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Appendix A: Autopoietic Systems1 Appendix A: Autopoietic Systems1 The interested reader of this monograph may find that there are certain concepts embraced by the oscillation-based multi-agent system (OSIMAS) and oscillation agent model (OAM) that are common to a number of mainstream models of cog- nition, neurodynamics and sociobiological/cultural systems. As steps to under- standing consciousness, such an association of ideas seems quite inevitable, and here one may underscore the important role of (coupled) oscillatory systems as incorporated into processes of massively parallel, and distributed type. To give a complete acknowledgement of those models concerned by combing through a large number of specific details, is a task that goes way beyond this present contribution. Instead, I will restrict attention to certain theories and concepts with which I have some familiarity, and consider to be germane to the tasking mechanisms of OSIMAS and OAM. Having said this, the main topics to be covered in this essay are: 1. The Maturana-Varela theory of autopoiesis, leading to Varela’s foundations for a theory of neurophenomenology. 2. Global Workspace Theory (GWT)—a principal forerunner in modern theories of cognition. 3. Distributed and Embodied Cognition. 4. Several other approaches inter-related to (1–3) that may also be significant for the OSIMAS and OAM models. Much of the content of (1)–(4) is increasingly applicable to many mainstream fields of cognition that are currently breaking ground towards a general model of experiential neuroscience. Many of the intrinsic properties are essential contribu- tions to the ongoing task of understanding cognition and consciousness within the framework of structural organization and the evolution of human and social sys- tems, rather much in tune with the drift of ideas of the present monograph. This is thanks to a number of extensive multi-disciplinary connections created over the last 1The appendix has been cordially contributed by prof. J.F. Glazebrook. © Springer International Publishing Switzerland 2016 267 D. Plikynas, Introducing the Oscillations Based Paradigm, DOI 10.1007/978-3-319-39040-6 268 Appendix A: Autopoietic Systems forty years or so, particularly those that have centered around the core of (applied) phenomenology, as was professed by the school of philosophers such as F. Brentano, E. Husserl, M. Heidegger, and M. Merleau-Ponty.2 A.1 Defining Autopoiesis and What It Means Autopoiesis (from the Greek meaning “self-generating”) is a theory conceived for living cellular organisms based upon the circular organization of metabolism and the organism’s structural organization. As it was originally proposed by Maturana and Varela (1980): … an autopoietic system is organized as a bounded network of processes and production, transformation and destruction of components which (i) through their interactions and transformations continuously regenerate and realize the network of processes that produced them; (ii) constitute the system as a concrete entity in the space in which the components exist by specifying the topological realization of the system as such a network. Consequently, the system specifies its own internal states, its domain of vari- ability and its boundary delimited in terms of its sovereign mechanisms. In the sense of a cellular system, this means that the flow of energy and matter onto the membrane boundaries bounds the dynamics of the metabolic network producing the metabolites, the latter constituting that same network together with its boundaries, out of which this flows continues its cycles. This ‘circularity’ characterizes autopoiesis as a property of autonomy for a living system. The term operational closure was introduced to describe how the product of functioning components in a network would be transformed by other processes into components of the initial process. This concept is ubiquitous to many systems such as AI, ALife, ecosystems, linguistics, economics and social/judicial organization in the form of self-referentiality. In this way, autopoiesis characterizes ‘organiza- tionally closed’ systems. A basic premise is that the brain and vital systems, as far-from-equilibrium open systems perturbed by an environment, possess this property. Thus, the contextual distinction between use of the terms ‘open’ and ‘closed’ is essential here. In fact, the entirety of the system is embodied in its organizational closure; thus the whole is not the sum of its parts; it is instead seen as the organizational closure of its parts, and this is the subtle distinction, following which the system’s intrinsic properties are seen to emerge through the interactions of its components via levels of iteration. To a certain extent autonomous systems and control systems are complementary in