Herbs, Folklore & Science

Herbology is one of the oldest sciences. Human beings have been using herbs for medicines for thousands of years, and almost every culture has had some herbal medicine tradition. Many modern medicines were derived, originally, from herbal remedies. In fact, it is a mystery as to how 'pre-scientific' cultures discovered some of these herbal concoctions. Some of the herbal effects are quite subtle, others require complex preparation, some herbs are only effective when mixed with other agents. How did our ancestors discover these remedies? This ancient knowledge is a true marvel (Davis 1996, Heatherley 1998).

Worldwide today there is a belief that natural herbal medicines are safer and better than synthetic pharmaceuticals. The fact that almost everyone has an elder who is a herbalist has hindered us from taking a critical look at herbs. (No nice person wants to dis an elder!) For it is not commonly realised that not all of traditional herbal lore is accurate. Some herbs are in fact toxic, others are merely placebos, and most have a milder pharmaceutical efficacy than tradition has maintained (Thase & Loredo 1998).

Scientific investigation has shown that herbal efficacy is due to natural chemicals in the herbs. In other words, herbs are drugs. Often some of the chemicals are pharmaceutically active, others are bio-irritants, others are toxins, and still others have little effect on the human body. All of these chemicals can be mixed up in a wild melange in a single herb (Greive & Leyel 1931, Thase & Loredo 1998). The mixtures depend not only on the species of plant, but also on individual genetic traits, and on growing conditions. Concentrations of active ingredients therefore vary widely between individual plants (Davis 1996, Thase & Loredo, 1998).

St. John's wort (Hypericum perforatum) is a common Eurasian weed. There are many other Hypericum species, but St. John's wort is commonly believed to have the strongest pharmaceutical properties. St. John's wort seems to have some ability to boost the moods of people are emotionally depressed , i.e. it is an antidepressant. Studies seem to indicate that hypercin, a dianthrone derivative, is one of the antidepressants. Another compound hyperforin blocks the re-uptake of several neurotransmitters. Hyperforin's mode of action is similar to many artificial anti-depressants. Other ingredients such as catechin and epicatechin seem to have some anti-inflammatory, antibacterial and antiviral properties (Thase & Loredo 1998). However, only the hyperforin has been subject to full scientific tests as of 2000 (Spinella 2001).

None of the chemicals in St. John's wort have proven to be superior to synthetic drugs. As of 2001, about 30 studies showed St. John's wort to be better than a placebo. About 10 studies show it to be equivalent to synthetic antidepressants such as Prozac. However, it has not been shown to be superior to Prozac (Rist 2002).

Hypercin does have some side-effects, it is phototoxic. It can react in sunlight to irritate and inflame the skin of those who have ingested too much of the chemical. St. John's wort can activate the liver enzyme CYP3A. Too much CYP3A activity can cause the liver to breakdown 'toxic' compounds. This can cause St. John's wort to interfere with prescribed medications. Some of the drugs it diminishes the effects of include: anticlotting agents, immune suppressants, certain HIV medications, and the birth control pill (Rist 2002). Also, like many other substances, St. John's wort can cause allergic reactions in some people (Thase & Loredo 1998).

Since hyperforin is an antidepressant, it should not be combined with other antidepressants without proper medical guidance. Essentially, this could entail overdosing on antidepressants (Spinella 2001).

Synthetic drugs are usually more accurately dose controlled than are herbs. Furthermore, herbal remedies have not been as critically tested as have artificial drugs. Therefore, uncritical acceptance of all things herbal should cease, because there is risk to human health involved. Herbs like any other drug should be used with caution (Thase & Loredo 1998).

However, in many countries there is an economic advantage to herbs like St. John's wort. Herbal remedies are often cheaper than factory made drugs. For example, in many cities in India naturopathic and homeopathic shops are as common as pharmacies. This reflects the economic reality of India just as much as it reflects local beliefs (White 1995). Herbal remedies are readily available in all parts of the world, so are interesting variants of herbal tradition. Herbal traditions are quite interesting right here in the Americas, where herbal traditions of Amerindian, Afro-Caribbean and European origin have co-existed, mixed and often fused (Davis 1996, Heatherley 1998).

