnerabilities in cancer and ways of tricking cancer evolution into dead ends.

Diet and mitonuclear haplotype interactions affect growth rate in a slime mould

Trait expression in metazoans is strongly influenced by the balance of macronutrients (i.e. protein, carbohydrate and fat) in the diet. At the same time, an individual's genetic background seems to regulate the magnitude of phenotypic response to a particular diet. It needs to be better understood whether interactions between diet, genetic background and trait expression are found in unicellular eukaryotes. A protist-the slime mould, Physarum polycephalum can choose diets based on protein-to-carbohydrate (P:C) content to support optimal growth rate. Yet, the role of genetic background (variation in the mitochondrial and nuclear DNAs) in mediating growth rate response to dietary P:C ratios in the slime mould is unknown. Here, we studied the effects of interactions between mitochondrial and nuclear DNA haplotypes and diet (i.e. G × G × E interactions) on the growth rate of P. polycephalum. A genetic panel of six distinct strains of P. polycephalum that differ in their mitochondrial and nuclear DNA haplotypes was used to measure growth rate across five diets that varied in their P:C ratio and total calories. We first determined the strains' growth rate (total biomass and surface area) when grown on a set menu with access to a particular diet. We then assessed whether the growth rate of strains increased on a buffet menu with access to all diets. Our findings show that the growth rate of P. polycephalum is generally higher on diets containing more carbohydrates than protein and that total calories negatively affect the growth rate. Three-way interactions between mitochondrial, nuclear haplotypes and dietary P:C ratios affected the strains' surface area of growth but not biomass. Intriguingly, strains did not increase their surface area and biomass when they had access to all diets on the buffet menu. Our findings have broad implications for our understanding of the effect of mitonuclear interactions on trait expression across diverse eukaryotic lineages.

Decision Making in Plants: A Rooted Perspective

This article discusses the possibility of plant decision making. We contend that recent work on bacteria provides a pertinent perspective for thinking about whether plants make choices. Specifically, the analogy between certain patterns of plant behaviour and apparent decision making in bacteria provides principled grounds for attributing decision making to the former. Though decision making is our focus, the discussion has implications for the wider issue of whether and why plants (and non-neural organisms more generally) are appropriate targets for cognitive abilities. Moreover, decision making is especially relevant to the issue of plant intelligence as it is commonly taken to be characteristic of cognition.

Behavioural changes in slime moulds over time

Changes in behaviour over the lifetime of single-cell organisms have primarily been investigated in response to environmental stressors. However, growing evidence suggests that unicellular organisms undergo behavioural changes throughout their lifetime independently of the external environment. Here we studied how behavioural performances across different tasks vary with age in the acellular slime mould Physarum polycephalum. We tested slime moulds aged from 1 week to 100 weeks. First, we showed that migration speed decreases with age in favourable and adverse environments. Second, we showed that decision making and learning abilities do not deteriorate with age. Third, we revealed that old slime moulds can recover temporarily their behavioural performances if they go throughout a dormant stage or if they fuse with a young congener. Last, we observed the response of slime mould facing a choice between cues released by clone mates of different age. We found that both old and young slime moulds are attracted preferentially toward cues left by young slime moulds. Although many studies have studied behaviour in unicellular organisms, few have taken the step of looking for changes in behaviour over the lifetime of individuals. This study extends our knowledge of the behavioural plasticity of single-celled organisms and establishes slime moulds as a promising model to investigate the effect of ageing on behaviour at the cellular level. This article is part of a discussion meeting issue 'Collective behaviour through time'.

Fungal biotechnology: From yesterday to tomorrow

Fungi have been used to better the lives of everyday people and unravel the mysteries of higher eukaryotic organisms for decades. However, comparing progress and development stemming from fungal research to that of human, plant, and bacterial research, fungi remain largely understudied and underutilized. Recent commercial ventures have begun to gain popularity in society, providing a new surge of interest in fungi, mycelia, and potential new applications of these organisms to various aspects of research. Biotechnological advancements in fungal research cannot occur without intensive amounts of time, investments, and research tool development. In this review, we highlight past breakthroughs in fungal biotechnology, discuss requirements to advance fungal biotechnology even further, and touch on the horizon of new breakthroughs with the highest potential to positively impact both research and society.

