Learning from Bacteria about Natural Information Processing

Living cognition and the nature of organisms

There is no consensus about what cognition is. Different perspectives conceptualize it in different ways. In the same vein, there is no agreement about which systems are truly cognitive. This begs the question, what makes a process or a system cognitive? One of the most conspicuous features of cognition is that it is a set of processes. Cognition, in the end, is a collection of processes such as perception, memory, learning, decision-making, problem-solving, goal-directedness, attention, anticipation, communication, and maybe emotion. There is a debate about what they mean, and which systems possess these processes. One aspect of this problem concerns the level at which cognition and the single processes are conceptualized. To make this scenario clear, evolutionary and self-maintenance arguments are taken. Given the evolutive landscape, one sees processes shared by all organisms and their derivations in specific taxa. No matter which side of the complexity spectrum one favors, the similarities of the simple processes with the complex ones cannot be ignored, and the differences of some complex processes with their simple versions cannot be blurred. A final cognitive framework must make sense of both sides of the spectrum, their differences and similarities. Here, we discuss from an evolutionary perspective the basic elements shared by all living beings and whether these may be necessary and sufficient for understanding the cognitive process. Following these considerations, cognition can be expanded to every living being. Cognition is the set of informational and dynamic processes an organism must interact with and grasp aspects of its world. Understood at their most basic level, perception, memory, learning, problem-solving, decision-making, action, and other cognitive processes are basic features of biological functioning.

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.

The sensual cell: Feeling and affect in unicellular species

Our previous efforts to probe the complex, rich experiential lives of unicellular species have focused on the origins of consciousness (Reber, 2019) and the biomolecular processes that underlie sentience (Reber et al., 2023). Implied, but unexplored, was the assumption that these cognitive functions and associated unicellular organismal behaviors were linked with and often driven by affect, feelings, sensual experiences. In this essay we dig more deeply into these valenced (We're using the term valence here to cover the aspects of sensory experiences that have evaluative elements, are experienced as positive or negative ─ those where this affective, internal representation is an essential element in how the input is interpreted and responded to.) self-referencing features. In the first part, we examine the empirical evidence for various sensual experiences that have been identified. In the second part, we look at other features of prokaryote life that appear to also have affective, valenced elements but where the data to support the proposition aren't as strong. We engage in some informed speculation about these phenomena.

Information Transmission via Molecular Communication in Astrobiological Environments

The ubiquity of information transmission via molecular communication between cells is comprehensively documented on Earth; this phenomenon might even have played a vital role in the origin(s) and early evolution of life. Motivated by these considerations, a simple model for molecular communication entailing the diffusion of signaling molecules from transmitter to receiver is elucidated. The channel capacity C (maximal rate of information transmission) and an optimistic heuristic estimate of the actual information transmission rate ℐ are derived for this communication system; the two quantities, especially the latter, are demonstrated to be broadly consistent with laboratory experiments and more sophisticated theoretical models. The channel capacity exhibits a potentially weak dependence on environmental parameters, whereas the actual information transmission rate may scale with the intercellular distance d as ℐ ∝ d-4 and could vary substantially across settings. These two variables are roughly calculated for diverse astrobiological environments, ranging from Earth's upper oceans (C ∼ 3.1 × 103 bits/s; ℐ ∼ 4.7 × 10-2 bits/s) and deep sea hydrothermal vents (C ∼ 4.2 × 103 bits/s; ℐ ∼ 1.2 × 10-1 bits/s) to the hydrocarbon lakes and seas of Titan (C ∼ 3.8 × 103 bits/s; ℐ ∼ 2.6 × 10-1 bits/s).

From reinforcement learning to agency: Frameworks for understanding basal cognition

Organisms play, explore, and mimic those around them. Is there a purpose to this behavior? Are organisms just behaving, or are they trying to achieve goals? We believe this is a false dichotomy. To that end, to understand organisms, we attempt to unify two approaches for understanding complex agents, whether evolved or engineered. We argue that formalisms describing multiscale competencies and goal-directedness in biology (e.g., TAME), and reinforcement learning (RL), can be combined in a symbiotic framework. While RL has been largely focused on higher-level organisms and robots of high complexity, TAME is naturally capable of describing lower-level organisms and minimal agents as well. We propose several novel questions that come from using RL/TAME to understand biology as well as ones that come from using biology to formulate new theory in AI. We hope that the research programs proposed in this piece shape future efforts to understand biological organisms and also future efforts to build artificial agents.

