| English
"Куда идет мир? Каково будущее науки? Как "объять необъятное", получая образование - высшее, среднее, начальное? Как преодолеть "пропасть двух культур" - естественнонаучной и гуманитарной? Как создать и вырастить научную школу? Какова структура нашего познания? Как управлять риском? Можно ли с единой точки зрения взглянуть на проблемы математики и экономики, физики и психологии, компьютерных наук и географии, техники и философии?"

«Network structures: typical organizational patterns (paradigms) in biological and social systems»" 
Alexander V. Oleskin, Vladimir S. Kurdyumov

1. Cellular paradigm. This paradigm is characteristic of the social structures of unicellular organisms including microbial colonies and biofilms; it is also exemplified by cell “collectives” that form tissues and organs in a multicellular organism. Most biosocial structures made up of cells represent almost completely flat networks. Hierarchization can be considered a temporary or exceptional phenomenon in cell network structures. In some of these structures, cells and their groups (clusters, microcolonies, rafts) can be functionally differentiated. The dominant role in regulating the activities of the entire network  is performed via chemical communication involving diffusing signal molecules that are exemplified by the pheromones of quorum-sensing systems. Behavioral coordination in cell structures is facilitated by the matrix that performs the structural, protective, and communication-promoting function. Cell networks apparently are capable of collective information processing and “decision-making” (Ben-Jacob, 2003; Ben-Jacob et al., 2004)  that are facilitated by quorum-sensing systems and other communication mechanisms.

2. Equipotential paradigm  that is implemented, for instance, by the leaderless shoals or schools of a large number of fish species. Individual differences are eliminated to a considerable extent within such a network structure. Effective behavior coordination within an equipotential network is mainly due to relay signal transfer using vision and mechanoreception (detecting movement and vibration in the surrounding water) involving the special organ most fish possess called the lateral line. Large networks tend to separate into smaller subnetworks (small fish groups) that are relatively loosely connected to one another[4]. The networks often posses quasi-organismic properties, i.e. resemble single organisms. This may bluff a predator into taking the whole network for a single giant fish. Individual fish obey network-level behavior rules that integrate the whole structure, in an analogy to the microbial matrix.

3. Modular paradigm. This organizational pattern was investigated in the seminal work by Nikolay Marfenin (2002, 2009) in the example of colonial cnidarians. Their decentralized colonies consist of a large number of structural units (zooids), i.e., polyps and medusae that are connected by a stalk (coenosarc) and perform the functions of specialized organs of the whole structures. The individuality of each of the zooids is suppressed by the whole network. A major role is played by contact interaction among zooids that is partly competitive (involving quasi-market interactivity). This competition among structural units is overridden by their cooperation within the framework of the whole decentralized structure.  The cooperation is based upon (1) the weak influence of each unit on its operation, and (2) an increase in a unit’s power in proportion to the concordance between its rhythm and the system-dominating rhythm. Most modular networks have no central leader, but they do contain a matrix-like integrating agent (in the form of the coenosarc in cnidarians), which connects the units and helps them synchronize their activities.

4. Rhizome paradigm is characteristic of many biological systems, including fungi. The term “rhizome” was coined by the post-modern philosophers Deleuze and Guattari (2004) who envisioned the rhizome as a cultural system that “has no beginning or end; it is always in the middle, between things, interbeing, intermezzo”. In contrast to the aforementioned modular paradigm, networks based upon the rhizome paradigm do not include modules (units, zooids) and connecting stalks. Rhizome-type network structures contain only stalks. In fungi, these filamentous bodies are called “hyphae”. They represent uniform components of the whole network (the mycelium). Secondarily, the mycelium can develop organs used by thewhole network, including root-like rhizoids and fruiting bodies. “By branching and fusing with one another, hyphae form a network-like structure that is denoted as the mycelium” (Kück et al., 2009, S.4).  A large number of fungi undergo transitions between mycelium formation and the yeast-like lifestyle, which is characterized by the disintegration of filaments (hyphae) into separate yeast-like cells. If mycelium forms, the cells in it can retain some degree of individuality (by forming septs separating them) or merge into the continuous mass of hyphae.

