The cognitive cell: bacterial behavior reconsidered

Vegetal memory through the lens of transcriptomic changes - recent progress and future practical prospects for exploiting plant transcriptional memory

Plant memory plays an important role in the efficient and rapid acclimation to a swiftly changing environment. In addition, since plant memory can be inherited, it is also of adaptive and evolutionary importance. The ability of a plant to store, retain, retrieve and delete information on acquired experience is based on cellular, biochemical and molecular networks in the plants. This review offers an up-to-date overview on the formation, types, checkpoints of plant memory based on our current knowledge and focusing on its transcriptional aspects, the transcriptional memory. Roles of long and small non-coding RNAs are summarized in the regulation, formation and the cooperation between the different layers of the plant memory, i.e. in the establishment of epigenetic changes associated with memory formation in plants. The RNA interference mechanisms at the RNA and DNA level and the interplays between them are also presented. Furthermore, this review gives an insight of how exploitation of plant transcriptional memory may provide new opportunities for elaborating promising cost-efficient, and effective strategies to cope with the ever-changing environmental perturbations, caused by climate change. The potentials of plant memory-based methods, such as crop priming, cross acclimatization, memory modification by miRNAs and associative use of plant memory, in the future's agriculture are also discussed.

The "plant neurobiology" revolution

The 21st-century "plant neurobiology" movement is an amalgam of scholars interested in how "neural processes", broadly defined, lead to changes in plant behavior. Integral to the movement (now called plant behavioral biology) is a triad of historically marginalized subdisciplines, namely plant ethology, whole plant electrophysiology and plant comparative psychology, that set plant neurobiology apart from the mainstream. A central tenet held by these "triad disciplines" is that plants are exquisitely sensitive to environmental perturbations and that destructive experimental manipulations rapidly and profoundly affect plant function. Since destructive measurements have been the norm in plant physiology, much of our "textbook knowledge" concerning plant physiology is unrelated to normal plant function. As such, scientists in the triad disciplines favor a more natural and holistic approach toward understanding plant function. By examining the history, philosophy, sociology and psychology of the triad disciplines, this paper refutes in eight ways the criticism that plant neurobiology presents nothing new, and that the topics of plant neurobiology fall squarely under the purview of mainstream plant physiology. It is argued that although the triad disciplines and mainstream plant physiology share the common goal of understanding plant function, they are distinct in having their own intellectual histories and epistemologies.

Epistolution: a new principle necessary to a learning-first theory of life

Biological theory assumes the organized appearance of life and the reliable recurrence of traits are due to inheritance. Natural selection acting on blind variations produces phenotypes with heritable traits, one of which may be natural learning. The aim of learning, then, is solving problems related to survival and reproduction. But what if these views confuse cause with effect? Perhaps a learning algorithm is required for any phenotype at all to arise. If so, evolution proceeds learning-first, with individuals pursuing another telos entirely. I argue that this aim may be epistemological, the drive to understand the world through an umwelt. By "understand" I mean neither association nor prediction but Karl Popper's concept of explanation through conjecture and refutation. I propose that if only genetic materials are truly heritable, not traits, then testing a successful physical theory of life will depend on building abiotic machines which can perform natural learning without the presence of any inherited materials or conditions. I name this process "epistolution," combining "epistemology" and "evolution," to distinguish it from other concepts. Epistolution is an integral consequence of any learning-first view of life, such as the Cellular Basis of Consciousness theory. This type of theory suggests that in all cells during the history of life full-blown agency, involving beliefs, intentions, and desires, generated all the phenotypes that have then been winnowed by natural selection. Unlike in other versions, I posit that the aim of agential living systems is the explanation of reality rather than inductive prediction or survival/reproduction.

An evaluation of the xenobotic cognitive project: Towards Stage 1 of xenobotic cognition

Xenobot, the world's first biological robot, puts numerous philosophical riddles before us. One among them pertains to the cognitive status of these entities. Are these biological robots cognitive? To evaluate the cognitive status of xenobots and to resolve the puzzle of a single mind emerging from smaller sub-units, in this article, I juxtapose the cognitive capacities of xenobots with that of two other minimal models of cognition, i.e., basal cognition and nonliving active matter cognition. Further, the article underlines the essential cognitive capabilities that xenobots need to achieve to enter what I call stage 1 of xenobotic cognition. Stage 1 is characterized by numerous cognitive mechanisms, which are integral for the survival and cognition of basal organisms. Finally, I suggest that developing xenobots that can reach Stage 1 can help us achieve sophistication in the areas of evolution of the human mind, robotics, biology and medicine, and artificial intelligence (AI).

Sentient cells as basic units of tissues, organs and organismal physiology

Cells evolved some 4 billion years ago, and since then the integrity of the structural and functional continuity of cellular life has been maintained via highly conserved and ancient processes of cell reproduction and division. The plasma membrane as well as all the cytoplasmic structures are reproduced and inherited uninterruptedly by each of the two daughter cells resulting from every cell division. Although our understanding of the evolutionary emergence of the very first cells is obscured by the extremely long timeline since that revolutionary event, the generally accepted position is that the de novo formation of cells is not possible; all present cells are products of other prior cells. This essential biological principle was first discovered by Robert Remak and then effectively coined as Omnis Cellula e Cellula (every cell of the cell) by Rudolf Virchow: all currently living cells have direct structural and functional connections to the very first cells. Based on our previous theoretical analysis, all cells are endowed with individual sentient cognition that guides their individual agency, behaviour and evolution. There is a vital consequence of this new sentient and cognitive view of cells: when cells assemble as functional tissue ecologies and organs within multicellular organisms, including plants, animals and humans, these cellular aggregates display derivative versions of aggregate tissue- and organ-specific sentience and consciousness. This innovative view of the evolution and physiology of all currently living organisms supports a singular principle: all organismal physiology is based on cellular physiology that extends from unicellular roots.