Memory capacity of adaptive flow networks

Biological flow networks adapt their network morphology to optimize flow while being exposed to external stimuli from different spatial locations in their environment. These adaptive flow networks retain a memory of the stimulus location in the network morphology. Yet, what limits this memory and how many stimuli can be stored are unknown. Here, we study a numerical model of adaptive flow networks by applying multiple stimuli subsequently. We find strong memory signals for stimuli imprinted for a long time into young networks. Consequently, networks can store many stimuli for intermediate stimulus duration, which balance imprinting and aging.

A survey on physarum polycephalum intelligent foraging behaviour and bio-inspired applications

In recent years, research on Physarum polycephalum has become more popular after Nakagaki (AIR 407: 6803-470, 2000) performed their famous experiment showing that Physarum was able to find the shortest route through a maze. Subsequent researches have confirmed the ability of Physarum-inspired algorithms to solve a wide range of real-world applications. In contrast to previous reviews that either focus on biological aspects or bio-inspired applications, here we present a comprehensive review that highlights recent Physarum polycephalum biological aspects, mathematical models, and Physarum bio-inspired algorithms and their applications. The novelty of this review stems from our exploration of Physarum intelligent behaviour in competition settings. Further, we have presented our new model to simulate Physarum in competition, where multiple Physarum interact with each other and with their environments. The bio-inspired Physarum in competition algorithms proved to have great potentials for future research.

Hybridizing slime mould algorithm with simulated annealing algorithm: a hybridized statistical approach for numerical and engineering design problems

The existing slime mould algorithm clones the uniqueness of the phase of oscillation of slime mould conduct and exhibits slow convergence in local search space due to poor exploitation phase. This research work exhibits to discover the best solution for objective function by commingling slime mould algorithm and simulated annealing algorithm for better variation of parameters and named as hybridized slime mould algorithm-simulated annealing algorithm. The simulated annealing algorithm improves and accelerates the effectiveness of slime mould technique as well as assists to take off from the local optimum. To corroborate the worth and usefulness of the introduced strategy, nonconvex, nonlinear, and typical engineering design difficulties were analyzed for standard benchmarks and interdisciplinary engineering design concerns. The proposed technique version is used to evaluate six, five, five unimodal, multimodal and fixed-dimension benchmark functions, respectively, also including 11 kinds of interdisciplinary engineering design difficulties. The technique's outcomes were compared to the results of other on-hand optimization methods, and the experimental results show that the suggested approach outperforms the other optimization techniques.

Competency in Navigating Arbitrary Spaces as an Invariant for Analyzing Cognition in Diverse Embodiments

One of the most salient features of life is its capacity to handle novelty and namely to thrive and adapt to new circumstances and changes in both the environment and internal components. An understanding of this capacity is central to several fields: the evolution of form and function, the design of effective strategies for biomedicine, and the creation of novel life forms via chimeric and bioengineering technologies. Here, we review instructive examples of living organisms solving diverse problems and propose competent navigation in arbitrary spaces as an invariant for thinking about the scaling of cognition during evolution. We argue that our innate capacity to recognize agency and intelligence in unfamiliar guises lags far behind our ability to detect it in familiar behavioral contexts. The multi-scale competency of life is essential to adaptive function, potentiating evolution and providing strategies for top-down control (not micromanagement) to address complex disease and injury. We propose an observer-focused viewpoint that is agnostic about scale and implementation, illustrating how evolution pivoted similar strategies to explore and exploit metabolic, transcriptional, morphological, and finally 3D motion spaces. By generalizing the concept of behavior, we gain novel perspectives on evolution, strategies for system-level biomedical interventions, and the construction of bioengineered intelligences. This framework is a first step toward relating to intelligence in highly unfamiliar embodiments, which will be essential for progress in artificial intelligence and regenerative medicine and for thriving in a world increasingly populated by synthetic, bio-robotic, and hybrid beings.