5. Neural paradigm is characterized by a number of features (learning capacity, collective information processing, cognitive activities, etc.) that were briefly considered in the preceding subsections. Neural networks are to an extent hierarchical, but the hierarchical organizational principle is overridden by the network principle. In contrast to many other biological networks, neural networks are predominantly coordinated via contact (synaptic), rather than distant, interaction between their nodes (neurons or their analogs). An important feature of decentralized networks in general, their capacity for “thinking“, i.e., collective information processing and decision making as well as collective learning and cognitive activities, is particularly prominent in neural networks. From the systems theory viewpoint, it is of particular interest that neural networks combine networked and hierarchical organizational scenarios, parallel and serial information processing, and the gradient and the modular principle of operation (see Oleskin, 2014 a, b).

6. Eusocial paradigm can be considered in the example of ant, bee, or termite societies. Eusocial network systems are characterized by a high degree of functional differentiation of their nodes (individuals) and quasi-organismic(supraorganismic) properties as well as by the formation of specialized “project teams” and permanent functional groups. Due to the existence of hierarchical dominance–submission relationships within eusocial systems, they are to be considered partly hierarchical systems. However, hierarchies are embedded in a predominantly network-type organizational environment. Hierarchical worker teams form part of a larger decentralized network structure.

Workers that are not involved in the activities of specialized teams belong to the relatively inactive pool of generalists. The pool can be mobilized for doing urgent tasks.

Eusocial systems  are multilevel structures: they represent networks consisting of hierarchies made up of networks that, in turn, consist of hierarchies (see Zakharov, 1987, 1991, 1995; Hölldobler & Wilson, 1990, 2009, 2010).

7. Egalitarian paradigm is typical of social groups of chimpanzees, bonobos, capuchins, and some other primate species. It is characterized by mitigated hierarchies with tolerant high-ranking individuals that function in conformity with a set of social norms—the matrix—that restrict their power and secure the “rights” of all network nodes, including low-ranking individuals. The hierarchy is also mitigated by a system of decentralized horizontal interindividual interactions involving empathy, affiliation, cooperation, and social cognitive function. These interactions manifest themselves in grooming, play, greeting rituals, food sharing, and postconflict reconciliation. Many egalitarian structures are multilevel systems; their large associations often include small-size loose fission–fusion groups.

Taking into account the limited size of this work, we shall only give several examples that illustrate the potentially fruitful application of the aforementioned paradigms in human society. The egalitarian (“ape”) paradigm seems to be applicable to the organization of networked creative teams of enthusiastic scientists or scholars. This was exemplified above by a team of software developers (The Agile Alliance) (Cohn, 2010). Without equating the organization of animal groups and human network structures, we should emphasize the similarity between the egalitarian groups of apes and the networks of enthusiastic researchers in the following respects:

  • Respect for individual freedoms (particularly the freedom of choice) and rights. The network of microbiologists discussed above respected the right of every individual or collective member to deal with his or her favorite area of research and to develop his or her own theories; this freedom was only limited by temporary obligations in terms of joint projects, publications, or conferences.
  • 2.  Partial hierarchization of the structure associated with acknowledging the merits and degrees/titles of high-ranking network members (analogs of silverback males in gorilla groups); however, no network member can become the central leader and play the dominant role across the entire structure.
  • 3.  Loose links between network members; in an analogy to fission–fusion groups formed by, e.g., chimpanzees, individuals or subgroups can choose to either join the network or quit it.

Analogous “ape-style” behavioral principles can be implemented in small-size decentralized associations made up of prominent business people, high-rank scientists, or politicians.

The eusocial paradigm that was discussed above in the example of ant societies, also seems to provide much ‘food for thought” for developers of network structures in human society.To reiterate, ant societies include a pool of worker individuals that normally do not belong to any specialist team (Schmidt-Hempel, 1990) and that can be mobilized for coping with urgent problems. Studies with ants were conducted in which the number of available foraging sites in the form of honeydew-excreting aphid colonies was limited. The ant societies mobilized part of the formerly inactive individuals that became “specialists belonging to small teams taking care of aphid colonies” (Novgorodova, 2003, p.229). In a honeybee colony, “the presence of just a few highly defensive individuals in a hive can incite less defensive colony members to join in an attack” (Wray et al., 2011, p.566).

