Skip to main content

Invariances in Theory

  • Chapter
  • First Online:
Invariants of Behavior

Part of the book series: Springer Series in Cognitive and Neural Systems ((SSCNS,volume 1))

  • 567 Accesses

Abstract

This chapter surveys the multifaceted roles that invariants play in theorizing, from physics and mathematics to biology and neurobiology. The question “What is an invariant of behavior?” is posed, and some alternatives are proposed and discussed: genes, neuroanatomy, and reflex theory. From that, the cybernetic take on the issue is introduced and placed in an evolutionary context, in which single behaviors are identified in respect to the goals they achieve and how they subserve the organism’s viability. The search for invariants of behavior is framed as a search for mechanisms. This search is far from trivial, as assumptions play a prominent role.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    Other purely theoretical examples exist, such as the entities in the study of topology. For example, a torus – a donut – will always have one hole irrespective of deformations, because its shape identity is defined by its topological properties. The invariant property is a part of the entity’s definition.

  2. 2.

    Noether’s theorem informally stated: differentiable symmetries generated by local actions have correspondent conserved current. An English translation of the original paper is found in [45].

  3. 3.

    Coextensive: If P is an invariant property of a system, then for all members of set A, it is true that A has P. In the example of life, if all the living A have life (property L), then ∀A : L(A) → L(A), a tautology. An explanatory principle such as this has vaporous foundation, and no logical derivations are possible. Nothing can be learned; life becomes magic.

  4. 4.

    See also [15] for an insightful book review on Oyama’s cycles of contingency.

  5. 5.

    Our working definition of behavioral function: when a goal can be attributed to a behavior, then the behavior is a functional behavior. Contrast that with behavior in toto.

  6. 6.

    Gross in the sense of coarse, at first glance.

  7. 7.

    Schema theory (see more in Sect. 2.3.12) exemplifies the attempts to overlay the brain with a structure of functional components, “boxes,” to aide in explanation of overall behavior. But although being a tenable level of functional analysis, it encounters the problems of arbitrariness. That is because, in an important sense, a function only exists while it is being executed, and only within the frame of a theory. Often, there will be no fundamental way to distinguish between different overlaying schemas which one is better or best.

  8. 8.

    Environmental context is meant broadly: a cell can be an environment for DNA, as blood can be an environment for a cell, or the body can be a contextual environment for a neural system.

  9. 9.

    This is one of the main difficulties with analogies in ethology and neuroethology. Descriptions of functions are shared across different organisms, whereas mechanisms are not.

References

  1. Arbib MA (1972) The metaphorical brain, an introduction to cybernetics and brain theory. MIT Press, Cambridge

    Google Scholar 

  2. Arbib MA (1982) Machine Intelligence 10, Chichester: Ellis Horwood, chap Rana Computatrix, an evolving model of visuomotor coordination in frog and toad, pp 501–517

    Google Scholar 

  3. Arbib MA, Fellous JM (2004) Emotions: From brain to robot. Trends Cogn Sci 8(12)

    Google Scholar 

  4. Ashby W (1960) Design for a brain: The origin of adaptive behavior, 2nd edn. Chapman & Hall, London

    Book  Google Scholar 

  5. Bateson G (1972) Steps to an ecology of mind. University of Chicago Press, p. 533

    Google Scholar 

  6. Benavides-Piccione R, Hamzei-Sichani F, Ballesteros-Yanez I, DeFelipe J, Yuste R (2006) Dendritic size of pyramidal neurons differs among mouse cortical regions. Cereb Cortex 16(7):990–1001

    Article  PubMed  Google Scholar 

  7. Berns GS, Sejnowski TJ (1998) A computational model of how the basal ganglia produce sequences. J Cogn Neurosci 10(1):108–121

    Article  PubMed  CAS  Google Scholar 

  8. Braitenberg V (1977) On the texture of brains: An introduction to neuroanatomy for the cybernetically minded. Springer, New York

    Google Scholar 

  9. Braitenberg V (1984) Vehicles, experiments in synthetic psychology. Bradford Book, Cambridge

    Google Scholar 

  10. Braitenberg V (2001) Brain size and number of neurons: An exercise in synthetic neuroanatomy. J. Comput. Neurosci. 10(1):71–77

    Article  PubMed  CAS  Google Scholar 

  11. Braitenberg V, Schüz A (1998) Cortex: Statistics and geometry of neuronal connectivity. Springer, Berlin

    Google Scholar 

  12. Brentano FC (1874) Psychologie vom empirischen Standpunkte. Duncker & Humblot, Leipzig

    Google Scholar 

  13. Cohen N, Squire L (1980) Preserved learning and retention of pattern-analyzing skill in amnesia: dissociation of knowing how and knowing that. Science 210(4466):207

