Human Brain Theory: Information-Commutation Device of the Brain and Principles of its Work and Modeling

Andrey S. Bryukhovetskiy, MD, PhD
Federal Research Center for Specialized Types of Medical Assistance and Medical Technologies of FMBA of Russia, Moscow, Russia

Series: Neuroscience Research Progress
BISAC: MED057000




Digitally watermarked, DRM-free.
Immediate eBook download after purchase.

Product price
Additional options total:
Order total:



The book was written as an attempt to find the solution to one of the most complex and unsolved issues of the human anatomy: the understanding of the human brain and the principles according to which it operates.

Currently, it is important to look at the challenge in an alternatively non-standard, yet still systemic way, paying less attention to details and outlining the ways out of this crisis of neuroscience.

The purpose of this monograph is to describe the author’s theory about the brain’s architecture and operation to the medical and scientific community. Accompanied with extensive clinical, research and training experience, the author’s theoretical concepts of the brain synthesized with scientific evidence brought about the conclusion that low efficiency in neurologic therapy and mental diseases; the inability to work out mathematical models and simulations that could compete with the human brain; an academic dead end in the development of artificial intelligence; as well as high energy consumption of the computing innovations were conditioned by the inaccurate methodology and outdated anatomical and physiological views of the neurologists and neuroscientists on information processing in the brain, registration of memories and basic functions of the key morphological structures of the brain.

The morphological structure and physiological functions of all known anatomical formations of the brain were defined in the late nineteenth century. Since then, these functions have been accepted as dogmatic.

The book shows that present day multi-level neuroresearch relies on the foundation of systemic, morphofunctional and neuroanatomic knowledge about the brain structure. It looks for correlations between genome and post-genome data of molecular research in the brain tissue, as well as with neuropsychological and cognitive data; that is, the book intends to integrate the non-integrable into unified information space. The systemic approach in neuroresearch has become outdated by now and interferes with scientific development.

The information approach in the author’s research of the genome, transcriptome, proteome in health and in disease permitted the analysis of the inductivity and magnetization of the nervous tissue. It also provided the explanation for targeted movement of the data in the module of the nervous tissue. The author came to the conclusion that gene, protein and neural networks “confused and chained” the pathways of scientific thought. Neural networks are only logistic constructions to provide data transfer in the brain between different modules of the nervous tissue. The author presumes that the funds invested in the development of brain simulations and artificial intelligence will hardly result in the expected advantages. If we are unable to step over the stereotypes of the systemic, morphofunctional research of the previous century, no progress shall come about. The author’s theoretical survey resulted in the unique information-commutation theory of the brain and formulation of the key principles of brain operation. As a clinician and professor of neurology, the author underpins his theory with clinical examples.

This book presents the framework of the ideas that require experimental research and proof. (Imprint: Nova Biomedical)

In Lieu of a Preface


Chapter 1. Neurology and Neural Research in the Early 21st Century

Chapter 2. Contemporary Scientific Concepts of the Human Brain Operation and Organization

Chapter 3. Current Global Research of Brain: Theoretical, Methodological and Technological Bases for the Discoveries, Inventions and Innovations in Contemporary Neuroscience

Chapter 4. A System Approach as the Basic Methodology of Contemporary Neuroresearch: Its Advantages and Disadvantages

Chapter 5. An Information Approach to the Fundamental and Theoretical Research of the Brain

Chapter 6. The Theory of the Information-Commutation Organization of Human Brain and Its Operations Principles

Chapter 7. The Methodology and Technologies of Developing 3D Virtual Models of the Brain

Chapter 8. Methodological Errors and Systemic Errors of Theoretical Neurology in the Development of 3D Virtual Models of Brain

Chapter 9. The Methodology to Develop a 3D Simulation of the Brain Using the Information Approach

Chapter 10. The Future of Theoretical Neurology in Clinical Medicine, the Mathematical Modeling of the Brain and the Development of a Brain-Computer Interface