Self-Improvising Memory: A Perspective on Memories as Agential, Dynamically Reinterpreting Cognitive Glue

Many studies on memory emphasize the material substrate and mechanisms by which data can be stored and reliably read out. Here, I focus on complementary aspects: the need for agents to dynamically reinterpret and modify memories to suit their ever-changing selves and environment. Using examples from developmental biology, evolution, and synthetic bioengineering, in addition to neuroscience, I propose that a perspective on memory as preserving salience, not fidelity, is applicable to many phenomena on scales from cells to societies. Continuous commitment to creative, adaptive confabulation, from the molecular to the behavioral levels, is the answer to the persistence paradox as it applies to individuals and whole lineages. I also speculate that a substrate-independent, processual view of life and mind suggests that memories, as patterns in the excitable medium of cognitive systems, could be seen as active agents in the sense-making process. I explore a view of life as a diverse set of embodied perspectives-nested agents who interpret each other's and their own past messages and actions as best as they can (polycomputation). This synthesis suggests unifying symmetries across scales and disciplines, which is of relevance to research programs in Diverse Intelligence and the engineering of novel embodied minds.

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.

Collective intelligence: A unifying concept for integrating biology across scales and substrates

A defining feature of biology is the use of a multiscale architecture, ranging from molecular networks to cells, tissues, organs, whole bodies, and swarms. Crucially however, biology is not only nested structurally, but also functionally: each level is able to solve problems in distinct problem spaces, such as physiological, morphological, and behavioral state space. Percolating adaptive functionality from one level of competent subunits to a higher functional level of organization requires collective dynamics: multiple components must work together to achieve specific outcomes. Here we overview a number of biological examples at different scales which highlight the ability of cellular material to make decisions that implement cooperation toward specific homeodynamic endpoints, and implement collective intelligence by solving problems at the cell, tissue, and whole-organism levels. We explore the hypothesis that collective intelligence is not only the province of groups of animals, and that an important symmetry exists between the behavioral science of swarms and the competencies of cells and other biological systems at different scales. We then briefly outline the implications of this approach, and the possible impact of tools from the field of diverse intelligence for regenerative medicine and synthetic bioengineering.

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.

"Nociplastic Pain": A Challenge to Nosology and to Nociception

The construct of "nociplastic pain" has met with divergent receptions. On the one hand it has been enthusiastically embraced, to the extent of conflation with central sensitization of nociception and the International Classification of Diseases 11th Revision (ICD-11) entity of "primary" pain, and the promulgation of "nociplastic pain syndromes." On the other hand, it has been rejected by those whose skepticism derives from the absence, by definition, of underlying activation of nociceptors. This article seeks to dissect these divergent views and search for reconciliation between them. One line of argument is that "nociplastic" pain, "primary" pain, and "central sensitisation of nociception" reflect different domains of inquiry and should not be conflated. "Nociplastic" pain emerges as a hypothesis that confers clinical legitimacy and utility; while that hypothesis needs a minor but important modification and continues to require testing, discipline in its usage is necessary. The other line of argument discovers an unexpected impasse: the construct of "nociplastic pain" describes a phenomenon that accords with the International Association for the Study of Pain definition of pain but occurs in the absence of nociception-as-currently-defined, thus challenging the definitional link between pain and tissue damage. The article offers a resolution of this impasse by suggesting that nociception-as-currently-defined be replaced by the resurrected concept of a nociceptive apparatus, activation of which is necessary but not sufficient for the experience of pain. One consequence would be to allow the assertions underpinning "nociplastic" to be tested empirically; another would be to relate the phenomenon of pain to a more biologically plausible basis than "actual" or "resemblance to" tissue damage. PERSPECTIVE: This article explores the major challenges posed by "nociplastic pain" to nosology and to nociception. While discipline in the clinical use of the construct is required, it also emerges that the main issue is the International Association for the Study of Pain definition of nociception. A reconceptualization of nociception is proposed for logical, biological, and clinical coherence.

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.

Thoughts from the forest floor: a review of cognition in the slime mould Physarum polycephalum

Sensing, communication, navigation, decision-making, memory and learning are key components in a standard cognitive tool-kit that enhance an animal's ability to successfully survive and reproduce. However, these tools are not only useful for, or accessible to, animals-they evolved long ago in simpler organisms using mechanisms which may be either unique or widely conserved across diverse taxa. In this article, I review the recent research that demonstrates these key cognitive abilities in the plasmodial slime mould Physarum polycephalum, which has emerged as a model for non-animal cognition. I discuss the benefits and limitations of comparisons drawn between neural and non-neural systems, and the implications of common mechanisms across wide taxonomic divisions. I conclude by discussing future avenues of research that will draw the most benefit from a closer integration of Physarum and animal cognition research.

Active oscillations in microscale navigation

Living organisms routinely navigate their surroundings in search of better conditions, more food, or to avoid predators. Typically, animals do so by integrating sensory cues from the environment with their locomotor apparatuses. For single cells or small organisms that possess motility, fundamental physical constraints imposed by their small size have led to alternative navigation strategies that are specific to the microscopic world. Intriguingly, underlying these myriad exploratory behaviours or sensory functions is the onset of periodic activity at multiple scales, such as the undulations of cilia and flagella, the vibrations of hair cells, or the oscillatory shape modes of migrating neutrophils. Here, I explore oscillatory dynamics in basal microeukaryotes and hypothesize that these active oscillations play a critical role in enhancing the fidelity of adaptive sensorimotor integration.

