Principles of Minimal Cognition: Casting Cognition as Sensorimotor Coordination

The cognitive cell: bacterial behavior reconsidered

Research on how bacteria adapt to changing environments underlies the contemporary biological understanding of signal transduction, and signal transduction provides the foundation of the information-processing approach that is the hallmark of the ‘cognitive revolution,’ which began in the mid-20th century. Yet cognitive scientists largely remain oblivious to research into microbial behavior that might provide insights into problems in their own domains, while microbiologists seem equally unaware of the potential importance of their work to understanding cognitive capacities in multicellular organisms, including vertebrates. Evidence in bacteria for capacities encompassed by the concept of cognition is reviewed. Parallels exist not only at the heuristic level of functional analogue, but also at the level of molecular mechanism, evolution and ecology, which is where fruitful cross-fertilization among disciplines might be found.

E. coli chemotaxis: the baffling intelligence of a single cell

I want to tell the story of a beautiful phenomenon in biology. In some sense it’s the prototype of much of the activity of life. The phenomenon is the way in which an individual cell of E. coli forages for nutrients. This process, known as “chemotaxis”—the “chemo-” for chemical and the “taxis” from the Greek τάξις, for tactics—is intelligence in one of its most elemental forms. An individual E. coli has no brain, obviously, and is even many orders of magnitude simpler than a human cell, and yet already it possesses something like a sense of smell, drive, even a memory. Chemotaxis recasts E. coli not as some aimless gut-pest but rather as an exquisitely sophisticated physical computer.

Cognition without brains? Learning and memory in microorganisms

Memory and learning are cognitive abilities typically associated with animals that possess a complex nervous system. Interestingly, recent studies suggest that microorganisms might also display learning-like behaviours. However, a factor limiting progress in this field is the lack of shared, microbe-specific frameworks that allow microbiologists to easily compare discoveries with concepts developed in cognitive sciences. In this review, we aim to bridge this gap by providing a conceptual overview of the definitional requirements for memory and learning to classify microbial behaviours and capabilities. Additionally, we identify and address problems that cause conceptual ambiguity in the microbial cognition literature, thereby facilitating more productive debates on the topic. Finally, we provide a novel perspective on how microbes might ‘learn’ from each other.

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

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

All living cells are cognitive

All living cells sense and respond to changes in external or internal conditions. Without that cognitive capacity, they could not obtain nutrition essential for growth, survive inevitable ecological changes, or correct accidents in the complex processes of reproduction. Wherever examined, even the smallest living cells (prokaryotes) display sophisticated regulatory networks establishing appropriate adaptations to stress conditions that maximize the probability of survival. Supposedly "simple" prokaryotic organisms also display remarkable capabilities for intercellular signalling and multicellular coordination. These observations indicate that all living cells are cognitive.

Functional Information: Towards Synthesis of Biosemiotics and Cybernetics

Biosemiotics and cybernetics are closely related, yet they are separated by the boundary between life and non-life: biosemiotics is focused on living organisms, whereas cybernetics is applied mostly to non-living artificial devices. However, both classes of systems are agents that perform functions necessary for reaching their goals. I propose to shift the focus of biosemiotics from living organisms to agents in general, which all belong to a pragmasphere or functional universe. Agents should be considered in the context of their hierarchy and origin because their semiosis can be inherited or induced by higher-level agents. To preserve and disseminate their functions, agents use functional information - a set of signs that encode and control their functions. It includes stable memory signs, transient messengers, and natural signs. The origin and evolution of functional information is discussed in terms of transitions between vegetative, animal, and social levels of semiosis, defined by Kull. Vegetative semiosis differs substantially from higher levels of semiosis, because signs are recognized and interpreted via direct code-based matching and are not associated with ideal representations of objects. Thus, I consider a separate classification of signs at the vegetative level that includes proto-icons, proto-indexes, and proto-symbols. Animal and social semiosis are based on classification, and modeling of objects, which represent the knowledge of agents about their body (Innenwelt) and environment (Umwelt).

The biogenic approach to cognition

After half a century of cognitive revolution we remain far from agreement about what cognition is and what cognition does. It was once thought that these questions could wait until the data were in. Today there is a mountain of data, but no way of making sense of it. The time for tackling the fundamental issues has arrived. The biogenic approach to cognition is introduced not as a solution but as a means of approaching the issues. The traditional, and still predominant, methodological stance in cognitive inquiry is what I call the anthropogenic approach: assume human cognition as the paradigm and work ‘down’ to a more general explanatory concept. The biogenic approach, on the other hand, starts with the facts of biology as the basis for theorizing and works ‘up’ to the human case by asking psychological questions as if they were biological questions. Biogenic explanations of cognition are currently clustered around two main frameworks for understanding biology: self-organizing complex systems and autopoiesis. The paper describes the frameworks and infers from them ten empirical principles—the biogenic ‘family traits’—that constitute constraints on biogenic theorizing. Because the anthropogenic approach to cognition is not constrained empirically to the same degree, I argue that the biogenic approach is superior for approaching a general theory of cognition as a natural phenomenon.

