The nature of cognition is being re-considered. Instead of emphasizing formal operations on abstract symbols, the new approach foregrounds the fact that cognition is, rather, a situated activity, and suggests that thinking beings ought therefore be considered first and foremost as acting beings. The essay reviews recent work in Embodied Cognition, provides a concise guide to its principles, attitudes and goals, and identifies the physical grounding project as its central research focus.

Open peer commentary on the article “A Computational Constructivist Model as an Anticipatory Learning Mechanism for Coupled Agent–Environment Systems” by Filipo Studzinski Perotto. Upshot: The schema system presented in the target article suffers from problems that had been acknowledged more than ten years ago. The main point is that our world is neither deterministic nor symbolic. Sensory as well as motor noise is ubiquitous in our environment. Symbols do not exist a priori but need to be grounded within our continuous world. In conclusion, I suggest that research on schema-learning systems should tackle small but real-world, continuous, and noisy problem domains.

The work of physicist and theoretical biologist Howard Pattee has focused on the roles that symbols and dynamics play in biological systems. Symbols, as discrete functional switching-states, are seen at the heart of all biological systems in the form of genetic codes, and at the core of all neural systems in the form of informational mechanisms that switch behavior. They also appear in one form or another in all epistemic systems, from informational processes embedded in primitive organisms to individual human beings to public scientific models. Over its course, Pattee’s work has explored (1) the physical basis of informational functions (dynamical vs. rule-based descriptions, switching mechanisms, memory, symbols), (2) the functional organization of the observer (measurement, computation), (3) the means by which information can be embedded in biological organisms for purposes of self-construction and representation (as codes, modeling relations, memory, symbols), and (4) the processes by which new structures and functions can emerge over time. We discuss how these concepts can be applied to a high-level understanding of the brain. Biological organisms constantly reproduce themselves as well as their relations with their environs. The brain similarly can be seen as a self-producing, self-regenerating neural signaling system and as an adaptive informational system that interacts with its surrounds in order to steer behavior.

Key words: Adaptive systems, biological cybernetics, biological semiotics, dynamical systems, emergence, epistemology, evolutionary robotics, genetic code, neural code, neurocomputation, self-organization, symbols.

Purpose: The purpose of this paper is to outline an integrative, high-level, neurocomputational theory of brain function based on temporal codes, neural timing nets, and active regeneration of temporal patterns of spikes within recurrent neural circuits that provides a time-domain alternative to connectionist approaches. Design/methodology/approach – This conceptual-theoretical paper draws from cybernetics, theoretical biology, neurophysiology, integrative and computational neuroscience, psychology, and consciousness studies. Findings: The high-level functional organization of the brain involves adaptive cybernetic, goal-seeking, switching, and steering mechanisms embedded in percept-action-environment loops. The cerebral cortex is conceived as a network of reciprocally connected, re-entrant loops within which circulate neuronal signals that build up, decay, and/or actively regenerate. The basic signals themselves are temporal patterns of spikes (temporal codes), held in the spike correlation mass-statistics of both local and global neuronal ensembles. Complex temporal codes afford multidimensional vectorial representations, multiplexing of multiple signals in spike trains, broadcast strategies of neural coordination, and mutually reinforcing, autopoiesis-like dynamics. Our working hypothesis is that complex temporal codes form multidimensional vectorial representations that interact with each other such that a few basic processes and operations may account for the vast majority of both lowand high-level neural informational functions. These operational primitives include mutual amplification/inhibition of temporal pattern vectors, extraction of common signal dimensions, formation of neural assemblies that generate new temporal pattern primitive “tags” from meaningful, recurring combinations of features (perceptual symbols), active regeneration of temporal patterns, content-addressable temporal pattern memory, and long-term storage and retrieval of temporal patterns via a common synaptic and/or molecular mechanism. The result is a relatively simplified, signal-centric view of the brain that utilizes universal coding schemes and pattern-resonance processing operations. In neurophenomenal terms, waking consciousness requires regeneration and build up of temporal pattern signals in global loops, whose form determines the contents of conscious experience at any moment. Practical implications: Understanding how brains work as informational engines has manifold long-reaching practical implications for design of autonomous, adaptive robotic systems. By proposing how new concepts might arise in brains, the theory bears potential implications for constructivist theories of mind, i.e. how observer-actors interacting with one another can self-organize and complexify. Originality/value – The theory is highly original and heterodox in its neural coding and neurocomputational assumptions. By providing a possible alternative to standard connectionist theory of brain function, it expands the scope of thinking about how brains might work as informational systems.