Herbal traditions, if for no other reason than that they are ancient, should be preserved. Herbal remedies are drugs. Associations between herbs and the zodiac and sympathetic magic, are all purely folkloric. There is no reason to believe that herbs are magical panacea. Each herb species should therefore be subject to safety tests and subject to recall if they are found to be unsafe.

Rarity of Herbs

Many wild herbs have been over-harvested. Unfortunately, this means that some species have become endangered. Many herbs are not common plants, and since it is cheaper to pick plants than grow them, many herbalists head for wild areas when they collect. (There is also a belief, mostly unjustified, that wild herbs are better.) The fact is, there are too many people in the world to tolerate the exploitation of wild herbs.

Wild herbs that have been harvested nearly to extinction include: tendrilled fritillary (Fritillaria cirrhosa), tetu lakha (Nothatodytes foetida), kusta (Saussurea lappa) and African cherry bark (Prunus africana).

All of these species have so far escaped actual extinction. Changing health fads, and collapsing supplies, have basically destroyed the markets for these herbs one by one (Edwards 2004). The herbal ransacking was a waste and a shame, none the herbal remedies were as effective as herbalists had claimed.

References

Davis, Wade. 1996. One River - explorations and discoveries in the Amazon rainforest. Touchstone. New York.

Edwards, Rob. 2004. No remedy in sight for herbal ransack. New Scientist. 181(2429): 10-11.

Grieve, M. and Leyel, C.F. (Ed.). 1973 (1931). A Modern Herbal - the medicinal, culinary, cosmetic and economic properties, cultivation and folklore of herbs, grasses, fungi, shrubs and trees with all their modern scientific uses. Tiger Books International. London.

Heatherley, Ana Nez. 1998. Healing Plants - a medicinal guide to native American plants and herbs. Harper Collins Publishers Ltd. Toronto.

Park, Robert L. 1997. Alternative Medicine and the Laws of Physics. Skeptical Inquirer. Vol. 21, No. 5. 24-28.

Soil, Climate & Biogeography

Tree Species

Forest Regions

Phytopathology

Physiological Plant Ecology

Each species of plant, even individual phenotypes, have limited conditions to which they can adapt. For example, apples (Malus) grow very well in parts of California, but they do not fair well in Kenya. California has a mild winter. Many parts of Kenya have two rainy seasons, the maize and millet rains, and two dry seasons per year. All seasons being fairly warm.

Apples are adapted to annual cycles of winter dormancy and summer growth. They are a temperate species. Apples require a chilling period, a dormant period before next year's buds can develop. This dormant period is initiated by low temperatures.Without this chill period, leaf and flower buds for the next year will not be set. For apples, this chilling period ranges from 700 hours to 1500 hours, depending on the variety.

Apples, like all plants, adjust their metabolism to the season. They act as if they 'expect' one season to follow another, and they adjust in advance for these changes. If the 'expected' changes do not occur, the plant is left mal-adjusted.

Many other examples could be given. This is the reason that plants often do fine, for a while, outside of their natural range. But, they succumb eventually to late frosts, or to temperature extremes, for which they have insufficient capacity to cope.

On the other hand, sometimes plants are, by chance, pre-adapted to places for which they were not endemic. Nowadays Opuntia cacti are common around the Mediterranean, and Tamarix grow abundantly in Mexico. In pre-Columbian times, before people spread these plants about, Opuntia were endemic to the Americas, and Tamarix strictly natives of the Old World.

There are many factors controlling where, and when, and how long, plants can grow in given locals. One of the most important skills in gardening, horticulture and silviculture, is to know what, where and when to plant.