Networks in human society that can apply similar scenarios are exemplified by various kinds of clubs that include (1) active members functioning as partial leaders dealing with specific projects and (2) their relatively passive supporters. The eusocial paradigm can be creatively used within the framework of civil society for setting up networked clubs concerned with ideological, environmental, and humanitarian issues. They should include a small subnetwork containing partial leaders (hubs) along with a relatively large pool of unspecialized helpers. Such clubs can combine network and hierarchical organizational patterns (at different structural levels).

Apart from fungi (and some other biological systems), the rhizome paradigm can be applied to dynamic networked alliances of enterprises. The transition between yeast-like growth (with separate cells) and the formation of mycelium (with cells merging into hyphae) corresponds, in the world of business, to the transition between a group of independent firms whose interaction is only based on contracts and a coherent networked interfirm alliance that carries out projects at the level of the whole network, despite bureaucratic barriers between the firms involved.

In conclusion, it should be stressed that a prerequisite for the successful development of all parts of the modern-day world, including East Europe, is harmonious interactivity between different kinds of structures, i.e., hierarchies, (quasi-)markets, and networks (which can be based on a large number of different scenarios that incorporate elements of the network paradigms used in biological systems).  It should be re-emphasized that the spreading of network structures in human society actually promotes the implementation of the basic principles of network socialism.

The next work in this series will address the political applications of networks as structural units of the new socio-economic formation that is currently under development in the whole world. 


Bard, A., & Söderqvist, A. (2002). Netocracy: The New Power Elite and Life after Capitalism. London, New York, & Toronto: Pearson Education. Ltd.

Balakrishman, S. N. & Weil, R. D. (1996). Neurocontrol: a literature survey. Mathematical & Computer Modelling, 23(1/2), 101-117.

Barabási, A.-L. (2002). Linked: The New Science of Networks. New York: Perseus.

Beck, K., Grenning, J., Martin, R. C. & et al. (2001). Manifesto for Agile Software Development.

Ben-Jacob, E. (2003). Bacterial self-organization: co-enhancement of complexification and adaptability in a dynamic environment. Philosophical Transactions of the Royal Society. A,. 361, 1283–1312.

Ben-Jacob, E., Becker, I., Shapira, Y., & Levine, H. (2004). Bacterial linguistic communication and social intelligence. Trends in Microbiology, 12(8), 366–372.

Birchall, J. (2004). Cooperatives and the Millennium Development Goals. Geneva: International Labour Office. Comnission for the promotion and Advancement of Cooperatives.

Bohlhalter, S., Fretz, C., & Weeter, B. (2002). Hierarchical versus parallel processing in tactile object recognition: a behavioural-neuroanatomical study of perceptive tactile agnosia. Brain, 125(11), 2537–2548.

Borgatti, S. P. & Foster, P. C. (2003). The network paradigm in organizational research: a review and typology. Journal of Managemant, 29(6), 991-1013.

Börzel, T. (1998). Organizing Babylon — on the different conceptions of policy networks. Public Administration, 76, 253–273.

Castells, M. (1996). The Rise of the Network Society, The Information Age: Economy, Society and Culture. Vol. I. Cambridge, MA & Oxford, UK: Blackwell.

Castells, M. (2004). Informationalism, networks, and the network society: a theoretical blueprint. In: M. Castells (Ed.), The Network Society: a Cross-Cultural Perspective (pp.3-45). Northampton, MA: Edward Elgar.

Chang, L.-C. & Lee, G. C. (2010). A team-teaching model for practicing project-based learning in high school: Collaboration between computer and subject teachers. Computers & Education, 55, 961-969.

Cohn, M. (2010). Succeeding with Agile: Software Development Using Scrum. Upper Saddle River, NJ, Boston etc.: Addison-Wesley.

Cooperative Grocer Network. (2014).

Deleuze, G. & Guattari, F.. (2004). A Thousand Plateaus. London & New York: Continuum.

Dubynin, V. A., Kamensky, A. A., Sapin, M. P., & Sivoglazov, V. N. (2003). Regulatory Systems of the Human Organism. Moscow: Drofa.

Hölldobler, B. & Wilson, E. O. (1990). The Ants. Cambridge, MA: Harvard University Press.

Hölldobler, B. & Wilson, E. O. (2009). The Superorganism: The Beauty, Elegance, and Strangeness of Insect Societies. New York: W.W. Norton.