Technological Approach to Mind Everywhere: An Experimentally-Grounded Framework for Understanding Diverse Bodies and Minds

Synthetic biology and bioengineering provide the opportunity to create novel embodied cognitive systems (otherwise known as minds) in a very wide variety of chimeric architectures combining evolved and designed material and software. These advances are disrupting familiar concepts in the philosophy of mind, and require new ways of thinking about and comparing truly diverse intelligences, whose composition and origin are not like any of the available natural model species. In this Perspective, I introduce TAME-Technological Approach to Mind Everywhere-a framework for understanding and manipulating cognition in unconventional substrates. TAME formalizes a non-binary (continuous), empirically-based approach to strongly embodied agency. TAME provides a natural way to think about animal sentience as an instance of collective intelligence of cell groups, arising from dynamics that manifest in similar ways in numerous other substrates. When applied to regenerating/developmental systems, TAME suggests a perspective on morphogenesis as an example of basal cognition. The deep symmetry between problem-solving in anatomical, physiological, transcriptional, and 3D (traditional behavioral) spaces drives specific hypotheses by which cognitive capacities can increase during evolution. An important medium exploited by evolution for joining active subunits into greater agents is developmental bioelectricity, implemented by pre-neural use of ion channels and gap junctions to scale up cell-level feedback loops into anatomical homeostasis. This architecture of multi-scale competency of biological systems has important implications for plasticity of bodies and minds, greatly potentiating evolvability. Considering classical and recent data from the perspectives of computational science, evolutionary biology, and basal cognition, reveals a rich research program with many implications for cognitive science, evolutionary biology, regenerative medicine, and artificial intelligence.

Intrinsically Disordered Proteins: Critical Components of the Wetware

Despite the wealth of knowledge gained about intrinsically disordered proteins (IDPs) since their discovery, there are several aspects that remain unexplored and, hence, poorly understood. A living cell is a complex adaptive system that can be described as a wetware─a metaphor used to describe the cell as a computer comprising both hardware and software and attuned to logic gates─capable of "making" decisions. In this focused Review, we discuss how IDPs, as critical components of the wetware, influence cell-fate decisions by wiring protein interaction networks to keep them minimally frustrated. Because IDPs lie between order and chaos, we explore the possibility that they can be modeled as attractors. Further, we discuss how the conformational dynamics of IDPs manifests itself as conformational noise, which can potentially amplify transcriptional noise to stochastically switch cellular phenotypes. Finally, we explore the potential role of IDPs in prebiotic evolution, in forming proteinaceous membrane-less organelles, in the origin of multicellularity, and in protein conformation-based transgenerational inheritance of acquired characteristics. Together, these ideas provide a new conceptual framework to discern how IDPs may perform critical biological functions despite their lack of structure.

Multi-scale Chimerism: An experimental window on the algorithms of anatomical control

Despite the immense progress in genetics and cell biology, major knowledge gaps remain with respect to prediction and control of the global morphologies that will result from the cooperation of cells with known genomes. The understanding of cooperativity, competition, and synergy across diverse biological scales has been obscured by a focus on standard model systems that exhibit invariant species-specific anatomies. Morphogenesis of chimeric biological material is an especially instructive window on the control of biological growth and form because it emphasizes the need for prediction without reliance on familiar, standard outcomes. Here, we review an important and fascinating body of data from experiments utilizing DNA transfer, cell transplantation, organ grafting, and parabiosis. We suggest that these are all instances (at different levels of organization) of one general phenomenon: chimerism. Multi-scale chimeras are a powerful conceptual and experimental tool with which to probe the mapping between properties of components and large-scale anatomy: the laws of morphogenesis. The existing data and future advances in this field will impact not only the understanding of cooperation and the evolution of body forms, but also the design of strategies for system-level outcomes in regenerative medicine and swarm robotics.

Behaviorist approaches to investigating memory and learning: A primer for synthetic biology and bioengineering

The fields of developmental biology, biomedicine, and artificial life are being revolutionized by advances in synthetic morphology. The next phase of synthetic biology and bioengineering is resulting in the construction of novel organisms (biobots), which exhibit not only morphogenesis and physiology but functional behavior. It is now essential to begin to characterize the behavioral capacity of novel living constructs in terms of their ability to make decisions, form memories, learn from experience, and anticipate future stimuli. These synthetic organisms are highly diverse, and often do not resemble familiar model systems used in behavioral science. Thus, they represent an important context in which to begin to unify and standardize vocabulary and techniques across developmental biology, behavioral ecology, and neuroscience. To facilitate the study of behavior in novel living systems, we present a primer on techniques from the behaviorist tradition that can be used to probe the functions of any organism – natural, chimeric, or synthetic – regardless of the details of their construction or origin. These techniques provide a rich toolkit for advancing the fields of synthetic bioengineering, evolutionary developmental biology, basal cognition, exobiology, and robotics.