Hierarchical network structure as the source of hierarchical dynamics (power-law frequency spectra) in living and non-living systems: How state-trait continua (body plans, personalities) emerge from first principles in biophysics

Living systems are hierarchical control systems that display a small world network structure. In such structures, many smaller clusters are nested within fewer larger ones, producing a fractal-like structure with a 'power-law' cluster size distribution (a mereology). Just like their structure, the dynamics of living systems shows fractal-like qualities: the timeseries of inner message passing and overt behavior contain high frequencies or 'states' (treble) that are nested within lower frequencies or 'traits' (bass), producing a power-law frequency spectrum that is known as a 'state-trait continuum' in the behavioral sciences. Here, we argue that the power-law dynamics of living systems results from their power-law network structure: organisms 'vertically encode' the deep spatiotemporal structure of their (anticipated) environments, to the effect that many small clusters near the base of the hierarchy produce high frequency signal changes and fewer larger clusters at its top produce ultra-low frequencies. Such ultra-low frequencies exert a tonic regulatory pressure that produces morphological as well as behavioral traits (i.e., body plans and personalities). Nested-modular structure causes higher frequencies to be embedded within lower frequencies, producing a power-law state-trait continuum. At the heart of such dynamics lies the need for efficient energy dissipation through networks of coupled oscillators, which also governs the dynamics of non-living systems (e.q., earthquakes, stock market fluctuations). Since hierarchical structure produces hierarchical dynamics, the development and collapse of hierarchical structure (e.g., during maturation and disease) should leave specific traces in system dynamics (shifts in lower frequencies, i.e. morphological and behavioral traits) that may serve as early warning signs to system failure. The applications of this idea range from (bio)physics and phylogenesis to ontogenesis and clinical medicine.

On being a Hydra with, and without, a nervous system: what do neurons add?

The small freshwater cnidarian Hydra has been the subject of scientific inquiry for over 300 years due to its remarkable regenerative capacities and apparent immortality. More recently, Hydra has been recognized as an excellent model system within neuroscience because of its small size, transparency, and simple nervous system, which allow high-resolution imaging of its entire nerve net while behaving. In less than a decade, studies of Hydra's nervous system have yielded insights into the activity of neural circuits in vivo unobtainable in most other animals. In addition to these unique attributes, there is yet another lesser-known feature of Hydra that makes it even more intriguing: it does not require its neural hardware to live. The extraordinary ability to survive the removal and replacement of its entire nervous system makes Hydra uniquely suited to address the question of what neurons add to an extant organism. Here, I will review what early work on nerve-free Hydra reveals about the potential role of the nervous system in these animals and point towards future directions for this work.

Chemical cognition: chemoconnectomics and convergent evolution of integrative systems in animals

Neurons underpin cognition in animals. However, the roots of animal cognition are elusive from both mechanistic and evolutionary standpoints. Two conceptual frameworks both highlight and promise to address these challenges. First, we discuss evidence that animal neural and other integrative systems evolved more than once (convergent evolution) within basal metazoan lineages, giving us unique experiments by Nature for future studies. The most remarkable examples are neural systems in ctenophores and neuroid-like systems in placozoans and sponges. Second, in addition to classical synaptic wiring, a chemical connectome mediated by hundreds of signal molecules operates in tandem with neurons and is the most information-rich source of emerging properties and adaptability. The major gap-dynamic, multifunctional chemical micro-environments in nervous systems-is not understood well. Thus, novel tools and information are needed to establish mechanistic links between orchestrated, yet cell-specific, volume transmission and behaviors. Uniting what we call chemoconnectomics and analyses of the cellular bases of behavior in basal metazoan lineages arguably would form the foundation for deciphering the origins and early evolution of elementary cognition and intelligence.

An evidence-based critical review of the mind-brain identity theory

In the philosophy of mind, neuroscience, and psychology, the causal relationship between phenomenal consciousness, mentation, and brain states has always been a matter of debate. On the one hand, material monism posits consciousness and mind as pure brain epiphenomena. One of its most stringent lines of reasoning relies on a 'loss-of-function lesion premise,' according to which, since brain lesions and neurochemical modifications lead to cognitive impairment and/or altered states of consciousness, there is no reason to doubt the mind-brain identity. On the other hand, dualism or idealism (in one form or another) regard consciousness and mind as something other than the sole product of cerebral activity pointing at the ineffable, undefinable, and seemingly unphysical nature of our subjective qualitative experiences and its related mental dimension. Here, several neuroscientific findings are reviewed that question the idea that posits phenomenal experience as an emergent property of brain activity, and argue that the premise of material monism is based on a logical correlation-causation fallacy. While these (mostly ignored) findings, if considered separately from each other, could, in principle, be recast into a physicalist paradigm, once viewed from an integral perspective, they substantiate equally well an ontology that posits mind and consciousness as a primal phenomenon.

Ownership psychology as a "cognitive cell" adaptation: A minimalist model of microbial goods theory

Microbes perfect social interactions with intuitive logics and goal-directed reciprocity. These multilevel, cognition-resembling adaptations in Dictyostelid cellular molds enable individual-to-group viability through public/private bacterial farming and dynamic marketspaces. Like humans and animals, Dictyostelid livestock-ownership depends on environmental sensing, cooperation, and competition. Moreover, social-norm policing of cosmopolitan colonies coordinates farmer decisions, phenotypes, and ownership identities with bacteria herding, privatization, and consumption.

