Menu Expand
  • Hochschule für angewandtes Management GmbH
  • EN / DE
  • Login

Individuation, Adaptability and Cognition in Biological Systems: A Philosophical Modeling

  1. Journals
  2. Yearbook for Philosophy of Complex Systems
  3. Online First
  4. pp. 1–34

JOURNAL ARTICLE

Cite JOURNAL ARTICLE

Style
Boisseau, A., Miquel, P. Individuation, Adaptability and Cognition in Biological Systems: A Philosophical Modeling. Yearbook for Philosophy of Complex Systems, 99999(), 1-34. https://doi.org/10.3790/pcs.2025.14601902
Boisseau, Alexis and Miquel, Paul-Antoine "Individuation, Adaptability and Cognition in Biological Systems: A Philosophical Modeling" Yearbook for Philosophy of Complex Systems 99999., 2025, 1-34. https://doi.org/10.3790/pcs.2025.14601902
Boisseau, Alexis/Miquel, Paul-Antoine (2025): Individuation, Adaptability and Cognition in Biological Systems: A Philosophical Modeling, in: Yearbook for Philosophy of Complex Systems, vol. 99999, iss. , 1-34, [online] https://doi.org/10.3790/pcs.2025.14601902
Format
Download

Individuation, Adaptability and Cognition in Biological Systems: A Philosophical Modeling

Boisseau, Alexis | Miquel, Paul-Antoine

Yearbook for Philosophy of Complex Systems, Online First : pp. 1–34 | First published online: July 25, 2025

Preview Login to order (PDF)

Additional Information

Article Details

Publisher Name
Duncker & Humblot
DOI
https://doi.org/10.3790/pcs.2025.14601902
Language
German
Pages
34
License
closed-access
Keywords

