Systems Theory and Cybernetics
was proposed by Ludwig von Bertalanffy (1901–1972), a biologist who worked on the basic principles of life and searched for universal laws of organization [80
]. The basic concepts of the systems approach are: (i) a system is a whole that functions by virtue of the interaction of its parts, and (ii) is defined by its elements and the relationship among these elements; (iii) the systems approach integrates the analytic and synthetic methods by taking into account the interaction of the system with its environment; (iv) living structures are open systems, which interact with other systems outside of themselves. Bertalanffy’s conceptual model of the living organism as an open system has had revolutionary implications for life and behavioral sciences.
, as a scientific discipline has been named by Norbert Wiener (1894–1964). It was the title of his book with the subtitle Control and Communication in the Animal and the Machine [86
]. Cybernetics was a pluralistic theory and an interdisciplinary movement of a number of leading intellectuals. The term cybernetics goes back to Plato, when he explained the principles of political self-governance. goal-directed behavior
Wiener himself emphasized the role of feedback mechanisms in the goal-oriented systems. While the physiologists already knew that the involuntary (autonomous) nervous systems control Bernard’s internal milieu, he extended the concept suggesting that the voluntary nervous system may control the environment by some feedback mechanisms and searched for a theory of goal-oriented behavior. This theory supplemented with the concept of circular causality promised a new framework to understand the behavior of animals, humans, and computers just under design and construction that time.
The other supporting pillar of cybernetics is the brain-computer analogy suggested by the spirit of the McCulloch-Pitts Neuron (MCP neuron). An MCP [55
] neuron is a formal model, and it can be identified as a binary threshold unit. A neuron initiates an impulse if the weighted sum of their inputs exceeds a threshold, otherwise it remains in silence.The MCP model framework wanted to capture the logical basis of neural computation, and intentionally contains neurobiological simplifications. The state is binary, the time is discrete, the threshold and the wiring are fixed. Chemical and electrical interactions are neglected, glial cells are also not taken into consideration. McCulloch and Pitts showed that a large enough number of synchronously updated neurons connected by appropriate weights could perform many possible computations. From retrospective we see that bottom up models of brain regions can be built based on networks of interconnected single cell models.
McCulloch (1898–1969) served as the chairman of a series of conferences (Macy conferences held between 1946–1953 sponsored by and named after the Macy Foundation, where at the beginning Wiener also played an important role. The main topics of the conferences were: (i) Applicability of a Logic Machine Model to both Brain and Computer, (ii) Analogies between Organisms and Machines; (iii) Information Theory; (iv) Neuroses and Pathology of Mental Life and (v) Human and Social Communication.
Systems theory and cybernetics emphasized the importance of organization principles and the have anticipated the use of abstract computational models in biology to study normal and pathological phenomena.
Genetic Determinism, Biological Complexity and Systems Biology
It is a mere coincidence that the last Macy conference was held in the same year (1953) when the Watson–Crick [11
] paper was published. The research program of the new “molecular biology” suggested that the replication, transcription and translation of the genetic material should and could be explained by chemical mechanisms. Crick’s central dogma of molecular biology stated that there was a unidirectional information flow from DNA via RNA (ribonucleic acid) to proteins.
While the central dogma was enormously successful in discovering many detailed chemical processes of life phenomena, philosophically it suggested, as Crick himself wrote [10
], that “the ultimate aim of the modern movement in biology is to explain all biology in terms of physics and chemistry”.1
The central dogma led to genetic determinism
. While certain phenotypes can be mapped to a single gene, the extreme form of genetic determinism, which probably nobody believes, would state that all phenotypes are purely genetically determined. Genetic determinism has lost its attraction as a unique explanation for the appearance of specific phenotypic traits. After 60 years of extensive research in molecular biology, there is a very good understanding of the intricate mechanisms that allow genes to be translated into proteins. However, this knowledge has given us very little insight about the causal chains
that link genes to the morphological and other phenotypic traits of organisms [48
]. Also, human diseases due to genetic disorders are the results of the interaction of many gene products. One generally used method to understand the performance of a complex genetic networks is the transgenic
In the spirit of systems theory and of cybernetics Robert Rosen (1934–1998) [58
] gave a formalism, which connected phenotype
(i.e. what we can observe directly about an organism) and genotype
(the genetic makeup). In particular, phenotype is interpreted as being “caused” by genotype. He also argued that to understand biological phenotype, in addition to the Newtonian paradigm, the organizational principles should be uncovered. He realized that a crucial property of living systems, that while they are thermodynamically open systems, organizationally they should be closed. To put it in another way, all components, which are subject of degradation due to ordinary wear and tear, should be repaired or resynthesized within the cell. Rosen gave a mathematical framework to show how it is possible to do.
