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One example of emergence:  When the components of signaling pathway that enable between-cell communication interact to form a signaling network system, novel properties/behaviors can emerge &mdash; such as a self-sustaining feedback loop and generation of the signals themselves; signal integration across nultiple time scales; and, generation of distinct outputs depending on input strength and duration.<ref name=bhalla99>Bhalla US, Iyengar R (1999) [http://dx.doi.org/10.1126/science.283.5400.381 Emergent properties of networks of biological signaling pathways.] ''Science'' 283:381-387 PMID 9888852
One example of emergence:  When the components of signaling pathway, one that enable between-cell communication, interact to form a signaling network system, novel properties/behaviors can arise &mdash; such as a self-sustaining feedback loop and generation of the signals themselves; signal integration across multiple time scales; and, generation of distinct outputs depending on input strength and duration.<ref name=bhalla99>Bhalla US, Iyengar R (1999) [http://dx.doi.org/10.1126/science.283.5400.381 Emergent properties of networks of biological signaling pathways.] ''Science'' 283:381-387 PMID 9888852
*'''<u>Abstract:</u>''' Many distinct signaling pathways allow the cell to receive, process, and respond to information. Often, components of different pathways interact, resulting in signaling networks. Biochemical signaling networks were constructed with experimentally obtained constants and analyzed by computational methods to understand their role in complex biological processes. These networks exhibit emergent properties such as integration of signals across multiple time scales, generation of distinct outputs depending on input strength and duration, and self-sustaining feedback loops. Feedback can result in bistable behavior with discrete steady-state activities, well-defined input thresholds for transition between states and prolonged signal output, and signal modulation in response to transient stimuli. These properties of signaling networks raise the possibility that information for "learned behavior" of biological systems may be stored within intracellular biochemical reactions that comprise signaling pathways.</ref> One cannot explain or predict those novelties from combined knowledge of the individuated properties of the separate components of the network system. Networks represent emergent phenomena.
*'''<u>Abstract:</u>''' Many distinct signaling pathways allow the cell to receive, process, and respond to information. Often, components of different pathways interact, resulting in signaling networks. Biochemical signaling networks were constructed with experimentally obtained constants and analyzed by computational methods to understand their role in complex biological processes. These networks exhibit emergent properties such as integration of signals across multiple time scales, generation of distinct outputs depending on input strength and duration, and self-sustaining feedback loops. Feedback can result in bistable behavior with discrete steady-state activities, well-defined input thresholds for transition between states and prolonged signal output, and signal modulation in response to transient stimuli. These properties of signaling networks raise the possibility that information for "learned behavior" of biological systems may be stored within intracellular biochemical reactions that comprise signaling pathways.</ref> One cannot explain or predict those novelties from combined knowledge of the individuated properties of the separate components of the network system. Networks represent emergent phenomena.


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Systems biologists and theoretical biologists study, among other things, the phenomenon of emergence, whereby properties, functions and behaviors manifest themselves in living systems though not exhibited by any individual component of the system, and not explainable or predictable from complete understanding the components' properties/behaviors considered in isolation from the system that embeds them. Every cellular system exhibits emergent behaviors. Emergent behaviors of living systems include such things as locomotion, sexual display, flocking, and conscious experiencing. Even the biological components of living cells, such as mitochondria and other organelles, exhibit emergent properties.

This article will explore emergence as a concept with a long history, differing interpretations, and much controversy.

Emergence vs. vitalism

Some biologists might find it tempting to see a type of 'vitalism', or 'life force', in living systems, given that some whole-system properties/behaviors of organisms, including even the activity of living itself, exemplify emergent phenomena as defined in the introduction. One could not explain, for example, the behavior of an organism fleeing from a predator from a study of the properties of an organism's component subsystems. The properties of the component parts in a living system depend on the organization of those parts in the system, which differ from those found when their properties are studied isolated from the system.[1] Because biologists and their co-scientists can explain emergent properties/phenomena, if only sometimes in principle, by mechanisms that do not transcend interactions of matter and energy, any such ‘vitalism’ properly qualifies only as a ‘materialistic vitalism’.

Examples of emergence

Emergence relates to phenomena that arise from and depend on some more basic phenomena yet are simultaneously autonomous from that base. [2]


One example of emergence: When the components of signaling pathway, one that enable between-cell communication, interact to form a signaling network system, novel properties/behaviors can arise — such as a self-sustaining feedback loop and generation of the signals themselves; signal integration across multiple time scales; and, generation of distinct outputs depending on input strength and duration.[3] One cannot explain or predict those novelties from combined knowledge of the individuated properties of the separate components of the network system. Networks represent emergent phenomena.

