The modern conception of enactive cognition is under discussion from the standpoint concerning the notions of nonlinear dynamics and synergetics. The contribution of Francisco Varela and his precursors is considered. It is shown that the perceptual and mental processes are bound up with the “architecture” of human body and nonlinear and circular connecting links between the subject of cognition and the world constructed by him can be metaphorically called a nonlinear cobweb of cognition. (...) class='Hi'>Cognition is an autopoietic activity because it is directed to the search of elements that are missed; it serves to completing integral structures. (shrink)

Although one can endorse the complexity of the data and processes that Phillips & Singer (P&S) review, their mathematical suggestions can be compared critically with cases in nonlinear psychophysics, where the theoretician is faced with analogous problems. Owing to P&S's failure adequately to recognise both the intricate properties of nonlinear dynamics in networks and the constraints of metabolic demands on the temporal generation of patterns in biological nets their conclusions fail to meet the problems they properly address.

The dynamic approach to understanding of the human consciousness, its cognitive activities and cognitive architecture is one of the most promising approaches in the modern epistemology and cognitive science. The conception of embodied mind is under discussion in the light of nonlinear dynamics and of the idea co-evolution of complex systems developed by the Moscow scientific school. The cognitive architecture of the embodied mind is rather complex: data from senses and products of rational thinking, the verbal and the pictorial, (...) logic and intuition, the analytical and synthetic abilities of perception and of thinking, the local and the global, the analogue and the digital, the archaic and the post-modern are intertwined in it. In the process of cognition, co-evolution of embodied mind as an autopoietic system and its surroundings takes place. The perceptual and mental processes are bound up with the structure of human body. Nonlinear and circular connecting links between the subject of cognition and the world constructed by him can be metaphorically called a nonlinear cobweb of cognition. Cognition is an autopoietic activity because it is directed to the search of elements that are missed; it serves to completing integral structures. According to the theory of blow-up regimes in complex systems elaborated by Sergey P.Kudyumov and his followers, the idea of co-evolution is connected with the concept of tempoworlds. To co-evolve means to start to develop in one and the same tempoworld and to use the possibility – in case of a proper intergation into a whole structure – to accelerate the tempo of evolution. The cognitive activities of the human being can be considered as a movement (active walk) in landscapes of co-evolution when he cognizes and changes environment and is changed himself by the very activities. The similar conclusion can be drawn from Francisco Varela’s conception of enactive cognition. (shrink)

This volume focuses on the modeling of cognition, and brings together contributions from psychologists and researchers in the field of cognitive science.

Mechanistic frameworks of investigation and explanation dominate the cognitive, neural, and psychological sciences. In this dissertation, I argue that mechanistic frameworks cannot, in principle, explain some kinds of cognition. In its place, I argue that complexity science has methods and theories more appropriate for investigating and explaining some cognitive phenomena. -/- I begin with an examination of the term 'cognition.' I defend the idea that "cognition" has been a moving target of investigation in the relevant sciences. As (...) such it is not historically true that there has been a thoroughly entrenched and agreed upon conception of "cognition." Next, I take up mechanistic frameworks. Although 'mechanism' is an umbrella term for a set of loosely related characteristics, there are common features: linearity, localization, and component dominance. I then describe complexity science, with emphasis on its utilization of dynamical systems modeling. Next, I discuss two phenomena that typically fall under the purview of complexity science: nonlinearity and interaction dominance. -/- A complexity science framework guided by the theory of self-organized criticality and utilizing the methods of dynamical systems modeling can surmount a number of challenges that face mechanistic frameworks when investigating some kinds of cognition. The first challenge is epistemic and concerns the inadequacy of mechanistic frameworks to facilitate the comprehensibility of massive amounts of data across various scales and areas of inquiry. I argue that complexity science is more appropriate for making big data comprehensible when investigating cognition, particularly across disciplines. I demonstrate this via an approach called nested dynamical modeling (NDM). NDM can facilitate comprehensibility of large amounts of data obtained from various scales of investigation by eliminating irrelevant degrees of freedom of that system as relates to the target of investigation. -/- The second shortcoming concerns ontological blind spots within mechanistic frameworks. Cognitive phenomena like extended cognition often fail to meet most, if not all, of the criteria assumed by many mechanistic approaches, especially component dominance. I argue that research guided by the notion of interaction dominance allows for extended cognition to be a real, empirically supported phenomenon within complex systems frameworks. In this chapter I discuss some of my experimental work on extended cognitive systems. -/- The search for mechanisms can be a reasonable starting position when attempting to explain natural phenomena in the life sciences. However, too strict of an adherence to theoretical and methodological commitments such as linearity, localization, and component dominance can result in intractable epistemic challenges and ontological blind spots. Complexity science has theories and methods to overcome such challenges in the investigation of cognition. (shrink)