Towards the Idea of Molecular Brains

How can single cells without nervous systems perform complex behaviours such as habituation, associative learning and decision making, which are considered the hallmark of animals with a brain? Are there molecular systems that underlie cognitive properties equivalent to those of the brain? This review follows the development of the idea of molecular brains from Darwin’s “root brain hypothesis”, through bacterial chemotaxis, to the recent discovery of neuron-like r-protein networks in the ribosome. By combining a structural biology view with a Bayesian brain approach, this review explores the evolutionary labyrinth of information processing systems across scales. Ribosomal protein networks open a window into what were probably the earliest signalling systems to emerge before the radiation of the three kingdoms. While ribosomal networks are characterised by long-lasting interactions between their protein nodes, cell signalling networks are essentially based on transient interactions. As a corollary, while signals propagated in persistent networks may be ephemeral, networks whose interactions are transient constrain signals diffusing into the cytoplasm to be durable in time, such as post-translational modifications of proteins or second messenger synthesis. The duration and nature of the signals, in turn, implies different mechanisms for the integration of multiple signals and decision making. Evolution then reinvented networks with persistent interactions with the development of nervous systems in metazoans. Ribosomal protein networks and simple nervous systems display architectural and functional analogies whose comparison could suggest scale invariance in information processing. At the molecular level, the significant complexification of eukaryotic ribosomal protein networks is associated with a burst in the acquisition of new conserved aromatic amino acids. Knowing that aromatic residues play a critical role in allosteric receptors and channels, this observation suggests a general role of π systems and their interactions with charged amino acids in multiple signal integration and information processing. We think that these findings may provide the molecular basis for designing future computers with organic processors.

Bioluminescence and Photoreception in Unicellular Organisms: Light-Signalling in a Bio-Communication Perspective

Bioluminescence, the emission of light catalysed by luciferases, has evolved in many taxa from bacteria to vertebrates and is predominant in the marine environment. It is now well established that in animals possessing a nervous system capable of integrating light stimuli, bioluminescence triggers various behavioural responses and plays a role in intra- or interspecific visual communication. The function of light emission in unicellular organisms is less clear and it is currently thought that it has evolved in an ecological framework, to be perceived by visual animals. For example, while it is thought that bioluminescence allows bacteria to be ingested by zooplankton or fish, providing them with favourable conditions for growth and dispersal, the luminous flashes emitted by dinoflagellates may have evolved as an anti-predation system against copepods. In this short review, we re-examine this paradigm in light of recent findings in microorganism photoreception, signal integration and complex behaviours. Numerous studies show that on the one hand, bacteria and protists, whether autotrophs or heterotrophs, possess a variety of photoreceptors capable of perceiving and integrating light stimuli of different wavelengths. Single-cell light-perception produces responses ranging from phototaxis to more complex behaviours. On the other hand, there is growing evidence that unicellular prokaryotes and eukaryotes can perform complex tasks ranging from habituation and decision-making to associative learning, despite lacking a nervous system. Here, we focus our analysis on two taxa, bacteria and dinoflagellates, whose bioluminescence is well studied. We propose the hypothesis that similar to visual animals, the interplay between light-emission and reception could play multiple roles in intra- and interspecific communication and participate in complex behaviour in the unicellular world.

Fungal behaviour: a new frontier in behavioural ecology

As human beings, behaviours make up our everyday lives. What we do from the moment we wake up to the moment we go back to sleep at night can all be classified and studied through the concepts of behavioural ecology. The same applies to all vertebrates and, to some extent, invertebrates. Fungi are, in most people's eyes perhaps, the eukaryotic multicellular organisms with which we humans share the least commonalities. However, they still express behaviours, and we argue that we could obtain a better understanding of their lives - although they are very different from ours - through the lens of behavioural ecology. Moreover, insights from fungal behaviour may drive a better understanding of behavioural ecology in general.