Hybrids & Clines

Many supposedly separate tree species hybridise in nature. Sometimes these hybrids form where their ranges overlap. (In other words, the so-called species may better be thought of as subspecies – i.e. races.) Often the different species have different habitat preferences. Thus, while neighbours, they tend to grow in different places. Sometimes, closely related species are separated by a natural barrier. For example, the boreal forest's jack pine and Appalachian's Virginia pine are very similar. These pine seldom hybridise because their natural ranges do not overlap. Many of the closely related oaks have different preferred habitats. They hybridise only occasionally in nature. Species is supposed to be defined as a population of organisms that have no mutual impediment to sexual reproduction in its natural state. (In reality, botanists do not strictly follow this definition.) Sometimes, the ends of a chain of hybridisable species are distinctly different species that do not cross in the wild. This is very evident in the cottowood to balsam poplar chain. Such ranges of variation are called clines. Examples of North American tree 'species' that intergrade into related species include:

black spruce - red spruce

Colorado blue spruce - Engelmann spruce - Sitka spruce & white spruce.

lodgepole pine - jack pine --- Virginia pine.

balsam fir - alpine fir.

red juniper - Rocky Mountain juniper.

cottonwood - plains cottonwood - narrowleaf cottonwood - black cottonwood - balsam poplar.

big-shellbark hickory - pecan - bitternut - shagbark - pignut hickory.

honey locust - Texas locust - waterlocust.

upland live oak - live oak - sand live oak - dwarf live oak

bur oak - swamp white oak - white oak - post oak - Rocky Mountain oak.

dwarf chinkapin oak - chinkapin oak - chestnut oak.

northern red oak - black oak - pin oak - scarlet oak - southern red oak.

crus-galli hawthorn - succulent haw - chrysocarp haw - flabella haw - punctate hawthorn.

silver maple - swamp maple - red maple.

black maple - sugar maple - Florida maple (= southern sugar maple) - chalk maple.

China, Beringia & Axel Heiberg

Autopoiesis

‘Cellular Intelligence’

D. Andrew White M.Sc. 31/10/2007

Living things are special manifestations of matter. The self-building and self-replication seem to be properties unique to biota. For the last several decades there has been much talk of the ‘cybernetic’ features of life. That is, there has been a superseding of the old ‘clockwork’ metaphor with one based on the computer metaphor. Even more a propos is the idea that biota are like the software virtual entities known as cellular automata. Biota have evolved to become evermore self-adjusting – or adaptable. This adaptability has been ratcheted-up by natural selection to ever higher levels of complexity. Eventually bio-systems attained a level of sophistication that they became quasi-intelligent. Which brings up the question, is the Creator still at work? Are cells themselves intelligent? Or is biotic intelligence just another metaphor?

Several words have been coined for this ability of biota to build themselves. ‘Entelechy’ was once a popular term for this trait. The preferred term is nowadays ‘autopoiesis’. The idea of autopoiesis as we know it is based on the work of the biologists Humberto Maturana and Francisco J. Varela. The basic idea is that living things dynamically maintain their structure. Furthermore, they reproduce. They are therefore somehow capable of self-maintenance and self-building. The word ‘autopoiesis’ is a transliteration of the Greek for: self (autos) writing-building (poiesis). F.J. Varela defined autopoietic systems as those structures that:

(1) Continuously regenerate and actualise the network of interactions that produce them, and
(2) They constitute a system that acts as a unified entity.

Many of the strategies of biota seem to be very clever. Consider the Myxobacteriales or bacterial moulds. Like many ‘colonial’ bacteria, each bacterium can communicate chemically with other bacteria. The co-operating bacterial cells specialise into different roles. They even have self-defence against ‘cheating’ bacteria that fail to co-operate. When sporulation is signalled the cells over a broad area are called together. They form a slug-like mass which crawls up to an exposed location. The cells collectively form a small toadstool-like sporangium. Some cells become the stalk of the spore-bearing body, others form the actual spores. The stem cells sacrifice their own continuance for their comrades’ chance at dissemination (Ben-Jacob et al 2004). In other words, the myxobacteriales co-operate strategically and seemingly ‘altruistically’.

