and so forth—and molecular biology became the new frontier of research. In all those endeavors the basic question had not changed since Greek antiquity: What is reality made of? What are its ultimate constituents?
At the same time, throughout the same history of philosophy and science the study of pattern was always present. It began with the Pythagoreans in Greece and was continued by the alchemists, the Romantic poets, and various other intellectual movements. However, for most of the time the study of pattern was eclipsed by the study of substance until it reemerged forcefully in our century, when it was recognized by systems thinkers as essential to the understanding of life.
I shall argue that the key to a comprehensive theory of living systems lies in the synthesis of those two very different approaches, the study of substance (or structure) and the study of form (or pattern). In the study of structure we measure and weigh things. Patterns, however, cannot be measured or weighed; they must be mapped. To understand a pattern we must map a configuration of relationships. In other words, structure involves quantities, while pattern involves qualities.
The study of pattern is crucial to the understanding of living systems because systemic properties, as we have seen, arise from a configuration of ordered relationships. 13 Systemic properties are properties of a pattern. What is destroyed when a living organism is dissected is its pattern. The components are still there, but the configuration of relationships among them—the pattern—is destroyed, and thus the organism dies.
Most reductionist scientists cannot appreciate critiques of reduc- tionism, because they fail to grasp the importance of pattern. They affirm that all living organisms are ultimately made of the same atoms and molecules that are the components of inorganic matter and that the laws of biology can therefore be reduced to those of physics and chemistry. While it is true that all living organisms are ultimately made of atoms and molecules, they are not “nothing but” atoms and molecules. There is something else to life, something nonmaterial and irreducible—a pattern of organization.
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Networks—the Patterns of Life
Having appreciated the importance of pattern for the understanding of life, we can now ask: Is there a common pattern of organization that can be identified in all living systems? We shall see that this is indeed the case. This pattern of organization, common to all living systems, will be discussed in detail below. 14 Its most important property is that it is a network pattern. Whenever we encounter living systems—organisms, parts of organisms, or communities of organisms—we can observe that their components are arranged in network fashion. Whenever we look at life, we look at networks.
This recognition came into science in the 1920s, when ecologists began to study food webs. Soon after that, recognizing the network as the general pattern of life, systems thinkers extended network models to all systems levels. Cyberneticists, in particular, tried to understand the brain as a neural network and developed special mathematical techniques to analyze its patterns. The structure of the human brain is enormously complex. It contains about 10 billion nerve cells (neurons), which are interlinked in a vast network through 1,000 billion junctions (synapses). The whole brain can be divided into subsections, or subnetworks, which communicate with each other in network fashion. All this results in intricate patterns of intertwined webs, networks nesting within larger networks. 15
The first and most obvious property of any network is its nonlinearity—it goes in all directions. Thus the relationships in a network pattern are nonlinear relationships. In particular, an influence, or message, may travel along a cyclical path, which may become a feedback loop. The concept of feedback is intimately connected with the network pattern. 16
Because networks of communication may generate feedback loops, they may acquire the ability to regulate themselves. For example, a community that maintains an active network of communication will learn from its mistakes, because the consequences of a mistake will spread through the network and return to the
source along feedback loops. Thus the community can correct its mistakes, regulate itself, and organize itself. Indeed, self-organization has emerged as perhaps the central concept in the systems view of life, and like the concepts of feedback and self-regulation, it is linked closely to networks. The pattern of life, we might say, is a network pattern capable of self-organization. This is a simple definition, yet it is based on recent discoveries at the very forefront of science.
Emergence of Self-Organization Concept
The concept of self-organization originated in the early years of cybernetics, when scientists began to construct mathematical models representing the logic inherent in neural networks. In 1943 the neuroscientist Warren McCulloch and the mathematician Walter Pitts published a pioneering paper entitled “A Logical Calculus of the Ideas Immanent in Nervous Activity,” in which they showed that the logic of any physiological process, of any behavior, can be transformed into rules for constructing a network. 17
In their paper the authors introduced idealized neurons represented by binary switching elements—in other words, elements that can switch on or off”—and they modeled the nervous system as complex networks of those binary switching elements. In such a McCulloch-Pitts network the “on-off’ nodes are coupled to one another in such a way that the activity of each node is governed by the prior activity of other nodes according to some “switching rule.” For example, a node may switch on at the next moment only if a certain number of adjacent nodes are “on” at this moment. McCulloch and Pitts were able to show that although binary networks of this kind are simplified models, they are a good approximation of the networks embedded in the nervous system.