For another example, in studying a protein separated from the cellular system that embeds it in a cell, one can observe many of its chemical and physical properties, but with increasing knowledge of those properties one approaches no closer to explaining any of the properties it has only in the context of the system that embeds it, such as the operation of catalyzing a biochemical reaction, or of binding to other proteins to form a protein complex that generates novel behavior. Those properties of the protein emerge in the context of the protein’s environment — how it interacts in the context of the system as a whole. Moreover, those emergent properties may result in effects within the system that, in a feedback way, further alters the emergent behavior of the protein in the system, as when a reaction product alters the catalytic ability of the protein.

Emergent processes have been recognised as, for example, contributing to understanding:

  • subcellular morphology[4],
  • developmental biology[5],
  • metabolic networks[6],
  • proteomics[7] [8]
  • evolution of complexity in living things

Emergent phenomena appear even in non-biological physical systems.[9] Emergent phenomena attract the attention of cellular neuroscientists;[10]  and cognitive scientists[11]. Emergent properties manifest in the behaviour of ant colonies and in swarm intelligence.[12] Systems scientists have simulated emergent phenomena.[13]  Emergent phenomena in human societies has also received attention. [14]. Biologists even explain the biosphere itself as emergent.[15]

Why emergence

Why do not all of the properties/behaviors of a system predictably result from the properties of its components? After all, the reductionist paradigm that dominated the Scientific method in the 20th century operated on the exactly opposite assumption. For one thing, the intrinsic properties of a system’s components themselves do not determine those of the whole system; rather, their 'organizational dynamics' does — how the components interact coordinately in time and space. Those organizational dynamics include not only the interrelations among the components themselves, but also interactions among the many different organizational units in the system. [16] Secondly, the living system always operates in a certain context (its external environment, or surroundings), and those surroundings, in turn, always affect the properties of the system-as-a-whole. For example, nutrient gradients in its environment influence the direction a bacterium’s locomotion. The impact of environmental context affects the dynamic organization of the components within the system — a 'downward causation'. [17] For another example, environmental signals can activate or suppress a metabolic pathway, reorganizing cellular activity[18] One cannot simply take a living system apart and predict how it will behave in its natural environment.

As Gilbert and Sarkar[1] puts it: “Thus, when we try to explain how the whole system behaves, we have to talk about its parts the context of the whole and cannot get away talking only about the parts.”

Philosopher of science D.M. Walsh puts it this way: "The constituent parts and processes of a living thing are related to the organism as a whole by a kind of 'reciprocal causation'."[19] In other words, the organization of the components determine the behavior of the system, but that organization arises from more than the set of its internal components. How the whole system behaves as it interacts with its environment determines how those components organize themselves, and so novel properties of the system 'emerge' that characterize neither the environment nor that set of internal components. For example, the behavior of a human kidney cell depends not only on its cellular physiology, but also on all the properties of the organ (kidney) which constitutes its environment. The kidney's overall structure and function influence the cell’s structure and behavior (e.g., by physical confinement and by cell-to-cell signaling), which in turn influence the organization of its intracellular components. The kidney in turn responds to its environment, namely the individual body that it lives in, and that body responds to its environment, which includes such factors as the availability of particular food items, fresh water, and ambient temperature and humidity. Systems biologists regard emergent properties as arising from a combination of bottom-up and top-down effects — Walsh's 'reciprocal causation'.

Using the example of termites out of whose combined individual behaviors without outside management emerge complex colony mounds, a recent National Research Council report on the role of theory in advancing 21st century biology commented on emergent behavior as follows:[20]

A reasonable way of thinking about emergent behavior might be to focus on the level or scale at which the rules reside. If the rules are specified at a low level, for example, the individual termites, and the patterns and structures, like termite mounds, emerge at a scale where there are no rules specified, we may call this emergent behavior.[20]

Other examples of rule-free emergent behavior for which the 'rules' appear specified at a lower level than the emergent behavior itself include the flocking behavior of birds, and the folding of amino acid polymers into catalytic proteins.

Emergence and complexity

Emergent systems always display what we recognize as ‘complexity’, a feature we have a difficult time precisely defining. Complex systems appear to require more bits of information (words, sentences, lines of computer code, etc.) to describe than the bits of information in the system itself. [21]  The operation of the system itself supplies its own most economical model.

