THE VITAL FORCE
New Science, Vitalism, & Healing
by Guido Masé
Guido Masé is a clinical herbalist, herbal educator, garden steward specializing in holistic Western herbalism, valued columnist for Plant Healer Magazine, and esteemed teacher at the upcoming Traditions in Western Herbalism Conference atop New Mexico’s Sky Island (click on: www.PlantHealer.org/intro.html). Guido’s teaching style is a good fit for Plant Healer publications and events, focusing as it does on conveying the interconnections within the human organism and between the organism and its surrounding ecology, with a constant eye to the amazing beauty such study reveals: at any level, and in many different “languages”, herbs mirror people, the plant and animal kingdoms grew up together as complements. Such a relational awareness provides meaning and context, critical elements to understanding and also to healing. Learn more about his work and the Vermont Center for Integrative Herbalism school programs at: http://www.vtherbcenter.org
The following essay is excerpted from the Summer issue of Plant Healer Magazine, available by subscription. To read an excerpt of an in-depth interview with Guido in an upcoming issue of Herbaria Newsletter, subscribe for free by entering your name and email at: www.PlantHealer.org
When I get to the top of a hill, or to a rocky outcrop in the forest, I like to take a moment and put my hands on the raw stone. It can feel hot, if it is exposed in the middle of a summer day; or cool, if it is deep in the shade of the forest. From here, if I slow down a bit, I can get a sense of the roots of the mountain, deep and rocky, cracked and trickling with water, deeper and deeper until it almost feels like I am in touch with a kind of consciousness. But are rocks conscious? Are they alive? Perhaps not in the traditional sense. Although without these rocky bones, the water would not flow the way it does. Streams and swamps would be different, soil would build up in different places. Different trees would grow, different birds would alight on different branches, we would walk different trails and build our homes in different ways. In short, without these rocks, everything would be different. Scoured by glaciers long ago, these stones are a vibrant, essential part of this valley. If the valley is alive, then the rocks must share a piece of its consciousness. Stones, plants, fungi and beasts co-evolved.
What does this mean? Can life forms be really simple – as simple as a pebble in the streambed? Can all the pieces of an ecosystem hold a kind of consciousness, maybe not exactly like ours, but still alive and perceptive? If you speak with healers from many different traditions, your answer will most often be affirmative. There is a vitality that courses through all of the world, from the waters of the ocean to the rocks of the highest mountains. There is vital force – and it may actually predate matter. It is pattern-organizing, it possesses understandable features, it is self-similar at many levels. Or so the story goes.
But this vital force, the élan vital, has been a discredited concept for over two hundred years in the Western system of thought. Those of us who talk about vitalism, about nourishing this power in our gardens, our forests, our bodies and spirits, are ostensibly barking up the wrong tree: a tree that withered and died long ago. So it becomes very difficult, in academic circles, in writing, or even at family gatherings, to have conversations about vitalism, energetics, or other models that speak of qi, unseen forces, humors and balance in our physiologies. Energy systems are an archaic way of thinking. If there is an “energy” coursing through the universe, it is the dissipative force: everything is fading into a slow, homogenous dust. Entropy rules. Vitalism is dead.
Or is it? The Taoist masters talk about a “way” that generates all things, but also grinds them into dust. All around us, we see life increasing in richness. How can we reconcile the homogenizing force of entropy with the “clumping” and complexity everywhere? Many argue that this “clumping” is a rarity – and that may be the case – but it seems that, out of an initial clumpy distribution of energy in the universe, matter and life have exploded into greater and greater diversity in those rare places of high energy concentration. Why is this? Why did the dust surrounding our proto-star clump into planets? Why did the crust of our planet become so complex, when it was once mostly molten silicates? It all makes little sense, because concentrating matter into planets is the exact opposite of diffusion (and diffusion is a clear outcome of the entropic drive).
It turns out that built right in to the concept of entropy is a tendency to generate more and more complex structures. Jeremy England, a researcher at the Massachusetts Institute of Technology, spends his days analyzing dissipative structures: systems that take in energy and efficiently distribute it over a wide area. The systems in question are exposed to an energy source and are suspended in a bath of some kind: water, air, plasma. A matrix. What the England lab has discovered is that a system of atoms or particles, when caught between an energy source and a matrix, will continually rearrange itself, increasing in complexity and reproducing its structure.
In so doing it dissipates energy into the matrix more and more efficiently. In other words, life arises to better fulfill the goals of entropy. Birth and death are the same thing. Yang flows into yin, harnesses substance, and generates the ten thousand things.
While this may help explain how life and a drive to complexity may exist hand-in-glove with the entropic drive of the second law of thermodynamics, it still doesn’t explain why people use concepts like the four elements, five phases, humors, ama and agni, or any other energetic descriptions. An animating, vital tendency may exist in all matter as it attempts to dissipate the energy of the universe, but why describe it in such broad, metaphorical strokes? Isn’t this outdated language?
One of recent history’s most prolific mathematical geniuses, Stephen Wolfram has spent years developing more and more sophisticated models of computation. He uses computers to simulate reality – and provide answers for engineers, weather forecasters, and scientists in a wide range of disciplines. But what makes his work unique is his approach to creating models. Take, for example, the problem of determining how a block of concrete will break under stress. What does the crack look like? Where does it go? This a very difficult process to predict accurately. Historically, it involved massive tangles of equations. Inputs including vector forces, the structure and density of the materials, temperature, pressure, and many, many more fed into these equations and a computer attempted to give a “best guess” as to the outcome. This approach attempts to predict outcomes by reducing the system to its components and their relationships. Wolfram’s approach is different: instead of trying to identify and catalog all of the complexity of a living system, he looks for a simple system that behaves just like the complex one. He has hit on a just such a simple mathematical tool that generates endless complexity: the cellular automaton(.