After more than 15 years of study, the 1/f noise or complex-systems approach to cognitive science has delivered promises of progress, colorful verbiage, and statistical analyses of phenomena whose relevance for cognition remains unclear. What the complex-systems approach has arguably failed to deliver are concrete insights about how people perceive, think, decide, and act. Without formal models that implement the proposed abstract concepts, the complex-systems approach to cognitive science runs the danger of becoming a philosophical exercise in futility. The (...) complex-systems approach can be informative and innovative, but only if it is implemented as a formal model that allows concrete prediction, falsification, and comparison against more traditional approaches. (shrink)

Complexity science is an investigative framework that stems from a number of tried and tested disciplines—including systems theory, nonlinear dynamical systems theory, and synergetics—and extends a common set of concepts, methods, and principles to understand how natural systems operate. By quantitatively employing concepts, such as emergence, nonlinearity, and self‐organization, complexity science offers a way to understand the structures and operations of natural cognitive systems in a manner that is conceptually compelling and mathematically rigorous. Thus, complexity science both transforms understandings (...) of cognition and reframes more traditional approaches. Consequently, if cognitive systems are indeed complex systems, then cognitive science ought to consider complexity science as a centerpiece of the discipline. (shrink)

Philosophical accounts of the constitution relation have been explicated in terms of synchronic relations between higher‐ and lower‐level entities. Such accounts, I argue, are temporally austere or impoverished, and are consequently unable to make sense of the diachronic and dynamic character of constitution in dynamical systems generally and dynamically extended cognitive processes in particular. In this paper, my target domain is extended cognition based on insights from nonlinear dynamics. Contrariwise to the mainstream literature in both analytical metaphysics and (...) extended cognition, I develop a nonstandard, alternative conception of constitution, which I call “diachronic process constitution”. It will be argued that only a diachronic and dynamical conception of constitution is consistent with the nature of constitution in distributed cognitive processes. (shrink)

A persistent criticism of radical embodied cognitive science is that it will be impossible to explain “real cognition” without invoking mental representations. This paper provides an account of explicit, real-time thinking of the kind we engage in when we imagine counter-factual situations, remember the past, and plan for the future. We first present a very general non-representational account of explicit thinking, based on pragmatist philosophy of science. We then present a more detailed instantiation of this general account drawing on (...) nonlinear dynamics and ecological psychology. (shrink)

Does a concurrent cognitive task affect the dynamics of bimanual rhythmic coordination? In‐phase coordination was performed under manipulations of phase detuning and movement frequency and either singly or in combination with an arithmetic task. Predicted direction‐specific shifts in stable relative phase from 0° due to detuning and movement frequency were amplified by the cognitive task. Nonlinear cross‐recurrence analysis suggested that this cognitive influence on the locations of the stable points or attractors of coordination entailed a magnification of attractor noise (...) without a reduction in attractor strength. An approximation to these findings was achieved through parameter changes in a motion equation in relative phase. Results are discussed in terms of dual‐task performance as limited resources, dynamics rather than chronometrics, and reparameterization rather than degradation. (shrink)

We analyze the dynamics of repeated interaction of two players in the Prisoner's Dilemma under various levels of interdependency information and propose an instance-based learning cognitive model to explain how cooperation emerges over time. Six hypotheses are tested regarding how a player accounts for an opponent's outcomes: the selfish hypothesis suggests ignoring information about the opponent and utilizing only the player's own outcomes; the extreme fairness hypothesis weighs the player's own and the opponent's outcomes equally; the moderate fairness hypothesis weighs (...) the opponent's outcomes less than the player's own outcomes to various extents; the linear increasing hypothesis increasingly weighs the opponent's outcomes at a constant rate with repeated interactions; the hyperbolic discounting hypothesis increasingly and nonlinearly weighs the opponent's outcomes over time; and the dynamic expectations hypothesis dynamically adjusts the weight a player gives to the opponent's outcomes, according to the gap between the expected and the actual outcomes in each interaction. When players lack explicit feedback about their opponent's choices and outcomes, results are consistent with the selfish hypothesis; however, when this information is made explicit, the best predictions result from the dynamic expectations hypothesis. (shrink)

Cognitive Science, Volume 45, Issue 11, November 2021.