Some of the mind-like attributes of life might be of purely mechanical origin. The Belgian cyber-philosopher Francis Heylighen proposed that life is dependent upon natural selection working at a variety of levels. Selection is involved in sorting out self-enhancing systems from self-destroying systems. The emergent properties that are life arise out of the struggle between self-replication (copying) and selection (sorting). While not downplaying other factors, theorists such as Heylighen argue that natural selection is a key ingredient in the generation of autopoiesis (Heylighen & Gershenson 2003).

One biologist, G. Albrecht-Buehler has detailed the workings of protozoan cells and showed how they process sensory information, assess its import, and respond in a nuanced fashion. Many protozoan cells can detect infrared light, exchange chemical signals with other cells and navigate around obstacles. He revived the idea of ‘cellular intelligence’ and attempted top explain it in material terms. More controversial has been Albrecht-Buehler hypothesis that the centromes of cells are control centres and that microtubules pass signals around inside the cell. The extent to which these tubes act as logic gates is still an open question (Albrecht-Buehler 1985).

Experiments indicate that some protozoa, such as the ciliate Stentor coerulens, can learn. If prodded with mechanical stimuli the protozoon defensively retracts. Repeatedly prodding elicits ever diminishing responses, provided the irritant is not actually harmful. Experiments indicate that combinations of mechanoreceptor ‘senses’ gives the little protozoon the ability to learn simple tasks. The creature can learn the best escape route from a very simple maze – a thin tube. Basically, it can learn whether the best escape is downwards or upwards (Wood 1988). The effect is considered to be a form of operant conditioning. Doubtless similar conditioning occurs in the wild. Though, it may be difficult to see these behaviours from the outside.

Another ciliate, Paramecium caudatum, can also be habituated and also learn to escape from a tube-maze. There are indications that the protozoon can associate two kinds of stimuli. They can be ‘taught’ to associate vibration and electrical stimulation. Other kinds of discriminatory learning can also occur (Armus et al 2006). The effect is a conditioned readjustment of the protozoon’s otherwise innate responses, i.e. operant conditioning.

The Phycomyces blakesleeanus fungus has been found to be able to learn after-a-fashion. The fungus naturally seeks out light. This is basically their way of finding open areas to release their spores. The sporangiophores of Phycomyces can become habituated to light. That is, it can ‘learn’ to ignore or tone-down responses to light stimuli that are repeated too often. (Ortega & Gamow 1970). Habituation is widely considered to be one of the ‘lowest’ forms of learning.

Plants are also capable of habituation. The sensitive plant (Mimosa pudica) is a legume that responds to touch. If touched, its compound leaves fold-up. This can protect the plant from grazing animals. If they are repeatedly prodded by the same kind of stimulus they habituate to it. Eventually they virtually ‘ignore’ that kind of stimulus. Interestingly, they can moderate their sensitivity to tactile stimuli that differ in rather subtle ways. For example, they can be conditioned to distinguish wet droplets that touch them from dry poking objects. While habituated to one kind of touch, they still can retain their sensitivity to the other kind (Applewhite 1972).

By the turn of the millennium the idea of ‘biotic intelligence’ was widely taken for granted. James Lovelock, Lynn Margulis, Dorian Sagan and many others began to write as if it were self-evident that evolution has perfected organisms such that they have become purposive. Margulis, for example, has often described the various biochemical means by which a protozoon can maintain its internal homeostasis. This balancing act figuratively speaking is like proto-intelligence. Very few researchers have directly attributed ‘intelligence’ to bio-systems. Mostly they merely suggested a tight analogous relationship between bio-systems and actual bona fide intelligence. It was widely agreed, even by the sceptics, that life has developed some attributes that are at least reminiscent of ‘mental function’.