Principles of cognitive biology and the concept of biocivilisations

A range of studies published in the last few decades promotes the cognitive aspects of life: all organisms, from bacteria to mammals, are capable of sensing/perception, decision-making, problem-solving, learning, and other cognitive functions, including sentience and consciousness. In this paper I present a scientific and philosophical synthesis of these studies, leading to an integrated view of cognitive biology. This view is expressed through the four principles applicable to all living systems: (1) sentience and consciousness, (2) autopoiesis, (3) free energy principle and relational biology, and (4) cognitive repertoire. The principles are circular, and they reinforce themselves. The circularity is not rigid, meaning that hierarchical and heterarchical shifts are widespread in the biosphere. The above principles emerged at the dawn of life, with the first cells, bacteria and archaea. All biogenic forms and functions that emerged since then can be traced to the first cells - indivisible units of biological agency. Following these principles, I developed the concept of biocivilisations to explain various forms of social intelligence in different kingdoms of life. The term biociviloisations draws on the human interpretation of the concept of civilisation, which searches for non-human equivalents of communication, engineering, science, medicine, art, and agriculture, in all kingdoms of life by applying the principles of cognitive biology. Potential avenues for testing the concept of biocivilisations are highlighted.

Planetary Scale Information Transmission in the Biosphere and Technosphere: Limits and Evolution

Information transmission via communication between agents is ubiquitous on Earth, and is a vital facet of living systems. In this paper, we aim to quantify this rate of information transmission associated with Earth's biosphere and technosphere (i.e., a measure of global information flow) by means of a heuristic order-of-magnitude model. By adopting ostensibly conservative values for the salient parameters, we estimate that the global information transmission rate for the biosphere might be ∼1024 bits/s, and that it may perhaps exceed the corresponding rate for the current technosphere by ∼9 orders of magnitude. However, under the equivocal assumption of sustained exponential growth, we find that information transmission in the technosphere can potentially surpass that of the biosphere ∼90 years in the future, reflecting its increasing dominance.

Embodied cognitive morphogenesis as a route to intelligent systems

The embryological view of development is that coordinated gene expression, cellular physics and migration provides the basis for phenotypic complexity. This stands in contrast with the prevailing view of embodied cognition, which claims that informational feedback between organisms and their environment is key to the emergence of intelligent behaviours. We aim to unite these two perspectives as embodied cognitive morphogenesis, in which morphogenetic symmetry breaking produces specialized organismal subsystems which serve as a substrate for the emergence of autonomous behaviours. As embodied cognitive morphogenesis produces fluctuating phenotypic asymmetry and the emergence of information processing subsystems, we observe three distinct properties: acquisition, generativity and transformation. Using a generic organismal agent, such properties are captured through models such as tensegrity networks, differentiation trees and embodied hypernetworks, providing a means to identify the context of various symmetry-breaking events in developmental time. Related concepts that help us define this phenotype further include concepts such as modularity, homeostasis and 4E (embodied, enactive, embedded and extended) cognition. We conclude by considering these autonomous developmental systems as a process called connectogenesis, connecting various parts of the emerged phenotype into an approach useful for the analysis of organisms and the design of bioinspired computational agents.

Is the tendency to maximise energy distribution an optimal collective activity for biological purposes? A proposal for a global principle of biological organization

Our purpose is to address the biological problem of finding foundations of the organization in the collective activity among cell networks in the nervous system, at the meso/macroscale, giving rise to cognition and consciousness. But in doing so, we encounter another problem related to the interpretation of methods to assess the neural interactions and organization of the neurodynamics, because thermodynamic notions, which have precise meaning only under specific conditions, have been widely employed in these studies. The consequence is that apparently contradictory results appear in the literature, but these contradictions diminish upon the considerations of the specific circumstances of each experiment. After clarifying some of these controversial points and surveying some experimental results, we propose that a necessary condition for cognition/consciousness to emerge is to have available enough energy, or cellular activity; and a sufficient condition is the multiplicity of configurations in which cell networks can communicate, resulting in non-uniform energy distribution, the generation and dissipation of energy gradients due to the constant activity. The diversity of sensorimotor processing of higher animals needs a flexible, fluctuating web on neuronal connections, and we review results supporting such multiplicity of configurations among brain regions associated with conscious awareness and healthy brain states. These ideas may reveal possible fundamental principles of brain organization that could be extended to other natural phenomena and how healthy activity may derive to pathological states.

Provenance of life: Chemical autonomous agents surviving through associative learning

We present a benchmark study of autonomous, chemical agents exhibiting associative learning of an environmental feature. Associative learning systems have been widely studied in cognitive science and artificial intelligence but are most commonly implemented in highly complex or carefully engineered systems, such as animal brains, artificial neural networks, DNA computing systems, and gene regulatory networks, among others. The ability to encode environmental information and use it to make simple predictions is a benchmark of biological resilience and underpins a plethora of adaptive responses in the living hierarchy, spanning prey animal species anticipating the arrival of predators to epigenetic systems in microorganisms learning environmental correlations. Given the ubiquitous and essential presence of learning behaviors in the biosphere, we aimed to explore whether simple, nonliving dissipative structures could also exhibit associative learning. Inspired by previous modeling of associative learning in chemical networks, we simulated simple systems composed of long- and short-term memory chemical species that could encode the presence or absence of temporal correlations between two external species. The ability to learn this association was implemented in Gray-Scott reaction-diffusion spots, emergent chemical patterns that exhibit self-replication and homeostasis. With the novel ability of associative learning, we demonstrate that simple chemical patterns can exhibit a broad repertoire of lifelike behavior, paving the way for in vitro studies of autonomous chemical learning systems, with potential relevance to artificial life, origins of life, and systems chemistry. The experimental realization of these learning behaviors in protocell or coacervate systems could advance a new research direction in astrobiology, since our system significantly reduces the lower bound on the required complexity for autonomous chemical learning.

