Printer Friendly

The need for a transdisciplinary approach to explain human brain structure and functioning mechanisms.


Due to the evolution of the knowledge theory, as well as of the new techniques and technologies, contemporary research paradigms have shown significant changes. The hyperspecialization developed in the late 19th and early 20th century was a stage when scientific disciplines crystallized and this allowed a positivist and analytical approach, but which in the end proved to be too restrictive and simplifying. A holistic approach to the knowledge of reality has proven to be increasingly necessary.

In this way, there appeared the necessity of an interdisciplinary approach among research disciplines, allowing the integration of knowledge in a epistemological complex, which is closer to reality. The interdisciplinary approach has proved to be increasingly evolved into a broad coverage, uniting different disciplines, but that need to be seen together, in order to integrate knowledge of reality. In the last half of the 20th, there have been developed a number of theories and concepts (fractals, chaos, nonlinear dynamics), which can be found in the complex systems theory. This enables a holistic approach from the atom to the cosmos, including the human brain structure and functions.

Nowadays, physics, quantum mechanics, biochemistry, cell biology, meteorology, cosmos and so on can be addressed by theories describing the essential functioning mechanisms. Although, there still remain phenomena of reality that cannot be covered by scientific methodology. Art, religion and culture, in general, represent forms of knowledge that have been circumvented by science. Transdisciplinarity aims to include all of them and, from the theoretical discussions, it starts to have practical consequences in the development of programs that include consortia of universities, such as the Human Genome Project and, recently, the Human Brain Project.


First of all, some clarifications of the terminology and concepts are in order (the reader can refer to [11, 23, 24, 25-27] for more details).

Disciplinarity is about mono-discipline, which represents specialization in isolation.

Multidisciplinarity means when a person studies, simultaneously or in sequence, more than one area of knowledge, without making any connections between them. Thus, it concerns itself with studying a research topic in not just one discipline, but in several simultaneously.

In recent decades, research has evolved from the study focused on disciplines, to the interdisciplinary one. Thus emerged the notion of interdisciplinarity in much broader sense, linking different disciplines of knowledge domains. Interdisciplinarity has a different goal than multidisciplinarity since it concerns the transfer of methods from one discipline to another.

Pluridisciplinarity means cooperation between disciplines, between compatible areas of knowledge, on a common hierarchical level, without any coordination. On the other hand, interdisciplinarity is, usually, organized on two hierarchical levels, thus implying coordination of a lower level from a higher one.

Transdisciplinarity concerns that which is at once between the disciplines, across the different disciplines, and beyond all disciplines.

Transdisciplinarity is a relatively young approach. Piaget developed the concept seven centuries after disciplinarity had evolved. The word itself first appeared in France, in 1970, in the talks of Jean Piaget, Erich Jantsch, and Andre Lichnerowicz at the international workshop "Interdisciplinarity--Teaching and Research Problems in Universities".

Transdisciplinarity represents the result of a coordination between all hierarchical levels. In fact, more than a new discipline or superdiscipline, transdisciplinarity is a systemic and more holistic way of perceiving the world. It overcomes the narrow areas of subjects and disciplines. It is a scientific principle of work and organisation which spans across subjects and disciplines. Without being a method or an elaborated form of a methodology, it represents a principle of research.

Nicolescu [25-27] defines transdisciplinarity through three methodological postulates: the existence of levels of Reality, the logic of the included middle, and complexity. In the presence of several levels of Reality, the space between disciplines and beyond disciplines is full of information. Disciplinary research concerns, at most, one and the same level of Reality; moreover, in most cases, it only concerns fragments of one level of Reality. On the contrary, transdisciplinarity concerns the dynamics engendered by the action of several levels of Reality at once. The discovery of these dynamics necessarily passes through disciplinary knowledge. While not a new discipline or a new superdiscipline, transdisciplinarity is nourished by disciplinary research; in turn, disciplinary research is clarified by transdisciplinary knowledge in a new, fertile way. In this sense, disciplinary and transdisciplinary research are complementary and not antagonistic. As in the case of disciplinarity, transdisciplinary research is not antagonistic, but complementary to multidisciplinarity and interdisciplinarity research.