“In this wonderful new book, Professor Andrey S. Bryukhovetskiy brings to the neuroscience and human brain operation community an exciting new intellectual plane for slicing through the knowledge of human brain information processing. The dimensionality of this plane is high and its orientation is very new and valuable. Specifically, what he proposes is that many of the original viewpoints from past history (which have been thoroughly ignored by neuroscience), such as that of John von Neumann, need to be reconsidered and carefully integrated into a new picture of how the human brain and mind function. For example, he mentions von Neumann’s extraordinarily high estimate of the information storage in an adult human Central Nervous System (CNS): (280,000,000,000,000,000,000 bits) or roughly 30 Exabytes (see Figure 1).
1 Bit = Binary Digit
8 Bits = 1 Byte
1024 Bytes = 1 Kilobyte
1024 Kilobytes = 1 Megabyte
1024 Megabytes = 1 Gigabyte
1024 Gigabytes = 1 Terabyte
1024 Terabytes = 1 Petabyte
1024 Petabytes = 1 Exabyte
Figure 1. The Scale of Binary Numbers
This is an extremely large storage capacity. For example, it is estimated that all of the data stored by humanity in all of its technological devices in 2007 was 2.4 × 1021 bits, or 260 Exabytes [1]. In other words, the total information storage capacity of humankind’s machines is equal to that of about 9 adult humans! Now, clearly, this is NOT what neuroscientists have been thinking. In fact, the overwhelmingly dominant view today is that the total number of information processing neurons in the human CNS is roughly 25 Billion. And this would mean that the average neuron is storing roughly 1 Trillion bits of information! Of course, that is one of the marvelous things about this book: Bryukhovetskiy makes it clear that the storage of information in the human brain is HIERARCHICAL, and so the main point is that neuronal coding is mostly about storing weighted combinations of features that are more explicitly described at lower levels.
Consider this excerpt:
“So, the level of the field of consciousness is the holographic information level, that is, the higher information level of the information processing in the brain by means of manipulation of the already commuted holographic IIMs.The holographic IIMs can be further manipulated on the basis of the mathematical theories of commutations, machines, image recognition and many other contemporary theoretical approaches of mathematics and cybernetics. The main scientific fact and fundamental basis of our theoretical study lies in the interaction of all information structures of the brain tissues and information structures of other solid organs at the level of their magnetomes of the information structures according to the holographic principle. The formed hologram integrates specific subpopulation of the information structure of the brain and other organs of the human body and is the main regulator of their information exchange, interinfluence and interaction. Formation of specific hologram of the IIM provides cognitive functions (thinking, learning etc.) in the brain. Moreover, the thought becomes material as it has its own IIM that is formed by the specific set of the information structures and organs of human/mammal body. Thus, the mechanisms of the therapy with words and psychotherapy become clear. In other mammals the IIMs also form as exact holograms integrating the activity of multilevel information structures and are associated with certain emotions, shouting, type of barking, wailing etc. Our supposition that the pia of the brain functions as the display of a human/mammal biocomputer and simultaneously as the hard drive for the storage of huge volumes of the data explains for the available evidence of the brain functioning.”
Of course, this view is in some ways similar to ideas going back many decades. But the key point made in this book is that there is enormous benefit associated with examining a wide variety of issues related to human brain information storage together; and integrating the conclusions reached. Finally, it is important to point out that Bryukhovetskiy’s analysis extends very widely and considers very competently the most powerful and deeply meaningful human neuroscience experimental approaches (e.g., fMRI and cortical afferent bundle tracing). And that makes this book one which a wide variety of human information processing personnel (neuroscientists, psychologists, neurologists and neurosurgeons, and animal behavior specialists) should buy and read carefully.” - Robert Hecht-Nielsen, MD, Professor, University of California, San Diego