understanding natural systems, as much as the methods of reductionism and holism can also be seen as complementary 2The work Thompson (2007a) provides an impressive scholarly account this respect, and since a complete philosophical discussion also flies out of the confines of this Appendix, I shall refer the philosophically-minded reader to this particular reference for a more comprehensive discussion [particularly of case (1)] and how this relates to the mind-body-brain problem. Appendix A: Autopoietic Systems 269 (in the descriptive framework, such complementarity can be approached by the notion of ‘adjointness’ in the mathematical theory of categories; see Goguen and Varela (1979) and cf. Baianu et al. (2006). Despite its growing attraction within the life sciences from the mid 1970s onwards, the theory of autopoietic systems remains to be universally accepted, least of all by experimental biologists who for some time have been greatly preoccupied with DNA, RNA and replication research. Questions have been raised concerning the interpretation of terms such as ‘operational closure’, ‘boundary’, and the seemingly implicit sense of ‘cognition’ that featured in the original theory, matter that might have misconstrued the relationship between ‘information’ and ‘knowl- edge’ (see e.g. Luisi 2003).3 So it is important to note that the definition of ‘au- topoiesis’, as originally defined in e.g. Maturana and Varela (1980, 1987), has over the years, undergone various adjustments and re-interpretation of meaning since its original conception. Indeed, using his encyclopedic knowledge of cell biology, immunology, and biophysics on the one hand, and neuroscience, cognition and anthropology, on the other hand, Varela spent a large part of his latter career (ending just at the age of 54) towards developing the concept of cognition beyond autopoiesis, to a more widely-based concept with notable epistemic and ontological foundations (see Varela 1996; Varela et al. 1992) as well as other extensive reviews of this work in e.g. Rudrauf et al. (2003), Thompson (2007). Before outlining the development of ideas, let us consider a sampling of issues that were at stake, and how they were remedied. The importance of the ‘boundary’ as produced by the network of processes for the sake of separating the system from the non-system, was further highlighted towards a modified definition of the term ‘autopoiesis’. As pointed out by (Bourgine and Stewart 2004), in his last work Varela redefined a system as ‘autopoietic’ if: (a) it has a semi-permeable boundary; (b) the boundary is produced from within the system, and (c) it encompasses reactions that regenerate the components of the system. By removing the restriction that the components should necessarily be molec- ular, Bourgine and Stewart (2004) later re-formulated this definition as follows: An autopoietic system is a closed network of productions of components that recursively produce the components and the same network that produced them; the network also specifies its own boundary, while remaining open to the flow of matter and energy through it. Observe that this re-formulation radically separates autopoiesis from cognition, a sense of which was implicit to the original concept as it was pre-supposed with respect to self-organization and structure. The hypothesis of (Bourgine and Stewart 2004) is that a living system is both autopoietic (in their sense) and cognitive. The meaning of ‘cognitive’ is proposed as follows: Consider two types of interactions between entities called A and B: (a) those that have consequences for the internal 3How the mechanisms of DNA, RNA, self-replication and protein synthesis can actually be incorporated into cellular autopoietic systems has been studied in e.g. Luisi (1993). 270 Appendix A: Autopoietic Systems state of the organism (type A), and (b) those that have consequences for the state of the (proximal) environment, or modify the system to its environment (type B). Then the system is cognitive if and only if type A interactions serve to trigger type B interactions in a specific way so as to satisfy a variability constraint. In a similar way, Atlan and Cohen (1998) view the complex regulatory activities of the immune system as cognitive in the sense that the system’s ‘cognition’ is its innate property of perceiving an incoming signal with an internally structured and hereditary conditioned image of the world, and then selecting a response from a much larger repertoire of possible responses. In other words, the cognitive pattern of recognition-and-response proceeds by an algorithmic combination of an incoming external, and broadly ‘sensory’ signal, with an internal ongoing activity influenced by this internal image. This is part of the ‘immune protocol’ that initiates a planned
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