According to Nicolescu, transdisciplinarity is nevertheless radically distinct from multidisciplinarity and interdisciplinarity because of its goal, the understanding of the present world, which cannot be accomplished in the framework of disciplinary research. The goal of multidisciplinarity and interdisciplinarity always remains within the framework of disciplinary research. If transdisciplinarity is often confused with interdisciplinarity and multidisciplinarity (and by the same token, we note that interdisciplinarity is often confused with multidisciplinarity), this is explained in a large part by the fact that all three overflow disciplinary boundaries.

In the last decades, neurosciences attempted to encompass the phenomenology of psychological reality within an interdisciplinary and even transdisciplinary approach. These wide necessities come from the need to apply the principles of complex systems to brain activity as well, in short presented further.


In the past decade, the Human Genome project has experienced such an approach, which proved successful. As a result, in 2013, it were opened an European offensive on knowledge of the human brain, called the Human Brain Project (HBP) [22], and also a Human Brain Mapping Initiative in USA. In both projects, there is a large concern of universities and private entities in a wide range of interdisciplinary research which federates European efforts to address one of the greatest challenges of modern science: understanding the human brain.

The goal of the Human Brain Project is to pull together all existing knowledge about the human brain and to reconstruct the brain, piece by piece, in supercomputer-based models and simulations. The models offer the prospect of a new understanding of the human brain and its diseases and of completely new computing and robotic technologies. The European Commission supported this vision, selecting the HBP as one of two projects to be funded through the new FET Flagship Programme.

Federating more than 80 European and international research institutions, the Human Brain Project is planned to last ten years (2013-2023) and the cost is estimated at 1.19 billion euros. The project associates some important North American and Japanese partners and it is coordinated at the Ecole Polytechnique Federale de Lausanne by the neuroscientist Henry Markram.

In neuroscience, the project will use neuroinformatics and brain simulation to collect and integrate experimental data, identifying and filling gaps in our knowledge and prioritising future experiments. In medicine, the HBP will use medical informatics to identify biological signatures of brain disease, allowing diagnosis at an early stage, before the disease has done irreversible damage, and enabling personalized treatment, adapted to the needs of individual patients. Better diagnosis, combined with disease and drug simulation, will accelerate the discovery of new treatments, drastically lowering the cost of drug discovery. In computing, new techniques of interactive supercomputing, driven by the needs of brain simulation, will impact a vast range of industries.

On the other hand, it became necessary to overcome the paradigm according to which psychological activity is an exclusive product of neuronal activity. The detailed understanding of the way in which the main types of neurons function, will not help us entirely understand the mental. The complex systems theory comes with totally different assumptions. In the complex systems generated by a great number of elements, the properties of the systems cannot be found in the sum of the properties of constitutive elements. The emergence property is the one that creates a link between the multitude of components and the properties of the complex system. As a result, even if we describe all the properties of all neurons, we will not be closer to understanding the mental.

In fact, the psychological system has all the necessary elements in order to associate it with a complex system. That is the reason why we sustain the theory of approaching the mental from the complex system theory perspective.

Memorizing takes place at the interface of the spectral field with the contribution of certain information patterns as well as new information from the complex space which represents the potential, unstructured, non-differentiable, unpredictable parts. Such a hypothesis is possible using a new vision on information according to which information is made up of energy patterns included in a topological dynamics. The dynamics between the complex space and the real space (the neuronal network) through the spectral field (the wave field represented by the totality of the waves associated to corpuscles within the neuronal network) lies at the basis of the psychological system functioning. This paradigm can generate new hypotheses which should explain the mysteries of the psychological life, just as the old "mind--body" duality. This brain dynamics between the complex space and the real one represents what we call the psyche and it consists of the information processing in neuronal networks.