[1] The Human Brain Project. A Report to the European Commission. Lausanne, Switzerland: The HBP-PS Consortium; 2012. Available from: https://www. Accessed November 30, 2014. Report.
[2] Jibu, M; Yasue, K. Quantum Brain Dynamics and Consciousness. An Introduction. Amsterdam, the Netherlands: John Benjamins Publishing Company, 1995. Book.
[3] Pribram, KH. Quantum holography: Is it relevant to brain function? Information Sciences, 1999, 115(1–4). Journal article.
[4] Taylor, JG. On the neurodynamics of the creation of consciousness. Cogn Neurodyn. 2007 June, 1(2), 97-118. Journal article.
[5] Labouvie-Vief, G. Dynamic integration theory: Emotion, cognition, and equilibrium in later life. In: Bengston, VL, Gans D, Pulney NM, Silverstein M, editors. Handbook of theories of aging. 2nd ed. New York, NY, US: Springer Publishing Co, 2009.
[6] Obama’s 2013 State of the Union Address. The New York Times [Internet], 2013 Feb 12 [cited 2013 Feb 12]; Available from politics/obamas-2013-state-of-the-union-address.html. Newspaper article.
[7] National Institutes of Health. Brain Research through Advancing Innovative Neurotechnologies (BRAIN). Working group Interim Report, 2013. Available from Report.
[8] Duus, P. Topicheskiy diagnoz v nevrologhii: anatomiya, priznaki, simptomy [Topical Diagnosis in Neurology: Anatomy, Physiology, Signs, Symptoms]. Moscow: Vasar-Ferro, 1995. Russian. Book.
[9] Turing, AM. Computing machinery and intelligence. Mind., 1950, 59, 433-460. Journal article.
[10] Shtulman, DR; Levin, OS. Nevrologhiya: Spravochnik praktisheskogo vracha [Neurology: A Guide for Medical Practitioner]. Moscow: MED Press-Inform, 2008, Russian. Book.
[11] Alzheimer’s Association. 2015 Alzheimer’s disease facts and figures. Alzheimer’s and dementia., 2015 March, 11 (3), 332–384.
[12] Bryukhovetskiy, AS. Klinichesaya onkoproteomika: personifitsirovannaya provioopukholevaya kletochanya terapiya [Clinical oncoproteomics: personalized anticancer cell therapy]. Moscow: Poligraf Plus, 2013. Russian. Book.
[13] International Association of Neurorestoratology. Beijing Declaration of International Association of Neurorestoratology (IANR). Cell Transplant., 2009, 18, 487.
[14] Hawkins, J. How brain science will change computing [Internet]. TED, 2003. Available from: computing.html. Accessed July 12, 2012. Web page.
[15] Crick, F. Thinking about the brain. Scientific American., September 1979, pp. 219-232. Journal article.
[16] Pavlov, IP. Dvadtsatilerniy opyt obyektivnogo izucheniya vysshey deyatelnosti (povedeniya) zhivotnikh [Twenty years’ experience of the objective observations over higher activity (behavior) of the animals]. Moscow: Nauka, 1973, Russian. Book.
[17] Ukhtomsky, AA. Dominanta kak rabochiy printsip nervnykh tsentrov [Dominance as the working principle of nervous centers]. Leningrad: Nauka, 1978, Russian. Book.
[18] Davidovskaya, NA. Neoriya kompleksov v neiropsikhologicheskom aspekte [Neuropsychological aspects of the theory of complexes]. Smalta., 2014, 3, 36-42. Russian. Journal article.
[19] Pribram, K. Languages of the Brain: Experimental Paradoxes and Principles in Neuropsychology. N.Y. : Prentice Hall/Brandon House, 1971. Book.
[20] Holonomic brain theory [Internet]. 2015 [cited April 4, 2014]. Available from: Web page.
[21] Einstein’s brain [Internet]. January 21, 2005 [cited January 2014]. Available from: Web page.
[22] Anokhin, PK. Biologhiya i neirophisiologhiya uslovnogo refleksa [Biology and neurophysiology of condioned reflex]. Moscow: Meditsina, 1968. Russian. Book.
[23] Feighenberg, IM. Veroyatnostnoye prognozirovaniye v deyatelnosti mozga [Probabilistic prediction in the brain activity]. 1963, 2. Russian. Journal article.
[24] Simonov, PV. Teoriya otrazheniya i psikhophisiologiya emotsiy [The theory of reflection and psychophysiology of emotions]. Moscow: Nauka, 1970. Russian. Book.
[25] Simonov, PV. Emotsionalniy mozg [Emotional brain]. Moscow: Nauka, 1981. Russian. Book.
[26] Sudakov, KV. Funktsionalniye sistemy [Functional systems]. Moscow: Izdatelstvo RAMN, 2011. Russian. Book.
[27] Sperry, R. Brain bisection and the neurology of consciousness. In Eccles J, editor. Brain and conscious experience. New York: Springer Verlag, 1966. Book section.
[28] Ornstein, RE. The right mind: Making sense of hemispheres. New York: Houghton Mifflin Harcourt, 1997. Book.
[29] Benson, F; Zaidel, E. The dual brain: hemispheric specialization in humans. New York; The Guilford Press, 1985. Book.
[30] Khomskaya, ED. Neiropsikhologhiya [Neuropsychology]. Moscow: Izdatelstvo Moskovskogo Universiteta, 1987. Russian. Book.
[31] Luria, AR. Vysshiye korkoviye funktsii i ikh narusheniye pri lokalnikh porazheniyakh mozga [High cortical functions and their disorders in local injuries of the brain]. Moscow: Prosvescheniye, 1989. Russian. Book.
[32] Luria, AR. Mozg i psikhicheskiye protsessi [The brain and psychic processes]. Moscow: Izdatelstvo MGU, 1990. Russian. Book.
[33] Strangman, G; Heindel, WC; Anderson, JA; Sutton, JP. Learning motor sequences with and without knowledge of governing rules. Neurorehabil Neural Repair., 2005 June, 19(2), 93-114. Journal article.
[34] Başar, E; Başar-Eroglu, C; Karakaş, S; Schürmann, M. Oscillatory Brain Theory: A New Trend in Neuroscience. Engineering in Medicine and Biology Magazine., 1999 May/June, 3, 56-66. Journal article.
[35] Başar, E; Başar-Eroglu, C; Karakaş, S; Schürmann, M. Gamma, alpha, delta, and theta oscillations govern cognitive processes. Int J Psychophysiol., 2001 January, 39(2-3), 241-248. Journal article.
[36] Jibu, M; Yasue, K. Quantum Brain Dynamics and Consciousness. Amsterdam: John Benjamins Publishing Company, 1995. Book.
[37] Beck, F; Eccles, JC. Quantum aspects of brain activity and the role of consciousness. Proc Natl Acad Sci U S A., 1992, December 1, 89(23), 11357-11361. Journal article.
[38] Czarnecki, R