Dynamical systems theory (DST) is a branch of mathematics that assesses abstract or physical systems that change over time. It has a quantitative part (mathematical equations) and a related qualitative part (plotting equations in a state space). Nonlinear dynamical systems theory applies the same tools in research involving phenomena such as chaos and hysteresis. These approaches have provided different ways of investigating and understanding cognitive systems in cognitive science and neuroscience. The ‘dynamical hypothesis’ claims that cognition is and (...) can be understood as dynamical systems. Common consequences for such an approach include rejecting understanding cognition as information processing in nature, including eschewing explanatory roles for computation or representation. Contemporary applications of DST include mouse‐tracking studies in cognitive science and nonrepresentational perspectives on motor control in neuroscience. Such work has philosophical implications concerning the boundaries of cognition, explanation, and representations. DST offers powerful methodology and theories that raise many topics of philosophical significance. (shrink)

Ever wonder if it is possible to construct a numeric scale for environmental variables, like one does for the temperature? This paper is an attempt to construct one. There are two main parts: section “Statistical Analysis of Variations” presents a general statistical strategy for environmental factor selection. Section “Nonlinear Analytical Geometric Model of Variations” develops an analytical geometric representation of system variations in response to environmental changes. The model is used to quantify the effects of environmental interactions. The paper (...) treats only one-dimensional case, however, the derivation of the case of multiple independent factors follows immediately. The general method developed in this paper may prove applicable to many different fields, such as extensions beyond classical physics, economics, and other sciences. Section “Conclusion” provides an illustration of applications, examples and implications of the results. (shrink)

Walter Freeman's theory of nonlinear neurodynamics has had a major impact on brain dynamics in modern cognitive neuroscience. Steven Bressler's theory of neurocognitive networks follows from Freeman's work, and his empirical evidence for the coordination of cortical areas by phase-coupled beta rhythms in large-scale cognitive brain networks supports Freeman's ideas on nonlinear brain dynamics. Bressler's work, taking Freeman's concepts into the realm of cognitive neurodynamics, also supports Scott Kelso's theory of metastability in coordination dynamics. The aims of the (...) present paper are threefold: 1) to explore relevant concepts in Freeman's theoretical framework, 2) unify it and provide empirical support for it, and 3) explore its import for the study of consciousness. We take as our point of departure Bressler and Kelso's 2016 publication on cortical coordination dynamics and the Freeman-Kelso dialogue noted in the literature on this topic. In our view, Freeman's conceptual framework has great explanatory power. Its grounding in a dynamical systems approach to the study of brain function, and its incorporation of embodiment, make it relevant to the study of consciousness. Thus, with Freeman, we argue that the scientific understanding of consciousness must move beyond notions of computationalism and mental representations, to employ concepts of nonlinear brain dynamics and embodiment. (shrink)

This study presents the results of an empirical analysis of the relationship between managerial thinking style and ethical decision-making. Data from 200 managers across multiple organizations and industries demonstrated that managers predominantly adopt a utilitarian perspective when forming ethical intent across a series of business ethics vignettes. Consistent with expectations, managers utilizing a balanced linear/nonlinear thinking style demonstrated a greater overall willingness to provide ethical decisions across ethics vignettes compared to managers with a predominantly linear thinking style. However, results (...) comparing the ethical decision-making of balanced thinking managers and nonlinear thinking managers were generally inconsistent across the ethics vignettes. Unexpectedly, managers utilizing a balanced linear/nonlinear thinking style were least likely to adopt an act utilitarian rationale for ethical decision-making across the vignettes, suggesting that balanced thinkers may be more likely to produce ethical decisions by considering a wider range of alternatives and ruling out those that are justified solely on the basis of their outcomes. Implications are discussed for future research and practice related to management education and development, and ethical decision-making theory. (shrink)