The principles of the complex systems theory can be applied through specific properties at any scale or reality level, from the string theory to the cosmologic models and to meteorology (see, for instance [6, 7, 8, 9, 21].

In the last decade, many studies try to apply this theory on biological systems, the human body and the human mind.

In the last years, however, the neurosciences must open up more to interdisciplinarity, as well as to transdisciplinarity, in order to include Quantum Physics, Information Technology and even Cosmology scientists, as well as traditional specialists in Psychology, Neurology and Psychopathology. This widely-interdisciplinary need emerges from the necessity to apply the principles of complex systems to brain activity.

The complex systems theory comes here with totally different prerequisites. In the systems made up of a great number of elements, the system properties are not to be found in the sum of the properties of the constitutive elements. The emergence property is the one which creates a connection between the multitude of the components and the properties of the complex system. As a consequence, even if we were to describe all the properties of all the neurons, we will not come closer to understanding the mental.

The main difficulty of the neuroscientists is the prejudice to study only the neuronal, neuroglial and neurotransmitters structure. Starting from the quantum theory according to which every particle has a corresponding wave, and taking into account that starting from the newest cell structures, the neurofibriles, down to the cell, tissues and organs, one can observe the existence of a strong wave spectral activity. This spectral wave component has been understudied, even if it is contained in the quantum physics theories, but also in the neurophysiological concepts and it is rudimentarily highlighted at the level of overall cerebral activity through EEG and EMG. This spectral component associated and related to the material, corpuscular one (the neuronal and non-neuronal structures of the brain) must be, at least, as important as the corpuscular part, which is structured and was studied in the last hundred years. Thus, we should pay more attention to the wave, spectral component of the brain.

Also, even the neuroscientists came 50 years ago to the conclusion that the transmission of signals at the level of analysers is made spectrally. De Valois and de Valois [17, 18] demonstrated that, at the level of perception of the visual analyser, the signal is transmitted towards the cerebral parietal cortex on a spectral way, using the Fourier series for the interpretation of their experiences, used in describing the wave phenomena. Also, von Bekesy [29] proved that the tactile transmission is made spectrally, later on drawing the conclusion that the transmission of the signals of all analysers can be described by mathematical equations specific to waves.

All these data, as well as the laser and hologram technology discovered in the same year made it possible that Bohm [10] and Pribram [28] brought arguments to sustain a theory of the holographic and holonomic brain, according to which in the spectral space associated to the structures of the brain were structuring conditions of a holographic system, which could both explain the enigma of memory structure and the connection with cognition and affection.

The description of fractals and of their role in structuring reality upheld this spectral approach, as the hologram is nothing else but a fractal structure, even more because the architecture of the brain, of the blood vessels in the brain and of the whole human body has an underlying fractal algorithm and a fractal geometry.

The approach of the structure and activity of the brain from a spectral perspective allows the study of the brain from the perspective of the theory of complex systems. We can try to identify the unstructured, chaotic, stochastic component, along with the structured, causal component with linear dynamics, as a dynamics between the two components on the phases space, in which there is a permanent exchange of energy, but also of information. If we come to accept this, then certain principles, properties and characteristics from plasma physics, fluids and non-linear dynamics, in general, could be used to study the mental.


We intend to bring a valuable and innovative contribution to the multi-scale theory in order to explain brain functioning and mechanisms from the fractal theory, chaos, non-linear systems dynamics, topology, complex analysis, set-valued analysis etc. perspective, all reunited in the complex systems theory.

Complex systems theory enables a holistic approach concerning human brain structure and functions. Many phenomena with complex patterns and structures are widely observed in the brain and these phenomena are manifestations of a multidisciplinary paradigm called emergence or complexity. In Scale Relativity Theory, the dynamics of any physical complex system (as the human brain is) is described through variables which can be expressed through fractal functions, i.e., functions which are dependent both on coordinates and on time, but also on resolution scales. At any scale there are the two types of realities that coexist, the differential and non-differential two parts, highlighted by the hydrodynamic theory and the stochastic theory.