Through these constructs, he has created models that predict concrete shear much more accurately than any reductionist system ever has. So much so, in fact, that engineers now use a cellular-automaton-based system much more often: not just for concrete fracturing(4), but for urban flood planning, evacuation protocols(6), even the stock market – among many others. Two interesting insights follow from this development: first, many processes in the universe seem to follow this simple model, from seashell patterning, to concrete shear, to wood snapping, to spirals forming, to fractals nesting. Second – and this is crucial – it is impossible to actually predict what the next step, the outcome of the system, will be without actually watching it move. That is to say, we can’t predict the future by taking a snapshot of the present, even if we know all the relationships and laws of the universe. This had been the dream of the Newtonian “clockwork” universe: the idea that we would
discover a master equation to predict all outcomes from a given set of conditions. Wolfram has proved that this is impossible for cellular automata, and calls it “the principle of computational irreducibility”. In the common tongue, it means we can’t get to understanding through reductionism. We have to watch the process flow. Ecologists are beginning to understand this inescapable fact.
Taking these two insights into the discipline of medicine, we can make some interesting observations. Prognosis – the art of understanding how a disease will progress, and also how a medicine or treatment will affect the progression – is very tricky business. There are many variables involved. We have attempted biomedical models, based on receptor structure, genetic expression, and so much more. These predictive models work fairly well, but there is still a lot of uncertainty, especially in the more subtle and complex situations. Take, for example, the use of antidepressants. Many physicians like to use SSRIs (selective serotonin reuptake inhibitors), but often cycle through many different ones, starting with Prozac, then maybe trying Paxil, and finally settling on Celexa (for example). They are all SSRIs, but some work in certain people, while others don’t. I have even heard physician speak in strange ways about them. “I’ve found Paxil is better for a skinnier, anxious person,” they say. Huh?
So perhaps we can inform prognosis, and perhaps diagnosis too, by applying the idea that a given set of conditions (patient, disease and intervention) can’t really ever give a consistently accurate prediction through an equation or algorithm. Even our most detailed understanding of the body, even a complete map of the whole genome, the whole proteome, microbiome and interactome, cannot yield the predictive power we are looking for. Computational irreducibility proves this. So what are we left with? Useful approximations, for one – and medicine has been relying on these for the last century. But more importantly, faced with the fact that reductionist approaches will always be approximate, to deepen our practice and improve our results we would do well to follow Wolfram’s lead: if we don’t want to watch the disease process unfold in order to see what the future holds (because the future could include death!), perhaps we should watch a simpler model. After all, simple models are able to predict a range of different phenomena incredibly accurately, much better than reductionist approximations. Can this apply to medicine?
The cellular automaton models seem to apply at many levels of reality – from weather patterns to chemical reactions. The patterns they weave hold within them spirals, self-similar cracks, repeaters, reproducing sequences. This presents powerful mathematical evidence, beyond such well-known constants such as φ (phi), that broad self-similarity exists at all levels of reality, and that the same models are equally applicable at all levels. What if the processes we observe in medicine (disease, pharmacodynamics, healing) draw on these models, too? If this were the case, then by observing processes at one level, we could gain relevant insight into medicine and healing. Perhaps the way the weather moves, the way ice cracks and flows into water, the way summer clouds gather into storms on the updrafts of July, all can tell us something about the human body. Perhaps the way fire warms your soup, or wind dries your skin, can give insight into medicine and healing. The current cutting edge of science is telling us that an animating drive towards complexity, adaptation, and reproduction exists at the most basic levels of matter. It affirms that it is impossible to predict outcomes by reducing the current situation to components and running those components through an equation. And it encourages us to seek out patterns we can observe to understand how health and disease work, because reality, though complex, is based on simple patterns and is largely self-similar, with simple models underlying all behavior. Does this sound familiar?
What remains to be seen is whether these energetic, vitalist ideas actually have any bearing in medicine and applied pharmacology. While we have not yet fully built this bridge, the basic infrastructure does exist: network pharmacology, which uses concepts from systems and network graph theories, attempts to understand how medicine works by focusing on structures that are echoed at many levels of reality. Concepts like “hubs” and connectors, which are absent from “random” networks, are found easily in everything from ecologies to the interaction of molecules with the protein networks in human physiology. They can be used to predict how drugs will work in a living system, and how a disease will progress. Since we understand how networks work (by observing them at many different levels of reality), academic researchers are starting to apply these ideas to how medicinal plants help with disease, and how different people with the same “condition” might respond differently to the same herb. This is powerful stuff, and it won’t be long now before traditional concepts of energetics will become a source of wisdom to understand how medicine works. Herbalists will be ready.
So next time you feel the cool stone beneath your fingers, deep in an old-growth grove, your harvest basket full of summer’s wild harvest, think about the vital force that brought this all into being. Remember how it courses through all things, invisible but understandable, with clear patterns that are both simple and incredibly powerful. Patterns that are encoded into energetic concepts. Energies that are brought to bear in healing human suffering. Vitalism is alive and well – you just need a new language if you want to talk about it with physicists and physicians. I prefer the poetry of weather, the whispers of spirits. But physics and math weave amazing stories, too. And herbalists have always been equal-opportunity storytellers.
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