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.

Gut Microbiota and Neuroplasticity

The accumulating evidence linking bacteria in the gut and neurons in the brain (the microbiota-gut-brain axis) has led to a paradigm shift in the neurosciences. Understanding the neurobiological mechanisms supporting the relevance of actions mediated by the gut microbiota for brain physiology and neuronal functioning is a key research area. In this review, we discuss the literature showing how the microbiota is emerging as a key regulator of the brain's function and behavior, as increasing amounts of evidence on the importance of the bidirectional communication between the intestinal bacteria and the brain have accumulated. Based on recent discoveries, we suggest that the interaction between diet and the gut microbiota, which might ultimately affect the brain, represents an unprecedented stimulus for conducting new research that links food and mood. We also review the limited work in the clinical arena to date, and we propose novel approaches for deciphering the gut microbiota-brain axis and, eventually, for manipulating this relationship to boost mental wellness.

Mechanosensation Mediates Long-Range Spatial Decision-Making in an Aneural Organism

The unicellular protist Physarum polycephalum is an important emerging model for understanding how aneural organisms process information toward adaptive behavior. Here, it is revealed that Physarum can use mechanosensation to reliably make decisions about distant objects in its environment, preferentially growing in the direction of heavier, substrate-deforming, but chemically inert masses. This long-range sensing is abolished by gentle rhythmic mechanical disruption, changing substrate stiffness, or the addition of an inhibitor of mechanosensitive transient receptor potential channels. Additionally, it is demonstrated that Physarum does not respond to the absolute magnitude of strain. Computational modeling reveales that Physarum may perform this calculation by sensing the fraction of its perimeter that is distorted above a threshold substrate strain-a fundamentally novel method of mechanosensation. Using its body as both a distributed sensor array and computational substrate, this aneural organism leverages its unique morphology to make long-range decisions. Together, these data identify a surprising behavioral preference relying on biomechanical features and quantitatively characterize how the Physarum exploits physics to adaptively regulate its growth and shape.

Reconfiguring SETI in the microbial context: Panspermia as a solution to Fermi's paradox

All SETI (Search for Extraterrestrial Intelligence) programmes that were conceived and put into practice since the 1960s have been based on anthropocentric ideas concerning the definition of intelligence on a cosmic-wide scale. Brain-based neuronal intelligence, augmented by AI, are currently thought of as being the only form of intelligence that can engage in SETI-type interactions, and this assumption is likely to be connected with the dilemma of the famous Fermi paradox. We argue that high levels of intelligence and cognition inherent in ensembles of bacteria are much more likely to be the dominant form of cosmic intelligence, and the transfer of such intelligence is enabled by the processes of panspermia. We outline the main principles of bacterial intelligence, and how this intelligence may be used by the planetary-scale bacterial system, or the bacteriosphere, through processes of biological tropism, to connect to any extra-terrestrial microbial forms, independently of human interference.

Non-Random Genome Editing and Natural Cellular Engineering in Cognition-Based Evolution

Neo-Darwinism presumes that biological variation is a product of random genetic replication errors and natural selection. Cognition-Based Evolution (CBE) asserts a comprehensive alternative approach to phenotypic variation and the generation of biological novelty. In CBE, evolutionary variation is the product of natural cellular engineering that permits purposive genetic adjustments as cellular problem-solving. CBE upholds that the cornerstone of biology is the intelligent measuring cell. Since all biological information that is available to cells is ambiguous, multicellularity arises from the cellular requirement to maximize the validity of available environmental information. This is best accomplished through collective measurement purposed towards maintaining and optimizing individual cellular states of homeorhesis as dynamic flux that sustains cellular equipoise. The collective action of the multicellular measurement and assessment of information and its collaborative communication is natural cellular engineering. Its yield is linked cellular ecologies and mutualized niche constructions that comprise biofilms and holobionts. In this context, biological variation is the product of collective differential assessment of ambiguous environmental cues by networking intelligent cells. Such concerted action is enabled by non-random natural genomic editing in response to epigenetic impacts and environmental stresses. Random genetic activity can be either constrained or deployed as a 'harnessing of stochasticity'. Therefore, genes are cellular tools. Selection filters cellular solutions to environmental stresses to assure continuous cellular-organismal-environmental complementarity. Since all multicellular eukaryotes are holobionts as vast assemblages of participants of each of the three cellular domains (Prokaryota, Archaea, Eukaryota) and the virome, multicellular variation is necessarily a product of co-engineering among them.