Author Details

Alexis Boisseau, Université de Toulouse Jean Jaurès

Paul-Antoine Miquel, Université de Toulouse Jean Jaurès

References

  1. Albert, R./Barabasi, A. L. (2002): Statistical mechanics of complex networks, in: Review Modern Physics, 74, 47–97.  Google Scholar
  2. Barabasi, A. L. et al. (2011): Network medicine: a network-based approach to human disease, Nature Reviews Genetics, 12, 56–68.  Google Scholar
  3. Bassett, D. S./Bullmore, E. T. (2006): Small-world brain networks, in: Neuroscientist, 12(6), 512–23.  Google Scholar
  4. Bassett, D. S./Bullmore, E. T. (2016): Small-World Brain Networks Revisited, in: The Neuroscientist, doi: 10.1177/1073858416667720.  Google Scholar
  5. Batterman, R. W. (2002): The devil in the details: asymptotic reasoning in explanation, reduction, and emergence. New York, Oxford University Press.  Google Scholar
  6. Batterman, R. W./Rice, C. C. (2014): Minimal Model Explanations, in: Philosophy of Science, 81(3), 349–376.  Google Scholar
  7. Bechtel, W./Abrahamsen, A. (2005): Explanation: A Mechanistic Alternative, in: Studies in History and Philosophy of the Biological and Biomedical Sciences, 36, 421–441.  Google Scholar
  8. Bouchard, F. (2013): How ecosystem evolution strengthens the case for functional pluralism, in: Huneman, P. (ed.), Functions: Selection and Mechanisms. Springer, 83–95.  Google Scholar
  9. Bullmore, E./Sporns, O. (2009): Complex brain networks: graph theoretical analysis of structural and functional systems, in: Nature Reviews Neuroscience, 10, 186–198.  Google Scholar
  10. Craver, C. (2007): Explaining the brain. New York, Oxford University Press.  Google Scholar
  11. Craver, C. (2016): The Explanatory Power of Network Model, in: Philosophy of Science, 83(5), 698–709.  Google Scholar
  12. Craver, C./Darden, L. (2013): In search for mechanisms: discovery across the life sciences. Chicago, University of Chicago Press.  Google Scholar
  13. Craver, C./Kaplan, D. M. (2020): Are More Details Better? On the Norms of Completeness for Mechanistic Explanations, in: British Journal for the Philosophy of Science, 71(1), 287–319.  Google Scholar
  14. Craver, C./Povich, M. (2017): The directionality of distinctively mathematical explanations, in: Studies in History and Philosophy of Science, Part A 63, 31–38.  Google Scholar
  15. Cummins, R. E. (1975): Functional analysis, in: Journal of Philosophy, 72, 741–64.  Google Scholar
  16. Dakos, V./Kéfi, S./Rietkerk, M./van Nes, E. H./Scheffer, M. (2011): Slowing down in spatially patterned ecosystems at the brink of collapse, in: American Naturalist, 177(6), E153–E166.  Google Scholar
  17. Darrason, M. (2018): Mechanistic and topological explanations in medicine: the case of medical genetics and network medicine, in: Synthese, 195(1), 147–173.  Google Scholar
  18. Davidson, E. H. (1986): Gene activity in early development. Orlando, Academic Press.  Google Scholar
  19. Díez, J./Suárez, J. (2023): How do networks explain? A neo-hempelian approach to network explanations of the ecology of the microbiom, in: European Journal for Philosophy of Science, 13(3), 1–26.  Google Scholar
  20. Dokholyan, N. V./Li, L./Ding, F./Shakhnovich, E. I. (2002): Topological determinants of protein folding. Proc. Natl. Acad. Sci. U.S.A., 99(13), 8637–41.  Google Scholar
  21. Du, Y./Fu, Z./Calhoun, V. D. (2018): Classification and Prediction of Brain Disorders Using Functional Connectivity: Promising but Challenging, in: Frontiers in neuroscience, 12, 525, doi: 10.3389/fnins.2018.00525.  Google Scholar
  22. Dupré, J. (2021): The Metaphysics of Biology. Cambridge University Press.  Google Scholar
  23. Elek, G./Babarczy, E. (2022): Taming vagueness: the philosophy of network science, in: Synthese, 200(2), 1–31.  Google Scholar
  24. Elton, C. S. (1927): Animal Ecology. London, Sidgwick and Jackson.  Google Scholar
  25. Felline, L. (2015): Mechanisms meet structural explanation, in: Synthese, doi: 10.1007/s11229-015-0746-9.  Google Scholar
  26. Fletcher, R./Ries, L./Battin, J./Chalfoun (2007): A The role of habitat area and edge in fragmented landscapes: definitively distinct or inevitably intertwined?, in: Can. J. Zool., 85, 1017–1030.  Google Scholar
  27. Fontaine, C./Guimaraes, P./Kéfi, S./Loeuille, N./Memmott, J./van der Putten, W. H./van Veen, F./Thébault, E. (2011): The ecological and evolutionary implications of merging different types of networks, in: Ecology letters, 14(11), 1170–81.  Google Scholar
  28. Ghasemian, A./Hosseinmardi, H./Galstyan, A./Airoldi, E. M./Clauset, A. (2020): Stacking models for nearly optimal link prediction in complex networks, in: Proc. Natl. Acad. Sci. U.S.A., 117, 23393–23400.  Google Scholar
  29. Glennan, S. (1996): Mechanisms and the Nature of Causation, in: Erkenntnis, 44, 49–71.  Google Scholar