. The Quantum Brain: Theory or Myth [Internet]? [cited Jan 2014]. Available from: Czarnecki3.html 1998. Journal article.
[39] Globus, GG; O’Carroll, CP. Nonlocal neurology: beyond localization to holonomy. Med Hypotheses., 2010 November, 75(5), 425-432. Journal article.
[40] Keppler, J. A new perspective on the functioning of the brain and the mechanisms behind conscious processes [Internet]. Front Psychol., 2013, April 30 [cited 2014, September]., 4, 242. Available from: PMC3639372/. DOI: 10.3389/fpsyg.2013.00242. Electronic article.
[41] Andrus, VF. Razmyshleniya o formirovanii “dush” (prizrakov) i “fantomov” (privideniy) fauny i flory s tochki zreniya neitronnykh nauk [Reflections on the formation of “souls” and “phantoms” from the viewpoint of neutron sciences] [Internet]. 2013, May 19 [cited 2014, Jan]. Available from: files/RU/reflections_ru.pdf. Russian. Web page.
[42] Reimann, MW; Anastassiou, CA; Perin, R; Hill, SL; Markram, H; Koch, C. A biophysically detailed model of neocortical local field potentials predicts the critical role of active membrane currents. Neuron., 2013, July 24, 79(2), 375-90. Journal article.
[43] Natarajan, R; Huys, QJ; Dayan, P; Zemel, RS. Encoding and decoding spikes for dynamic stimuli. Neural Comput., 2008, September, 20(9), 2325-2360. Journal article.
[44] Sarajedini, A; Hecht-Nielsen, R; Chau, PM. Conditional probability density function estimation with sigmoidal neural networks. IEEE Trans Neural Netw., 1999 October, 10(2), 231-238. Journal article.
[45] Freeman, WJ. Definitions of state variables and state space for brain-computer interface: Part 1. Multiple hierarchical levels of brain function. Cogn Neurodyn., 2007 March, 1(2), 3-14. Journal article.
[46] Freeman, WJ. Understanding perception through neural “codes”. IEEE Trans Biomed Eng., 2011 July, 58(7), 1884-1890. Journal article.
[47] Capolupo, A; Freeman, WJ; Vitiello, G. Dissipation of ‘dark energy’ by cortex in knowledge retrieval [internet]. Phys Life Rev., 2013, March [cited 2014, Jan]. 10(1), 85-94. Available from: 20% E2%80%98dark%20energy%E2%80%99%20by%20cortex%20in%20knowledge%20retrieval.pdf. DOI: 10.1016/j.plrev.2013.01.001. Electronic article.
[48] Cauller, LJ. The Neurointeractibe Paradigm: Dynamical Mechanics and the Emergence of Higher Cortical Function. In: Hecht-Nielsen R, McKenna T, editors. Computational Models for Neuroscience. Berlin: Springer, 2003. Book section.
[49] Kosslyn, SM; Ganis, G; Thompson, WL. Neural foundations of imagery. Nat Rev Neurosci., 2001 September, 2(9), 635-642. Journal article.
[50] Cauller, LJ; Kulics, AT. The neural basis of the behaviorally relevant N1 component of the somatosensory-evoked potential in SI cortex of awake monkeys: evidence that backward cortical projections signal conscious touch sensation. Exp Brain Res., 1991, 84(3), 607-619. Journal article.
[51] Cauller, LJ; Connors, BW. Synaptic physiology of horizontal afferents to layer I in slices of rat SI neocortex. J Neurosci., 1994, Feb, 14(2)751-762. Journal article.
[52] Taylor, JG. On the neurodynamics of the creation of consciousness. Cogn Neurodyn., 2007, 1, 97-118. Journal article.
[53] Favorov, O. The Cortical Pyramidal Cell as a Set of Interacting Error Backpropagating Dendrites: Mechanism for Discovering Nature’s Order. In: Hecht-Nielsen R, McKenna T, editors. Computational Models for Neuroscience. Berlin: Springer, 2003. Book section.
[54] Freeman, WJ. Performance of Intelligent Systems Governed by Internally Generated Goals. In: Hecht-Nielsen R, McKenna T, editors. Computational Models for Neuroscience. Berlin: Springer, 2003. Book section.
[55] Hecht-Nielsen, R. A Theory of Thalamocortex. In: Hecht-Nielsen R, McKenna T, editors. Computational Models for Neuroscience. Berlin: Springer, 2003. Book section.
[56] Markram, H. The Blue Brain Project. Nat Rev Neurosci., 2006 February, 7(2), 153-160. Journal article.
[57] McKenna, T. The development of Cortical Models to Enable Neural-based Cognitive Architectures. In: Hecht-Nielsen R, McKenna T, editors. Computational Models for Neuroscience. Berlin: Springer, 2003. Book section.
[58] Sutton, JP; Strangman, G. The Behaving Neocortex as a Dynamic Network of Networks. In: Hecht-Nielsen R, McKenna T, editors. Computational Models for Neuroscience. Berlin: Springer, 2003. Book section.
[59] Taylor, JG. Towards Global Principles of Brain Processing. In: Hecht-Nielsen R, McKenna T, editors. Computational Models for Neuroscience. Berlin: Springer, 2003. Book section.
[60] Taylor, JG; Taylor, NR. The Neural Networks for Language in the Brain: Creating LAD. In: Hecht-Nielsen R, McKenna T, editors. Computational Models for Neuroscience. Berlin: Springer, 2003. Book section.
[61] Zemel, R

. Cortical Belief Networks. In: Hecht-Nielsen R, McKenna T, editors. Computational Models for Neuroscience. Berlin: Springer, 2003. Book section.
[62] Zemel, RS; Mozer, MC. Localist attractor networks. Neural Comput., May, 2001, 13(5), 1045-64. Journal article.
[63] Friston, K. A Free Energy Principle for Biological Systems. Entropy., 2012, Nov, 14(11), 2100-2121. Journal article.
[64] Knill, DC; Pouget, A. The Bayesian brain: the role of uncertainty in neural coding and computation. Trends in Neurosciences., 2004, December 1, 27(12), 712-719. Journal article.
[65] Huang, GT. Is this a unified theory of the brain[Internet]? New Scientist. May 28, 2008 [cited 2014, Feb]; Available from: %20a%20unified%20theory%20of%20the%20brain.pdf. Electronic article.
[66] Taylor, JG; Taylor, NR. Analysis of recurrent cortico-basal ganglia-thalamic loops for working memory. Biol Cybern., May, 2000, 82(5), 415-32. Journal article.
[67] Taylor, NR; Hartley, M; Taylor, JG