    Article  PubMed  CAS  Google Scholar 

  14. Dawkins R (1976) The selfish gene. Oxford University Press, New York

    Google Scholar 

  15. Di Paolo E (2002) Book review: Cycles of contingency. Artif Life 8(2)

    Google Scholar 

  16. Dörner D (1999) Bauplan für eine Seele. Rowohlt, Reinbek

    Google Scholar 

  17. Edelman G (1988) Topobiology: An introduction to molecular embryology. Basic Books

    Google Scholar 

  18. Eigen M, Schuster P (1978) The hypercycle. Naturwissenschaften 65(1):7–41

    Article  Google Scholar 

  19. Elston G, Rockland K (2002) The pyramidal cell of the sensorimotor cortex of the Macaque Monkey: Phenotypic variation. Cereb Cortex 12(10):1071–1078

    Article  PubMed  Google Scholar 

  20. Elston GN (2005) Cortex, cognition and the cell: New insights into the pyramidal neuron and prefrontal function. Cereb Cortex 13(11):1124–1238

    Article  Google Scholar 

  21. von Foerster H, von Glaserfeld E (2005) Einführung in den Konstruktivismus, 9th edn. Piper Press, Munich

    Google Scholar 

  22. Fox Keller E, Harel D (2007) Beyond the Gene. PLoS ONE 2(11):e1231

    Article  Google Scholar 

  23. Glaserfeld Ev (1990) Teleology and the concepts of causation. Philosophica 46(2):17–42

    Google Scholar 

  24. Goodwin B (2001) The evolution of complexity: How the leopard changed its spots. Princeton Academic, Princeton

    Google Scholar 

  25. Goodwin B, Briere C (1989) A mathematical model of cytoskeletal dynamics and morphogenesis in acetabularia. The Cytoskeleton of the Algae. CRC Press, Boca Raton, pp 219–238

    Google Scholar 

  26. Gould SJ, Lewontin RD (1979) The spandrels of San Marcos and the Panglossian paradigm: A critic of the adaptationist programme. Proc R Soc Lond 205:581–598

    Article  PubMed  CAS  Google Scholar 

  27. Griffiths PE, Gray RD (2000) Darwinism and developmental systems. MIT Press, Cambridge

    Google Scholar 

  28. Griffiths PE, Stoltz K (2007) The cambridge companion to the philosophy of biology. chap Gene, Cambridge University Press, Cambridge, pp 103–119

    Google Scholar 

  29. Hanlon R (2007) Cephalopod dynamic camouflage. Curr Biol 17(11):400–404

    Article  Google Scholar 

  30. Heylighen F, Joslyn C (2001) Cybernetics and second-order cybernetics. In: Meyers R (ed) Encyclopedia of Physical Science and Technology, 3rd edn. Academic, New York

    Google Scholar 

  31. von Holst VE, Mittelstaedt H (1950) Das Reafferenzprinzip. Die Naturwiss 37(20):464–476

    Article  Google Scholar 

  32. Homberg U, Paech A (2002) Ultrastructure and orientation of ommatidia in the dorsal rim area of the locust compound eye. Arthropod Struct Dev 30(4):271–280

    Article  PubMed  Google Scholar 

  33. Jablonka E, Lamb M (2005) Evolution in four dimensions: Genetic, epigenetic, behavioral, and symbolic variation in the history of life. MIT Press, Cambridge

    Google Scholar 

  34. Jablonka E, Lamb M, Avital E (1998) ‘lamarckian’ mechanisms in darwinian evolution. Trends Ecol Evol 13(5):206–210

    Article  PubMed  CAS  Google Scholar 

  35. Jewell E, Abate F, McKean E (2001) The new Oxford American dictionary. Oxford University Press, Oxford

    Google Scholar 

  36. Jonas H (2001 (1966)) The phenomenon of life. Northwestern University Press, Evanston, IL

    Google Scholar 

  37. Kauffman S (1969) Metabolic stability and epigenesis in randomly constructed genetic nets. J Theor Biol 22(3):437–67

    Article  PubMed  CAS  Google Scholar 

  38. Mayr E (1961) Cause and Effect in Biology Kinds of causes, predictability, and teleology are viewed by a practicing biologist. Science 134(3489):1501–1506

    Article  PubMed  CAS  Google Scholar 

  39. Mayr E (1976) Evolution and the diversity of life. Harvard University Press, Cambridge

    Google Scholar 

  40. Merleau-Ponty M (1963 (translation), 1942) The Structure of Behavior. Duquesne University Press, Philadelphia

    Google Scholar 

  41. Minksy M (1975) The psychology of computer vision, chap A Framework for representing knowledge. McGraw-Hill, New York