According the paleontologist and origin of life researcher, Robert Hazen, four basic complexity elements underpin emergence in a system: [22]

  • a sufficiently large ‘density’ of components, with increasing complexity as the concentration increases, up to a point;
  • sufficient interconnectivity of the components, with increasing complexity with greater and more varied types of interconnectivity, up to a point;
  • a sufficient energy flow through the system to enable the system’s components to perform the work of interacting in the self-organized way characteristic of the energized system;
  • flow of energy through the system in a cyclic manner, presumably facilitating the spatiotemporal patterning characteristic of organized systems.

References

Citations and notes

  1. ↑ 1.0 1.1 Gilbert SF, Sarkar S. (2000) Embracing complexity: organicism for the 21st century. Dev. Dyn 219:1-9 PMID 10974666
    • Abstract: Organicism (materialistic holism) has provided the philosophical underpinnings for embryology since the time of Kant. It had influenced the founders of developmental mechanics, and the importance of organicism to embryology was explicitly recognized by such figures as O. Hertwig, H. Spemann, R. Harrison, A. M. Dalq, J. Needham, and C. H. Waddington. Many of the principles of organicism remain in contemporary developmental biology, but they are rarely defined as such. A combination of genetic reductionism and the adoption of holism by unscientific communities has led to the devaluation of organicism as a fruitful heuristic for research. This essay attempts to define organicism, provide a brief history of its importance to experimental embryology, outline some sociologically based reasons for its decline, and document its value in contemporary developmental biology. Based on principles or organicism, developmental biology should become a science of emerging complexity. However, this does mean that some of us will have to learn calculus.
  2. ↑ Bedau MA, Humphreys P. (editors) (2008) Emergence: contemporary readings in philosophy and science. A Bradford book." ISBN 978-0-262-02621-5 (hc), ISBN 978-0-262-52475-9 (pbk)
    • Publisher´s Description:  Emergence, largely ignored just thirty years ago, has become one of the liveliest areas of research in both philosophy and science. Fueled by advances in complexity theory, artificial life, physics, psychology, sociology, and biology and by the parallel development of new conceptual tools in philosophy, the idea of emergence offers a way to understand a wide variety of complex phenomena in ways that are intriguingly different from more traditional approaches. This reader collects for the first time in one easily accessible place classic writings on emergence from contemporary philosophy and science. The chapters, by such prominent scholars as John Searle, Stephen Weinberg, William Wimsatt, Thomas Schelling, Jaegwon Kim, Robert Laughlin, Daniel Dennett, Herbert Simon, Stephen Wolfram, Jerry Fodor, Philip Anderson, and David Chalmers, cover the major approaches to emergence. Each of the three sections ("Philosophical Perspectives," "Scientific Perspectives," and "Background and Polemics") begins with an introduction putting the chapters into context and posing key questions for further exploration. A bibliography lists more specialized material, and an associated website (http://mitpress.mit.edu/emergence) links to downloadable software and to other sites and publications about emergence.
    • Contributors:  P. W. Anderson, Andrew Assad, Nils A. Baas, Mark A. Bedau, Mathieu S. Capcarrère, David Chalmers, James P. Crutchfield, Daniel C. Dennett, J. Doyne Farmer, Jerry Fodor, Carl Hempel, Paul Humphreys, Jaegwon Kim, Robert B. Laughlin, Bernd Mayer, Brian P. McLaughlin, Ernest Nagel, Martin Nillson, Paul Oppenheim, Norman H. Packard, David Pines, Steen Rasmussen, Edmund M. A. Ronald, Thomas Schelling, John Searle, Robert S. Shaw, Herbert Simon, Moshe Sipper, Stephen Weinberg, William Wimsatt, and Stephen Wolfram
    • About the Editors:  Mark A. Bedau is Professor of Philosophy and Humanities at Reed College in Portland, Oregon. He is the coeditor of Emergence: Contemporary Readings in Science and Philosophy and Protocells: Bridging Nonliving and Living Matter, both published by the MIT Press in 2008….Paul Humphreys is Professor of Philosophy at the University of Virginia.
    • Table of Contents and Downloadable Sample Chapters.
  3. ↑ Bhalla US, Iyengar R (1999) Emergent properties of networks of biological signaling pathways. Science 283:381-387 PMID 9888852