In the 1950s scientists began to actually build models of such binary networks, including some with little lamps flickering on and off at the nodes. To their great amazement they discovered that after a short time of random flickering, some ordered patterns would emerge in most networks. They would see waves of flicker-
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ing pass through the network, or they would observe repeated cycles. Even though the initial state of the network was chosen at random, after a while those ordered patterns would emerge spontaneously, and it was that spontaneous emergence of order that became known as “self-organization.”
As soon as this evocative term appeared in the literature, systems thinkers began to use it widely in different contexts. Ross Ashby in his early work was probably the first to describe the nervous system as “self-organizing.” 18 The physicist and cyberneticist Heinz von Foerster became a major catalyst for the selforganization idea in the late 1950s, organizing conferences around this topic, providing financial support for many of the participants, and publishing their contributions. 19
For two decades Foerster maintained an interdisciplinary research group dedicated to the study of self-organizing systems. Centered at the Biological Computer Faboratory of the University of Illinois, this group was a close circle of friends and colleagues who worked away from the reductionist mainstream and whose ideas, being ahead of their time, were not widely published. However, those ideas were the seeds of many of the successful models of self-organizing systems developed during the late seventies and the eighties.
Heinz von Foerster’s own contribution to the theoretical understanding of self-organization came very early and had to do with the concept of order. He asked: Is there a measure of order one could use to define the increase of order implied by “organization”? To solve this problem Foerster used the concept of “redundancy,” defined mathematically in information theory by Claude Shannon, which measures the relative order of the system against the background of maximum disorder. 20
Since then this approach has been superseded by the new mathematics of complexity, but in the late 1950s it allowed Foerster to develop an early qualitative model of self-organization in living systems. He coined the phrase “order from noise” to indicate that a self-organizing system does not just “import” order from its environment, but takes in energy-rich matter, integrates it into its own structure, and thereby increases its internal order.
During the seventies and eighties the key ideas of this early model were refined and elaborated by researchers in several countries who explored the phenomenon of self-organization in many different systems from the very small to the very large—Ilya Prigogine in Belgium, Hermann Haken and Manfred Eigen in Germany, James Lovelock in England, Lynn Margulis in the United States, Humberto Maturana and Francisco Varela in Chiles 1 The resulting models of self-organizing systems share certain key characteristics, which are the main ingredients of the emerging unified theory of living systems to be discussed in this book.
The first important difference between the early concept of selforganization in cybernetics and the more elaborate later models is that the latter include the creation of new structures and new modes of behavior in the self-organizing process. For Ashby all possible structural changes take place within a given “variety pool of structures, and the survival chances of the system depend on the richness, or “requisite variety,” of that pool. There is no creativity, no development, no evolution. The later models, by contrast, include the creation of novel structures and modes of behavior in the processes of development, learning, and evolution.
A second common characteristic of these models of self-organization is that they all deal with open systems operating far from equilibrium. A constant flow of energy and matter through the system is necessary for self-organization to take place. The striking emergence of new structures and new forms of behavior, which is the hallmark of self-organization, occurs only when the system is far from equilibrium.
The third characteristic of self-organization, common to all models, is the nonlinear interconnectedness of the system’s components. Physically this nonlinear pattern results in feedback loops; mathematically it is described in terms of nonlinear equations.
Summarizing those three characteristics of self-organizing systems, we can say that self-organization is the spontaneous emergence of new structures and new forms of behavior in open systems far from equilibrium, characterized by internal feedback loops and described mathematically by nonlinear equations.
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Dissipative Structures
The first, and perhaps most influential, detailed description of self-organizing systems was the theory of “dissipative structures” by the Russian-born chemist and physicist Ilya Prigogine, Nobel Laureate and professor of physical chemistry at the Free University of Brussels. Prigogine developed his theory from studies of physical and chemical systems, but according to his own recollections, he was led to do so after pondering the nature of life:
I was very much interested in the problem of life. ... I thought always that the existence of life is telling us something very important about nature. 22
What intrigued Prigogine most was that living organisms are able to maintain their life processes under conditions of nonequilibrium. He became fascinated by systems far from thermal equilibrium and began an intensive investigation to find out under exactly what conditions nonequilibrium situations may be stable.