. The micro-structure of attention. Neural Netw., 2006, November, 19(9), 1347-1370. Journal article.
[68] Carnegie Melon University. Carnegie Melon neuroscientist proposes new theory of brain flexibility [Internet]. 2007, Nov 15 [cited 2014, Feb]. Available from: http:// Web page.
[69] Just, MA; Varma, S. The organization of thinking: What functional brain imaging reveals about the neuroarchitecture of complex cognition. Cognitive, Affective, & Behavioral Neuroscience., September 2007, 7(3), 153-191. Journal article.
[70] Wallis, C. Study Advances New Theory of How the Brain Is Wired [Internet]. 2013, June 27 [cited 2013, Dec]. Available from: Web page.
[71] Constantinople, CM; Bruno, RM. Deep cortical layers are activated directly by thalamus. Science., 2013, June 28, 1591-1594. Journal article.
[72] Baev, KV. A new conceptual understanding of brain function: basic mechanisms of brain-initiated normal and pathological behaviors. Crit Rev Neurobiol., 2007, 19(2-3), 119-202. Journal article.
[73] Zyga, L. Professor finally publishes controversial brain theory [Internet]. 2008, November 19 [cited 2014, Jan]. Available from: Web page.
[74] Roy, A. Connectionism, Controllers, and a Brain Theory. IEEE Transactions on Systems, Man and Cybernetics, – Part A: Systems and Human., November 2008, 38(6), 1434-1441.
[75] Crown, E. New theory challenges current view of how brain stores long-term memory [Internet]. 2005, Jan 14 [cited 2013 Nov]. Available from: pub_releases/2005-01/nu-ntc011405.php. Web page.
[76] Routtenberg, A. Long-lasting memory from evanescent networks. Eur J Pharmacol., 2008, May 6, 585(1), 60-3. Journal article.
[77] Ramirez, S; Liu, X; Lin, Pi-A; Suh, J; Pignatelli, M; Redondo, RL; Ryan, TJ; Tonegawa, S. Creating a False Memory in the Hippocampus. Science., 2013, July 26, 341(6144), 387-391. Journal article.
[78] Fingelkurts, AA; Fingelkurts, AA; Neves, CF. Natural world physical, brain operational, and mind phenomenal space-time. Phys Life Rev., 2010, June, 7(2), 195-249. Journal article.
[79] Fingelkurts, AA; Fingelkurts, AA. Alpha rhythm operational architectonics in the continuum of normal and pathological brain states: current state of research. Int J Psychophysiol., 2010, May76(2), 93-106. doi: 10.1016/j.ijpsycho.2010.02.009. Electronic article.
[80] Neftci, E; Binas, J; Rutishauser, U; Chicca, E; Indiveri, G; Douglas, RJ. Synthesizing cognition in neuromorphic electronic systems. Proc Natl Acad Sci U S A., 2013, Sep 10, 110, E3468-3476. doi: 10.1073/pnas.1212083110. Electronic article.
[81] Inside Paul Allen’s Quest To Reverse Engineer The Brain [Internet]. Forbes., 2012, Sep 18 [cited 2014, Jan]. Available from: matthewherper/2012/09/18/inside-paul-allens-quest-to-reverse-engineer-the-brain. Web page.
[82] Herper, M. Microsoft Co-Founder Paul Allen’s Health Philanthropy [Internet]. Forbes., 2012, Nov 29 [cited 2014, Jan]. Web page.
[83] Leon, SP; Knock, SA; Woodman, MM; Domide, L; Mersmann, J; McIntosh, AR; Jirsa, V. The Virtual Brain: a simulator of primate brain network dynamics. Front. Neuroinform., 2013, June 11, 7, 10. doi: 10.3389/fninf.2013.00010.
[84] Vityaev, EE. Komputernoye poznaniye [Scientific discovery and computational cognition] [Internet] [updated 2014, Jan 15, cited 2014, Feb]. Available from: http:// Russian. Web page.
[85] Vityaev, EE. Ptintsipy raboty mozga, soderzhaschiyesya v teorii funktsionalnykh sistem PK Anokhina I teorii emotsiy PV Simonova [The principles of operation of the brain contained in the theory of functional systems of Anokhin PK and theory of emotions of Simonov PV]. Neiroinformatika, 2008, 3(1), 25-78. Russian. Journal article.
[86] An Overview of the Human Genome Project [Internet] [updated 2012 Nov; cited 2014 Jan]. Available from: Web Page.
[87] Human Proteome Project [Internet]. 2015 [cited 2015 Apr]. Available from: http:// Web Page.
[88] US scientists relieved as Obama lifts ban on stem cell research [Internet]. 2009 March 10 [cited 2014 March]. Available from: mar/10/obama-stem-cell-research. Web Page.
[89] New Armed Forces Institute of Regenerative Medicine to Lead Way in Caring for Wounded [Internet]. 2008 April 17 [cited 2014 Jan]. Available from: Web Page.
[90] The Human Connectome Project [Internet]. 2009 [updated 2015 June; cited 2015 July]. Available from: Web Page.
[91] Marcus, G. The three-billion dollar brain [Internet]. 2013, March 12 [cited 2014 April]. Available from: Web Page.
[92] Fact Sheet: Over $300 Million in Support of the President’s BRAIN Initiative [Internet]. 2014, Sep 30 [cited 2014 Dec]. Available from: https://www. Web Page.
[93] Terentyev, AA; Moldogaziyeva, NT; Shaitan, KV.

Dinamicheskaya proteomika v modelirovanii zhivoy kletki. Belok-belkoviye vzaimodeistviya [Dynamic proteomics in the modeling of a living cell. Protein-protein interactions]. Uspekhi biologhicheskoy khimii., 2009, 49, 429–480. Journal article. Russian.
[94] Ferrell, JE.