    • Abstract: Many distinct signaling pathways allow the cell to receive, process, and respond to information. Often, components of different pathways interact, resulting in signaling networks. Biochemical signaling networks were constructed with experimentally obtained constants and analyzed by computational methods to understand their role in complex biological processes. These networks exhibit emergent properties such as integration of signals across multiple time scales, generation of distinct outputs depending on input strength and duration, and self-sustaining feedback loops. Feedback can result in bistable behavior with discrete steady-state activities, well-defined input thresholds for transition between states and prolonged signal output, and signal modulation in response to transient stimuli. These properties of signaling networks raise the possibility that information for "learned behavior" of biological systems may be stored within intracellular biochemical reactions that comprise signaling pathways.
  4. ↑ Tabony J (2006) Microtubules viewed as molecular ant colonies. Biol Cell 98:603-17 PMID 16968217
  5. ↑ Theise ND, d'Inverno M (2004) Understanding cell lineages as complex adaptive systems. Blood Cells Mol Dis 32:17-20 PMID 14757407 and Ruiz i Altaba A et al. (2003) The emergent design of the neural tube: prepattern, SHH morphogen and GLI code. Curr Opin Genet Dev 13:513-21 PMID 14550418
  6. ↑ Jeong H et al.(2000) The large scale organisation of metabolic networks. Nature 407:651-4
  7. ↑ e.g. Grindrod P, Kibble M (2004) Review of uses of network and graph theory concepts within proteomics. Expert Rev Proteomics 1:229-38 PMID 15966817
  8. ↑ Ye X et al.(2005) Multi-scale methodology: a key to deciphering systems biology. Front Biosci 10:961-5 PMID 15569634
  9. ↑ Cho YS et al. (2005) Self-organization of bidisperse colloids in water droplets. J Am Chem Soc 127:15968-75 PMID 16277541
  10. ↑ see e.g. Burak Y, Fiete I (2006) Do we understand the emergent dynamics of grid cell activity? J Neurosci 26:9352-4 PMID 16977716
  11. ↑ e.g. Courtney SM (2004) Attention and cognitive control as emergent properties of information representation in working memory. Cogn Affect Behav Neurosci 4:501-16 PMID 15849893
  12. ↑ Theraulaz G et al (2002) Spatial patterns in ant colonies. Proc Natl Acad Sci USA 99:9645-9 PMID 12114538
  13. ↑ Theraulaz G, Bonabeau E (1999)A brief history of stigmergy. Artif Life 5:97-116 PMID 10633572
  14. ↑ Bonabeau E, Meyer C (2001) Swarm intelligence. A whole new way to think about business. Harv Bus Rev 79:106-14 PMID 11345907
  15. ↑ Field CB, Behrenfeld MJ, Randerson JT, Falkowski P (1998) Primary production of the biosphere: Integrating terrestrial and oceanic components. Science 281:237-40.
  16. ↑ Note: For example, physical chemists cannot predict the properties of water from knowledge of its components, hydrogen and oxygen. The way hydrogen and water interact to form H2O, and the way H2O molecules interact, enables the properties of water to 'emerge'.
  17. ↑ Note: Following up on the example of water, the properties of its environment (e.g., temperature, pressure) affect the way the H2O molecules organize themselves, as ice, or liquid, or steam
  18. ↑ Note: In relation to downward causation, the environment’s effect can sometimes reach down to the genetic database with molecular signals, altering its expression and consequently the characteristics of the cells without altering the database itself — so-called 'epigenetic' effects. When epigenetic alterations of gene expression occur in the reproductive organs, the system changes can be transmitted to the next generation. See
    • Jablonka E, Lamb MJ (2005) Evolution in Four Dimension: Genetic, Epigenetic, Behavioral, and Symbolic Variation in the History of Life. Cambridge: MIT Press
    • Gorelick R (2004) Neo-Lamarckian medicine. Med Hypotheses 62:299-303 PMID 14962644
  19. ↑ Walsh DM (2006) Organisms as natural purposes: the contemporary evolutionary perspective. Stud Hist Philos Biol Biomed Sci 37: 771-91
  20. ↑ 20.0 20.1 Committee on Defining and Advancing the Conceptual Basis of Biological Sciences in the 21st Century, National Research Council. (2008) The Role of Theory in Advancing 21st Century Biology: Catalyzing Transformative Research. Board on Life Sciences, Division on Earth and Life Studies, National Research Council of the National Academies. The National Academies Press, Washington, D.C. ISBN 978-0-309-11249-9.
  21. ↑ (1991) Zurek WJ (ed) Complexity, Entropy, and the Physics of Information: The Proceedings of the Workshop on the Complexity, Entropy, and the Physics of Information May-June, 1989, Santa Fe, New Mexico. Addison-Wesley Publishing Company, The Advanced Book Program, Redwood City. ISBN 0201515091
  22. ↑ Hazen RM (2005) Genesis: The Scientific Quest for Life's Origin. Joseph Henry Press, Washington DC. ISBN 0309094321
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