We want to emphasize that not only the corpuscular, but also the wave, spectral part essentially intervenes in human brain structure and functioning mechanisms. In this sense, we began to develop in [1-5, 12-16, 19, 20] new models and theories based on complex systems theory, precisely, using fractal theory, chaos theory, topology, complex analysis, modern physics etc.

Gabriel CRUMPEI--M. D., Ph. D., Catharsis Psychiatry, Psychotherapy and Counselling Centre Iasi, No. 2 Vasile Conta street, zip code 700106, Iasi, Romania, E-mail:

Alina GAVRILUT--M. D., Ph. D., Faculty of Mathematics, "Alexandru Ioan Cuza" University, No. 11 Carol I Bd., Iasi, zip code 700506, Romania, E-mail:

Maricel AGOP--M. D., Ph. D., "Gheorghe Asachi" Technical University of Iasi, Department of Physics, No. 67 Professor Dr. Doc. Dimitrie Mangeron Bd., zip code 700050, Iasi, Romania, E-mail:

Irina CRUMPEI TANASA--M. D., Ph. D., Psychology and Education Sciences Department, "Alexandru Ioan Cuza" University, No. 11 Carol I Bd., Iasi, zip code 700506, Romania, E-mail:

Gabriel GAVRILUT--M. D., Comarna College of Iasi, Romania, E-mail:


The authors state that they are no declared conflicts of interest regarding this paper.


[1.] Agop, M., Gavrilut, A., Crumpei, G., Doroftei, B. (2014). Informational Non-differentiable Entropy and Uncertainty Relations in Complex Systems. Entropy 6 (11), 6042-6058.

[2.] Agop, M., Gavrilut, A., Crumpei, G., Gavrilut, G. (2015). On a new possible class of cellular neural network. Proceedings of the 11th International Conference Constructive and technological design optimization in the machine building field. OPROTEH--2015 Bacau, June, 4th-6th.

[3.] Agop, M., Gavrilut, A., Stefan, G., Doroftei, B. (2015). Implications of Non-Differentiable Entropy on a Space-Time Manifold. Entropy, 17 (4), 2184-2197.

[4.] Agop, M., Gavrilut, A., Stefan, G. (2015) SL (2R) invariance of the Kepler type motions and Shannon informational entropy. Uncertainty relations through the constant value of the Onicescu informational energy. Rep. Math. Phys, Vol. 75, No. 1, 101-112.

[5.] Agop, M., Gavrilut, A., Rezus, E. (2015). Implications of Onicescu's informational energy in some fundamental physical models. International Journal of Modern physics B, Vol. 29, No. 0, DOI: 10.1142/S0217979215500459.

[6.] Atmanspacher, H. (2011). Quantum approaches to consciousness. The Stanford Encyclopaedia of Philosophy.

[7.] Atmanspacher, H., Fach, W. (2013). A structural-phenomenological typology of mind-matter correlations. Journal of Analytical Psychology, 219-244.

[8.] Bellomo, N., Bianca, C., Mongiovi, M.S. (2010). On the modelling of nonlinear interactions in large complex systems. Applied Mathematics Letters, Vol. 23, Issue 11, 1372-1377.

[9.] Bianca, C., Bellomo, N. (2011). Towards a Mathematical Theory of Complex Biological Systems. Series in Mathematical Biology and Medicine, Vol. 11, World Scientific Publishing.

[10.] Bohm, D. (1993). The Undivided Universe: An ontological interpretation of quantum theory. B. J. Hiley, London: Routledge.

[11.] Brown, V. A. (2015). Utopian thinking and collective mind: Beyond transdisciplinarity. Futures, Vol. 65, 209-216.

[12.] Crumpei, G., Gavrilut, A., Agop, M., Crumpei, I., Negura, L., Grecu, I. (2014). New Mathematical and Theoretical Foundation in Human Brain Research. An interdisciplinary approach in a transdisciplinary world. Human and Social Studies, Vol. 3, No. 1, 45-58.