The crucial breakthrough occurred for Prigogine during the early 1960s, when he realized that systems far from equilibrium must be described by nonlinear equations. The clear recognition of this link between “far from equilibrium” and “nonlinearity” opened an avenue of research for Prigogine that would culminate a decade later in his theory of self-organization.
In order to solve the puzzle of stability far from equilibrium, Prigogine did not study living systems but turned to the much simpler phenomenon of heat convection, known as the “Benard instability,” which is now regarded as a classical case of self-organization. At the beginning of the century the French physicist Henri Benard discovered that the heating of a thin layer of liquid may result in strangely ordered structures. When the liquid is uniformly heated from below, a constant heat flux is established, moving from the bottom to the top. The liquid itself remains at rest, and the heat is transferred by conduction alone. However, when the temperature difference between the top and bottom surfaces reaches a certain critical value, the heat flux is replaced by
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heat convection, in which the heat is transferred by the coherent motion of large numbers of molecules.
At this point a very striking ordered pattern of hexagonal
Figure 5-1
Pattern of hexagonal Benard cells in a cylindrical container, viewed from above. The diameter of the container is approximately 10cm, the depth of the liquid approximately 0.5cm;
from Berge (1981).
(“honeycomb”) cells appears, in which hot liquid rises through the center of the cells, while the cooler liquid descends to the bottom along the cell walls (see figure 5-1). Prigogine’s detailed analysis of these “Benard cells” showed that as the system moves farther away from equilibrium (that is, from a state with uniform temperature throughout the liquid), it reaches a critical point of instability, at which the ordered hexagonal pattern emerges. 23
The Benard instability is a spectacular example of spontaneous self-organization. The nonequilibrium that is maintained by the continual flow of heat through the system generates a complex spatial pattern in which millions of molecules move coherently to form the hexagonal convection cells. Benard cells, moreover, are not limited to laboratory experiments but also occur in nature in a wide variety of circumstances. For example, the flow of warm air
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from the surface of the earth toward outer space may generate hexagonal circulation vortices that leave their imprints on sand dunes in the desert and on arctic snow fields. 24
Figure 5-2
Wavelike chemical activity in the so-called Belousov-Zhabotinskii
reaction; from Prigogine (1980).
Another amazing self-organization phenomenon studied extensively by Prigogine and his colleagues in Brussels are the so-called chemical clocks. These are reactions far from chemical equilibrium, which produce very striking periodic oscillations. 25 For example, if there are two kinds of molecules in the reaction, one “red” and one “blue,” the system will be all blue at a certain point; then change its color abruptly to red; then again to blue; and so on at regular intervals. Different experimental conditions may also produce waves of chemical activity (see figure 5-2).
To change color all at once, the chemical system has to act as a whole, producing a high degree of order through the coherent activity of billions of molecules. Prigogine and his colleagues discovered that, as in the Benard convection, this coherent behavior emerges spontaneously at critical points of instability far from equilibrium.
During the 1960s Prigogine developed a new nonlinear thermodynamics to describe the self-organization phenomenon in open systems far from equilibrium. “Classical thermodynamics,” he explains, leads to the concept of ‘equilibrium structures’ such as crystals. Benard cells are structures too, but of a quite different nature. That is why we have introduced the notion of dissipative
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structures,’ to emphasize the close association, at first paradoxical, in such situations between structure and order on the one side, and dissipation . . . on the other.” 26 In classical thermodynamics the dissipation of energy in heat transfer, friction, and the like was always associated with waste. Prigogine’s concept of a dissipative structure introduced a radical change in this view by showing that in open systems dissipation becomes a source of order.
In 1967 Prigogine presented his concept of dissipative structures for the first time in a lecture at a Nobel Symposium in Stockholm, 27 and four years later he published the first formulation of the full theory together with his colleague Paul Glansdorff. 28 According to Prigogine’s theory, dissipative structures not only maintain themselves in a stable state far from equilibrium, but may even evolve. When the flow of energy and matter through them increases, they may go through new instabilities and transform themselves into new structures of increased complexity.