  30. Glennan, S. (2017): The new mechanical philosophy. New York: Oxford University Press.  Google Scholar
  31. Green, S./Jones, N. (2015): Constraint-Based Reasoning for Search and Explanation: Strategies for Understanding Variation and Patterns in Biology: Constraint-Based Reasoning for Search and Explanation, in: Dialectica, 70(3), 343–374.  Google Scholar
  32. Green, S./Serban, M./Jones, N./Sholl, R./Brigandt, I./Bechtel, W. (2017): Network analyses in systems biology: new strategies for dealing with biological complexity, in: Synthese, doi: 10.1007/s11229-016-1307-6.  Google Scholar
  33. Guimerà, R. (2020): One model to rule them all in network science? Proc. Natl. Acad. Sci. U.S.A., 13, 117(41), 25195–25197.  Google Scholar
  34. Guimerà, R./Sales-Pardo, M./Amaral, L. A. N. (2007): Classes of complex networks defined by role-to-role connectivity profiles, in: Nature Physics, 3, 63–69.  Google Scholar
  35. Hanski, I. (1998): Metapopulation dynamics, in: Nature, 396, 41–49.  Google Scholar
  36. Hanski, I. (1999): Metapopulation Ecology, Oxford, Oxford University Press.  Google Scholar
  37. Hanski, I./Ovaskainen, O. (2000): The metapopulation capacity of a fragmented landscape, in: Nature, 404, 755–758.  Google Scholar
  38. Hardcastle, VG (2002): On the Normativity of Functions, in: Ariew, A./Cummins, R./Perlman, M. (eds.), Functions: New Essays in the Philosophy of Psychology and Biology. Clarendon Press.  Google Scholar
  39. Hiebeler, D. (2000): Populations on fragmented landscapes with spatially structured heterogeneities: landscape generation and local dispersal, in: Ecology, 81(6), 1629–1641.  Google Scholar
  40. Hubbell, S. (2001): The unificatory neutral theory in ecology and biogeography. Princeton, Princeton University Press.  Google Scholar
  41. Huneman, P. (2010): Topological explanations and robustness in biological sciences, in: Synthese, 177(2), 213–245.  Google Scholar
  42. Huneman, P. (2015): Diversifying the picture of explanations in biological sciences: ways of combining topology with mechanisms, in: Synthese, doi: 10.1007/s11229-015-0808-z.  Google Scholar
  43. Huneman, P. (2018): Outlines of a theory of structural explanations, in: Philosophical Studies, 175(3), 665–702.  Google Scholar
  44. Huneman, P. (2023): Why? The philosophy behind the question. Stanford, Stanford University Press.  Google Scholar
  45. Huth, G./Lesne, A./Pittard, E./Munoz, F. (2014): Correlated percolation models of structured habitat in ecology, in: Physica A, 416, 290–308.  Google Scholar
  46. Huth, G./Pittard, E./Haegemann, B./Munoz, F. (2015): Long-Distance Rescue and Slow Extinction Dynamics Govern Multiscale Metapopulations, in: American Naturalist, 186(4), 460–9.  Google Scholar
  47. Jones, N. (2014): Bowtie structures, pathway diagrams, and topological explanation, in: Erkenntnis, 89(5), 1355–1555.  Google Scholar
  48. Kaplan, D. M./Craver, C. (2011): The Explanatory Force of Dynamical and Mathematical Models in Neuroscience: A Mechanistic Perspective, in: Philosophy of Science, 78(4), 601–627.  Google Scholar
  49. Kéfi, S./Miele, V./Wieters, E. A./Navarrete, S. A./Berlow, E. L. (2016): How Structured Is the Entangled Bank? The Surprisingly Simple Organization of Multiplex Ecological Networks Leads to Increased Persistence and Resilience, in: PLoS Biol, 14(8), e1002527.  Google Scholar
  50. Lange, M. (2016): Because without cause. New York, Oxford University Press.  Google Scholar
  51. Levins, R. (1966): The Strategy of Model Building in Population Biology, in: American Scientist, 54, 421–431.  Google Scholar
  52. Levins, R. (1969): Some demographic and genetic consequences of environmental heterogeneity for biological control, in: Bulletin of the Entomology Society of America, 71, 237–240.  Google Scholar
  53. Levy, A./Bechtel, W. (2013): Abstraction and the Organization of Mechanisms, in: Philosophy of Science, 80, 241–61.  Google Scholar
  54. Li Vigni, F. (2023): The Promises of Complexity Sciences: A Critique, in: Perspectives on Science, 31(4), 465–502.  Google Scholar
  55. MacArthur, R. H./Wilson, E. O. (1967): The theory of island biogeography. Princeton, N.J., Princeton University Press.  Google Scholar
  56. Machamer, P./Darden, L./Craver, C. (2000): Thinking of mechanisms, in: Philosophy of science, 67(1), 1–25.  Google Scholar
  57. Matthiessen, D. (2017): Mechanistic Explanation in Systems Biology: Cellular Network, in: British Journal for the Philosophy of Science, 68(1), 1–25.  Google Scholar
  58. May, R./Levin, S./Sugihara, G. (2008): Complex systems: Ecology for bankers, in: Nature, 451, 893–895.  Google Scholar
  59. Montoya, J./Pimm, S./Solé, R. (2006): Ecological networks and their fragility, in: Nature, 442, 259–267.  Google Scholar