Effect of monochromatic light on the behavior of the ctenophore Mnemiopsis leidyi (A. Agassiz, 1865)

Ctenophores are invertebrate, gelatinous predators that perform complex movements due to their numerous ciliary comb plates. We investigated the behavioral responses of the ctenophore Mnemiopsis leidyi A. Agassiz, 1865 to red, green, and blue lights of different powers and fluxes emitted by LEDs or lasers. White LEDs were used to mimic natural sunlight. When laser light was directed to the aboral organ, the animals tended to leave the illumination zone. The blue-light reaction was six times faster than the red-light reaction. The behavioral strategy of the animals changed significantly when their freedom of maneuvering was restricted. Typical locomotions were ranked according to the laser beam avoidance time from the beginning of exposure to going into darkness. The minimum reaction time was required for turning and moving the ctenophore, while moving along the laser beam and turning around required more time. Typical patterns of behavior of M. leidyi in the light flux were established using cluster analysis. Three preferential behavioral strategies were identified for avoiding laser irradiation: 1) body rotation; 2) shifting sideways; and 3) movement with deviation from the beam. The elementary ability of ctenophores to make decisions in situative conditions has been demonstrated.

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.

Closing the loop on morphogenesis: a mathematical model of morphogenesis by closed-loop reaction-diffusion

Morphogenesis, the establishment and repair of emergent complex anatomy by groups of cells, is a fascinating and biomedically-relevant problem. One of its most fascinating aspects is that a developing embryo can reliably recover from disturbances, such as splitting into twins. While this reliability implies some type of goal-seeking error minimization over a morphogenic field, there are many gaps with respect to detailed, constructive models of such a process. A common way to achieve reliability is negative feedback, which requires characterizing the existing body shape to create an error signal-but measuring properties of a shape may not be simple. We show how cells communicating in a wave-like pattern could analyze properties of the current body shape. We then describe a closed-loop negative-feedback system for creating reaction-diffusion (RD) patterns with high reliability. Specifically, we use a wave to count the number of peaks in a RD pattern, letting us use a negative-feedback controller to create a pattern with N repetitions, where N can be altered over a wide range. Furthermore, the individual repetitions of the RD pattern can be easily stretched or shrunk under genetic control to create, e.g., some morphological features larger than others. This work contributes to the exciting effort of understanding design principles of morphological computation, which can be used to understand evolved developmental mechanisms, manipulate them in regenerative-medicine settings, or engineer novel synthetic morphology constructs with desired robust behavior.

Regulative development as a model for origin of life and artificial life studies

Using the formal framework of the Free Energy Principle, we show how generic thermodynamic requirements on bidirectional information exchange between a system and its environment can generate complexity. This leads to the emergence of hierarchical computational architectures in systems that operate sufficiently far from thermal equilibrium. In this setting, the environment of any system increases its ability to predict system behavior by "engineering" the system towards increased morphological complexity and hence larger-scale, more macroscopic behaviors. When seen in this light, regulative development becomes an environmentally-driven process in which "parts" are assembled to produce a system with predictable behavior. We suggest on this basis that life is thermodynamically favorable and that, when designing artificial living systems, human engineers are acting like a generic "environment".

The brain is not mental! coupling neuronal and immune cellular processing in human organisms

Significant efforts have been made in the past decades to understand how mental and cognitive processes are underpinned by neural mechanisms in the brain. This paper argues that a promising way forward in understanding the nature of human cognition is to zoom out from the prevailing picture focusing on its neural basis. It considers instead how neurons work in tandem with other type of cells (e.g., immune) to subserve biological self-organization and adaptive behavior of the human organism as a whole. We focus specifically on the immune cellular processing as key actor in complementing neuronal processing in achieving successful self-organization and adaptation of the human body in an ever-changing environment. We overview theoretical work and empirical evidence on "basal cognition" challenging the idea that only the neuronal cells in the brain have the exclusive ability to "learn" or "cognize." The focus on cellular rather than neural, brain processing underscores the idea that flexible responses to fluctuations in the environment require a carefully crafted orchestration of multiple cellular and bodily systems at multiple organizational levels of the biological organism. Hence cognition can be seen as a multiscale web of dynamic information processing distributed across a vast array of complex cellular (e.g., neuronal, immune, and others) and network systems, operating across the entire body, and not just in the brain. Ultimately, this paper builds up toward the radical claim that cognition should not be confined to one system alone, namely, the neural system in the brain, no matter how sophisticated the latter notoriously is.

Cellular signaling pathways as plastic, proto-cognitive systems: Implications for biomedicine

Many aspects of health and disease are modeled using the abstraction of a "pathway"-a set of protein or other subcellular activities with specified functional linkages between them. This metaphor is a paradigmatic case of a deterministic, mechanistic framework that focuses biomedical intervention strategies on altering the members of this network or the up-/down-regulation links between them-rewiring the molecular hardware. However, protein pathways and transcriptional networks exhibit interesting and unexpected capabilities such as trainability (memory) and information processing in a context-sensitive manner. Specifically, they may be amenable to manipulation via their history of stimuli (equivalent to experiences in behavioral science). If true, this would enable a new class of biomedical interventions that target aspects of the dynamic physiological "software" implemented by pathways and gene-regulatory networks. Here, we briefly review clinical and laboratory data that show how high-level cognitive inputs and mechanistic pathway modulation interact to determine outcomes in vivo. Further, we propose an expanded view of pathways from the perspective of basal cognition and argue that a broader understanding of pathways and how they process contextual information across scales will catalyze progress in many areas of physiology and neurobiology. We argue that this fuller understanding of the functionality and tractability of pathways must go beyond a focus on the mechanistic details of protein and drug structure to encompass their physiological history as well as their embedding within higher levels of organization in the organism, with numerous implications for data science addressing health and disease. Exploiting tools and concepts from behavioral and cognitive sciences to explore a proto-cognitive metaphor for the pathways underlying health and disease is more than a philosophical stance on biochemical processes; at stake is a new roadmap for overcoming the limitations of today's pharmacological strategies and for inferring future therapeutic interventions for a wide range of disease states.