An effective solution to numerical and multi-disciplinary design optimization problems using chaotic slime mold algorithm

Slime mold algorithm (SMA) is a recently developed meta-heuristic algorithm that mimics the ability of a single-cell organism (slime mold) for finding the shortest paths between food centers to search or explore a better solution. It is noticed that entrapment in local minima is the most common problem of these meta-heuristic algorithms. Thus, to further enhance the exploitation phase of SMA, this paper introduces a novel chaotic algorithm in which sinusoidal chaotic function has been combined with the basic SMA. The resultant chaotic slime mold algorithm (CSMA) is applied to 23 extensively used standard test functions and 10 multidisciplinary design problems. To check the validity of the proposed algorithm, results of CSMA has been compared with other recently developed and well-known classical optimizers such as PSO, DE, SSA, MVO, GWO, DE, MFO, SCA, CS, TSA, PSO-DE, GA, HS, Ray and Sain, MBA, ACO, and MMA. Statistical results suggest that chaotic strategy facilitates SMA to provide better performance in terms of solution accuracy. The simulation result shows that the developed chaotic algorithm outperforms on almost all benchmark functions and multidisciplinary engineering design problems with superior convergence.

Life, death, and self: Fundamental questions of primitive cognition viewed through the lens of body plasticity and synthetic organisms

Central to the study of cognition is being able to specify the Subject that is making decisions and owning memories and preferences. However, all real cognitive agents are made of parts (such as brains made of cells). The integration of many active subunits into a coherent Self appearing at a larger scale of organization is one of the fundamental questions of evolutionary cognitive science. Typical biological model systems, whether basal or advanced, have a static anatomical structure which obscures important aspects of the mind-body relationship. Recent advances in bioengineering now make it possible to assemble, disassemble, and recombine biological structures at the cell, organ, and whole organism levels. Regenerative biology and controlled chimerism reveal that studies of cognition in intact, "standard", evolved animal bodies are just a narrow slice of a much bigger and as-yet largely unexplored reality: the incredible plasticity of dynamic morphogenesis of biological forms that house and support diverse types of cognition. The ability to produce living organisms in novel configurations makes clear that traditional concepts, such as body, organism, genetic lineage, death, and memory are not as well-defined as commonly thought, and need considerable revision to account for the possible spectrum of living entities. Here, I review fascinating examples of experimental biology illustrating that the boundaries demarcating somatic and cognitive Selves are fluid, providing an opportunity to sharpen inquiries about how evolution exploits physical forces for multi-scale cognition. Developmental (pre-neural) bioelectricity contributes a novel perspective on how the dynamic control of growth and form of the body evolved into sophisticated cognitive capabilities. Most importantly, the development of functional biobots - synthetic living machines with behavioral capacity - provides a roadmap for greatly expanding our understanding of the origin and capacities of cognition in all of its possible material implementations, especially those that emerge de novo, with no lengthy evolutionary history of matching behavioral programs to bodyplan. Viewing fundamental questions through the lens of new, constructed living forms will have diverse impacts, not only in basic evolutionary biology and cognitive science, but also in regenerative medicine of the brain and in artificial intelligence.

Are paradoxes of amoeboid cognition, memristors, and memory mandating a re-conceptualization of actions and behaviors?

Background From intelligent behaviors of individual molecules and primitive organisms to those with a nervous system and brain, nature displays a fascinating collective memory across time and space. Using certain electronic circuits called memristors, it has been possible to emulate several processes of memory and learning, including a predictive form of intelligence of simple amoebas. Purpose What is the core of such intelligent performances? Although memristors are able to effectively describe puzzling biologic behaviors, recent results challenge their very existence altogether. This paper asks what can be gleaned from the underlying controversy itself, which will be argued is analogous to the observer principle in quantum physics. It is hypothesized that the material phenomena of resonance and sync have a counterpart involving behavior and memory. This questions the prominent role of a causative agent, and which type of behavior or memory is being occasioned. Results Building on the theory of memristors, the challenge of their actualization, and puzzling behaviors of amoebas, this paper proposes that 'resonating actions' - that is, similar or interlinked behaviors beyond space and time - are enabled by an underlying field of potentiation or domain of influence, and not by a cause-effect relationship. Such linked behaviors resemble a form of 'action coherence.' Habituated actions, memory, and behavior may arise out of a similar field of consciousness (here, modeled as memristors). These principles may be at the core of many hitherto unexplained mysteries of collective learning and behavior beyond space and time. Although this study is based on amoebas, the key postulates are also of great relevance to human thinking, behavior, and performance (including the representation of illness), and have independently been confirmed in the fields of consciousness research and spirituality.