Prigogine’s detailed analysis of this striking phenomenon showed that while dissipative structures receive their energy from outside, the instabilities and jumps to new forms of organization are the result of fluctuations amplified by positive feedback loops. Thus amplifying “runaway” feedback, which had always been regarded as destructive in cybernetics, appears as a source of new order and complexity in the theory of dissipative structures.
Laser Theory
During the early sixties, at the time when Ilya Prigogine realized the crucial importance of nonlinearity for the description of selforganizing systems, the physicist Hermann Haken in Germany had a very similar realization while studying the physics of lasers, which had just been invented. In a laser, certain special conditions combine to produce a transition from normal lamplight, which consists of an “incoherent” (unordered) mixture of light waves of different frequencies and phases, to “coherent” laser light consisting of one single, continuous, monochromatic wave train.
The high coherence of laser light is brought about by the coordination of light emissions from the individual atoms in the laser.
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Haken recognized that this coordinated emission, resulting in the spontaneous emergence of coherence, or order, is a process of selforganization and that a nonlinear theory is needed to describe it properly. “In those days I had a lot of arguments with several American theorists,” Haken remembers, “who were also working on lasers, but with a linear theory, and who did not realize that something qualitatively new is happening at this point.” 29
When the laser phenomenon was discovered, it was interpreted as an amplification process, which Einstein had already described in the early days of quantum theory. Atoms emit light when they are “excited”—that is, when their electrons have been lifted to higher orbits. After a while the electrons will spontaneously jump back to lower orbits and in the process emit energy in the form of wavelets of light. A beam of ordinary light consists of an incoherent mixture of these tiny wavelets emitted by individual atoms.
Under special circumstances, however, a passing light wave can “stimulate”—or, as Einstein called it, “induce”—an excited atom to emit its energy in such a way that the light wave is amplified. This amplified wave can, in turn, stimulate another atom to amplify it further, and eventually there will be an avalanche of amplifications. The resulting phenomenon was called “light amplification through stimulated emission of radiation,” which gave rise to the acronym LASER.
The problem with this description is that different atoms in the laser material will simultaneously generate different light avalanches that are incoherent relative to each other. How then, Haken asked, do these unordered waves combine to produce a single coherent wave train? He was led to the answer by observing that a laser is a many-particle system far from thermal equilibrium. 30 It needs to be “pumped” from the outside to excite the atoms, which then radiate energy. Thus there is a constant flow of energy through the system.
While studying this phenomenon intensely during the 1960s, Haken found several parallels to other systems far from equilibrium, which led him to speculate that the transition from normal light to laser light might be an example of the self-organization processes that are typical of systems far from equilibrium. 31
MODELS OF SELF-ORGANIZATION
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Haken coined the term “synergetics” to indicate the need for a new field of systematic study of those processes, in which the combined actions of many individual parts, such as the laser atoms, produce a coherent behavior of the whole. In an interview given in 1985 Haken explained:
In physics, there is the term “cooperative effects,” but it is used mainly for systems in thermal equilibrium. ... I felt I should coin a term for cooperation [in] systems far from thermal equilibrium. ... I wanted to emphasize that we need a new discipline for those processes. . . . So, one could see synergetics as a science dealing, perhaps not exclusively, with the phenomenon of selforganization. 32
In 1970 Haken published his full nonlinear laser theory in the prestigious German physics encyclopedia Handbuch der Physi \. 33 Treating the laser as a self-organizing system far from equilibrium, he showed that the laser action sets in when the strength of the external pumping reaches a certain critical value. Due to a special arrangement of mirrors on both ends of the laser cavity, only light emitted very close to the direction of the laser axis can remain in the cavity long enough to bring about the amplification process, while all other wave trains are eliminated.
Haken’s theory makes it clear that although the laser needs to be pumped energetically from the outside to remain in a state far from equilibrium, the coordination of emissions is carried out by the laser light itself; it is a process of self-organization. Thus Haken arrived independently at a precise description of a selforganizing phenomenon of the kind Prigogine would call a dissipative structure.