A theory of biological relativity: no privileged level of causation

Abstract. Must higher level biological processes always be derivable from lower level data and mechanisms, as assumed by the idea that an organism is compl

The sentient cell: the cellular foundations of consciousness

"All species, extant and extinct, from the simplest unicellular prokaryotes to humans, have an existential consciousness. Without sentience, the first cells that emerged some 4 billion years ago would have been evolutionary dead-ends, unable to survive in the chaotic, dangerous environment in which life first appeared and evolved. In this book, Arthur Reber's theory, the Cellular Basis of Consciousness (CBC), is outlined and distinguished from those models that argue that minds could be instantiated on artificial entities and those that maintain consciousness requires a nervous system. The CBC framework takes a novel approach to classic topics such as the origin-of-life, philosophy of mind, the role of genes, the impact of cognition, and how biological information is processed by all species. It also calls for a rethinking of a variety of issues including the moral implications of the sentient capacities of all species, how welfare concerns need to be expanded beyond where they currently are, and critically, how all life is intertwined in a coordinated cognitive ecology. The Sentient Cell explores this revolutionary model, which updates the standard neo-Darwinian framework within which current approaches operate and examines the underlying biomolecular features that are the likely candidates for the "invention" of consciousness and outline their role in cellular life." --

Learning Outside the Brain: Integrating Cognitive Science and Systems Biology

Learning is commonplace in organisms such as ourselves and even in organisms as far distant as the bee and the octopus. Such learning is implemented by brains, or neuronal networks, and has been extensively studied within ethology, psychology, cognitive science, and neuroscience. Whether learning also takes place in nonneuronal settings has remained a matter of sustained controversy, too often dominated by ideological views. In this survey, I will explain how learning can be rigorously interpreted as a form of information processing and then explore the evidence for whether learning also takes place in organismal contexts outside the brain, such as physiology, development, and individual cells. I will try to explain why it is important to build bridges in this way between cognitive science and systems biology, why concepts and methods from various branches of engineering may be helpful in this task, and what the eventual impact may be on how we think about the organism.

560 – Ecological Cognition II: Resonance

560 What the heck does the brain do in Ecological Dynamics, if it isn’t computing, processing, or representing? An introduction to the concept of Resonance.Download link

Holobiont

A holobiont is an assemblage of a host and the many other species living in or around it, which together form a discrete ecological unit through symbiosis, though there is controversy over this discreteness. The components of a holobiont are individual species or bionts, while the combined genome of all bionts is the hologenome. The holobiont concept was initially introduced by the German theoretical biologist Adolf Meyer-Abich in 1943, and then apparently independently by Dr. Lynn Margulis in her 1991 book Symbiosis as a Source of Evolutionary Innovation. The concept has evolved since the original formulations. Holobionts include the host, virome, microbiome, and any other organisms which contribute in some way to the functioning of the whole. Well-studied holobionts include reef-building corals and humans.

Lectures on Perception: An Ecological Perspective

Lectures on Perception: An Ecological Perspective addresses the generic principles by which each and every kind of life form—from single celled organisms (e.g., difflugia) to multi-celled organisms (e.g., primates)—perceives the circumstances of their living so that they can behave adaptively. It focuses on the fundamental ability that relates each and every organism to its surroundings, namely, the ability to perceive things in the sense of how to get about among them and what to do, or not

The Umwelt Representation Hypothesis: rethinking Universality

Recent studies reveal striking representational alignment between artificial neural networks (ANNs) and biological brains, leading to proposals that all sufficiently capable systems converge on universal representations of reality. We argue that this claim of Universality is premature. We introduce the Umwelt Representation Hypothesis, which proposes that alignment arises not from convergence toward a single global optimum but from overlap in the ecological constraints under which systems develop. We review empirical evidence showing that representational differences between species, individuals, and ANNs are systematic and adaptive, which is difficult to reconcile with Universality. Finally, we reframe ANN model comparison as a method for mapping clusters of alignment in the ecological constraint space rather than as a search for a single optimal world model.

EPISTEMIC STIGMERGY: NATURAL VS. ARTIFICIAL INTELLIGENCE

The article\(^{1}\) defends the thesis that intelligent behavior might require not internal complexity but complex interaction. This is demonstrated by the various forms of stigmergy that can be observed both in social insects and in humans. The exposition is structured as follows: (§0) explains how the term “intelligence” is interpreted in the following text; (§1) clarifies the relation between intelligence and complexity; (§2) shows that intelligent behavior does not require internal complexity; (§3) introduces the concept of stigmergy; (§4) presents the mechanisms that give rise to this phenomenon; (§5) distinguishes several types of stigmergic interaction; (§6) briefly discusses the evolutionary mechanisms that could have produced them; (§7) sketches the possible ways in which the concept of stigmergy is used outside biology; (§8) examines collaborative stigmergy in humans; (§9) points to its epistemic projections; (§10) outlines some conclusions concerning the role of artificial intelligence systems and their place in human society.

Our Eukaryotic Moment

Counterprogramming premature ontological closure in conceptualizing AI