Bioelectrical approaches to cancer as a problem of the scaling of the cellular self

One lens with which to understand the complex phenomenon of cancer is that of developmental biology. Cancer is the inevitable consequence of a breakdown of the communication that enables individual cells to join into computational networks that work towards large-scale, morphogenetic goals instead of more primitive, unicellular objectives. This perspective suggests that cancer may be a physiological disorder, not necessarily due to problems with the genetically-specified protein hardware. One aspect of morphogenetic coordination is bioelectric signaling, and indeed an abnormal bioelectric signature non-invasively reveals the site of incipient tumors in amphibian models. Functionally, a disruption of resting potential states triggers metastatic melanoma phenotypes in embryos with no genetic defects or carcinogen exposure. Conversely, optogenetic or molecular-biological modulation of bioelectric states can override powerful oncogenic mutations and prevent or normalize tumors. The bioelectrically-mediated information flows that harness cells toward body-level anatomical outcomes represent a very attractive and tractable endogenous control system, which is being targeted by emerging approaches to cancer.

Learning in single cell organisms

The survival of all species requires appropriate behavioral responses to environmental challenges. Learning is one of the key processes to acquire information about the environment and adapt to changing and uncertain conditions. Learning has long been acknowledged in animals from invertebrates to vertebrates but remains a subject of debate in non-animal systems such a plants and single cell organisms. In this review I will attempt to answer the following question: are single cell organisms capable of learning? I will first briefly discuss the concept of learning and argue that the ability to acquire and store information through learning is pervasive and may be found in single cell organisms. Second, by focusing on habituation, the simplest form of learning, I will review a series of experiments showing that single cell organisms such as slime molds and ciliates display habituation and follow most of the criteria adopted by neuroscientists to define habituation. Then I will discuss disputed evidence suggesting that single cell organisms might also undergo more sophisticated forms of learning such as associative learning. Finally, I will stress out that the challenge for the future is less about whether or not to single cell organisms fulfill the definition of learning established from extensive studies in animal systems and more about acknowledging and understanding the range of behavioral plasticity exhibited by such fascinating organisms.

Valuing what happens: a biogenic approach to valence and (potentially) affect

Valence is half of the pair of properties that constitute core affect, the foundation of emotion. But what is valence, and where is it found in the natural world? Currently, this question cannot be answered. The idea that emotion is the body's way of driving the organism to secure its survival, thriving and reproduction runs like a leitmotif from the pathfinding work of Antonio Damasio through four book-length neuroscientific accounts of emotion recently published by the field's leading practitioners. Yet while Damasio concluded 20 years ago that the homeostasis-affect linkage is rooted in unicellular life, no agreement exists about whether even non-human animals with brains experience emotions. Simple neural animals-those less brainy than bees, fruit flies and other charismatic invertebrates-are not even on the radar of contemporary affective research, to say nothing of aneural organisms. This near-sightedness has effectively denied the most productive method available for getting a grip on highly complex biological processes to a scientific domain whose importance for understanding biological decision-making cannot be underestimated. Valence arguably is the fulcrum around which the dance of life revolves. Without the ability to discriminate advantage from harm, life very quickly comes to an end. In this paper, we review the concept of valence, where it came from, the work it does in current leading theories of emotion, and some of the odd features revealed via experiment. We present a biologically grounded framework for investigating valence in any organism and sketch a preliminary pathway to a computational model. This article is part of the theme issue 'Basal cognition: conceptual tools and the view from the single cell'.

Biofilm and swarming emergent behaviours controlled through the aid of biophysical understanding and tools

Bacteria can organise themselves into communities in the forms of biofilms and swarms. Through chemical and physical interactions between cells, these communities exhibit emergent properties that individual cells alone do not have. While bacterial communities have been mainly studied in the context of biochemistry and molecular biology, recent years have seen rapid advancements in the biophysical understanding of emergent phenomena through physical interactions in biofilms and swarms. Moreover, new technologies to control bacterial emergent behaviours by physical means are emerging in synthetic biology. Such technologies are particularly promising for developing engineered living materials (ELM) and devices and controlling contamination and biofouling. In this minireview, we overview recent studies unveiling physical and mechanical cues that trigger and affect swarming and biofilm development. In particular, we focus on cell shape, motion and density as the key parameters for mechanical cell-cell interactions within a community. We then showcase recent studies that use physical stimuli for patterning bacterial communities, altering collective behaviours and preventing biofilm formation. Finally, we discuss the future potential extension of biophysical and bioengineering research on microbial communities through computational modelling and deeper investigation of mechano-electrophysiological coupling.