From his earliest work forward, phenomenologist Maurice Merleau-Ponty attempted to develop a new ontology of nature that would avoid the antinomies of realism and idealism by showing that nature has its own intrinsic sense which is prior to reflection. The key to this new ontology was the concept of form, which he appropriated from Gestalt psychology. However, Merleau-Ponty struggled to give a positive characterization of the phenomenon of form which would clarify its ontological status. Evan Thompson has recently taken up (...) Merleau-Ponty’s ontology as the basis for a new, “enactive” approach to cognitive science, synthesizing it with concepts from dynamic systems theory and Francisco Varela’s theory of autopoiesis. However, Thompson does not quite succeed in resolving the ambiguities in Merleau-Ponty’s account of form. This article builds on an indication from Thompson in order to propose a new account of form as asymmetry, and of the genesis of form in nature as symmetry-breaking. These concepts help us to escape the antinomies of Modern thought by showing how nature is the autoproduction of a sense which can only be known by an embodied perceiver. (shrink)

A fundamental problem in spoken language is the duality between the continuous aspects of phonetic performance and the discrete aspects of phonological competence. We study 2 instances of this problem from the phenomenon of voicing neutralization and vowel harmony. In each case, we present a model where the experimentally observed continuous distinctions are linked to the discreteness of phonological form using the mathematics of nonlinear dynamics.

This article argues that the process of development as such explains a great deal of the forms and properties of individual developmental trajectories, without the necessity of having to rely on either external or internal factors or causes. Both the problem of developmental change and invariance can be explained by employing a dynamic systems conceptualization of development. It is shown that dynamic systems models on the one hand and those of the genuine developmental models in psychology on the other, share (...) a set of important general properties that are able to explain both the universal and the idiosyncratic aspects of developmental processes. The concept of mental and behavioral ecology, which may serve as a starting point for specific theories of development of cognition, social behavior, personality and so forth, is discussed. It is concluded that both long-term and short-term developmental patterns will be shown to follow similar abstract dynamical principles. (shrink)

This paper presents a theory of algorithms designed to optimize highly interactive systems (multi-diminsional, multi-peak, nonlinear functions). Two applications are discussed: one concerns cognitive systems capable of learning and generalization, and one concerns calculations dealing with the "origin of life" from "organic soups". The algorithms are intrinsically parallel--each function argument processed serves as a carrier for information about a tremendous number of regions (hyperplanes) in the function's domain. Each region is automatically ranked according to the estimated average value of (...) the function over that region, and the rankings are compactly stored in the algorithm's data base (M l-tuples store approximately M-2 l/2 rankings). Thus, the algorithm implicitly processes hyperplanes by manipulating function arguments. (shrink)

By emphasizing nonlinear dynamics between appraisal and emotions, Lewis's model provides a valuable platform for integrating psychological and neural perspectives on the emotion-cognition interface. In this commentary, I discuss the role of neuroscience in shaping new conceptualizations of emotion and the putative role of theta oscillation within frontocingulate pathways in depression, a syndrome in which emotion-cognition relations are dysfunctional.

Typically, human decision making is emotionally and does not conform to classical probability (CP) theory. As quantum probability (QP) theory emphasises order, context, superimposition states, and nonlinear dynamic effects, one of its major strengths may be its power to unify formal modeling and realistic psychological theory (e.g., information uncertainty, anxiety, and indecision, as seen in the Prisoner's Dilemma).

In this paper, I question the notion that tool-use must be driven by an internal representation which specifies the “motor program” enacted in the behaviour of the tool-user. Rather, it makes more sense to define tool-use in terms of characteristics of the dynamics of this behaviour. As the behaviour needs to be adjusted to suit changes in context, so there is unlikely to be a one-to-one, linear mapping between an action and its effect. Thus, tool-use can best be described using (...) concepts from Nonlinear Dynamics. Such an approach can be used to create a sort of cybernetic model of tool-use. However, there is a danger that such a model can either lead us back to internal representations or could fail to capture cognitive aspects of behaviour. In particular, the question of how the craftworker’s intent can be enacted in the use of tools to produce a specific object seems to be lost in the cybernetic account. My solution is two-fold. First, the “model” is created on-the-fly and adapted through moment-by-moment interactions in the system of tool-user–tool–material–environment. This means that, rather than assuming a pre-defined internal representation that drives behaviour, I propose that cognition involves the selection of salient parameters that characterize the behaviour and the continued monitoring and management of behaviour in terms of these parameters. Second, intent is only loosely defined a priori but crystallizes through the continued interactions between craftworker and object through a process in which the affordances of the object become apparent to, and responded to by, the craftworker. (shrink)