Key words: Cognition, consciousness, neural nets, cybernetics, autopoiesis, brain.

Excerpt: Is the mind contained (always? sometimes? never?) in the head? Or does the notion of thought allow mental processes (including believings) to inhere in extended systems of body, brain, and aspects of the local environment? The answer, we claimed, was that mental states, including states of believing, could be grounded in physical traces that remained firmly outside the head. As long as a few simple conditions were met (more on which below), Leonard’s notes and tattoos could indeed count as new additions to his store of long-term knowledge and dispositional belief. In the present treatment I revisit this argument, defending our strong conclusion against a variety of subsequent observations and objections. In particular, I look at objections that rely on a contrast between the (putatively) intrinsic content of neural symbols and the merely derived content of external inscriptions, at objections concerning the demarcation of scientifific domains via natural kinds, and at objections concerning the ultimate locus of agentive control and the nature of perception versus introspection.

In this chapter, I focus on one of the aspects of constructivist theory that Glasersfeld (Ch. 1) identifies as in need of further development. This aspect of the theory involves locating students’ mathematical development in social and cultural context while simultaneously treating learning as a process of adaptive reorganization. In addressing this issue, I illustrate the approach that I and my colleagues currently take when accounting for the process of students’ mathematical learning as it occurs in the social context of the classroom. In the opening section of the chapter, I clarify why this is a significant issue for us as mathematics educators. I then outline my general theoretical orientation by discussing Glasersfeld’s constructivism and Bauersfeld’s interactionism. Against this background, I develop criteria for classroom analyses that are relevant to our interests as researchers who develop learning environments for students in collaboration with teachers. Next, I illustrate the interpretive framework that I and my colleagues currently use by presenting a sample classroom analysis. Finally, in the concluding sections of the chapter, I reflect on the sample analysis to address four more general issues. These concern the contributions of analyses of the type outlined in the illustrative example, the relationship between instructional design and classroom-based research, the role of symbols and other tools in mathematical learning, and the relation between individual students’ mathematical activity and communal classroom processes.

Taking a unified view of life, language, and cognition, the Special Issue contests linguistic (or enactivist) models that grant “reality” to symbolic entities. Rather than focus on texts, utterances, or communication, language is traced to living in the extended human ecology. On a distributed view, languaging arises as, alone or together, people act while orienting to denotata and (physical) wordings. Languaging requires, not linguistic bodies, but skills based in common ways of understanding. While verbal entities are of immense value, they draw on a history of reflecting on languaging from a language stance; people need only imagine “symbols.” Accordingly, languaging is part of acting, observing and imagining. Using a language stance suffices for reflecting on human practices and written marks as if linguistic entities were “real.” The deflationary view extends to semiotics. As Ho and Li (2019) document, languaging-and-action enables a learner to grasp a Chinese character as a sign. While, in principle, semiosis might draw from physics or life, signs are also likely to derive from human practice. Coming to read Chinese may require not a semiotic ontology, but a human ability to self-fabricate new powers. By deflating linguistic models one can avoid appeal to observer-independent signs.

Key words: distributed cognition, distributed language, enactivism, language use, semiotics, understanding.

This paper reviews Pattee’s ideas about the symbolic domain as a phenomenon related to the self-simplifying processes of certain hierarchical systems, such as the living. We distinguish the concepts of constraint, record, and symbol to explain how the Semantic Closure Principle, that is to say, the view that symbols are self-interpreted by the cell, emerges. Related to this, the notion of complementarity is discussed both as an epistemological and as an ontological principle. In the final discussion we consider whether autonomous systems can exist in which constraints are not symbolically preserved, and if biological symbols can be considered to have a descriptive nature.

Key words: Constraint, record, semantic closure, symbol

Excerpt: The following is an attempt to establish clues for the understanding of potentialities and limits of symbolization through the understanding of variety and constraints in the maker and user of symbols and in his environment.

Excerpt: A theoretical clarification of terms in the area of numerical competence has been lacking for quite some time. The ascendency of formalism in mathematics during the last half century, which propagated the notion that if learns to manipulate the symbols the concepts will look after themselves (Hilbert 1899; Peano 1894; Whitehead & Russell 1927), was of little help, not only in education but also in number-oriented studies with animals. When researchers use terms such as number and counting, with all their ordinary-language ambiguities, it is not surprising that claims as well as theories turn out to be incompatible with one another. Davis & Perusse’s (D & P’s) target article does a welcome sorting job and, although there will certainly be dissidents, it prepares the ground for productive communication. My comments, therefore, should be taken as an attempt at expansion rather than disagreement.