Breaking explanatory boundaries: flexible borders and plastic minds
In this paper, we offer reasons to justify the explanatory credentials of dynamical modeling in the context of the metaplasticity thesis, located within a larger grouping of views known as 4E Cognition. Our focus is on showing that dynamicism is consistent with interventionism, and therefore with a difference-making account at the scale of system topologies that makes sui generis explanatory differences to the overall behavior of a cognitive system. In so doing, we provide a general overview of the interventionist approach. We then argue that recent mechanistic attempts at reducing dynamical modeling to a merely descriptive enterprise fail given that the explanatory standard in dynamical modeling can be shown to rest on interventionism. We conclude that dynamical modeling captures features of nested and developmentally plastic cognitive systems that cannot be explained by appeal to underlying mechanisms alone.
KeywordsMetaplasticity Dynamicism Mechanism Intervention Boundaries Extended cognition Material engagement theory
Kirchhoff’s work was supported by an Australian Research Council Discovery Project “Minds in Skilled Performance” (DP170102987), a John Templeton Foundation grant “Probabilitizing Consciousness: Implications and New Directions”, and by a John Templeton Foundation Academic Cross-Training Fellowship (ID#60708). The opinions expressed in this publication are those of the author and do not necessarily reflect the views of the John Templeton Foundation. Thanks to Lambros Malafouris for inviting us to take part in this special issue and to two anonymous reviewers for insightful comments.
- Allen, M., & Friston, K. J. (2016). From cognitivism to autopoiesis: Towards a computational framework for the embodied mind. Synthese, 2016. https://doi.org/10.1007/s112 29-016-1288-5.
- Bechtel, W., & Richardson, R. C. (1993). Discovering complexity: Decomposition and localization as scientific research strategies. Princeton: Princeton University Press.Google Scholar
- Beer, R. D. (1995). Computational and dynamical languages for autonomous agents. In R. F. Port & T. van Gelder (Eds.), Mind as motion: Explorations in the dynamics of cognition (pp. 121–147). Cambridge: MIT Press.Google Scholar
- Clark, A. (2017). How to Knit Your Own Markov Blanket: Resisting the Second Law with Metamorphic Minds. Available online: http://www.x-spect.org/uploads/9/8/1/5/98154170/knittingmarkov8.pdf.
- Craver, C., and Tabery, J. (2015). Mechanisms in Science. Stanford Encyclopedia of Philosophy, pp. 1–25.Google Scholar
- Friston, K., & Stephan, K. (2007). Free-energy and the brain. Synthese, 159, 417–458.Google Scholar
- Friston, K., & Frith, C. (2015). A duet for one. Consciousness and Cognition, 1–16. https://doi.org/10.1016/j.concog.2014.12.003.
- Haken, H. (1983). Synergetics: Non-equilibrium phase transition and self-organization in physics, chemistry and biology. Berlin: Springer.Google Scholar
- Kelso, S. (1995). Dynamic patterns. Cambridge: The MIT Press.Google Scholar
- Kirchhoff, M. D. (2016). From mutual manipulation to cognitive extension: Challenges and implications. Phenomenology and the Cognitive Sciences, 1–16. https://doi.org/10.1007/s11097-016-9483-x.
- Koschmieder, E. L. (1993). Bénard cells and Taylor vortices. Cambridge: Cambridge University Press.Google Scholar
- Malafouris, L. (2004). The cognitive basis of material engagement: Where brain, body and culture conflate. In E. DeMarrais, C. Gosden, & C. Renfrew (Eds.), Rethinking Mareriality: The engagement of mind with the material world (pp. 53–62). Cambridge: McDonald Institute Monographs.Google Scholar
- Malafouris, L. (2010). Metaplasticity and the human becoming: Principles of neuroarchaeology. Journal of Anthropological Sciences, 88, 49–72.Google Scholar
- Spivey, M. (2007). The continuity of mind. Oxford and New York: Oxford University Press.Google Scholar
- Sporns, O. (2011). Networks of the brain. Cambridge: The MIT Press.Google Scholar
- Thompson, E. (2007). Mind in Life. Cambridge: The MIT Press.Google Scholar
- Thiese, N. D., & Kafatos, M. (2013). Complementarity in biological systems: a complexity view. Complexity, 18(6), 1–11.Google Scholar
- Tronick, E. Z., Als, H., & Adamson, L. (1979). The communicative structure of face-to-face interaction. In M. Bullowa (Ed.), Before SpHEECh: The beginnings of human communication (pp. 349–372). Cambridge: Cambridge University Press.Google Scholar
- Varela, F., Thompson E., & Rosch, E. (1991). The embodied mind. Cambridge: The MIT Press.Google Scholar
- Varga, S. (2015). Interaction and extended cognition. Synthese, 1–28. https://doi.org/10.1007/s11229-015-0861-7.
- Wolpert, D. (1996). The lack of a prior distinctions between learning algorithms. Neural Computation, 8, 1341–1390.Google Scholar
- Woodward, J. (2003). Making things happen: A theory of causal explanation. Oxford: Oxford University Press.Google Scholar
- Woodward, J. (2013). Mechanistic explanation: Its scope and limits. In Aristotelian Society Supplementary Volume, 87(1), 39–65.Google Scholar