Stress signalling in acellular slime moulds and its detection by conspecifics

Unicellular organisms live in unpredictable environments. Therefore, they need to continuously assess environmental conditions and respond appropriately to survive and thrive. When subjected to rapid changes in their environment or to cellular damages, unicellular organisms such as bacteria exhibit strong physiological reactions called stress responses that can be sensed by conspecifics. The ability to detect and use stress-related cues released by conspecifics to acquire information about the environment constitutes an adaptive survival response by prompting the organism to avoid potential dangers. Here, we investigate stress signalling and its detection by conspecifics in a unicellular organism, Physarum polycephalum. Slime moulds were subjected to either biotic (i.e. nutritional) or abiotic (i.e. chemical and light) stressors or left undisturbed while they were exploring a homogeneous environment. Then, we observed the responses of slime moulds facing a choice between cues released by stressed clone mates and cues released by undisturbed ones. We found that slime moulds actively avoided environments previously explored by stressed clone mates. These results suggest that slime moulds, like bacteria or social amoeba, exhibit physiological responses to biotic and abiotic stresses that can be sensed by conspecifics. Our results establish slime moulds as a promising new model to investigate the use of social information in unicellular organisms. This article is part of the theme issue 'Signal detection theory in recognition systems: from evolving models to experimental tests'.

The brain: a concept in flux

One of the most important aspects of the scientific endeavour is the definition of specific concepts as precisely as possible. However, it is also important not to lose sight of two facts: (i) we divide the study of nature into manageable parts in order to better understand it owing to our limited cognitive capacities and (ii) definitions are inherently arbitrary and heavily influenced by cultural norms, language, the current political climate, and even personal preferences, among many other factors. As a consequence of these facts, clear-cut definitions, despite their evident importance, are oftentimes quite difficult to formulate. One of the most illustrative examples about the difficulty of articulating precise scientific definitions is trying to define the concept of a brain. Even though the current thinking about the brain is beginning to take into account a variety of organisms, a vertebrocentric bias still tends to dominate the scientific discourse about this concept. Here I will briefly explore the evolution of our 'thoughts about the brain', highlighting the difficulty of constructing a universally (or even a generally) accepted formal definition of it and using planarians as one of the earliest examples of organisms proposed to possess a 'traditional', vertebrate-style brain. I also suggest that the time is right to attempt to expand our view of what a brain is, going beyond exclusively structural and taxa-specific criteria. Thus, I propose a classification that could represent a starting point in an effort to expand our current definitions of the brain, hopefully to help initiate conversations leading to changes of perspective on how we think about this concept. This article is part of the theme issue 'Liquid brains, solid brains: How distributed cognitive architectures process information'.

The Computational Boundary of a "Self": Developmental Bioelectricity Drives Multicellularity and Scale-Free Cognition

All epistemic agents physically consist of parts that must somehow comprise an integrated cognitive self. Biological individuals consist of subunits (organs, cells, and molecular networks) that are themselves complex and competent in their own native contexts. How do coherent biological Individuals result from the activity of smaller sub-agents? To understand the evolution and function of metazoan creatures' bodies and minds, it is essential to conceptually explore the origin of multicellularity and the scaling of the basal cognition of individual cells into a coherent larger organism. In this article, I synthesize ideas in cognitive science, evolutionary biology, and developmental physiology toward a hypothesis about the origin of Individuality: "Scale-Free Cognition." I propose a fundamental definition of an Individual based on the ability to pursue goals at an appropriate level of scale and organization and suggest a formalism for defining and comparing the cognitive capacities of highly diverse types of agents. Any Self is demarcated by a computational surface - the spatio-temporal boundary of events that it can measure, model, and try to affect. This surface sets a functional boundary - a cognitive "light cone" which defines the scale and limits of its cognition. I hypothesize that higher level goal-directed activity and agency, resulting in larger cognitive boundaries, evolve from the primal homeostatic drive of living things to reduce stress - the difference between current conditions and life-optimal conditions. The mechanisms of developmental bioelectricity - the ability of all cells to form electrical networks that process information - suggest a plausible set of gradual evolutionary steps that naturally lead from physiological homeostasis in single cells to memory, prediction, and ultimately complex cognitive agents, via scale-up of the basic drive of infotaxis. Recent data on the molecular mechanisms of pre-neural bioelectricity suggest a model of how increasingly sophisticated cognitive functions emerge smoothly from cell-cell communication used to guide embryogenesis and regeneration. This set of hypotheses provides a novel perspective on numerous phenomena, such as cancer, and makes several unique, testable predictions for interdisciplinary research that have implications not only for evolutionary developmental biology but also for biomedicine and perhaps artificial intelligence and exobiology.