Hölldobler, B. & Wilson, E. O. (2010). The Leafcutter Ants: Civilization by Instinct. New York: W.W. Norton.

Kück, U., Nowrousian, M., Hoff, B., & Engh, I. (2009). Schimmelpilze. Lebensweise, Nutzen, Schaden, Bekämpfung. Springer-Verlag: Berlin u. Heidelberg.

Malinetsky, G. G. (2014). Synergetics, Interdisciplinarity, and the Post-nonclassical Science of the 21st Century. S. P. Kurdyumov’s Website. http:

Marfenin, N. N. (2002). Decentralized self-regulation of integrity of colonial polyps. Zhurnal Obschei Biologii (Journal of General Biology), 63(1), 26–39.

Marfenin, N. N. (2011). Principles of Organization and Functioning of the Network Structure within a Hydroid Colony. Presentation at a Meeting of the Club of Biopolitics, a Subdivision of the Moscow Society of Natural Scientists.

Meulemann, L. (2008). Public Management and the Metagovernance of Hierarchies, Networks and Markets. Heidelberg: Physica-Verlag. 2008.

Millner, B. Z. (2006). Organization Theory. A Guidebook. Moscow: Infra-M.

Networks. (2003). We Are Everywhere. The Irresistible Rise of Global Anticapitalism. K. Arier, G. Chesters, T. Credland, J. Jordan, A. Stern, & J. Whity (Eds.).

Newman, M. E. J. (2003). The structure and function of complex networks. SIAM Review, 45(2), 167–256.

Newman, M. E. J. (2012). Networks. An Introduction. Oxford & New York: Oxford University Press.

Novgorodova, T. A. (2003). Intraspecies diversity of behavior models in the ant Formica cunicularia glauca during trophobiosis. Uspekhi Sovremennoi Biologii, 123(3), 229-233.

Oleskin, A. V. (1996). Making a new case for voluntary cooperation-based fission-fusion structures in human society. Social Science Information, 35(4), 619-627.

Oleskin, A. V., & Masters, R. D. (1997). Biopolitics in Russia: history and prospects for the future. Research in Biopolitics, 5, 279—299.

Oleskin, A. V., Pivovarova, L. V., Kartashova, E. R., & Gusev, M. V. (2001). Teaching biopolitics in terms of school biology syllabi. Moscow University Herald. Biology Series, No. 3, 3-13.

Oleskin, A. V. (2014a). Network Structures in Biological Systems and in Human Society. Haupauge (New York): Nova Science Publishers.

Oleskin, A. V. (2014b). Network structures in biological systems. Biology Bulletin Reviews, V.74(1), 47-40.

Powell, W. W. (1990). Neither market nor hierarchy: network forms of organization. Research in Organizational Behavior, 12, 295-336.

Putnam, R. D., (2000). Bowling Alone: The Collapse and Revival of American Community. New York: Simon & Schuster.

Schmidt-Hempel, P. (1990). Reproductive competition and the evolution of workload in social insects. American Naturalist, 135(4), 501-526.

Trkman, P. & Desouza, K. C. (2012). Knowledge risks in organizational networks: an exploratory framework. Journal of Strategic Information Systems, 21, 1-17.

van Alstyne, M. (1997). The state of network organizations: a survey in three frameworks.

Wray, M. K., Mattila, H. R., & Seeley, T. D. (2011). Collective personalities in honeybee colonies are linked to colony fitness. Animal Behaviour, 81, 559-568.

Zakharov, A. A. (1987). Ant societies. Science in the USSR, No. 1, 118—127.

Zakharov, A. A. (1991). Organization of Communities in Ants. Moscow: Nauka.

Zakharov, A. A. (1995). Alliances of workers in the family of the ants of the genus Formica (Hymenoptera, Formicidae). Uspekhi Sovremennoi Biologii (Advances in Modern Biology), 115(6), 459–469.

[1] The prefix quasi- should be used for biological systems and the stages of evolution of human society during which there was no market as such, although competitive relations among individuals and groups were quite widespread.

[2] In some synapses, the axon of one neuron directly interacts with another neuron’s soma, in the absence of a connecting dendrite.

[4] This illustrates the general property of many networks that break down into small subnetworks or clusters; the phenomenon is called “clustering” of “cliquishness”.