The Dynamical Systems Approach to Cognition (original) (raw)
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Dynamics, control, and cognition
Aydede and Robbins, 2008
A dynamic object is an object whose properties change over time. A static object is an object whose properties do not change over time. Given such an idealization, the notion of 'static' lies at an extreme end of the spectrum of temporal relations between objects and properties. Indeed, modern physics tells us that no objects are truly static. Nevertheless, many of our physical, computational, and metaphysical theories turn a blind eye to the role of time, often for practical reasons. So, perhaps it is not surprising that in the philosophy of mind -where physical, computational, and metaphysical theories meet -there has been a consistent tendancy to articulate theories that consider function and time independently. As a result, contemporary theories in cognitive science consider time unsystematically (see the next section for specific examples). In this chapter, I suggest that the problem with this 'ad hocery' is that the systems we are trying to characterize are real-time systems, whose real-time performance demands principled explanation (a point on which many of these same contemporary theorists agree). After a discussion of the importance and roots of dynamics in cognitive theorizing, I describe the role of time in each of the three main approaches to cognitive science: symbolicism, connectionism and dynamicism. Subsequently, I outline a recently proposed method, the Neural Engineering Framework (NEF), that, unlike past approaches, permits a principled integration of dynamics into biologically realistic models of high-level cognition. After briefly presenting a model, BioSLIE, that demonstrates this integration using the NEF, I argue that this approach alone is in a position to properly integrate dynamics, biological realism, and high-level cognition.
Dynamical Systems Theory in Cognition: Are We Really Gaining?
2011
Dynamical Systems Theory (DST) claims to be an epistemological weapon particularly broad and rich in providing a fair explanatory account of the operations of our mind. However, the very features that this DST espouses as reasons for having an edge over Computational Theory of Mind (CTM) and Artificial Neural Networks (ANN), are the ones that are causing trouble in the philosophy of science speculation, especially regarding issues of Explanation. This paper aims to suggest some possible problems that could arise from the application of DST’s characteristically abstract mathematical framework to the study of the mind. As I have not found anything that suggests something like this, my aim is to at least show the reasonability of a possibility.
Dynamical Systems in Cognition: Are We Really Gaining?
Dynamical Systems Theory (DST) claims to be an epistemological weapon particularly broad and rich in providing a fair explanatory account of the operations of our mind. However, the very features that DST espouses as reasons for having an edge over Computational Theory of Mind (CTM) and Artificial Neural Networks (ANN) are the ones that are causing trouble in the philosophy of science, especially regarding issues of Explanation. This paper aims to suggest some possible problems that could arise from the application of DST’s characteristically abstract mathematical framework to the study of the mind. As I have not found anything that suggests something like this, my aim is to at least show the reasonableness of a possibility.
1995
Recently, a new approach to modeling cognitive phenomena has been gaining recognition: the dynamical systems approach. Proponents of this theory claim to have identified a new paradigm for the study of cognition which is superior to both symbolicism and connectionism.
A Critical Reappraisal of the Dynamical Approach to Cognition
2007
Approaches to cognitive science have been socially divided into dynamical and computational camps. We break down the dynamical approach into finer components, suggesting a new taxonomy of dynamical approaches to cognition and questioning the logical unity of the dynamical school. We dispel some confusions surrounding the concepts of dynamical systems, computation, and the relation between the two. We introduce and argue for the notion of "cognition as it could be" and show its value in analysing the dynamicists' account of time.
Structure and Application of Dynamical Models in Cognitive Science
In philosophy of science, Neo-mechanists argue that explanations are only successful when formulated in terms of the behaviors of discrete decomposable components that constitute the system of interest. This approach to explanation implicitly denies the significance of non-linear interactions in structuring the behavior of complex cognitive systems. Recently, Neo-mechanists have claimed that JAS Kelso and colleagues have begun to favor neo-mechanistic explanations of neuroscientific phenomena; particularly in the application of the neural field model to rhythmic coordination behaviors. We will argue that this view is the result of a failure to understand dynamic systems explanations and the general structure of dynamic systems research. Further, we argue that the explanations cited are in fact not neo-mechanistic explanations. In this paper, we will show that these neo-mechanists have misunderstood the work by Kelso and colleagues, which blunts the force of one of their arguments
Dynamical Systems Hypothesis in Cognitive Science
Encyclopedia of Cognitive Science, 2006
The dynamical hypothesis in cognition identifies various research paradigms applying the mathematics of dynamical systems to understanding cognitive function. The approach is allied with and partly inspired by research in neural science over the past fifty years for which dynamical equations have been found to provide excellent models for the behavior of single neurons (Hodgkins and Huxley, 1952). It also derives inspiration from work on gross motor activity by the limbs (e.g., Bernstein, 1967. In the early 1950s, Ashby made the startling proposal that all of cognition might be accounted for with dynamical system models (1952), but little work directly followed from his speculation due to a lack of appropriate mathematical methods and computational tools to implement practical models. More recently, the connectionist movement (Rumelhart and McClelland, 1986) provided insights and mathematical implementations of perception and learning, for example, that have helped restore interest in dynamical modeling.
Debates in dynamics: A dynamical systems perspective on action and perception
Human Movement Science, 2000
Since the seminal publication by Kugler, , which formulated an agenda for understanding movement coordination based on the merging of Bernstein's insights and modern nonlinear dynamics, and since the classic results on phase transitions in rhythmic bimanual coordination the dynamical systems approach to action and perception has made considerable progress. The special issue collects research presented in a 3-day workshop``Debates in Dynamics'' that portrays recent advances in the dynamical systems account to perception and action. As re¯ected in the wide spectrum of themes, the dynamical systems account has clearly diverged in the issues it addresses, in the levels of analysis, and in the formal concepts and tools it applies, without loosing its common thread of convergent assumptions and language. Ó (D. Sternad). 0167-9457/00/$ -see front matter Ó 2000 Elsevier Science B.V. All rights reserved. PII: S 0 1 6 7 -9 4 5 7 ( 0 0 ) 0 0 0 2 4 -5
A real dynamical system is any concrete object which changes over time. A mathematical dynamical system, on the other hand, is an abstract mathematical structure which can be used to describe the change of a real system . as an evolution through a series of states . ( Thus , only real dynamical systems actually undergo change ; mathematical dynamical systems are timeless , unchanging entities which can nevertheless be used as models of change in real systems . ) If the evolution of the real system is detenninistic , i.e. , if the state at any future time is determined by the state at the present time, then the abstract mathematical structure consists of three elements . The first element is Real VB . Mathematical