Q&A: Cooperativity. J Biol., 2009, Jun 17, Vol. 8(6), 53. doi: 10.1186/ jbiol157. Electronic article.
[95] Shaitan, KV. Energheticheskaya poverkhnost’ i dinamika konfrontatsii molekul [Energy Surface and Conformation Dynamics of Molecules]. Russian Journal of Electrochemistry., 2003, 39(2), 198–204. Russian. Journal article.
[96] Milo, R. Dynamic proteomics in mammalian cells: capabilities and challenges. Mol Biosyst., 2007 Aug, 3(8), 542-6. Journal article.
[97] Trinkle-Mulcahy, L; Lamond, AI. Toward a high-resolution view of nuclear dynamics. Science., 2007 Nov 30, 318(5855), 1402-1407. Journal article.
[98] Mayer, BJ. Protein-protein interactions in signaling cascades. Mol Biotechnol., 1999 Dec 15, 13(3), 201-213. Journal article.
[99] Houtman, JC1; Barda-Saad, M; Samelson, LE. Examining multiprotein signaling complexes from all angles. FEBS J., 2005 Nov, 272(21), 5426-5435. Journal article.
[100] Terentyev, AA, Moldogaziyeva NT. Strukturno-funktionalnoye kartirovaniye α-fetoproteina [Structural-functional mapping of α-fetoprotein]. Biokhimiya, Feb 2006, 71, 157-172. Russian.
[101] Zaretsky, JZ; Wreschner, DH.

Protein multifunctionality: principles and mechanisms. Transl Oncogenomics., 2008 May 15, 3, 99-136. Journal article.
[102] Ghaemmaghami, S; Huh, WK; Bower, K; Howson, RW; Belle, A; Dephoure, N; O’Shea, EK; Weissman, JS.Global analysis of protein expression in yeast. Nature., 2003 Oct 16, 425(6959), 737-41. Journal article.
[103] Parrish, JR; Gulyas, KD; Finley, RL. Jr. Yeast two-hybrid contributions to interactome mapping. Curr Opin Biotechnol, 2006 Aug, 17(4), 387-93. Journal article.
[104] Stumpf, MP; Thorne, T; de Silva, E; Stewart, R; An, HJ; Lappe, M; Wiuf, C. Estimating the size of the human interactome. Proc Natl Acad Sci U S A., 2008, May 13, 105(19), 6959-6964. Journal article.
[105] Venkatesan, K; Rual, JF; Vazquez, A; Stelzl, U; Lemmens, I; Hirozane-Kishikawa, T; Hao, T; Zenkner, M; Xin, X; Goh, KI; Yildirim, MA; Simonis, N; Heinzmann, K; Gebreab, F; Sahalie, JM; Cevik, S; Simon, C; de Smet, AS; Dann, E; Smolyar, A; Vinayagam, A; Yu, H; Szeto, D; Borick, H. An empirical framework for binary interactome mapping. Nat Methods., 2009 Jan, 6(1), 83-90. Journal article.
[106] Cusick, ME; Klitgord, N; Vidal, M; Hill, DE. Interactome: gateway into systems biology. Hum Mol Genet., 2005 Oct 15, 14 Spec No. 2, R171-181. Journal article.
[107] Mika, S; Rost, B. Protein-protein interactions more conserved within species than across species. PLoS Comput Biol., 2006 Jul 21, 2(7), e79. Electronic article.
[108] Causier, B. Studying the interactome with the yeast two-hybrid system and mass spectrometry. Mass Spectrom Rev., 2004 Sep-Oct, 23(5), 350-367. Journal article.
[109] Puig, O; Caspary, F; Rigaut, G; Rutz, B; Bouveret, E; Bragado-Nilsson, E; Wilm, M; Séraphin, B.The tandem affinity purification (TAP) method: a general procedure of protein complex purification. Methods., 2001 Jul, 24(3), 218-229. Journal article.
[110] Rigaut, G; Shevchenko, A; Rutz, B; Wilm, M; Mann, M; Séraphin, B. A generic protein purification method for protein complex characterization and proteome exploration. Nat Biotechnol., 1999 Oct, 17(10), 1030-1032. Journal article.
[111] Ho, Y; Gruhler, A; Heilbut, A; Bader, GD; Moore, L; Adams, SL; Millar, A; Taylor, P; Bennett, K; Boutilier, K; Yang, L; Wolting, C; Donaldson, I; Schandorff, S; Shewnarane, J; Vo, M; Taggart, J; Goudreault, M; Muskat, B; Alfarano, C; Dewar, D; Lin, Z; Michalickova, K; Willems, A. Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry. Nature., 2002 Jan 10, 415(6868), 180-183. Journal article.
[112] Zhou, M; Veenstra, TD. Proteomic analysis of protein complexes. Proteomics., 2007 Aug, 7(16), 2688-97. Journal article.
[113] Domon, B; Aebersold,