The role of quantum mechanics in cognition based evolution

In 2021 I noted that in all information-based systems we understand, Cognition creates Code, which controls Chemical reactions. Known agents write software which controls hardware, and not the other way around. I proposed the same is true in all of biology. Though the textbook description of cause and effect in biology proposes the reverse, that Chemical reactions produce Code from which Cognition emerges, there are no examples in the literature demonstrating either step. A mathematical proof for the first step, cognition generating code, is based on Turing's halting problem. The second step, code controlling chemical reactions, is the role of the genetic code. Thus a central question in biology: What is the nature and source of cognition? In this paper I propose a relationship between biology and Quantum Mechanics (QM), hypothesizing that the same principle that enables an observer to collapse a wave function also grants biology its agency: the organism's ability to act on the world instead of merely being a passive recipient. Just as all living cells are cognitive (Shapiro 2021, 2007; McClintock 1984; Lyon 2015; Levin 2019, Pascal and Pross, 2022), I propose humans are quantum observers because we are made of cells and all cells are observers. This supports the century-old view that in QM, the observer does not merely record the event but plays a fundamental role in its outcome.The classical world is driven by laws, which are deductive; the quantum world is driven by choices, which are inductive. When the two are combined, they form the master feedback loop of perception and action for all biology. In this paper I apply basic definitions of induction, deduction and computation to known properties of QM to show that the organism altering itself (and its environment) is a whole shaping its parts. It is not merely parts comprising a whole. I propose that an observer collapsing the wave function is the physical mechanism for producing negentropy. The way forward in solving the information problem in biology is understanding the relationship between cognition and QM.

Cellular and Natural Viral Engineering in Cognition-Based Evolution

Neo-Darwinism conceptualizes evolution as the continuous succession of predominately random genetic variations disciplined by natural selection. In that frame, the primary interaction between cells and the virome is relegated to host-parasite dynamics governed by selective influences. Cognition-Based Evolution regards biological and evolutionary development as a reciprocating cognition-based informational interactome for the protection of self-referential cells. To sustain cellular homeorhesis, cognitive cells collaborate to assess the validity of ambiguous biological information. That collective interaction involves coordinate measurement, communication, and active deployment of resources as Natural Cellular Engineering. These coordinated activities drive multicellularity, biological development, and evolutionary change. The virome participates as the vital intercessory among the cellular domains to ensure their shared permanent perpetuation. The interactions between the virome and the cellular domains represent active virocellular cross-communications for the continual exchange of resources. Modular genetic transfers between viruses and cells carry bioactive potentials. Those exchanges are deployed as nonrandom flexible tools among the domains in their continuous confrontation with environmental stresses. This alternative framework fundamentally shifts our perspective on viral-cellular interactions, strengthening established principles of viral symbiogenesis. Pathogenesis can now be properly appraised as one expression of a range of outcomes between cells and viruses within a larger conceptual framework of Natural Viral Engineering as a co-engineering participant with cells. It is proposed that Natural Viral Engineering should be viewed as a co-existent facet of Natural Cellular Engineering within Cognition-Based Evolution.

Single-cell analysis of habituation in Stentor coeruleus

Although learning is often viewed as a unique feature of organisms with complex nervous systems, single-celled organisms also demonstrate basic forms of learning. The giant ciliate Stentor coeruleus responds to mechanical stimuli by contracting into a compact shape, presumably as a defense mechanism. When a Stentor cell is repeatedly stimulated at a constant level of force, it will learn to ignore that stimulus but will still respond to stronger stimuli. Prior studies of habituation in Stentor reported a graded response, suggesting that cells transition through a continuous range of response probabilities. By analyzing single cells using an automated apparatus to deliver calibrated stimuli, we find that habituation occurs via a single step-like switch in contraction probability within each cell, with the graded response in a population arising from the random distribution of switching times in individual cells. This step-like response allows Stentor behavior to be represented by a simple two-state model whose parameters can be estimated from experimental measurements. We find that transition rates depend on stimulus force and also on the time between stimuli. The ability to measure the behavior of the same cell to the same stimulus allowed us to quantify the functional heterogeneity among single cells. Together, our results suggest that the behavior of Stentor is governed by a two-state stochastic machine whose transition rates are sensitive to the time series properties of the input stimuli.