[13.] Crumpei, G., Gavrilut, A., Agop, M., Crumpei, I. (2014). An Exercise in a Transdisciplinary Approach for New Knowledge Paradigms. Human and Social Studies, Vol. 3, No. 3, 114-143.

[14.] Crumpei, G., Gavrilut, A., Agop, M., Crumpei, I. (2015). An approach on information from topological view. Proceedings of the 8th Chaos 2015 International Conference, Paris, France, 26-29 May.

[15.] Crumpei, G., Gavrilut, A., Agop, M., Crumpei, I. (2015). Brain functionality via complex systems theory, Proceedings of the 8th Chaos 2015 International Conference, Paris, France, 26-29 May.

[16.] Crumpei, G., Gavrilut, A., Agop, M., Crumpei, I., Negura, L., Grecu, I. (2014). Spafiul imaginar din perspectiva sistemelor complexe (in Romanian). Philologica Jassyensia, X, No. 1 (19), Suppl., 617-626.

[17.] De Valois, R. L., de Valois, K. K. (1988). Spatial vision. (Oxford Psychology series No. 14), New York, Oxford University Press.

[18.] De Valois, R. L., de Valois, K. K. (1993). A multi-stage color model. Vision Res. 33. 8, 1053-1065.

[19.] Gavrilut, A., Agop, M. (2013). A Mathematical Approach in the Dynamics of the Complex Systems. Ars Longa Publishing House (in Romanian).

[20.] Gavrilut, A., Agop, M., Crumpei, G., Gavrilut, G. (2015). Approximation properties from a mathematical-physical perspective and possible correlations with the neuronal network fractality. Proceedings of the 11th International Conference Constructive and technological design optimization in the machine building field, OPROTEH--2015, Bacau, June 4th-6th.

[21.] Hooker, C. (2011). Introduction to Philosophy of Complex Systems, A: Part A: Towards a framework for complex systems. Philosophy of Complex Systems, 3-90.


[23.] Max-Neef, M. A. (2005). Foundations of transdisciplinarity. Ecological Economics 53, 5-16.

[24.] Mittelstrass, J. (2002). Transdisciplinarity--new structures in science. in Innovative Structures in Basic Research (Ringberg Symposium, 4-7 October 2000), 43-54. Munich: Max-PlanckGesellschaft.

[25.] Nicolescu, B. (2000). Transdisciplinarity and Complexity. Bulletin Interactif du CIRET, Paris.

[26.] Nicolescu, B. (2010). Methodology of Transdisciplinarity--Levels of Reality, Logic of the Included Middle and Complexity. Transdisciplinary Journal of Engineering & Science Vol. 1, No. 1, 19-38.

[27.] Nicolescu, B. (2012). Complexity and transdisciplinarity--Discontinuity, levels of Reality and the Hidden Third. Futures, Vol. 44, Issue 8, 711-718.

[28.] Pribram, K. (1986). The Cognitive Revolution and Mind/Brain Issues. American Psychologist 41 (5), 507-520.

[29.] Von Bekesy, G. (1970). Problems relating psychological and electrophysiological observations in sensory perception. Perspectives in Biology and Medicine, 11, 179-194.





No. 11 Carol I Bd., zip code 700506, Iasi, Romania

Tel: +40 751 242 004


Submission: September, 7th, 2015

Acceptance: October, 12th, 2015
COPYRIGHT 2015 Institute of Psychiatry Socola, Iasi
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2015 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Author:Crumpei, Gabriel; Gavrilut, Alina; Agop, Maricel; Tanasa, Irina Crumpei; Gavrilut, Gabriel
Publication:Bulletin of Integrative Psychiatry
Article Type:Report
Date:Dec 1, 2015
Previous Article:Reflections on psychiatry.
Next Article:Preliminary data on sexual dysfunction in depressed patients.

Terms of use | Privacy policy | Copyright © 2019 Farlex, Inc. | Feedback | For webmasters