Systems biology is an emergent movement to combine system-level description with microscopic details. It might be interpreted as the renaissance of cybernetics and of system theory, materialized in the works of Robert Rosen. In an excellent review Olaf Wolkenhauer [87
] explained how the concepts of systems theory, and of cybernetics were applied by Rosen to biology, and how his ideas returned now under the name of systems biology. For a very good new introductory textbook on systems biology, see [30
Genetic reductionism, in particular, has been abandoned as a useful explanatory scheme for understanding the phenotypic traits of complex biological systems. Genes are increasingly studied today because they are involved in the genetic program that unfolds during development and embryogenesis rather than as agents responsible for the inheritance of traits from parents to offspring [73
As a reaction to something that some people might have seen as the “tyranny of molecular biology”, the systems thinking has been revitalized in the last several years. Systems thinking correctly states that while reductionist research strategy was very successful, it underestimates the complexity of life. It is clear, that decomposing, dissecting and analyzing constituents of a complex system is indispensable and extremely important. Molecular biology achieved a lot to uncover the structures of many chemical molecules and chemical reactions among the molecules behind life processes. The typical molecular biologist’s approach suggests that there is an “upward causation” from molecular states to behavior. The complex systems perspective [15
] does not deny the fundamental results of molecular biology, but emphasizes other principles of biological organization.
One of the pioneers of systems biology, Denis Noble offers ten principles of systems biology [52
Biological functionality is multi-level
Transmission of information is not one way
DNA is not the sole transmitter of inheritance
The theory of biological relativity: there is no privileged level of causality
Gene ontology will fail without higher-level insight
There is no genetic program
There are no programs at any other level
There are no programs in the brain
The self is not an object
There are many more to be discovered; a genuine “theory of biology” does not yet exist
Systems biology emphasizes (i) the interactions among cell constituents and (ii) the dynamic character of these interactions. Biological systems are paradigmatic of hierarchical dynamical systems. For such systems, levels are often connected by some feedback control mechanism. Famously, protein channels carry current that changes the membrane potential of a cell, while the membrane potential changes the protein channels. This mechanism implements circular causality.
Generally, what we see is that systems biology, partially unwittingly, returned to its predecessors, systems theory and cybernetics.
Systems Neuroscience and Systems Neuropharmacology
Systems Neuroscience is a field devoted to understanding whole systems of the brain, such as those involved in sensation, movement, learning and memory, attention, reward, decision-making, reasoning, executive functions, and emotions. The structural, functional and dynamic aspects are integrated into a coherent framework [3
]. It also deals with the principles of information processing, storage and retrieval at the systems level.
The study of brain systems includes the analysis of individual regions, as well as hierarchical levels of information processing. In terms of methodologies, it benefits from diverse techniques from single-cell recording to high-resolution imaging of brain activity. Systems neuroscience also uses computational studies to organize data into a coherent picture.
While the standard structure-based design of drugs for psychiatric disorders is based on drug-receptor interactions, the systems physiology perspective [7
] emphasizes the effects of drugs on spatiotemporal brain activities. The theoretical framework for understanding normal and pathological spatiotemporal activities should be dynamical system theory to identify targets, and then, in the next stage, chemists should design molecules to modify the desired target.
Dynamical system theory and computational neuroscience combined with traditional molecular and electrophysiological methods would open new avenues in drug discovery that may lead to genuinely new neurological and psychiatric therapies [1
]. More specifically, these model-based highly valuable techniques are able to integrate multiple disciplines at different spatiotemporal scales [16
Recently the concepts and methods of systems biology have been used in pharmacology [67
] and psychiatry [70
]. Specifically Noble [52
] states that there is no privileged level of causality, and there is no reason to assume that the molecular/genetic level uniquely determines mental activities, so the levels should be integrated.
Our own belief is [72
]: “…Multi-scale modeling has multiple meanings and goals including different time and spatial scales, levels of organization, even multi-stage processing. While the significance and importance of describing neural phenomena at different levels simultaneously is clear in many cases, we certainly don’t have a single general mathematical framework. Mostly we have specific examples for coupling two or more levels. The understanding and control of normal and pathological behavior, the transfer of knowledge about the brain function and dynamics to establish new computational and technological devices needs the integration of molecular, cellular, network, regional and system levels, and now the focus ins on elaborating mathematically well-founded and biologically significant multi-scale models.”