The predictions of laser theory have been verified in great detail, and due to the pioneering work of Hermann Haken, the laser has become an important tool for the study of self-organization. At a symposium honoring Haken’s sixtieth birthday, his collaborator Robert Graham paid an eloquent tribute to his work:
It is one of Haken’s great contributions to recognize that lasers are not only extremely important technological tools, but also highly
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interesting physical systems in themselves, which can teach us important lessons. . . . Lasers occupy a very interesting place between the quantum world and the classical world, and Haken’s theory tells us how these worlds can be connected. . . . The laser can be seen at the crossroads between quantum and classical physics, between equilibrium and non-equilibrium phenomena, between phase transitions and self-organization, and between regular and chaotic dynamics. At the same time, it is a system which we understand both on a microscopic quantum mechanical and a macroscopic classical level. It is a solid ground for discovering general concepts of non-equilibrium physics. 34
Hypercycles
Whereas Prigogine and Haken were led to the concept of selforganization by studying physical and chemical systems that go through points of instability and generate new forms of order, the biochemist Manfred Eigen used the same concept to shed light on the puzzle of the origin of life. According to standard Darwinian theory, living organisms formed out of “molecular chaos” by chance through random mutations and natural selection. However, it has often been pointed out that the probability of even simple cells to emerge in this way during the known age of the Earth is vanishingly small.
Manfred Eigen, Nobel Laureate in chemistry and director of the Max Planck Institute for Physical Chemistry in Gottingen, proposed in the early seventies that the origin of life on Earth may have been the result of a process of progressive organization in chemical systems far from equilibrium, involving “hypercycles” of multiple feedback loops. Eigen, in effect, postulated a prebiologi- cal phase of evolution, in which selection processes occur in the molecular realm “as a material property inherent in special reaction systems,” 35 and he coined the term “molecular self-organization” to describe these prebiological evolutionary processes. 36
The special reaction systems studied by Eigen are known as “catalytic cycles.” A catalyst is a substance that increases the rate of a chemical reaction without itself being changed in the process.
Catalytic reactions are crucial processes in the chemistry of life. The most common and most efficient catalysts are the enzymes, which are essential components of cells promoting vital metabolic processes.
When Eigen and his colleagues studied catalytic reactions involving enzymes in the 1960s, they observed that in biochemical systems far from equilibrium, i.e., systems exposed to energy flows, different catalytic reactions combine to form complex networks that may contain closed loops. Figure 5-3 shows an example of such a catalytic network, in which fifteen enzymes catalyze each other’s formations in such a way that a closed loop, or catalytic cycle, is formed.
Figure 5-3
A catalytic network of enzymes, including a closed loop (El . . . El 5); from Eigen (1971).
These catalytic cycles are at the core of self-organizing chemical systems such as the chemical clocks studied by Prigogine, and they
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also play an essential role in the metabolic functions of living organisms. They are remarkably stable and can persist under a wide range of conditions. 37 Eigen discovered that with sufficient time and a continuing flow of energy, catalytic cycles tend to interlock to form closed loops in which the enzymes produced in one cycle act as catalysts in the subsequent cycle. He coined the term “hypercycles” for those loops in which each link is a catalytic cycle.
Hypercycles turn out to be not only remarkable stable, but also capable of self-replication and of correcting replication errors, which means that they can conserve and transmit complex information. Eigen’s theory shows that such self-replication—which is, of course, well-known for living organisms—may have occurred in chemical systems before the emergence of life, before the formation of a genetic structure. These chemical hypercycles, then, are self-organizing systems that cannot properly be called “living” because they lack some key characteristics of life. However, they must be seen as precursors to living systems. The lesson to be learned here seems to be that the roots of life reach down into the realm of nonliving matter.
One of the most striking lifelike properties of hypercycles is that they can evolve by passing through instabilities and creating successively higher levels of organization that are characterized by increasing diversity and richness of components and structures. 38 Eigen points out that the new hypercycles created in this way may be in competition for natural selection, and he refers explicitly to Prigogine’s theory to describe the whole process: “The occurrence of a mutation with selective advantage corresponds to an instability, which can be explained with the help of the [theory] ... of Prigogine and Glansdorff.” 39
Manfred Eigen’s theory of hypercycles shares the key concepts of self-organization with Ilya Prigogine’s theory of dissipative structures and Hermann Haken’s laser theory—the state of the system far from equilibrium; the development of amplification processes through positive feedback loops; and the appearance of instabilities leading to the creation of new forms of organization. In addition, Eigen made the revolutionary step of using a Darwin-