The immunologist E.J. Steele and T. Steele began describing immunocyte interactions as ‘quasi-Lamarckian’. The idea being that evolution is not always directed by external selection. In some cases selection operating inside an organism can sort and cull cell lines. H. Hoenigsberg hypothesized that such ‘internal selection’ was the original impetus in the evolution of cell differentiation. Inter-cellular struggle eventually gave rise to cells working in co-operation in the embryogenesis of multi-cellular creatures. If true, this scenario implies that evolution can have a high degree of internal directivity. Lamarck’s vision of evolution having internal foresight may not have been totally off target (Steele et al 1981, Steele et al 1989, Hoenigsberg 2003).

The physicist Eshel Ben-Jacob, in Israel, has argued that bacterial colonies evolve by endogenous adaptive mutagenesis. It is as if a bacterium is programmed to allow hyper-mutation in a select set of genes apropos to changing environmental conditions. Furthermore, these hyper-mutations can be shared via plastid exchange and spread rapidly through the colony. One can appreciate therefore that there is a semblance of a memory-learning algorithm in bacterial colonies. An individual bacterium does not learn much in itself. The algorithmic ‘learning’ of the collective works at the multi-generational level. It is not like animal learning that occurs inside of a single organism and during its lifetime (Ben-Jacob et al 2004).

Claus Emmeche has critiqued the computational metaphor for life, but he has found some merit in it. Likewise the team of Steen Rasmussen, Carsten Knudsen and Rasmus Feldberg studied the relationship between computer programs and life. This work suggested that biota is somehow similar to programmable devices. The fact that cellular networks are like programmes to some degree was not in doubt. The novelty was the suggestion that cell interactions can be close enough to computational networks for the computer metaphor to be usefully applied to life (Emmeche 1994).

One recent proponent of the intelligent biota idea was Frank T. Vertosick Jr. Vertosick, an American neurosurgeon, argued that intelligence varies by degree, and is not confined to brains, nor is it restricted to individual animals. His most forceful claim was that Darwinian evolution as a whole is like intelligence in that it is similar to an algorithm that learns. He included examples such as the mammalian immune systems, the rapidly adaptive natural selection of bacteria, and even the regulatory logic of social insects’ interactions (Vertosick 2005).

In Scotland the molecular biologist Anthony Trewavas suggested that plants have some features similar to intelligent behaviour. In particular, it is well known that plants can be preconditioned or acclimated. For example seeds can be hardened by exposure to cold, and become more tolerant of cold-spells than are seeds not so pre-conditioned. Basically when a plant responds to a stimulus, the response can become quicker during repeat stimulations. Plants adaptively respond in many ways, including osmotic adjustments to calcium levels and by protein syntheses. Either cold or drought stress will increase the expression of these proteins. The physical adjustments wrought by the stress can linger around after an initial stimulus. This lingering effect preconditions the plant for further stresses (Trewavas 1999 & 2003). This kind of response is certainly at least a little bit like memory.

The Italian horticultural botanist Stefano Mancuso has become famous for his references to ‘plant smarts’. Plants in their pre-conditioned responses do seem to have a sort of memory. Furthermore, the growing apices of roots or shoots act like ‘command centres’ for co-ordinating signals within a plant, signalling whether to stimulate or to inhibit other tissues. In addition to chemical signals, electrical impulses are also used for cell–to-cell messaging. Plants can seemingly ‘compute’ solutions to conflicting physiological demands (Baluška et al 2004, Brenner et al 2006).

‘Memory’ in plants can be even stranger. Some plants determine which bud shall become the dominant apex by external signals. In the case of Bidens pilosa seedlings, irritating one cotyledon can simulate a lateral bud on the opposite side. Usually this is most evident when the leading bud is removed, and the laterals are thus ‘released’, the bud opposite the irritation becoming the new leader. The release of the lateral can be delayed by delaying the removal of the apex. This stimulation of the cotyledon can be ‘recalled’ even after very long delay (Tafforeau et al 2006). Plant reactions are certainly quite comparable in their complexity to the behaviours of ‘lower’ animals like jellyfish and sea-sponges. If the very same behaviours occurred in animals they would be considered examples of primitive cognition.