A Complex Hierarchy of Avoidance Behaviors in a Single-Cell Eukaryote

Complex behavior is associated with animals with nervous systems, but decision-making and learning also occur in non-neural organisms [1], including singly nucleated cells [2-5] and multi-nucleate synctia [6-8]. Ciliates are single-cell eukaryotes, widely dispersed in aquatic habitats [9], with an extensive behavioral repertoire [10-13]. In 1906, Herbert Spencer Jennings [14, 15] described in the sessile ciliate Stentor roeseli a hierarchy of responses to repeated stimulation, which are among the most complex behaviors reported for a singly nucleated cell [16, 17]. These results attracted widespread interest [18, 19] and exert continuing fascination [7, 20-22] but were discredited during the behaviorist orthodoxy by claims of non-reproducibility [23]. These claims were based on experiments with the motile ciliate Stentor coeruleus. We acquired and maintained the correct organism in laboratory culture and used micromanipulation and video microscopy to confirm Jennings' observations. Despite significant individual variation, not addressed by Jennings, S. roeseli exhibits avoidance behaviors in a characteristic hierarchy of bending, ciliary alteration, contractions, and detachment, which is distinct from habituation or conditioning. Remarkably, the choice of contraction versus detachment is consistent with a fair coin toss. Such behavioral complexity may have had an evolutionary advantage in protist ecosystems, and the ciliate cortex may have provided mechanisms for implementing such behavior prior to the emergence of multicellularity. Our work resurrects Jennings' pioneering insights and adds to the list of exceptional features, including regeneration [24], genome rearrangement [25], codon reassignment [26], and cortical inheritance [27], for which the ciliate clade is renowned.

Active poroelastic two-phase model for the motion of physarum microplasmodia

The onset of self-organized motion is studied in a poroelastic two-phase model with free boundaries for Physarum microplasmodia (MP). In the model, an active gel phase is assumed to be interpenetrated by a passive fluid phase on small length scales. A feedback loop between calcium kinetics, mechanical deformations, and induced fluid flow gives rise to pattern formation and the establishment of an axis of polarity. Altogether, we find that the calcium kinetics that breaks the conservation of the total calcium concentration in the model and a nonlinear friction between MP and substrate are both necessary ingredients to obtain an oscillatory movement with net motion of the MP. By numerical simulations in one spatial dimension, we find two different types of oscillations with net motion as well as modes with time-periodic or irregular switching of the axis of polarity. The more frequent type of net motion is characterized by mechano-chemical waves traveling from the front towards the rear. The second type is characterized by mechano-chemical waves that appear alternating from the front and the back. While both types exhibit oscillatory forward and backward movement with net motion in each cycle, the trajectory and gel flow pattern of the second type are also similar to recent experimental measurements of peristaltic MP motion. We found moving MPs in extended regions of experimentally accessible parameters, such as length, period and substrate friction strength. Simulations of the model show that the net speed increases with the length, provided that MPs are longer than a critical length of ≈ 120 μm. Both predictions are in line with recent experimental observations.

Unpredictable homeodynamic and ambient constraints on irrational decision making of aneural and neural foragers

Foraging for nutritional sustenance represents common significant learned/heritable survival strategies evolved for phylum-diverse cellular life on Earth. Unicellular aneural to multicellular neural foragers display conserved rational or irrational decision making depending on outcome predictions for noise-susceptible real/illusory homeodynamic and ambient dietary cues. Such context-dependent heuristic-guided foraging enables optimal, suboptimal, or fallacious decisions that drive organismal adaptation, health, longevity, and life history.

Nano-sized TiO2 (nTiO2) induces metabolic perturbations in Physarum polycephalum macroplasmodium to counter oxidative stress under dark conditions