  60. Moreno, A./Suárez, J. (2020): Plurality of Explanatory Strategies in Biology: Mechanisms and Networks, in: Moreno, A./Suárez, J. (eds.), Methodological Prospects for Scientific Research, 141–165.  Google Scholar
  61. Muldoon, S./Bassett, D. (2016): Network and Multilayer Network Approaches to Understanding Human Brain Dynamics, in: Philosophy of Science, 83(5), 710–720.  Google Scholar
  62. Neander, K. (1991): The teleological notion of ‘function’, in: Australasian Journal of Philosophy, 69(4), 454–468.  Google Scholar
  63. Newman, M. (2008): Networks. New York, Oxford University Press.  Google Scholar
  64. Nicholson, D. J./Dupré, J. (eds.) (2018): Everything Flows: Towards a Processual Philosophy of Biology. Oxford, Oxford University Press.  Google Scholar
  65. Olds, J./Milner, P. (1954): Positive reinforcement produced by electrical stimulation of septal area and other regions of rat brain, in: J Comp Physiol Psychol, 47(6), 419–27.  Google Scholar
  66. Olff, H./Alonso, D./Berg, M. P./Eriksson, B. K./Loreau, M./Piersma, T./Rooney, N. (2009): Parallel ecological networks in ecosystems, in: Philos. Trans. R. Soc. London, B, 364, 1755–1779.  Google Scholar
  67. Oliveri, P./Tu, Q./Davidson, E. H. (2008): Global regulatory logic for specification of an embryonic cell lineage, in: Proc. Natl. Acad. Sci. U.S.A., 22, 105(16), 5955–62.  Google Scholar
  68. Orzack, S. H./Sober, E. (1993): A Critical Assessment of Levins’s The Strategy of Model Building in Population Biology (1966), in: The Quarterly Review of Biology, 68(4), 533–546.  Google Scholar
  69. Ovaskainen, O./Hanski, I. (2001): Spatially Structured Metapopulation Models: Global and Local Assessment of Metapopulation Capacity, in: Theoretical Population Biology, 60(4), 281–302.  Google Scholar
  70. Park, J./Newman, M. (2003): The origin of degree correlations in the Internet and other networks, in: Physical Review E, 68, 2, 026112.  Google Scholar
  71. Pimm, S. (2002): Food webs. Chicago, University of Chicago Press.  Google Scholar
  72. Putnam, H. (2002): The collapse of the fact/value dichotomy and other essays. Cambridge, MA, Harvard University Press.  Google Scholar
  73. Rathkopf, C. (2015): Network representation and complex systems, in: Synthese, doi: 10.1007/s11229-015-0726-0.  Google Scholar
  74. Ravasz, E./Somera, A. L./Mongru, D. A./Oltvai, Z. N./Barabási, A. L. (2002): Hierarchical organization of modularity in metabolic networks, in: Science, 297, 1551–1555.  Google Scholar
  75. Rodriguez Caso, C./Conde Puyeo, N. (2009): Topological Analysis of Cellular networks, in: Giannopoulou, E. G. (ed.), Data mining in Medical and Biological Research. Vienna, ARS publishing, 253–267.  Google Scholar
  76. Ross, L. N. (2023): The explanatory nature of constraints: Law-based, mathematical, and causa, in: Synthese, 202(2), 1–19.  Google Scholar
  77. Seung, S. H. (2012): Connectome: How the Brain’s Wiring Makes Us Who We Are. Houghton Mifflin Harcourt Trade, New York.  Google Scholar
  78. Silberstein, M. (2021): Constraints on Localization and Decomposition as Explanatory Strategies in the Biological Sciences 2.0, in: Calzavarini, F./Viola, P., Neural Mechanisms (eds.): New Challenges in the Philosophy of Neuroscience. Dordrecht, Springer, 363–395.  Google Scholar
  79. Silberstein, M./Chemero, A. (2013): Constraints on Localization and Decomposition as Explanatory Strategies in the Biological Sciences, in: Philosophy of Science, 80(5), 958–970.  Google Scholar
  80. Solé, R. V./Montoya, J. M. (2001): Complexity and fragility in ecological networks, in: Proc. R. Soc. Lond. B 268, 2039–2045.  Google Scholar
  81. Steel, D. (2007): Across the boundaries: extrapolation in biology and social science. New York, Oxford University Press.  Google Scholar
  82. Strogatz, S. (2001): Exploring complex networks, in: Nature, 410, 268–276.  Google Scholar
  83. Watts, D. J./Strogatz, S. H. (1998): Collective dynamics in “small-world” networks, in: Nature, 393.  Google Scholar
  84. Weisberg, M. (2013): Simulation and Similarity: Using Models to Understand the World. New York, Oxford University Press.  Google Scholar
  85. Whitehead, A. N. (1929): Process and reality: an essay in cosmology. New York, Free Press.  Google Scholar
  86. Woodward, J. (2013): II–Mechanistic Explanation: Its Scope and Limits, in: Aristotelian Society Supplementary, 87(1), 39–65.  Google Scholar
  87. Wright, L. (1973): Functions, in: Philosophical Review, 82(2), 139–168.  Google Scholar
  88. Zhang, Z./Liao, W./Chen, H./Mantini, D./Ding, J.-R./Xu, Q./Wang, Z./Yuan, C./Chen, G./Jiao, Q./Lu, G. (2011): Altered functional-structural coupling of large-scale brain networks in idiopathic generalized epilepsy. Brain, 134(10), 2912–2928.  Google Scholar