Biotic processes can be somewhat analogous to intelligence. Consider for example the true slime mould Physarum polycephalum. In the early 2000s Toshiyuki Nakagaki, in Japan, found that slime moulds could ‘calculate’ the shortest route to food. They could ‘solve’ mazes. Nakagaki’s team placed a slime mould in a maze. There was a food source at two portals of the maze. At first the slime mould’s plasmodium spread out its slimy tendrils throughout the maze. Though, once the food was found the whole plasmodium condensed into a few strands. Eventually these strands condensed into a single strand spanning the shortest route between the two sources of food (Nakagaki 2003).

Since the 1930s it has been suggested that sexual reproduction is a strategy for evolving. Research suggests that ‘evolvability’ can be a set of traits that are themselves favoured by natural selection. Under certain conditions sexual reproduction has a strategic advantage over asexual reproduction. Sexual recombination has the advantage of mixing alleles from different lineages. This gene mixing makes evolution at once more rapid and more controlled. Some other examples of evolvability traits include the hyper-mutation in bacteria, and the chromosome crossing-over of eukaryotes (Stewart 1993).

In computing theory information must be processed for a system’s ordered states to increase. Biota apparently obeys both the laws of thermodynamics and the ‘laws’ of computation. Life increases local order (negentropy) at the expense of external disorder (entropy). Metabolism utilises externally derived energy (via. catabolism) to forcedly press molecules into an ordered state (via anabolism). Overall the external disordering caused by life is greater than the order life creates.

It has sometimes been maintained that ‘natural selection’ is logistically incapable of creating ‘specified complexity’. However, computerised models of selection belie this presumption. Clearly natural selection is at least logically possible. But just because something is not self-contradictory, that does not mean that it really does happen in practice. So, is natural selection physically feasible? Empirical studies seem to indicate that it really does occur (Heylighen & Gershenson 2003). The claim of autopoietic theory is that this selection is has become biased in favour of teleonomic traits.

Does life evolve ‘on purpose’? Does it ‘plan’? It almost seems so. Here it is important to remember that bio-theorists are not positing that physical processes have an innate intelligence. Rather, the more mind-like biota evolved gradually from less mind-like predecessors. Natural selection has ratcheted-up the level of biotic complexity over time. Eventually this selection gave rise to organisms that can adjust to their environment. This autopoiesis could then itself be fine tuned by natural selection. These autopoietic systems have at least a metaphoric resemblance to ‘intelligence’.

References

Applewhite, P.B. 1972. Behavioral plasticity in the sensitive plant, Mimosa. Behavioral Biolog. 7(7):47-53.

Armus, H. L., Montgomery, A. R. & Gurney, R. L. 2006. Discrimination learning and extinction in paramecia (P. caudatum). Psychological Reports. 98:705-711.

Baluška F., Mancuso, S., Volkmann, D. and Barlow, P.W. 2004. Root apices as plant command centres: the unique ‘brain-like‘ status of the root apex transition zone. Biologia (Bratislava). 59: 7-19.

Ben-Jacob, Eshel. ; Becker, Israela ; Shapira, Yoash and Levine, Herbert. 2004. Bacterial linguistic communication and social intelligence. Trends in Microbiology. 12(8): 366-372.

Bergson, Henri. 1948. L’Évolution Créatrice. 77ieme Édition. Presses Universitaires de France. Paris.

Brenner, E.D. Stahberg, R., Mancuso, S. Vivanco, Baluška, F. and Van Volkenburgh, E. 2006. Plant neurobiology: an integrated view of plant signaling. TRENDS in Plant Science. 11(8): 413-419.

Emmeche, Claus .1994.The Computational Notion of Life. Theoria - Segunda Epoca 9 (21): 1-30.