    Google Scholar 

  42. Nagel E (1979) The structure of science: Problems in the logic of scientific explanation. Hackett Publishing, USA

    Google Scholar 

  43. Niven J (2008) Evolution: Convergent eye losses in fishy circumstances. Curr Biol 18(1):27–29

    Article  Google Scholar 

  44. Noether E (1918) Invariante variationsprobleme. Gott Nachr 235

    Google Scholar 

  45. Noether E, Tavel M (2005) Invariant variation problems. Arxiv preprint physics/0503066

    Google Scholar 

  46. O’Keefe J, Dostrovsky J (1971) The hippocampus as spatial map: preliminary evidence from unit activity in the freely moving rat. Brain Res 34:171–175

    Article  PubMed  Google Scholar 

  47. Oyama S (2000) The ontogeny of information: Developmental systems and evolution. Duke University Press, Durham

    Google Scholar 

  48. Oztop E, Kawato M, Arbib M (2006) Mirror neurons and imitation: A computationally guided review. Neural Netw 19(3):254–271

    Article  PubMed  Google Scholar 

  49. Pais A (1982) Subtle is the Lord. The science and the life of A. Einstein. Oxford University Press, Oxford

    Google Scholar 

  50. Porter J, Baker R (1997) Absence of oculomotor and trochlear motoneurons leads to altered extraocular muscle development in the Wnt-1 null mutant mouse. Dev Brain Res 100(1): 121–126

    Article  CAS  Google Scholar 

  51. Quiroga R, Reddy L, Kreiman G, Koch C, Fried I (2005) Invariant visual representation by single neurons in the human brain. Nature 435(7045):1102–1107

    Article  PubMed  CAS  Google Scholar 

  52. Rosenblueth A, Wiener N, Bigelow J (1943) Behavior, purpose and teleology. Philos Sci 10: 18–24

    Article  Google Scholar 

  53. Ryan L, Cox C, Hayes SM, Nadel L (2008) Hippocampal activation during episodic and semantic memory retrieval: Comparing category production and category cued recall. Neuropsychologia 46(8):2109–2121, DOI http://dx.doi.org/10.1016/j.neuropsychologia.2008.02.030, URL http://dx.doi.org/10.1016/j.neuropsychologia.2008.02.030

  54. Smith JM, Burrian R, Kauffmann S, Alberch P, Campbell J, Goodwin B, Lande L, Raul D, Wolpert L (1985) Developmental constraints and evolution. Q Rev Biol 60(3):265–287

    Article  Google Scholar 

  55. Smith PG (2007) The cambridge companion to the philosophy of biology. Cambridge University Press, Cambridge, chap Information in Biology, pp 103–119

    Google Scholar 

  56. Sterelny K (2005) Thought in a hostile world. MIT Press, Cambridge

    Google Scholar 

  57. Swammerdam J (1737) Biblia Naturae, Sive Historia Insecto, vol 1. IDC (Leiden)

    Google Scholar 

  58. Ton R, Hackett J (1984) Neural mechanisms of startle behavior, Springer, Berlin, chap The Role of the Mauthner Cell in fast starts involving escape in Teleost Fishes

    Google Scholar 

  59. Tracy A, Jarrard L, Davidson T (2001) The hippocampus and motivation revisited: appetite and activity. Behav Brain Res 127(1–2):13–23

    Article  PubMed  CAS  Google Scholar 

  60. Turchin VF (1977) The Phenomenon of Science: a cybernetic approach to human evolution. Electronic URL http://pespmc1.vub.ac.be/POSBOOK.html

  61. Varela F (1979) Principles of biological autonomy. North Holland, New York

    Google Scholar 

  62. Varela F, Maturana H (1987, 1998) The tree of knowledge, 1st edn. Shambala, Boston, MA

    Google Scholar 

  63. Varela F, Maturana H, Uribe R (1974) Autopoiesis: the organization of living systems, its characterization and a model. Curr Model Biol 5(4):187–96

    CAS  Google Scholar 

  64. Wiener N (1961) Cybernetics: or the control and communication in the animal and the machine, 2nd edn. MIT Press, Cambridge

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mario Negrello .

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer Science+Business Media, LLC

About this chapter

Cite this chapter

Negrello, M. (2011). Invariances in Theory. In: Invariants of Behavior. Springer Series in Cognitive and Neural Systems, vol 1. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-8804-1_2

Download citation

Publish with us

Policies and ethics