R. Mass spectrometry and protein analysis. Science., 2006 Apr 14, 312(5771), 212-7. Journal article.
[114] Eilbeck, K; Brass, A; Paton, N; Hodgman, C. INTERACT: an object oriented protein-protein interaction database. Proc Int Conf Intell Syst Mol Biol., 1999, 87-94. Journal article.
[115] Xenarios, I; Salwínski, L; Duan, XJ; Higney, P; Kim, SM; Eisenberg, D. DIP, the Database of Interacting Proteins: a research tool for studying cellular networks of protein interactions. Nucleic Acids Res., 2002 Jan 1, 30(1), 303-305. Journal article.
[116] Bader, GD; Betel, D; Hogue, CW. BIND: the Biomolecular Interaction Network Database. Nucleic Acids Res., 2003 Jan 1, 31(1), 248-50. Journal article.
[117] Breitkreutz, BJ; Stark, C; Reguly, T; Boucher, L; Breitkreutz, A; Livstone, M; Oughtred, R; Lackner, DH; Bähler, J; Wood, V; Dolinski, K; Tyers, M. The BioGRID Interaction Database: 2008 update. Nucleic Acids Res., 2008 Jan, 36(Database issue), D637-40. Journal article.
[118] Teyra, J; Doms, A; Schroeder, M; Pisabarro, MT. SCOWLP: a web-based database for detailed characterization and visualization of protein interfaces. BMC Bioinformatics., 2006 Mar 2, 7, 104. Journal article.
[119] Teyra, J; Paszkowski-Rogacz, M; Anders, G; Pisabarro, MT. SCOWLP classification: structural comparison and analysis of protein binding regions. BMC Bioinformatics., 2008 Jan 8, 9, 9. Journal article.
[120] Spirin, S; Titov, M; Karyagina, A; Alexeevski, A. NPIDB: a database of nucleic acids-protein interactions. Bioinformatics., 2007 Dec 1, 23(23), 3247-3248. Journal article.
[121] Gong, S; Yoon, G; Jang, I; Bolser, D; Dafas, P; Schroeder, M; Choi, H; Cho, Y; Han, K; Lee, S; Choi, H; Lappe, M; Holm, L; Kim, S; Oh, D; Bhak, J. PSIbase: a database of Protein Structural Interactome map (PSIMAP). Bioinformatics., 2005 May 15, 21(10), 2541-2543. Journal article.
[122] Shannon, CE. A Mathematical Theory of Communication. The Bell System Technical Journal., July, 1948, October, 27, 379-423, 623-656. Journal article.
[123] Wiener, N. Cybernetics Or Control and Communication in the Animal and the Machine. Cambridge, Mass: MIT Press, 1948. Book.
[124] Korotenkov, YuG. Formalizovannaya informatsiologhiya [Formalized Informationology]. Moscow: Mezhdunarodnoye izdatelstvo Informatsiologhiya., 2005. Book. Russian.
[125] Simonov, PV. Teoriya otrazheniya i psikhophisiologiya emotsiy [The theory of reflection and psychophysiology of emotions]. Moscow: Nauka, 1970. Book. Russian.
[126] Simonov, PV. Emotsionalniy mozg [Emotional brain]. Moscow: Nauka, 1981. Book. Russian.
[127] Hinton, GE; Andreson, JA. Parallel Models of Associative Memory. Hillsdale, New Jersey : Lawrence Erlbaum Associates Publishers, 1981. Book.
[128] Atick, JJ; Redlich, AN. Toward a theory of early visual processing. Neural Computation., 1990, 2, 308-320. Journal article.
[129] Atick, JJ; Redlich, AN. What does the Retina Know about Natural Scenes [Internet]? Neural Comput, 1992 [cited 2014, Feb]; 4, 196-210. Available from: http://www. cnbc. Journal article.
[130] Baddeley, R; Hancock, P; Foldiak, P. editors. Information theory and the brain. New York: Cambridge University Press. 2000. Book.
[131] Bryukhovetskiy, AS. Transplantatsiya nervnikh kletok i tkanevaya engineeriya mozga pri nervnikh bolezniakh [Transplantation of nerve cells and tissue engineering of brain in nerve diseases]. Moscow: ZAO Neurovita, 2003. Russian. Book.
[132] Devyatkov, ND; Golant, MB; Betskiy, OV. Milimetroviye volny i ikh rol’ v protsessakh zhiznedeyatelnosti [Millimeter waves and their role in the life activity]. Radio i svyaz’., 1991. Russian. Book
[133] Kanchjen, C. BioSVCHsvyaz’ [(BioSHFconnection]. Information package on the conference in non-traditional aspects of natural sciences. Tomsk, 1992. Conference paper.
[134] Venkataramanan, M. Darpa’s 5 Radical Plans for Military Medicine [Internet]., 2011 [updated 2011 March 01; cited 2013 Jan]. Available from:
[135] Neymark, YuI. Mathematical models in Natural Science and Engineering. Berlin-Heidelberg: Springer Verlag, 2003. Book.
[136] Karlov, VA. Nevrologhiya. Rukovodstvo dlya vrachey [Neurology. Manual for doctors.]. Moscow: Meditsinskoye Informatsionnoye Agentstvo, 2002. Russian. Book.
[137] Sandrigailo, LI. Anatomo-klinicheskiy atlas po nevropatologhii [Anatomic clinical atlas in neuropathology]. Minsk: Vysheishaya shkola, 1978. Russian. Book.
[138] Duus, P. Topicheskiy diagnoz v nevrologhii: anatomiya, fiziologhiya, priznaki, simptomy [Topical Diagnosis in Neurology: Anatomy, Physiology, Signs, Symptoms]. Moscow: Vasar-Ferro, 1995. Book. Russian.
[139] Kandel, ER. The molecular biology of memory storage: a dialog between genes and synapses. Biosci Rep., 2004 Aug-Oct. 24(4-5), 475-522. Journal article.
[140] Friston, K; Kilner, J; Harrison, L. A free energy principle for the brain. J Physiol Paris., 2006 Jul-Sep. 100(1-3), 70-87. Journal article.
[141] Friston, KJ; Stephan, KE. Free-energy and the brain [Internet]. Synthese. 2007 Dec 1 [cited 2014 Jan]. 159(3), 417–458. Available from: pmc/articles/PMC2660582. doi: 10.1007/s11229-007-9237-y. Electronic article.
[142] Friston, K; Mattout, J; Trujillo-Barreto, N; Ashburner, J; Penny, W. Variational free energy and the Laplace approximation. Neuroimage., 2007 January 1. 34(1), 220-34. Journal article.
[143] Memory [Internet]. 2002 June 01 [cited 2013 Dec]. Available from: https://www. 1DzS6cAw&sig2=xDP_C0cPeeomhj7OTIWIMg&bvm=bv.98717601,d.bGg. Web Page.
[144] Off-Axis “Leith & Upatnieks” Holography [Internet]. In Benton SA, Bove VM Jr. Holographic imaging. New Jersey: John Wiley & Sons, Inc., 2008 [cited 205 Jan]. Available from: Book section.
[145] In-Line “Denisyuk” Reflection Holography [Internet]. In Benton SA, Bove VM Jr. Holographic imaging. New Jersey: John Wiley & Sons, Inc., 2008 [cited 205 Jan]. Available from: Book section.
[146] Luria, AR. O yestestvenno-nauchnikh osnovah psikhologhii [On scientific fundamentals of psychology]. In Smirnova AA, Luria AR, Nebylitsin VD, editors. Yestestvennonauchniye osnovy psikhologhii [Scientific fundamentals of psychology]. Moscow: Pedagoghika, 1978. Russian. Book.
[147] Vygotskiy, LS.