We describe a way of modeling high‐dimensional data vectors by using an unsupervised, nonlinear, multilayer neural network in which the activity of each neuron‐like unit makes an additive contribution to a global energy score that indicates how surprised the network is by the data vector. The connection weights that determine how the activity of each unit depends on the activities in earlier layers are learned by minimizing the energy assigned to data vectors that are actually observed and maximizing the (...) energy assigned to “confabulations” that are generated by perturbing an observed data vector in a direction that decreases its energy under the current model. (shrink)

Most Chinese words are compounds formed through the combination of meaningful characters. Yet, due to compositional complexity, it is poorly understood how this combinatorial process affects the access to the whole‐word meaning. In the present study, we turned to the recent development in compositional distributional semantics, and employed a deep neural network to learn the less‐than‐systematic relationship between the constituent characters and the compound words. Based on the compositional representations derived from the computational model, we investigated the combinatorial process in (...) terms of the degree of overlap between the compositional and the lexicalized representations as well as the degree of distinctness of the compositional representation. Analyses of lexical decision and eye‐tracking data revealed the effects of both compositional attributes over and above the effects of constituent character features and compound features, indicating an active engagement of the combinatorial process in compound processing. Moreover, with the increase of compound frequency, and thus the increased likelihood that the holistic route prevails, these compositional effects appeared to be dampened. These findings, therefore, provided a computational characterization for the dual‐route framework, which sheds light on the universal process of compound comprehension across different languages. (shrink)

Concern over the nature of AI is, for the tastes many AI scientists, probably overdone. In this they are like all other scientists. Working scientists worry about experiments, data, and theories, not foundational issues such as what their work is really about or whether their discipline is methodologically healthy. However, most scientists aren’t in a field that is approximately fifty years old. Even relatively new fields such as nonlinear dynamics or branches of biochemistry are in fact advances in older (...) established sciences and are therefore much more settled. Of course, by stretching things, AI can be said to have a history reaching back t o Charles Babbage, and possibly back beyond that to Leibnitz. However, all of that is best viewed as prelude. AI’s history is punctuated with the invention of the computer (and, if one wants t o stretch our history back to the 1930s, the development of the notion of computation by Turing, Church, and others). Hence, AI really began (or began in earnest) sometime in the late 1940s or early 1950s (some mark the conference a t Dartmouth in the summer of 1957 as the moment of our birth). And since those years we simply have not had time to settle into a routine science attacking reasonably well understood questions (for example, many of the questions some of us regard as supreme are regarded by others as inconsequential or mere excursions). (shrink)

Tim van Gelder, following Brandom, Collins and others, uses the so‐called wide content of capacities which support social, norm governed activities, such as language, to argue for their anti‐natural, abstract, but socially instituted nature and thence for the failure of the entire traditional mind‐body discussion as ill‐posed. We argue that his former conclusion is wrong, that such properties are naturalisable, complicated organisational properties of the complexly organised, non‐linearly interactive systems that human beings are. This analysis also provides principled support, but (...) on other grounds, for van Gelder’s latter conclusion. We outline a new naturalist approach to the organisational capacities of such systems that is intended to ground their biological, cognitive and social characters. (shrink)

We review how leaky competing accumulators (LCAs) can be used to model decision making in two‐alternative, forced‐choice tasks, and we show how they reduce to drift diffusion (DD) processes in special cases. As continuum limits of the sequential probability ratio test, DD processes are optimal in producing decisions of specified accuracy in the shortest possible time. Furthermore, the DD model can be used to derive a speed–accuracy trade‐off that optimizes reward rate for a restricted class of two alternative forced‐choice decision (...) tasks. We review findings that compare human performance with this benchmark, and we reveal both approximations to and deviations from optimality. We then discuss three potential sources of deviations from optimality at the psychological level—avoidance of errors, poor time estimation, and minimization of the cost of control—and review recent theoretical and empirical findings that address these possibilities. We also discuss the role of cognitive control in changing environments and in modulating exploitation and exploration. Finally, we consider physiological factors in which nonlinear dynamics may also contribute to deviations from optimality. (shrink)

