Hostname: page-component-848d4c4894-75dct Total loading time: 0 Render date: 2024-05-17T06:13:00.126Z Has data issue: false hasContentIssue false
  • English
  • Français

Return of the math: Markov blankets, dynamical systems theory, and the bounds of mind

Published online by Cambridge University Press:  29 September 2022

Lincoln John Colling Open the ORCID record for Lincoln John Colling [Opens in a new window]
Lincoln John Colling*
Affiliation:
School of Psychology, University of Sussex, Falmer BN1 9QH, UK l.colling@sussex.ac.uk http://research.colling.net.nz
Get access Rights & Permissions [Opens in a new window]

Abstract

Bruineberg and colleagues highlight work using Markov blankets to demarcate the bounds of the mind. This echoes earlier attempts to demarcate the bounds of the mind from a dynamical systems perspective. Advocates of mechanistic explanation have challenged the dynamical approach to independently motivate the application of the formalism, a challenge that Markov blanket theorists must also meet.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 45 , 2022 , e190
Check for updates
Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Chemero, A. (2011). Radical embodied cognitive science. MIT Press.Google Scholar
Colling, L. J., & Williamson, K. (2014). Entrainment and motor emulation approaches to joint action: Alternatives or complementary approaches? Frontiers in Human Neuroscience, 8, 754. https://doi.org/10.3389/fnhum.2014.00754CrossRefGoogle ScholarPubMed
Friston, K. (2019). A free energy principle for a particular physics. Retrieved January 3, 2022, from http://arxiv.org/abs/1906.10184Google Scholar
Haken, H., Kelso, J. A. S., & Bunz, H. (1985). A theoretical model of phase transitions in human hand movements. Biological Cybernetics, 51(5), 347–356. https://doi.org/10.1007/BF00336922CrossRefGoogle ScholarPubMed
Kaplan, D. M., & Bechtel, W. (2011). Dynamical models: An alternative or complement to mechanistic explanations? Topics in Cognitive Science, 3(2), 438–444. https://doi.org/10.1111/j.1756-8765.2011.01147.xCrossRefGoogle ScholarPubMed
Kaplan, D. M., & Craver, C. F. (2011). The explanatory force of dynamical and mathematical models in neuroscience: A mechanistic perspective. Philosophy of Science, 78(4), 601–627. https://doi.org/10.1086/661755CrossRefGoogle Scholar
Kelso, J. A. (1984). Phase transitions and critical behavior in human bimanual coordination. The American Journal of Physiology, 246, R1000–R1004. https://doi.org/10.1152/ajpregu.1984.246.6.R1000Google ScholarPubMed
Kirchhoff, M. D., & Kiverstein, J. (2021). How to determine the boundaries of the mind: A Markov blanket proposal. Synthese, 198, 4791–4810.CrossRefGoogle Scholar
Kirchhoff, M. D., Parr, T., Palacios, E., Friston, K., & Kiverstein, J. (2018). The Markov blankets of life: Autonomy, active inference and the free energy principle. Journal of the Royal Society Interface, 15(138), 20170792. https://doi.org/10.1098/rsif.20170792.CrossRefGoogle ScholarPubMed
Ramstead, M. J. D., Kirchhoff, M. D., Constant, A., & Friston, K. J. (2021). Multiscale integration: Beyond internalism and externalism. Synthese, 198(1), 41–70. https://doi.org/10.1007/s11229-019-02115-xCrossRefGoogle ScholarPubMed
Schmidt, R. C., Carello, C., & Turvey, M. T. (1990). Phase transitions and critical fluctuations in the visual coordination of rhythmic movements between people. Journal of Experimental Psychology: Human Perception and Performance, 16(2), 227–247. https://doi.org/10.1037/0096-1523.16.2.227Google ScholarPubMed