Thanks Jon for your links. For the benefit of members who are not familiar with semiotic theory and why it is important for the life sciences...
Semiotic theory... namely, the semiotics of CS Peirce and the biosemiotics of Jakob von Uexküll, holds the greatest promise for an axiomatic framework for the life sciences. We are all familiar with the axiomatic framework that Isaac Newton provided for the physical sciences. A comparable axiomatic framework is absent from the mainstream life sciences. There is good reason to anticipate semiotic theory to fix this dire situation.
All living organisms share the same fundamental principles, best understood within the context of semiosis. The triadic scheme of Peirce relates to the three categories, namely, firstness, secondness and thirdness. These three categories can be best understood in the context of motivation, association (associative learning) and habituation, and they apply throughout all levels, including the cellular.
Eric Kandel has done considerable research in associative learning and habituation in neurons (e.g., his work on Aplysia). And Klopf’s thesis of associative learning in neurons (1982) has been successfully implemented in neural net architectures, such as that of Mobus (given that the hard-wired circuits of neural nets persists across time, we can assume habituation to be a given, at least as an approximation... thus the single missing parameter is motivation). Furthermore, if bacteria “communicate like neurons in the brain” (McDonald 2015), we can infer that the same principles apply to bacteria. Googling around on search terms such as [habituation singe cells] or [associative learning single cell] yields plenty of results to explore.
Forbes writer Morris (2018) references the work of Monica Gagliano, who has shown that plants also make choices from the environment and learn by habituation and association.
Systems theorist Humberto Maturana received his original inspiration from the biosemiotics of Jakob von Uexküll (Wikipedia 2018).
Semiotic theory has enormous potential as a solid axiomatic framework for the life sciences. A lot of concepts come together within the semiotic paradigm. For example, Hebb’s rule (neurons that fire together wire together).
Kandel, E. R. & Hawkins, R. D. (1992). The biological basis of learning and individuality. Scientific American: Mind and Brain, 267(3), 53-60.
Klopf, A. H. (1982). The hedonistic neuron: A theory of memory, learning and intelligence. Washington, DC: Hemisphere.
McDonald, K (2015). Biologists discover bacteria communicate like neurons in the brain. UCS San Diego News Center:
Mobus, George E. “Toward a Theory of Learning and Representing Causal Inferences in Neural Networks.” In Neural Networks for Knowledge Representation and Inference, edited by D. S. Levine and M. Aparicio. Lawrence Erlbaum Associates, Hillsdale, New Jersey, 1994: 339-374:
Morris, A (2018). A mind without a brain: The science of plant intelligence takes root. Forbes:
Wikipedia contributors. (2018, May 22). Humberto Maturana. In Wikipedia, The Free Encyclopedia.
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