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Structure and Application of Dynamical Models in Cognitive Science

2014; Wiley; Volume: 36; Issue: 36 Linguagem: Inglês

1551-6709

Maurice Lamb, Anthony Chemero,

Complex Systems and Decision Making

Structure and Application of Dynamical Models in Cognitive Science Maurice Lamb (Lambmi@mail.uc.edu) Department of Philosophy, 206 McMicken Hall, University of Cincinnati Cincinnati, OH 45221 USA Anthony Chemero (Anthony.chemero@uc.edu) Department of Philosophy and Department of Psychology, 206 McMicken Hall, University of Cincinnati Cincinnati, OH 45221 USA not, in this very short paper, offer a full defense of dynamical models as genuine explanations. Here, we will simply show that these neo-mechanists have misunderstood the work by Kelso and colleagues, which blunts the force of one of their arguments. Our paper will proceed in three parts. First, we will briefly describe neo-mechanisms and what we will call “The Scott Freaking Kelso Argument”. Second, we will outline the basic methodology of one form of dynamic systems research. In this section our aim is to clarify the structure and formulation of dynamic systems models in the context of Synergetics in order to distinguish this strand of dynamic systems research from neo-mechanistic theories. Third, we will examine the role of the neural field model in dynamic systems research (Jirsa and Haken, 1996; Jirsa et al. 1998; Jantzen et al. 2009). This work has been cited as a supposedly clear example that dynamic systems researchers ultimately depend on neo-mechanistic explanations to make their models explanatory (Kaplan and Bechtel 2011; Kaplan and Craver 2011). We will show that the neural field model is a dynamic systems model, and thus, application of the neural field model is continuous with dynamic systems theory not contrary to it. Abstract 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. Keywords: Explanation; Dynamic systems; Mechanism; HKB; Neural Field Model; Tripartite Scheme; Neuroscience Introduction Many scientists have some criteria for deeming some findings as explanatory and others as useful but not explanatory, though these criteria are rarely formalized. Attempts at defining a simple account of explanation in terms of necessary and sufficient conditions have often come up short. In the philosophy of science, a theory of explanation, referred to as the neo-mechanist approach, has been developed in terms of a particular understanding of mechanisms in scientific investigations. In the context of cognitive science, Neo-mechanists (Bechtel and Abrahamsen 2005; Craver 2007; Bechtel 2009, 2011; Kaplan and Bechtel 2011; Kaplan and Craver 2011) argue that in order for a claim to be an explanation in cognitive science it must reveal something about the decomposable mechanisms of a cognitive system. As part of their arguments, they claim that JAS Kelso and colleagues working on cognitive systems are shifting away from dynamic systems explanations of cognitive and behavioral phenomena in favor of neo-mechanistic explanation of neuroscientific phenomena (Kaplan and Bechtel, 2011; Kaplan and Craver 2011). 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, and that the explanations by Kelso and colleagues cited are in fact not neo-mechanistic explanations. We will Neo-Mechanism and the SFK Argument For the past 20 years, there has been a consensus among philosophers of science that mechanistic explanation is important in the life sciences. Bechtel and Richardson (2010) defined neo-mechanistic explanation as explanation that involves decomposing some phenomenon into component operations, and then localizing those component operations in physiological structures of organisms. These component operations are taken to produce or to be responsible or to account for the phenomena. Decomposition involves developing a model of a system’s behavior by identifying discrete component parts and their linear, or weakly non-linear, interactions. While it cannot be argued here, non-linearity in a system is not trivial. Genuinely non-mechanistic descriptive and explanatory strategies are required to capture features of non-linear interactions that are otherwise unavalible to neo-mechanistic paradigms of explanation. Many of these non-linear features are at the center of debates over emergence in natural systems, though these debates are outside the scope of the current project. Localization involves mapping those discrete components and interactions onto features of a