Abstract

In his doctoral thesis, L’individu et sa genèse physico-biologique, Simondon formulates three key philosophical claims that we consider crucial. First, in complex physical or biological systems, individuation is not merely a property of an individual, rather, individuality always results from an individuation process. Second, a biological individuated system has a distinctive feature: it acts on its own stage. Third, there must be some non-trivial recursive procedure through which a physical individuated system can switch into a biological one. In this chapter, we propose a philosophical model to further develop this conceptual scheme. This will allow us to characterize biological individuation as a second-order organisation, and to directly connect it with the two concepts of heteronomy and adaptability. We will show that, unlike physical individuation, biological individuation is self-specifying. However it does not do so within a logic of maintenance, as proposed by Francisco Varela, who used a symbolism similar to us. Instead, it follows a logic of heteronomy and adaptability, the logic of life. Varela’s model therefore appears to be a special case within a broader theoretical framework, which is the only way to understand how new constraints/norms/functions can emerge in a biological system, whether at the evolutionary, ontogenetic or behavioural level. Finally, to say that biological individuation is self-specifying is to say that it can be interpreted, and that we cannot understand how a biological system works if we remain fixated on a strictly causal mode of explanation, and on the search for mechanisms, as if it were a watch, a radiator or a computer. We fail to see that, through and by specific biological repair, immune and perceptive devices, it works in a world of signs, in such a way that biological organisation and cognition are always already coupled at the outset. It is only evolution that will gradually uncouple what has been coupled.

Table of Contents

Section Title Page Action Price
Alexis Boisseau / Paul-Antoine Miquel: Individuation, Adaptability and Cognitionin Biological Systems: A Philosophical Modeling 1
Abstract 1
I. Individuation as a Conceptual Scheme 2
1. The Individual as a Process 2
2. Biological Individuation as a Second-Order Process 2
3. Recursive Transition from First- to Second-Order Individuation 2
II. Physical Individuation andthe Epistemic Operators R1 and R2 3
1. Physical Individuation and Self-Organization 3
2. A Detailed Explanation of Epistemic Operators 4
3. An Example to Illustrate 5
4. Invoking the Methods of Statistical Physics Does not,by Itself, Resolve the Underlying Issue 6
III. The Transition to Biological Systems 7
1. Preliminary Research Hypothesis 7
2. A Second and Third Research Hypothesis 8
IV. The Logic of Life 9
1. Organization as Closure of Constraints: The Search of Maintenance 9
2. A Non-Binary Logic 11
a) Heteronomy: Levels Entanglement,Physiological Closure on Disruptions and Unachieved Autonomy 12
b) Adaptability: Spontaneous Reorganization and Control 12
V. Heteronomy and Heterogenesis 14
1. Heteronomy: The Structural and Functional Dependency 14
a) Multicellular Systems and the Degrees of Closure 15
b) Unicellular Systems and the Necessity of Collective Constraints 16
c) Concluding Remarks on Heteronomy:The Internal Limitation Theorem 17
2. Heterogenesis: Historical Dependence 17
VI. What Does Adaptability Mean? 18
1. Plasticity and Robustness in Biology 18
2. Adaptability and Temporality 20
3. Causal Specification and Semiotic Agency in Living Systems 21
4. Causal Specification and the Resolution of Logical Incompatibilitiesin Biological Systems 26
5. The Three Levels in Action:Three Examples of Adaptative Recomposition 27
VII. Conclusion 31
References 31

Contact

Duncker & Humblot GmbH Carl-Heinrich-Becker-Weg 9 12165 Berlin, Deutschland T: +49 30 790006-0

Quick Navigation

2025 Duncker & Humblot GmbH

Powered by CloudPublish

We use cookies to ensure that you get the best experience on our website. Learn more about how we use cookies.