Nano-sized TiO₂ (nTiO₂) exerts an oxidative effect on cells upon exposure to solar or UV irradiation and ecotoxicity of the nTiO₂ is an urgent concern. Little information is available regarding the effect of TiO₂ on cells under dark conditions. Metabolomics is a unique approach to the discovery of biomarkers of nTiO₂ cytotoxicity, and leads to the identification of perturbed metabolic pathways and the mechanism underlying nTiO₂ toxicity. In the present study, gas chromatography mass spectrometry (GC/MS)-based metabolomics was performed to investigate the effect of nTiO₂ on sensitive cells (P. polycephalum macroplasmodium) under dark conditions. According to the multivariate pattern recognition analysis, at least 60 potential metabolic biomarkers related to sugar metabolism, amino acid metabolism, nucleotide metabolism, polyamine biosynthesis, and secondary metabolites pathways were significantly perturbed by nTiO₂. Notably, many metabolic biomarkers and pathways were related to anti-oxidant mechanisms in the living organism, suggesting that nTiO₂ may induce oxidative stress, even under dark conditions. This speculation was further validated by the biochemical levels of reactive oxygen species (ROS), 8-hydroxy-2-deoxyguanosine (8-OHdG), and total soluble phenols (TSP). We inferred that the oxidative stress might be related to nTiO₂-induced imbalance of cellular ROS. To the best of our knowledge, the present study is the first to investigate the nTiO₂-induced metabolic perturbations in slime mold, provide a new perspective of the mechanism underlying nTiO₂ toxicity under dark conditions, and show that metabolomics can be employed as a rapid, reliable and powerful tool to investigate the interaction among organisms, the environment, and nanomaterials.

The foundations of plant intelligence

Intelligence is defined for wild plants and its role in fitness identified. Intelligent behaviour exhibited by single cells and systems similarity between the interactome and connectome indicates neural systems are not necessary for intelligent capabilities. Plants sense and respond to many environmental signals that are assessed to competitively optimize acquisition of patchily distributed resources. Situations of choice engender motivational states in goal-directed plant behaviour; consequent intelligent decisions enable efficient gain of energy over expenditure. Comparison of swarm intelligence and plant behaviour indicates the origins of plant intelligence lie in complex communication and is exemplified by cambial control of branch function. Error correction in behaviours indicates both awareness and intention as does the ability to count to five. Volatile organic compounds are used as signals in numerous plant interactions. Being complex in composition and often species and individual specific, they may represent the plant language and account for self and alien recognition between individual plants. Game theory has been used to understand competitive and cooperative interactions between plants and microbes. Some unexpected cooperative behaviour between individuals and potential aliens has emerged. Behaviour profiting from experience, another simple definition of intelligence, requires both learning and memory and is indicated in the priming of herbivory, disease and abiotic stresses.

The foundations of plant intelligence

Intelligence is defined for wild plants and its role in fitness identified. Intelligent behaviour exhibited by single cells and systems similarity between the interactome and connectome indicates neural systems are not necessary for intelligent capabilities. Plants sense and respond to many environmental signals that are assessed to competitively optimize acquisition of patchily distributed resources. Situations of choice engender motivational states in goal-directed plant behaviour; consequent intelligent decisions enable efficient gain of energy over expenditure. Comparison of swarm intelligence and plant behaviour indicates the origins of plant intelligence lie in complex communication and is exemplified by cambial control of branch function. Error correction in behaviours indicates both awareness and intention as does the ability to count to five. Volatile organic compounds are used as signals in numerous plant interactions. Being complex in composition and often species and individual specific, they may represent the plant language and account for self and alien recognition between individual plants. Game theory has been used to understand competitive and cooperative interactions between plants and microbes. Some unexpected cooperative behaviour between individuals and potential aliens has emerged. Behaviour profiting from experience, another simple definition of intelligence, requires both learning and memory and is indicated in the priming of herbivory, disease and abiotic stresses.

On Having No Head: Cognition throughout Biological Systems

The central nervous system (CNS) underlies memory, perception, decision-making, and behavior in numerous organisms. However, neural networks have no monopoly on the signaling functions that implement these remarkable algorithms. It is often forgotten that neurons optimized cellular signaling modes that existed long before the CNS appeared during evolution, and were used by somatic cellular networks to orchestrate physiology, embryonic development, and behavior. Many of the key dynamics that enable information processing can, in fact, be implemented by different biological hardware. This is widely exploited by organisms throughout the tree of life. Here, we review data on memory, learning, and other aspects of cognition in a range of models, including single celled organisms, plants, and tissues in animal bodies. We discuss current knowledge of the molecular mechanisms at work in these systems, and suggest several hypotheses for future investigation. The study of cognitive processes implemented in aneural contexts is a fascinating, highly interdisciplinary topic that has many implications for evolution, cell biology, regenerative medicine, computer science, and synthetic bioengineering.