The phenomena of human consciousness and subjectivity are explored from the perspective of affect-logic, a comprehensive meta-theory of the interactions between emotion and cognition based mainly on cognitive and social psychology, psychopathology, neurobiology Piaget?s genetic epistemology, psychoanalysis, and evolutionary science. According to this theory, overt or covert affective-cognitive interactions are obligatorily present in all mental activity, seemingly ?neutral? thinking included. Emotions continually exert numerous so-called operator-effects, both linear and nonlinear, on attention, on memory and on comprehensive thought, or (...) logic in a broad sense. They deeply ?affect? also consciousness and subjectivity, as showed by the analysis of four crucially involved phenomena, namely (1) attention, (2) abstraction, (3) language, and (4) the prevailing affective state. The conclusion is that neither consciousness nor subjectiovity can be adequately understood without fully considering their emotional aspects. (shrink)

Although emotion is closely associated with motivation, and interacts with perception, cognition, and action, many conceptualizations still treat emotion as separate from these domains. Here, a comparative/evolutionary anatomy framework is presented to motivate the idea that long-range, distributed circuits involving the midbrain, thalamus, and forebrain are central to emotional processing. It is proposed that emotion can be understood in terms of large-scale network interactions spanning the neuroaxis that form “functionally integrated systems.” At the broadest level, the argument is made (...) that we need to move beyond a Newtonian view of causation to one involving complex systems where bidirectional influences and nonlinearities abound. Therefore, understanding interactions between subsystems and signal integration becomes central to unraveling the organization of the emotional brain. (shrink)

Modern cognitive approach represents the interdisciplinary branch of scientific reflection uniting researchers of knowledge, studying laws of purchase, transformation, representation, storages and reproduction of the information. People react to own experience, instead of "objective" reality. Cognitive map of the world according to which we operate, our feelings, belief and life experience create. We have no direct access to a "objective" reality, therefore our cognitive map is for us this unique "real" reality. Cognitive science widely uses methodology of synergetic approach successfully (...) describing processes of self‐organizing. On the other hand, the synergetic addresses to modelling cognitive systems both the separate individual and collective cognitive processes. Therefore there are bases tospeak about formation cognitive‐synergetic scientific program ‐ the approach which is under construction on principles of modern nonlinear thinking. (shrink)

Most philosophical accounts of emergence are based on supervenience, with supervenience being an ontologically synchronic relation of determination. This conception of emergence as a relation of supervenience, I will argue, is unable to make sense of the kinds of emergence that are widespread in self-organizing and nonlinear dynamical systems, including distributed cognitive systems. In these dynamical systems, an emergent property is ontological and diachronic.

Recognition of the plasticity of development — from gene expression to neuroplasticity — is increasingly undermining the traditional distinction between structure and function, or anatomy and behavior. At the same time, dynamic systems theory — a set of tools and concepts drawn from the physical sciences — has emerged as a way of describing what Maurice Merleau-Ponty calls the “dynamic anatomy” of the living organism. This article surveys and synthesizes dynamic systems models of development from biology, neuroscience, and psychology in (...) order to propose an integrated account of growth, learning, and behavior. Key to this account is the concept of self-differentiation or symmetry-breaking. I argue that development can be understood as a cascade of symmetry-breaking events brought about by the ongoing interactions of multiple, nested, nonlinear dynamic systems whose self-organizing behaviors gradually alter their own anatomical conditions. I begin by introducing the concept of symmetry-breaking as a way of understanding anatomical development. I then extend this approach to motor development by arguing that the organism’s behavior grows along with its body, like a new organ. Finally, I argue that the organism’s behavior and its world grow together dialectically, each driving the other to become more complex and asymmetrical through its own increasing asymmetry. Thus development turns out to be a form of cognition or sense-making, and cognition a form of development. (shrink)

The heuristic value of synergetic models of evolving and self-organizing complex systems as well as their application to epistemological problems is shown in this paper. Nonlinear synergetic models turn out to be fruitful in comprehending epistemological problems such as the nature of human creativity, the functioning of human intuition and imagination, the historical development of science and culture. In the light of synergetics creative thinking can be viewed as a selforganization and self-completion of images and thoughts, filling up gaps (...) in the nets of knowledge. Insight, fast and sudden solutions of scientific problems, instabilities when “an idea is in the air” are considered as examples of blow-up regimes in the cognitive field. (shrink)

From the perspective of nonlinear science, it is argued that one may accept physicalism and reject substance dualism without being forced into reductionism. This permits a property dualism under which biological and mental phenomena may emerge from intricate positive feedback networks, involving many levels of both the biological and cognitive hierarchies.