Cellular Competency during Development Alters Evolutionary Dynamics in an Artificial Embryogeny Model

Biological genotypes do not code directly for phenotypes; developmental physiology is the control layer that separates genomes from capacities ascertained by selection. A key aspect is cellular competency, since cells are not passive materials but descendants of unicellular organisms with complex context-sensitive behavioral capabilities. To probe the effects of different degrees of cellular competency on evolutionary dynamics, we used an evolutionary simulation in the context of minimal artificial embryogeny. Virtual embryos consisted of a single axis of positional information values provided by cells' 'structural genes', operated upon by an evolutionary cycle in which embryos' fitness was proportional to monotonicity of the axial gradient. Evolutionary dynamics were evaluated in two modes: hardwired development (genotype directly encodes phenotype), and a more realistic mode in which cells interact prior to evaluation by the fitness function ("regulative" development). We find that even minimal ability of cells with to improve their position in the embryo results in better performance of the evolutionary search. Crucially, we observed that increasing the behavioral competency masks the raw fitness encoded by structural genes, with selection favoring improvements to its developmental problem-solving capacities over improvements to its structural genome. This suggests the existence of a powerful ratchet mechanism: evolution progressively becomes locked in to improvements in the intelligence of its agential substrate, with reduced pressure on the structural genome. This kind of feedback loop in which evolution increasingly puts more effort into the developmental software than perfecting the hardware explains the very puzzling divergence of genome from anatomy in species like planaria. In addition, it identifies a possible driver for scaling intelligence over evolutionary time, and suggests strategies for engineering novel systems in silico and in bioengineering.

Mind the matter: Active matter, soft robotics, and the making of bio-inspired artificial intelligence

Philosophical and theoretical debates on the multiple realisability of the cognitive have historically influenced discussions of the possible systems capable of instantiating complex functions like memory, learning, goal-directedness, and decision-making. These debates have had the corollary of undermining, if not altogether neglecting, the materiality and corporeality of cognition-treating material, living processes as "hardware" problems that can be abstracted out and, in principle, implemented in a variety of materials-in particular on digital computers and in the form of state-of-the-art neural networks. In sum, the matter in se has been taken not to matter for cognition. However, in this paper, we argue that the materiality of cognition-and the living, self-organizing processes that it enables-requires a more detailed assessment when understanding the nature of cognition and recreating it in the field of embodied robotics. Or, in slogan form, that the matter matters for cognitive form and function. We pull from the fields of Active Matter Physics, Soft Robotics, and Basal Cognition literature to suggest that the imbrication between material and cognitive processes is closer than standard accounts of multiple realisability suggest. In light of this, we propose upgrading the notion of multiple realisability from the standard version-what we call 1.0-to a more nuanced conception 2.0 to better reflect the recent empirical advancements, while at the same time averting many of the problems that have been raised for it. These fields are actively reshaping the terrain in which we understand materiality and how it enables, mediates, and constrains cognition. We propose that taking the materiality of our embodied, precarious nature seriously furnishes an important research avenue for the development of embodied robots that autonomously value, engage, and interact with the environment in a goal-directed manner, in response to existential needs of survival, persistence, and, ultimately, reproduction. Thus, we argue that by placing further emphasis on the soft, active, and plastic nature of the materials that constitute cognitive embodiment, we can move further in the direction of autonomous embodied robots and Artificial Intelligence.

On the Chemical Origin of Biological Cognition

One of life's most striking characteristics is its mental dimension, one whose very existence within a material system has long been a deep scientific mystery. Given the current scientific view that life emerged from non-life, how was it possible for 'dead' matter to have taken on mental capabilities? In this Perspective we describe the existence of a recently discovered non-equilibrium state of matter, an energized dynamic kinetic state, and demonstrate how particular chemical systems once activated into that kinetic state could manifest rudimentary cognitive behavior. Thus, contrary to a common view that biology is not reducible to physics and chemistry, recent findings in both chemistry and biology suggest that life's mental state is an outcome of its physical state, and therefore may be explicable in physical/chemical terms. Such understanding offers added insight into the physico-chemical process by which life was able to emerge from non-life and the perennial 'what is life?' question. Most remarkably, it appears that Darwin, through his deep understanding of the evolutionary process, already sensed the existence of a connection between life's physical and mental states.

Ecological memory of prior nutrient exposure in the human gut microbiome

Many ecosystems have been shown to retain a memory of past conditions, which in turn affects how they respond to future stimuli. In microbial ecosystems, community disturbance has been associated with lasting impacts on microbiome structure. However, whether microbial communities alter their response to repeated stimulus remains incompletely understood. Using the human gut microbiome as a model, we show that bacterial communities retain an "ecological memory" of past carbohydrate exposures. Memory of the prebiotic inulin was encoded within a day of supplementation among a cohort of human study participants. Using in vitro gut microbial models, we demonstrated that the strength of ecological memory scales with nutrient dose and persists for days. We found evidence that memory is seeded by transcriptional changes among primary degraders of inulin within hours of nutrient exposure, and that subsequent changes in the activity and abundance of these taxa are sufficient to enhance overall community nutrient metabolism. We also observed that ecological memory of one carbohydrate species impacts microbiome response to other carbohydrates, and that an individual's habitual exposure to dietary fiber was associated with their gut microbiome's efficiency at digesting inulin. Together, these findings suggest that the human gut microbiome's metabolic potential reflects dietary exposures over preceding days and changes within hours of exposure to a novel nutrient. The dynamics of this ecological memory also highlight the potential for intra-individual microbiome variation to affect the design and interpretation of interventions involving the gut microbiome.