Hameroff, S.R. (1994) Quantum coherence in microtubules: A neural basis for emergent consciousness? Journal of Consciousness Studies1(1):91-118.

Hameroff, Stuart; Rasmussen, Steen and Månsson, Bengt. 1989. "Molecular automata in microtubules: basic computational logic of the living state?", pp. 521-553 in: C.G. Langton, ed.: Artificial Life, (Santa Fe Institute Studies in the Sciences of Complexity, vol.6). Redwood City, Calif.: Addison-Wesley Publ. Co.

Hellingwerf, KJ. 2005. Bacterial observations: a rudimentary form of intelligence? Trends in Microbiology. 13(4):152-158.

Heylighen, Francis. and Gershenson, Carlos 2003. The Meaning of Self-organization in Computing. IEEE Intelligent Systems. 18(4): 72-75.

Hoenigsberg, H. 2003. Cell biology, molecular embryology, Lamarckian and Darwinian selection as evolvability. Genet. Mol. Res. 2 (1): 7-28.

Margulis, Lynn and Sagan, Dorian. 1995. What is Life? Simon & Schuster. New York.

Nakagaki, Toshiyuki; Yamada, Hiroyasu and Hara, Masahiko. 2003. Smart Network Solutions in an Amoeboid Organism. Biophysical Chemistry. 107(1): 1-5.

Ortega, J.K.E. and Gamow, R.I. 1970. 1970. Phycomyces: habituation of the light growth response. Plant Physiology. 168: 1374-1375.

Sharov, A. A. 1998.From cybernetics to semiotics in biology. Semiotica 120: 403-419.

Steele, E.J.;, Lindley, R.A. and Blanden, R.V. 1998. Lamarck’s Signature, How Retrogenes are Changing Darwin’s Natural Selection Paradigm. Helix Books, Perseus Books, Reading, MA, USA.

Steele, T. 1981. Lamarck and immunity; a conflict resolved. New Sci. 90: 360-361.

Stewart, J. E. 1993. The maintenance of sex. Evol. Theory. 10: 195-202.

Stewart, J. E. 1995. Metaevolution. Journal of Social and Evolutionary Systems. 18: 113-114.

Tafforeau, M., Verdus, M.C., Norris, V., Ripoll, C. and Thellier, M. 2006. Memory Processes in the Response of Plants to Environmental Signals. Plant Signaling & Behavior. 1(1): 9-14.

Trewavas, Anthony.1999. Commentary: How plants learn. Proceedings of the National Academy of Sciences. 96 (8): 4216-4218.

Trewavas, Anthony. 2003. Aspects of Plant Intelligence. Annals of Botany 92: 1-20.

Varela, F. 1986. Sur l'emergence de l'ordre dans les reseaux neuronaux modulaires in: Jeux de Reseaux, Cahiers STS du CNRS, Nº9-10, Paris, pp.201-209.

Varela, F. 1988. Structural coupling of simple cellular automata: On the origin of meaning in: E.Secarz, F.Celada, N.A.Mitchinson, and T.Tada, The Semiotics of Cellular Communication in the Immune System, NATO ASI Series, Vol. H23, Springer-Verlag, New York, pp. 151-161.

Varela, F.; Anspach, M. and Coutinho, A. 1991. Immuknowledge: Learning mechanisms of somatic individuation in: J.Brockman (Ed.), Doing Science, Prentice-Hall, New York, pp.237-257.

Vertosick, Jr., Frank T, 2002. The Genius Within – discovering the intelligence of every living thing. Harcourt, Inc. New York.

Wolfram, Stephen. 2002. A New Kind of Science. Wolfram Media, Inc. Champaign, Illinois.

Wood, David C. 1988. Habituation in Stentor: Produced by Mechanoreceptor Channel Modification. The Journal of Neuroscience. 8(7): 2254-2258.

West-Eberhard, Mary Jane. 1998. Evolution in the light of developmental and cell biology, and vice versa. Proceedings of National Academy Sciences. 95, 15: 8417-8419.