The target article developed a dynamic systems framework that viewed the causal basis of emotion as a self-organizing process giving rise to cognitive appraisal concurrently. Commentators on the article evaluated this framework and the principles and mechanisms it incorporated. They also suggested additional principles, mechanisms, modeling strategies, and phenomena related to emotion and appraisal, in place of or extending from those already proposed. There was general agreement that nonlinear causal processes are fundamental to the psychology and neurobiology of emotion.

Neurally inspired models of human cognition exude explanatory power without necessarily making predictions that can be verified behaviorally. This is the case for Tsuda's dynamic model. It is suggested that a simpler principle based on the nonlinear dynamic interaction between modules based on control of chaos, can achieve a similar theoretical goal in a cognitively verifiable way.

Through a close study of T. Yunkaporta's 2019’s Sand Talk, this article explores fractal thinking and the pattern of creation in Indigenous cosmology; the role of custodianship in respectful interaction between living systems; alternative Indigenous understandings of nonlinearity, time, and transience; the process-panpsychism and animism present in Indigenous perceptions of cosmos as living Country, illustrated in the Dreaming and Turnaround creation event; the role of embodied cognition and haptic and situated knowledge in Indigenous science; Indigenous holistic reasoning and the (...) mind-body connection; the process-relational metaphysic embedded in ritual and yarning practice; the knowledge encoded in place-based totemic mythology, lore, and ritual; and Indigenous understandings of complex systems as adaptive, self-organizing, and patterned. This article does not offer a process reading of Indigenous thought but rather demonstrates the significant contribution to process metaphysics that may be provided by an Aboriginal Australian perspective. Yunkaporta's text carves out a language of resistance to the McDonaldization of Indigenous research. While historic scholarly engagement with Aboriginal culture has overemphasized content, Yunkaporta demonstrates how this has occurred to the exclusion of the processes of Indigenous knowledge transmission and creation. Yet a process view requires engagement with the how, not only with the what. Such knowledge transmission is discerned in daily lived relationships among land, spirit, and people—binding epistemology to participation in a specific landscape embedded within a living culture. Place-making for Indigenous knowledges requires exploring how Indigenous ways of valuing, knowing, and being, shaped by cultural activities on Country, offer new understandings for Western metaphysics. (shrink)

The fateful combination of (i) the Dunning‐Kruger effect (ignorance of one's own ignorance) with (ii) the nonlinear dynamics of the echo‐chamber between reviewers and editors fuels a self‐reinforcing collective delusion system that sometimes spirals uncontrollably away from objectivity and truth. Escape from this subconscious meta‐ignorance is a formidable challenge but if achieved will help correct a central deficit of the peer‐review process that stifles innovation and paradigm shifts.

What is the core of the distinctiveness of Homo sapiens? Some of the most famous hypotheses include tool use and tool making, language, free will and moral agency, self-consciousness, mind itself, and reason or rational problem-solving. All these answers are partly true. But recent work in comparative psychology, primatology, and cognitive science have converged on a conception of human distinctiveness that underlies these. Remarkably, it was explored a century ago by George Herbert Mead. The American pragmatists played a special role (...) in the development of non-reductive naturalism. But among them, Mead uniquely endorsed the notion of “emergence” developed by the British Emergentists. This led him to an analysis of the emergence of the human self and mind out of social processes, most famously employing his concept of “significant gesture.” In recent decades both notions have been buttressed by philosophical and scientific work. Emergence has returned in the sciences of nonlinear dynamics and complexity, and has been re-conceptualized by philosophers like Wiliiam Wimsatt. Mead’s social conception of the human mind and self have been repurposed by a host of scientists, as in Michael Tomasello’s conception of “joint intentionality” and Antonio Damasio’s analysis of self-consciousness. These developments show that Mead was remarkably prescient in his core insights. (shrink)

As an imitation of the biological nervous systems, neural networks, which have been characterized as powerful learning tools, are employed in a wide range of applications, such as control of complex nonlinear systems, optimization, system identification, and patterns recognition. This article aims to bring a brief review of the state-of-the-art NNs for the complex nonlinear systems by summarizing recent progress of NNs in both theory and practical applications. Specifically, this survey also reviews a number of NN based robot (...) control algorithms, including NN based manipulator control, NN based human-robot interaction, and NN based cognitive control. (shrink)

A new theoretical model of oncogenesis that incorporates a systemic view of biodynamics was developed and analyzed. According to our model, the emergent behavior at the cell population level is the result of nonlinear interactions between the neoplastic and immune subsystems. Our approach allows subsequent extensions of the model to span multiple levels of biological organization. The model opens the possibility of a flexible connection between the molecular and tissue level descriptions of oncogenesis.