Natural Morphological Computation as Foundation of Learning to Learn in Humans, Other Living Organisms, and Intelligent Machines

The emerging contemporary natural philosophy provides a common ground for the integrative view of the natural, the artificial, and the human-social knowledge and practices. Learning process is central for acquiring, maintaining, and managing knowledge, both theoretical and practical. This paper explores the relationships between the present advances in understanding of learning in the sciences of the artificial (deep learning, robotics), natural sciences (neuroscience, cognitive science, biology), and philosophy (philosophy of computing, philosophy of mind, natural philosophy). The question is, what at this stage of the development the inspiration from nature, specifically its computational models such as info-computation through morphological computing, can contribute to machine learning and artificial intelligence, and how much on the other hand models and experiments in machine learning and robotics can motivate, justify, and inform research in computational cognitive science, neurosciences, and computing nature. We propose that one contribution can be understanding of the mechanisms of ‘learning to learn’, as a step towards deep learning with symbolic layer of computation/information processing in a framework linking connectionism with symbolism. As all natural systems possessing intelligence are cognitive systems, we describe the evolutionary arguments for the necessity of learning to learn for a system to reach human-level intelligence through evolution and development. The paper thus presents a contribution to the epistemology of the contemporary philosophy of nature.

Cellular senomic measurements in Cognition-Based Evolution

All living entities are cognitive and dependent on ambiguous information. Any assessment of that imprecision is necessarily a measuring function. Individual cells measure information to sustain self-referential homeostatic equipoise (self-identity) in juxtaposition to the external environment. The validity of that information is improved by its collective assessment. The reception of cellular information obliges thermodynamic reactions that initiate a self-reinforcing work channel. This expresses as natural cellular engineering and niche constructions which become the complex interrelated tissue ecologies of holobionts. Multicellularity is collaborative cellular information management directed towards the optimization of information quality through its collective measured assessment. Biology and its evolution can now be re-framed as the continuous process of self-referential cellular measurement in the perpetual defense of individual cellular self-identities through the collective form.

The N-space Episenome unifies cellular information space-time within cognition-based evolution

Self-referential cellular homeostasis is maintained by the measured assessment of both internal status and external conditions based within an integrated cellular information field. This cellular field attachment to biologic information space-time coordinates environmental inputs by connecting the cellular senome, as the sum of the sensory experiences of the cell, with its genome and epigenome. In multicellular organisms, individual cellular information fields aggregate into a collective information architectural matrix, termed a N-space Episenome, that enables mutualized organism-wide information management. It is hypothesized that biological organization represents a dual heritable system constituted by both its biological materiality and a conjoining N-space Episenome. It is further proposed that morphogenesis derives from reciprocations between these inter-related facets to yield coordinated multicellular growth and development. The N-space Episenome is conceived as a whole cell informational projection that is heritable, transferable via cell division and essential for the synchronous integration of the diverse self-referential cells that constitute holobionts.

Reappraising the exteriorization of the mammalian testes through evolutionary physiology

A number of theories have been proposed to explain the exteriorization of the testicles in most mammalian species. None of these provide a consistent account for the wide variety of testicular locations found across the animal kingdom. It is proposed that testicular location is the result of coordinate action of testicular tissue ecologies to sustain preferential states of homeostatic equipoise throughout evolutionary development in response to the advent of endothermy.

Are plants cognitive? A reply to Adams

According to F. Adams [this journal, vol. 68, 2018] cognition cannot be realized in plants or bacteria. In his view, plants and bacteria respond to the here-and-now in a hardwired, inflexible manner, and are therefore incapable of cognitive activity. This article takes issue with the pursuit of plant cognition from the perspective of an empirically informed philosophy of plant neurobiology. As we argue, empirical evidence shows, contra Adams, that plant behavior is in many ways analogous to animal behavior. This renders plants suitable to be described as cognitive agents in a non-metaphorical way. Sections two to four review the arguments offered by Adams in light of scientific evidence on plant adaptive behavior, decision-making, anticipation, as well as learning and memory. Section five introduces the 'phyto-nervous' system of plants. To conclude, section six resituates the quest for plant cognition into a broader approach in cognitive science, as represented by enactive and ecological schools of thought. Overall, we aim to motivate the idea that plants may be considered genuine cognitive agents. Our hope is to help propel public awareness and discussion of plant intelligence once appropriately stripped of anthropocentric preconceptions of the sort that Adams' position appears to exemplify.

Information Processing and Distributed Computation in Plant Organs

The molecular networks plant cells evolved to tune their development in response to the environment are becoming increasingly well understood. Much less is known about how these programs function in the multicellular context of organs and the impact this spatial embedding has on emergent decision-making. Here I address these questions and investigate whether the computational control principles identified in engineered information processing systems also apply to plant development. Examples of distributed computing underlying plant development are presented and support the presence of shared mechanisms of information processing across these domains. The coinvestigation of computation across plant biology and computer science can provide novel insight into the principles of plant development and suggest novel algorithms for use in distributed computing.

