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Plant Neurobiology: Lessons for the Unity of Science

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Part of the book series: Logic, Epistemology, and the Unity of Science ((LEUS,volume 24))

Abstract

I propose to study the integration of contemporary scientific knowledge in cognitive neuroscience and plant neurobiology in order to assess the Unity of Science hypothesis. Oppenheim and Putnam (Unity of science as a working hypothesis. In: Feigl H, Maxwell G, Scriven M (eds) Minnesota studies in the philosophy of science. University of Minnesota Press, Minneapolis, pp 3–36, 1958. Reprinted in Boyd R, Gasper P, Trout JD (1991) The Philosophy of Science) considered the sort of mereological support that the Unity of Science hypothesis may receive from the principles of ontogenesis and evolution. I shall argue that a mechanistic understanding of eukaryote communication via the propagation of action potentials shows that the principle of ontogenesis does not support the hypothesis. Although the safest bet in my view is to press on a particular form of indirect evidence that the principle of evolution provides, I shall conclude that at present the Unity of Science remains an open empirical working

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Notes

  1. 1.

    For an introduction to plant neurobiology, see http://www.plantbehavior.org/neuro.html

  2. 2.

    The crucial difference between APs mechanistic components in animals and plants is that the electric profile of APs in the former is implemented, mainly, via potassium and sodium channels, whereas in the latter case, potassium, chloride, and calcium channels are primarily involved. For a classic review of plant APs, see Pickard (1973).

  3. 3.

    Ion channels implement excitability in cellular tissues in animals, fungi, and plants. As a matter of fact, they can be traced back to bacteria in philogenia (Hille 2001).

  4. 4.

    For a comparison of APs in animal and “plant neurons” in Nitella and the giant axon of squids, see Cole and Curtis (1938, 1939). For a brief but interesting historical overview of the concept of nervous systems in plants, see Stahlberg (2006).

  5. 5.

    APs propagate from stem to root and viceversa via the phloem sieve-tube system.

  6. 6.

    Obviously, were we to consider the modelling and quantification of specific APs in animals and plants, a number of differences would be found. Resting potentials in Chara cells, for example, are more hyperpolarized than their counterpart in animal cells. Also, depolarization is induced by anions, rather than by cations as is the case in the triggering of depolarization in animal APs (see Kikuyama 2001). In addition, APs amplitudes and refractory periods are significantly larger in Chara, taking up to several seconds, whereas they last msecs in animal nerve cells.

  7. 7.

    In fact, it has been suggested many times that the sine qua non of representation-based competency is off-line adaptive behaviour (see, for example, Clark 1997). For a critical appraisal of Clark’s suggestion in the context of representational theories of cognition, see Calvo Garzón (2008).

  8. 8.

    For plant life based on photosynthesis there was no need to evolve locomotion. In this way, whereas animals found a heterotrophic way out of their energy-consumption needs (hunting, etc.), plants found an autotrophic solution (motionless organic synthesis) (Trewavas 2002).

  9. 9.

    Carnovorous D. muscipula and A. vesiculosa, for example, would furnish us with a primitive form of plant memory subject to a mechanistic interpretation in the context of off-line adaptive behaviour. In the case of D. muscipula, an AP is generated whenever an upper trap hair is bent. Crucially, one single stimulation of the hair does not trigger the closing of the trap. For the trap to close it is necessary a second AP that takes place only when another hair is bent within 40 s after the first AP has been generated (see Baluška et al. 2006a, b, for the details). We may then interpret the second AP as a primitive form of plant memory.

  10. 10.

    Functionally similar results obtain in the case of shoots. Other typical examples include making decisions about the number of flowers to produce 1 year in advance of the flowering season, or branching-related decisions made with in some cases years of anticipation. Some plants predict potential future shades out of reflected far-red/red light. Also, some trees synchronize their metabolic activity with non-drought periods after exposition to long epochs of rain drought (see Trewavas 2005, and references therein).

  11. 11.

    Since plants in cabinet 2 had only been illuminated vertically, the re-orientation exhibited could only be due to the sunrising information being stored in advance.

  12. 12.

    Circadian clocks are a wide-spread trick that evolution found in order to keep track of the rythms of nature in the absence of direct stimulation. In evolutionary terms, circadian clocks have emerged as a minimum of four times (see Dodd et al. 2005). It is then clear that organisms endowed with such an estimate of ecological cycles must have some sort of Darwinian advantage.

  13. 13.

    Bickle (2003) has recently presented an illustration of a successful linkage between lower level molecular mechanisms and stable overt behaviour. He contends that an explanation of ‘quantitative behavioral data at the level of biochemical pathways and intracellular molecular mechanisms’ is already on offer. Specifically, he shows how particular behavioural data can be explained at the level of the molecular mechanisms that implement long-term potentiation (LTP). For a discussion of linkages between lower and higher levels in the context of dynamicism, see Calvo Garzón (2008).

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Acknowledgements

I would like to thank Paul Humphreys, John Symons and Anthony Trewavas for their comments on a previous version of this manuscript. Preparation of this manuscript was supported by DGICYT Projects HUM2006-11603-C02-01 (Spanish Ministry of Science and Education and Feder Funds) and FFI2009-13416-C02-01 (Spanish Ministry of Science and Innovation), and by Fundación Séneca-Agencia de Ciencia y Tecnología de la Región de Murcia, through project 11944⁄PHCS⁄ 09.

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Garzón, P.C. (2012). Plant Neurobiology: Lessons for the Unity of Science. In: Pombo, O., Torres, J., Symons, J., Rahman, S. (eds) Special Sciences and the Unity of Science. Logic, Epistemology, and the Unity of Science, vol 24. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-2030-5_8

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