Novel prokaryotic system employing previously unknown nucleic acids-based receptors

The present study describes a previously unknown universal system that orchestrates the interaction of bacteria with the environment, named the Teazeled receptor system (TR-system). The identical system was recently discovered within eukaryotes. The system includes DNA- and RNA-based molecules named "TezRs", that form receptor's network located outside the membrane, as well as reverse transcriptases and integrases. TR-system takes part in the control of all major aspects of bacterial behavior, such as intra cellular communication, growth, biofilm formation and dispersal, utilization of nutrients including xenobiotics, virulence, chemo- and magnetoreception, response to external factors (e.g., temperature, UV, light and gas content), mutation events, phage-host interaction, and DNA recombination activity. Additionally, it supervises the function of other receptor-mediated signaling pathways. Importantly, the TR-system is responsible for the formation and maintenance of cell memory to preceding cellular events, as well the ability to "forget" preceding events. Transcriptome and biochemical analysis revealed that the loss of different TezRs instigates significant alterations in gene expression and proteins synthesis.

Investigation of the bactericidal mechanism of Penicilazaphilone C on Escherichia coli based on 4D label-free quantitative proteomic analysis

There is an urgent need to find new antibiotics to fight against the increasing drug resistance of microorganisms. A novel natural compound, Penicilazaphilone C (PAC), was isolated from a marine-derived fungus. It has displayed broad bactericidal activities against Gram-negative and Gram-positive bacteria. However, its bactericidal mechanism is still unknown. Herein, time-kill assays verified that PAC is a fast and efficient bactericidal agent. Furthermore, data from 4D label-free quantitative proteome assays revealed that PAC significantly influences over 898 proteins in Escherichia coli. Combining the results of biofilm formation, β-galactosidase measurement, TEM observation, soft agar plate swimming, reactive oxygen species measurement, qRT-PCR, and west-blotting, the mode of PAC action against E. coli was to block respiration, inhibit assimilatory nitrate reduction and dissimilar sulfur reduction, facilitate assimilatory sulfate reduction, suppress cysteine and methionine biosynthesis, down-regulate antioxidant protein expression and induced intracellular ROS accumulation, weaken bacterial chemotaxis, destroy flagellar assembly, etc., and finally cause the bacteria's death. Our findings suggest that PAC could have a multi-target regulatory effect on E. coli and could be used as a new antibiotic in medicine.

Endless forms most beautiful 2.0: teleonomy and the bioengineering of chimaeric and synthetic organisms

The rich variety of biological forms and behaviours results from one evolutionary history on Earth, via frozen accidents and selection in specific environments. This ubiquitous baggage in natural, familiar model species obscures the plasticity and swarm intelligence of cellular collectives. Significant gaps exist in our understanding of the origin of anatomical novelty, of the relationship between genome and form, and of strategies for control of large-scale structure and function in regenerative medicine and bioengineering. Analysis of living forms that have never existed before is necessary to reveal deep design principles of life as it can be. We briefly review existing examples of chimaeras, cyborgs, hybrots and other beings along the spectrum containing evolved and designed systems. To drive experimental progress in multicellular synthetic morphology, we propose teleonomic (goal-seeking, problem-solving) behaviour in diverse problem spaces as a powerful invariant across possible beings regardless of composition or origin. Cybernetic perspectives on chimaeric morphogenesis erase artificial distinctions established by past limitations of technology and imagination. We suggest that a multi-scale competency architecture facilitates evolution of robust problem-solving, living machines. Creation and analysis of novel living forms will be an essential testbed for the emerging field of diverse intelligence, with numerous implications across regenerative medicine, robotics and ethics.

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.

Neurons as hierarchies of quantum reference frames

Conceptual and mathematical models of neurons have lagged behind empirical understanding for decades. Here we extend previous work in modeling biological systems with fully scale-independent quantum information-theoretic tools to develop a uniform, scalable representation of synapses, dendritic and axonal processes, neurons, and local networks of neurons. In this representation, hierarchies of quantum reference frames act as hierarchical active-inference systems. The resulting model enables specific predictions of correlations between synaptic activity, dendritic remodeling, and trophic reward. We summarize how the model may be generalized to nonneural cells and tissues in developmental and regenerative contexts.

Biology, Buddhism, and AI: Care as the Driver of Intelligence

Intelligence is a central feature of human beings' primary and interpersonal experience. Understanding how intelligence originated and scaled during evolution is a key challenge for modern biology. Some of the most important approaches to understanding intelligence are the ongoing efforts to build new intelligences in computer science (AI) and bioengineering. However, progress has been stymied by a lack of multidisciplinary consensus on what is central about intelligence regardless of the details of its material composition or origin (evolved vs. engineered). We show that Buddhist concepts offer a unique perspective and facilitate a consilience of biology, cognitive science, and computer science toward understanding intelligence in truly diverse embodiments. In coming decades, chimeric and bioengineering technologies will produce a wide variety of novel beings that look nothing like familiar natural life forms; how shall we gauge their moral responsibility and our own moral obligations toward them, without the familiar touchstones of standard evolved forms as comparison? Such decisions cannot be based on what the agent is made of or how much design vs. natural evolution was involved in their origin. We propose that the scope of our potential relationship with, and so also our moral duty toward, any being can be considered in the light of Care-a robust, practical, and dynamic lynchpin that formalizes the concepts of goal-directedness, stress, and the scaling of intelligence; it provides a rubric that, unlike other current concepts, is likely to not only survive but thrive in the coming advances of AI and bioengineering. We review relevant concepts in basal cognition and Buddhist thought, focusing on the size of an agent's goal space (its cognitive light cone) as an invariant that tightly links intelligence and compassion. Implications range across interpersonal psychology, regenerative medicine, and machine learning. The Bodhisattva's vow ("for the sake of all sentient life, I shall achieve awakening") is a practical design principle for advancing intelligence in our novel creations and in ourselves.