Biological evolution as defense of 'self'

Although the origin of self-referential consciousness is unknown, it can be argued that the instantiation of self-reference was the commencement of the living state as phenomenal experientiality. As self-referential cognition is demonstrated by all living organisms, life can be equated with the sustenance of cellular homeostasis in the continuous defense of 'self'. It is proposed that the epicenter of 'self' is perpetually embodied within the basic cellular form in which it was instantiated. Cognition-Based Evolution argues that all of biological and evolutionary development represents the perpetual autopoietic defense of self-referential basal cellular states of homeostatic preference. The means by which these states are attained and maintained is through self-referential measurement of information and its communication. The multicellular forms, either as biofilms or holobionts, represent the cellular attempt to achieve maximum states of informational distinction and energy efficiency through individual and collective means. In this frame, consciousness, self-consciousness and intelligence can be identified as forms of collective cellular phenotype directed towards the defense of fundamental cellular self-reference.

Four domains: The fundamental unicell and Post-Darwinian Cognition-Based Evolution

Contemporary research supports the viewpoint that self-referential cognition is the proper definition of life. From that initiating platform, a cohesive alternative evolutionary narrative distinct from standard Neodarwinism can be presented. Cognition-Based Evolution contends that biological variation is a product of a self-reinforcing information cycle that derives from self-referential attachment to biological information space-time with its attendant ambiguities. That information cycle is embodied through obligatory linkages among energy, biological information, and communication. Successive reiterations of the information cycle enact the informational architectures of the basic unicellular forms. From that base, inter-domain and cell-cell communications enable genetic and cellular variations through self-referential natural informational engineering and cellular niche construction. Holobionts are the exclusive endpoints of that self-referential cellular engineering as obligatory multicellular combinations of the essential Four Domains: Prokaryota, Archaea, Eukaryota and the Virome. Therefore, it is advocated that these Four Domains represent the perpetual object of the living circumstance rather than the visible macroorganic forms. In consequence, biology and its evolutionary development can be appraised as the continual defense of instantiated cellular self-reference. As the survival of cells is as dependent upon limitations and boundaries as upon any freedom of action, it is proposed that selection represents only one of many forms of cellular constraint that sustain self-referential integrity.

Synthetic associative learning in engineered multicellular consortia

Associative learning (AL) is one of the key mechanisms displayed by living organisms in order to adapt to their changing environments. It was recognized early as a general trait of complex multicellular organisms but is also found in 'simpler' ones. It has also been explored within synthetic biology using molecular circuits that are directly inspired in neural network models of conditioning. These designs involve complex wiring diagrams to be implemented within one single cell, and the presence of diverse molecular wires become a challenge that might be very difficult to overcome. Here we present three alternative circuit designs based on two-cell microbial consortia able to properly display AL responses to two classes of stimuli and displaying long- and short-term memory (i.e. the association can be lost with time). These designs might be a helpful approach for engineering the human gut microbiome or even synthetic organoids, defining a new class of decision-making biological circuits capable of memory and adaptation to changing conditions. The potential implications and extensions are outlined.

Biological information systems: Evolution as cognition-based information management

An alternative biological synthesis is presented that conceptualizes evolutionary biology as an epiphenomenon of integrated self-referential information management. Since all biological information has inherent ambiguity, the systematic assessment of information is required by living organisms to maintain self-identity and homeostatic equipoise in confrontation with environmental challenges. Through their self-referential attachment to information space, cells are the cornerstone of biological action. That individualized assessment of information space permits self-referential, self-organizing niche construction. That deployment of information and its subsequent selection enacted the dominant stable unicellular informational architectures whose biological expressions are the prokaryotic, archaeal, and eukaryotic unicellular forms. Multicellularity represents the collective appraisal of equivocal environmental information through a shared information space. This concerted action can be viewed as systematized information management to improve information quality for the maintenance of preferred homeostatic boundaries among the varied participants. When reiterated in successive scales, this same collaborative exchange of information yields macroscopic organisms as obligatory multicellular holobionts. Cognition-Based Evolution (CBE) upholds that assessment of information precedes biological action, and the deployment of information through integrative self-referential niche construction and natural cellular engineering antecedes selection. Therefore, evolutionary biology can be framed as a complex reciprocating interactome that consists of the assessment, communication, deployment and management of information by self-referential organisms at multiple scales in continuous confrontation with environmental 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.

Cognition, Information Fields and Hologenomic Entanglement: Evolution in Light and Shadow

As the prime unification of Darwinism and genetics, the Modern Synthesis continues to epitomize mainstay evolutionary theory. Many decades after its formulation, its anchor assumptions remain fixed: conflict between macro organic organisms and selection at that level represent the near totality of any evolutionary narrative. However, intervening research has revealed a less easily appraised cellular and microbial focus for eukaryotic existence. It is now established that all multicellular eukaryotic organisms are holobionts representing complex collaborations between the co-aligned microbiome of each eukaryote and its innate cells into extensive mixed cellular ecologies. Each of these ecological constituents has demonstrated faculties consistent with basal cognition. Consequently, an alternative hologenomic entanglement model is proposed with cognition at its center and conceptualized as Pervasive Information Fields within a quantum framework. Evolutionary development can then be reconsidered as being continuously based upon communication between self-referential constituencies reiterated at every scope and scale. Immunological reactions support and reinforce self-recognition juxtaposed against external environmental stresses.