Myshleniye i rech. [Thinking and speech]. Moscow: Nauka, 1934. Russian. Book.
[148] DARPA SyNAPSE Program [Internet] [updated 2013 Jan 11; cited 2014 Dec]. Available from: Web Page.
[149] Lilly, JC. Programming and Metaprogramming in the Human Biocomputer: Theory and Experiments. New York: Three Rivers Press/Julian Press, 1987. Book.
[150] Eliasmith, Chris. How to Build a Brain. A Neural Architecture for Biological Cognition. Oxford University Press, 2013. Book.
[151] Bekolay, T; Bergstra, J; Hunsberger, E; Dewolf, T; Stewart, TC; Rasmussen, D; Choo, X; Voelker, AR; Eliasmith, C. Nengo: a Python tool for building large-scale functional brain models [Internet]. Front Neuroinform., 2014 Jan 6 [cited 2014 Feb]., 7, 48. doi: 10.3389/fninf.2013.00048. Electronic article.

[152] Eliasmith, C; Stewart, TC; Choo, X; Bekolay, T; DeWolf, T; Tang, C; Rasmussen, D. A large-scale model of the functioning brain [Internet]. Science, 2012 Nov 30. 338, 1202-5. doi: 10.1126/science.1225266. Electronic article.

[153] Boyle, R. Meet Spaun, The Most Complex Simulated Brain Ever [Internet], 2012 November 30 [cited 2014 Feb]. Available from, article/2012-11/meet-spaun-first-computer-model-complex-brain-behavior. Web Page.

[154] Lehrer, J. The Human Brain Gets a New Map., 2011 April 12 [cited 2014 Dec]. Available from: Web Page.

[155] Woollaston, V. Scientists create the world’s first high-definition 3D model of a human brain. Daily Mail [serial online]. 2013 June 21 [cited 2014 Dec]; Sect. Science. Available from: Newspaper article.
[156] Galushkin, AI.Neironniye seti. Osnovi teorii [Neural networks. The fundamentals of the theory]. Moscow: Goryachaya Liniya –Telecom, 2012. Russian. Book.

[157] Anokhin, KP. Obshiye principy kompensatsii narushennykh funktsiy i ikh fisiologhisheskoye obosnovaniye [General principles of compensation for disordered functions and their physiological validation]. The proceedings of the conference in defectology. Moscow: APN RSFSR, 1956. Russian. Conference paper.

[158] Yevreinov, EV; Kosarev, YuG. Odnorodniye univesralniye vichislitelniye sistemy visokoy proizviditelnosti [Homogeneous universal calculation systems of high productivity]. Novosibirsk: Nauka, 1966. Russian. Book.
[159] Fitzsimmons, NA; Lebedev, MA; Peikon, ID; Nicolelis, MA. Extracting kinematic parameters for monkey bipedal walking from cortical neuronal ensemble activity [Internet]. Front Integr Neurosci. 2009 Mar 9 [cited 2014 Dec].; 3, 3. Available from: doi: 10.3389/neuro.07. 003.2009. Electronic article.

[160] Nicolelis, MA. A monkey that controls a robot with its thought. No, really [Talk on the Internet], 2012 Apr [cited 2014 Feb]. Available from: miguel_nicolelis_a_monkey_that_controls_a_robot_with_its_thoughts_no_really?language=en. Web Page.

[161] Wang, W; Collinger, JL; Degenhart, AD; Tyler-Kabara, EC; Schwartz, AB; Moran, DW; Weber, DJ; Wodlinger, B; Vinjamuri, RK; Ashmore, RC; Kelly, JW; Boninger, ML. An electrocorticographic brain interface in an individual with tetraplegia. PLoS One [Internet]., 2013 Feb 6 [cited 2014 Dec]; 8(2). Available from: http://www. doi: 10.1371/journal.pone.0055344.

The book will be interesting to the neuroscientists, neurobiologists and neuropsychologists. It also can have potential demand among the technical specialists who work in the field of neurocybernetics, neurobionics and neuromathematics, among the electronic engineers and software engineers involved in modeling of the human brain functions, development of brain emulators and simulators and artificial intellect, as well as among the neuroengineers who develop brain implantable micro-electrodes, micro-chips and brain-computer interfaces. The book presents interest to the military specialists in double purpose neurotechnologies

You have not viewed any product yet.