Vitalism and cognition in a conscious universe

According to the current scientific paradigm, what we call ‘life’, ‘mind’, and ‘consciousness’ are considered epiphenomenal occurrences, or emergent properties or functions of matter and energy. Science does not associate these with an inherent and distinct existence beyond a materialistic/energetic conception. ‘Life’ is a word pointing at cellular and multicellular processes forming organisms capable of specific functions and skills. ‘Mind’ is a cognitive ability emerging from a matrix of complex interactions of neuronal processes, while ‘consciousness’ is an even more elusive concept, deemed a subjective epiphenomenon of brain activity. Historically, however, this has not always been the case, even in the scientific and academic context. Several prominent figures took vitalism seriously, while some schools of Western philosophical idealism and Eastern traditions promoted conceptions in which reality is reducible to mind or consciousness rather than matter. We will argue that current biological sciences did not falsify these alternative paradigms and that some forms of vitalism could be linked to some forms of idealism if we posit life and cognition as two distinct aspects of consciousness preeminent over matter. However, we will not argue in favor of vitalistic and idealistic conceptions. Rather, contrary to a physicalist doctrine, these were and remain coherent worldviews and cannot be ruled out by modern science.

Probabilistic Inference with Polymerizing Biochemical Circuits

Probabilistic inference-the process of estimating the values of unobserved variables in probabilistic models-has been used to describe various cognitive phenomena related to learning and memory. While the study of biological realizations of inference has focused on animal nervous systems, single-celled organisms also show complex and potentially "predictive" behaviors in changing environments. Yet, it is unclear how the biochemical machinery found in cells might perform inference. Here, we show how inference in a simple Markov model can be approximately realized, in real-time, using polymerizing biochemical circuits. Our approach relies on assembling linear polymers that record the history of environmental changes, where the polymerization process produces molecular complexes that reflect posterior probabilities. We discuss the implications of realizing inference using biochemistry, and the potential of polymerization as a form of biological information-processing.

Naturalising Agent Causation

The idea of agent causation—that a system such as a living organism can be a cause of things in the world—is often seen as mysterious and deemed to be at odds with the physicalist thesis that is now commonly embraced in science and philosophy. Instead, the causal power of organisms is attributed to mechanistic components within the system or derived from the causal activity at the lowest level of physical description. In either case, the ‘agent’ itself (i.e., the system as a whole) is left out of the picture entirely, and agent causation is explained away. We argue that this is not the right way to think about causation in biology or in systems more generally. We present a framework of eight criteria that we argue, collectively, describe a system that overcomes the challenges concerning agent causality in an entirely naturalistic and non-mysterious way. They are: (1) thermodynamic autonomy, (2) persistence, (3) endogenous activity, (4) holistic integration, (5) low-level indeterminacy, (6) multiple realisability, (7) historicity, (8) agent-level normativity. Each criterion is taken to be dimensional rather than categorical, and thus we conclude with a short discussion on how researchers working on quantifying agency may use this multidimensional framework to situate and guide their research.

Biological computation: hearts and flytraps

The original computers were people using algorithms to get mathematical results such as rocket trajectories. After the invention of the digital computer, brains have been widely understood through analogies with computers and now artificial neural networks, which have strengths and drawbacks. We define and examine a new kind of computation better adapted to biological systems, called biological computation, a natural adaptation of mechanistic physical computation. Nervous systems are of course biological computers, and we focus on some edge cases of biological computing, hearts and flytraps. The heart has about the computing power of a slug, and much of its computing happens outside of its forty thousand neurons. The flytrap has about the computing power of a lobster ganglion. This account advances fundamental debates in neuroscience by illustrating ways that classical computability theory can miss complexities of biology. By this reframing of computation, we make way for resolving the disconnect between human and machine learning.

Predictive Neuronal Adaptation as a Basis for Consciousness

Being able to correctly predict the future and to adjust own actions accordingly can offer a great survival advantage. In fact, this could be the main reason why brains evolved. Consciousness, the most mysterious feature of brain activity, also seems to be related to predicting the future and detecting surprise: a mismatch between actual and predicted situation. Similarly at a single neuron level, predicting future activity and adapting synaptic inputs accordingly was shown to be the best strategy to maximize the metabolic energy for a neuron. Following on these ideas, here we examined if surprise minimization by single neurons could be a basis for consciousness. First, we showed in simulations that as a neural network learns a new task, then the surprise within neurons (defined as the difference between actual and expected activity) changes similarly to the consciousness of skills in humans. Moreover, implementing adaptation of neuronal activity to minimize surprise at fast time scales (tens of milliseconds) resulted in improved network performance. This improvement is likely because adapting activity based on the internal predictive model allows each neuron to make a more "educated" response to stimuli. Based on those results, we propose that the neuronal predictive adaptation to minimize surprise could be a basic building block of conscious processing. Such adaptation allows neurons to exchange information about own predictions and thus to build more complex predictive models. To be precise, we provide an equation to quantify consciousness as the amount of surprise minus the size of the adaptation error. Since neuronal adaptation can be studied experimentally, this can allow testing directly our hypothesis. Specifically, we postulate that any substance affecting neuronal adaptation will also affect consciousness. Interestingly, our predictive adaptation hypothesis is consistent with multiple ideas presented previously in diverse theories of consciousness, such as global workspace theory, integrated information, attention schema theory, and predictive processing framework. In summary, we present a theoretical, computational, and experimental support for the hypothesis that neuronal adaptation is a possible biological mechanism of conscious processing, and we discuss how this could provide a step toward a unified theory of consciousness.