Re-membering the body: applications of computational neuroscience to the top-down control of regeneration of limbs and other complex organs

A major goal of regenerative medicine and bioengineering is the regeneration of complex organs, such as limbs, and the capability to create artificial constructs (so-called biobots) with defined morphologies and robust self-repair capabilities. Developmental biology presents remarkable examples of systems that self-assemble and regenerate complex structures toward their correct shape despite significant perturbations. A fundamental challenge is to translate progress in molecular genetics into control of large-scale organismal anatomy, and the field is still searching for an appropriate theoretical paradigm for facilitating control of pattern homeostasis. However, computational neuroscience provides many examples in which cell networks - brains - store memories (e.g., of geometric configurations, rules, and patterns) and coordinate their activity towards proximal and distant goals. In this Perspective, we propose that programming large-scale morphogenesis requires exploiting the information processing by which cellular structures work toward specific shapes. In non-neural cells, as in the brain, bioelectric signaling implements information processing, decision-making, and memory in regulating pattern and its remodeling. Thus, approaches used in computational neuroscience to understand goal-seeking neural systems offer a toolbox of techniques to model and control regenerative pattern formation. Here, we review recent data on developmental bioelectricity as a regulator of patterning, and propose that target morphology could be encoded within tissues as a kind of memory, using the same molecular mechanisms and algorithms so successfully exploited by the brain. We highlight the next steps of an unconventional research program, which may allow top-down control of growth and form for numerous applications in regenerative medicine and synthetic bioengineering.

Electrical spiking in bacterial biofilms

In nature, biofilms are the most common form of bacterial growth. In biofilms, bacteria display coordinated behaviour to perform specific functions. Here, we investigated electrical signalling as a possible driver in biofilm sociobiology. Using a multi-electrode array system that enables high spatio-temporal resolution, we studied the electrical activity in two biofilm-forming strains and one non-biofilm-forming strain. The action potential rates monitored during biofilm-forming bacterial growth exhibited a one-peak maximum with a long tail, corresponding to the highest biofilm development. This peak was not observed for the non-biofilm-forming strain, demonstrating that the intensity of the electrical activity was not linearly related to the bacterial density, but was instead correlated with biofilm formation. Results obtained indicate that the analysis of the spatio-temporal electrical activity of bacteria during biofilm formation can open a new frontier in the study of the emergence of collective microbial behaviour.

Elements of the cellular metabolic structure

A large number of studies have demonstrated the existence of metabolic covalent modifications in different molecular structures, which are able to store biochemical information that is not encoded by DNA. Some of these covalent mark patterns can be transmitted across generations (epigenetic changes). Recently, the emergence of Hopfield-like attractor dynamics has been observed in self-organized enzymatic networks, which have the capacity to store functional catalytic patterns that can be correctly recovered by specific input stimuli. Hopfield-like metabolic dynamics are stable and can be maintained as a long-term biochemical memory. In addition, specific molecular information can be transferred from the functional dynamics of the metabolic networks to the enzymatic activity involved in covalent post-translational modulation, so that determined functional memory can be embedded in multiple stable molecular marks. The metabolic dynamics governed by Hopfield-type attractors (functional processes), as well as the enzymatic covalent modifications of specific molecules (structural dynamic processes) seem to represent the two stages of the dynamical memory of cellular metabolism (metabolic memory). Epigenetic processes appear to be the structural manifestation of this cellular metabolic memory. Here, a new framework for molecular information storage in the cell is presented, which is characterized by two functionally and molecularly interrelated systems: a dynamic, flexible and adaptive system (metabolic memory) and an essentially conservative system (genetic memory). The molecular information of both systems seems to coordinate the physiological development of the whole cell.

Menaquinone and iron are essential for complex colony development in Bacillus subtilis

Cells of undomesticated species of Bacillus subtilis frequently form complex colonies during spreading on agar surfaces. Given that menaquinone is involved in another form of coordinated behavior, namely, sporulation, we looked for a possible role for menaquinone in complex colony development (CCD) in the B. subtilis strain NCIB 3610. Here we show that inhibition of menaquinone biosynthesis in B. subtilis indeed abolished its ability to develop complex colonies. Additionally some mutations of B. subtilis which confer defective CCD could be suppressed by menaquinone derivatives. Several such mutants mapped to the dhb operon encoding the genes responsible for the biosynthesis of the iron siderophore, bacillibactin. Our results demonstrate that both menaquinone and iron are essential for CCD in B. subtilis.