Neural complexity and brain entropy have gained greater interest in recent years. The dynamics of neural signals and their relations with information processing continue to be investigated through different measures in a variety of noteworthy studies. The BEN of spontaneous neural activity decreases during states of reduced consciousness. This evidence has been showed in primary consciousness states, such as psychedelic states, under the name of “the entropic brain hypothesis.” In this manuscript we propose an extension of this hypothesis to physiological (...) and pathological aging. We review this particular facet of the complexity of the brain, mentioning studies that have investigated BEN in primary consciousness states, and extending this view to the field of neuroaging with a focus on resting-state functional Magnetic Resonance Imaging. We first introduce historic and conceptual ideas about entropy and neural complexity, treating the mindbrain as a complex nonlinear dynamic adaptive system, in light of the free energy principle. Then, we review the studies in this field, analyzing the idea that the aim of the neurocognitive system is to maintain a dynamic state of balance between order and chaos, both in terms of dynamics of neural signals and functional connectivity. In our exploration we will review studies both on acute psychedelic states and more chronic psychotic states and traits, such as those in schizophrenia, in order to show the increase of entropy in those states. Then we extend our exploration to physiological and pathological aging, where BEN is reduced. Finally, we propose an interpretation of these results, defining a general trend of BEN in primary states and cognitive aging. (shrink)

The understanding of emergent, self-organizing phenomena has been immensely deepened in recent years on the basis of simulation-based theoretical research. We discuss these new ideas, and illustrate them using examples from several fields. Our discussion serves to introduce equivalent self-organized phenomena in social interaction. Interaction systems appear to be structured partly by virtue of such emergents. These appear under specific conditions: When cognitive buffering is inadequate relative to the levels of stress persons are subjected to, anxiety-spreading has the potential of (...) pushing their interaction into nonlinear conditions. Arousal in these conditions produces effects on behavior arising from biological sources-indeed, behavior can come under the control of reflex patterns. When this occurs, psychological activity no longer screens off biological controls over behavior. As the direct effects of biological activity spill into interaction, attachment behavior introduced into an interaction system can produce effects that are transmitted beyond dyads to produce global social patterns. These effects illustrate how strong interactions based in biological activity can produce an architecture for social systems. (shrink)

The article explores the unique, its essence and role in the development of types of rationality. The unique is explained as unrepeatable, which does not fit into the actual implemented reversibility, repeatability and cyclicality. This is a universal property that is inherent in the individual education and is expressed in the individual and unique elements, properties and relations. The purpose of the research is to reveal the unique as a scientific concept, apply it to the rationale for the processes of (...) changing types of rationality. The connection of the unique with a single, natural, indefinite, negation is revealed. Negation is presented as a form of thinking of a cognizing subject for the realities of scientific knowledge. Analysis of recent research and publications, initiated the solution of the problem of unique : use of the articles by authors G. Bashlyar, P. Burak, P. А. Vodopyanov, A. I. Zelenkov, V. H. Voronkova, O. P. Punchenko, I. Prigogine, I. Stengers, V. S. Stepin, L. P. Turkin and others. Research Methodology: general logical and theoretical research methods are used, representing their procedural adaptation to the solution of the problem. Unique in science is determined by the subject through its critical understanding of innovation, value context and essential for a given level of development of science. It is divided by type, depending on the scientific problems to be solved. Scientific novelty – unique is presented as a form of rationality movement, the moment of development of knowledge, it is also a test of knowledge for innovation, scientific character, clarification and their correlation. The types of rationality – classical, non-classical and post-non-classical – are identified and the role of the unique in their development and changes is clarified. Results of the research : on the analysis of the development of the natural sciences, it was proved that the change of types of rationality is associated with the growth of the innovative spirit of these sciences. Conclusions – the innovative potential constantly consisted in the damage to the stability of the old methodological principles that could not be adapted to the new discoveries. In classical rationality, unique principles were: unambiguity, clarity, obviousness; in non-classical – relativity, complexity, chance, complementarity; in the post-non-classical determining principles are steel: nonlinearity, chaos, self-organization, open systems, and more. The change of types of rationality gradually turned the unique from exceptions for natural science into its subject. (shrink)