High-order social interactions in groups of mice

Social behavior in mammals is often studied in pairs under artificial conditions, yet groups may rely on more complicated social structures. Here, we use a novel system for tracking multiple animals in a rich environment to characterize the nature of group behavior and interactions, and show strongly correlated group behavior in mice. We have found that the minimal models that rely only on individual traits and pairwise correlations between animals are not enough to capture group behavior, but that models that include third-order interactions give a very accurate description of the group. These models allow us to infer social interaction maps for individual groups. Using this approach, we show that environmental complexity during adolescence affects the collective group behavior of adult mice, in particular altering the role of high-order structure. Our results provide new experimental and mathematical frameworks for studying group behavior and social interactions. DOI:http://dx.doi.org/10.7554/eLife.00759.001.

Microorganism and filamentous fungi drive evolution of plant synapses

In the course of plant evolution, there is an obvious trend toward an increased complexity of plant bodies, as well as an increased sophistication of plant behavior and communication. Phenotypic plasticity of plants is based on the polar auxin transport machinery that is directly linked with plant sensory systems impinging on plant behavior and adaptive responses. Similar to the emergence and evolution of eukaryotic cells, evolution of land plants was also shaped and driven by infective and symbiotic microorganisms. These microorganisms are the driving force behind the evolution of plant synapses and other neuronal aspects of higher plants; this is especially pronounced in the root apices. Plant synapses allow synaptic cell–cell communication and coordination in plants, as well as sensory-motor integration in root apices searching for water and mineral nutrition. These neuronal aspects of higher plants are closely linked with their unique ability to adapt to environmental changes.

Self-similar dynamics of bacterial chemotaxis

Colonies of bacteria grown on thin agar plate exhibit fractal patterns as a result of adaptation to their environments. The bacterial colony pattern formation is regulated crucially by chemotaxis, the movement of cells along a chemical concentration gradient. Here, the dynamics of pattern formation in a bacterial colony is investigated theoretically through a continuum model that considers chemotaxis. In the case of the gradient sensed by the bacterium is nearly uniform, the bacterial colony patterns are self-similar, which means they look the same at every scale. The scaling law of the bacterial colony growth has been revealed explicitly. Chemotaxis biases the movement of the bacterial population in colony to trend toward the chemical attractant. Moreover, the bacterial colonies evolve for a long time as the traveling wave with a sharp front.

Origins of regulated cell-to-cell variability

Single-cell measurements and lineage-tracing experiments are revealing that phenotypic cell-to-cell variability is often the result of deterministic processes, despite the existence of intrinsic noise in molecular networks. In most cases, this determinism represents largely uncharacterized molecular regulatory mechanisms, which places the study of cell-to-cell variability in the realm of molecular cell biology. Further research in the field will be important to advance quantitative cell biology because it will provide new insights into the mechanisms by which cells coordinate their intracellular activities in the spatiotemporal context of the multicellular environment.

Defense against cannibalism: the SdpI family of bacterial immunity/signal transduction proteins

The SdpI family consists of putative bacterial toxin immunity and signal transduction proteins. One member of the family in Bacillus subtilis, SdpI, provides immunity to cells from cannibalism in times of nutrient limitation. SdpI family members are transmembrane proteins with 3, 4, 5, 6, 7, 8, or 12 putative transmembrane alpha-helical segments (TMSs). These varied topologies appear to be genuine rather than artifacts due to sequencing or annotation errors. The basic and most frequently occurring element of the SdpI family has 6 TMSs. Homologues of all topological types were aligned to determine the homologous TMSs and loop regions, and the positive-inside rule was used to determine sidedness. The two most conserved motifs were identified between TMSs 1 and 2 and TMSs 4 and 5 of the 6 TMS proteins. These showed significant sequence similarity, leading us to suggest that the primordial precursor of these proteins was a 3 TMS-encoding genetic element that underwent intragenic duplication. Various deletional and fusional events, as well as intragenic duplications and inversions, may have yielded SdpI homologues with topologies of varying numbers and positions of TMSs. We propose a specific evolutionary pathway that could have given rise to these distantly related bacterial immunity proteins. We further show that genes encoding SdpI homologues often appear in operons with genes for homologues of SdpR, SdpI's autorepressor. Our analyses allow us to propose structure-function relationships that may be applicable to most family members.

Uniform categorization of biocommunication in bacteria, fungi and plants

This article describes a coherent biocommunication categorization for the kingdoms of bacteria, fungi and plants. The investigation further shows that, besides biotic sign use in trans-, inter- and intraorganismic communication processes, a common trait is interpretation of abiotic influences as indicators to generate an appropriate adaptive behaviour. Far from being mechanistic interactions, communication processes within organisms and between organisms are sign-mediated interactions. Sign-mediated interactions are the precondition for every cooperation and coordination between at least two biological agents such as cells, tissues, organs and organisms. Signs of biocommunicative processes are chemical molecules in most cases. The signs that are used in a great variety of signaling processes follow syntactic (combinatorial), pragmatic (context-dependent) and semantic (content-specific) rules. These three levels of semiotic rules are helpful tools to investigate communication processes throughout all organismic kingdoms. It is not the aim to present the latest empirical data concerning communication in these three kingdoms but to present a unifying perspective that is able to interconnect transdisciplinary research on bacteria, fungi and plants.