DOI: 10.14704/nq.2015.13.3.846

The Quantum Phenomena in Computational Model of Neuro-Cognition States: An Analytical Approach

Susmit Bagchi


The modeling of neurobiologic brain functions such as, cognition and consciousness are important research challenges having applications to other disciplines such as, bio-inspired soft computing and, adaptive distributed computing systems. The functions of brain and distributed computing structures have resemblances. This paper proposes a computational model of cognitive function and consciousness by using algebraic methods. Furthermore, the quantum mechanical basis of the cognitive model is formulated by using linear Hermitian. A set of choice functions is computed following the neurodynamics. The neuronal excitation is modeled by using trigonometric wave functions closely matching the neuronal firing. This paper illustrates an analytical approach to model neuronal excitation and, associated cognitive functions having quantum mechanical behaviour.


Cognition; Consciousness; Hermitian operator; Distributed computing; Quantum mechanics

Full Text:

Full Text PDF


Alfinito E, Vitiello G. The dissipative quantum model of brain: how does memory localize in correlated neuronal domains. Information Sciences 2000; 128(3/4): 217–229.

Arbib M A, Caplan D. Neurolinguistics must be computational. Behavioral & Brain Sciences 1979; 2(3): 449-483.

Baars B J, Franklin S. An architectural model of conscious and unconscious brain function. Neural Networks 2007; 20(9): 955–961.

Beck F, Eccles J. Quantum aspects of brain activity and the role of consciousness. Proceedings of the National Academy of Sciences of the USA 1992; 89(23): 11357–11361.

Beck F. Quantum brain dynamics and consciousness. The Physical Nature of Consciousness, ed. by P. van Loocke, Amsterdam: Benjamins, 2001, 83–116.

Bonchek-Dokow E, Kaminka GA. Towards computational models of intention detection and intention prediction. Cognitive Systems Research 2014; 28:44-79.

Conte E, Federici A, Zbilut JP. On a Simple Case of Possible non Deterministic Chaotic Behavior in Compartment Theory of Biological Observables. Chaos, Solitons and Fractals 2004; 22(2): 277-284.

Conte E, Todarello O, Federici A, Vitiello F, Lopane M, Khrennikov A, Zbilut J P. Some remarks on an experiment suggesting quantum-like behavior of cognitive entities and formulation of an abstract quantum mechanical formalism to describe cognitive entity and its dynamics. Chaos, Solitons and Fractals 2009; 31(5): 1076–1088.

Fekete T, Edelman S. Towards a computational theory of experience. Consciousness and Cognition 2011; 20(3): 807-827.

Filk T, Müller von A. Quantum physics and consciousness: The quest for a common conceptual foundation. Mind and Matter 2009; 7(1): 59–79.

Fitch WT. Toward a Computational Framework for Cognitive Biology: Unifying approaches from cognitive neuroscience and comparative cognition. Physics of Life Reviews 2014; Elsevier, DOI: 10.1016/j.plrev.2014.04.005.

Hameroff S R, Penrose R. Conscious events as orchestrated spacetime selections. Journal of Consciousness Studies 1996; 3(1): 36–53.

Hagan S, Hameroff S R, Tuszynski J A. Quantum computation in brain microtubules: decoherence and biological feasibility. Phys. Rev. E. 2002; 65(6): 061901.

Koch C, Tononi G. Can machines be conscious? IEEE Spectrum 2008; 55–59.

Kurita Y. Indispensable role of quantum theory in the brain dynamics. Biosystems Journal 2005; 80(3): 263–272.

Lin J, Yang J G. Consciousness modeling: A neural computing approach. Proceedings of the Third International Conference on Machine Learning and Cybernetics. Shanghai; IEEE. 2004.

Mumford D, Desolneux A. Pattern Theory: The stochastic analysis of real-world signals. A K Peters Ltd., CRC Press, 2010.

Mumford D. On the computational architecture of the neocortex. II. The role of cortico-cortical loops. Biological Cybernetics 1992; 66(3): 241-251.

Poeppel D, Embick D. Defining the relation between linguistics and neuroscience. Twenty-First Century Psycholinguistics: Four Cornerstones, Ed. A. Cutler, Lawrence Erlbaum, London, 2005; pp.103-120.

Pribram K H. Brain and Perception. Lawrence Erlbaum, Hillsdale, USA, 1991.

Reggia JA. The rise of machine consciousness: Studying consciousness with computational models. Neural Networks 2013; 44: 112-131.

Rees G, Kreiman G, Koch C. Neural correlates of consciousness in humans. Nature Reviews Neuroscience 2002; 3(4): 261–270.

Ricciardi L M, Umezawa H. Brain physics and many-body problems. Kibernetik 1967; 4: 44-48.

Rolls ET, Deco G. Computational Neuroscience of Vision. Oxford University Press, Oxford, 2001.

Starzyk JA, Prasad DK. A Computational model of machine consciousness. Int J Machine Consciousness 2011; 3(2); 255-282.

Sun R, Franklin S. Computational models of consciousness. Cambridge handbook of consciousness, Cambridge University Press, 2007; pp.151-174.

Tegmark M. Quantum computation in brain microtubules? Decoherence and biological feasibility. Phys Rev E 2000; (61): 4194.

Williams CP. Explorations in Quantum Computing (2nd Edition), Springer, 2011.

Supporting Agencies

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

| NeuroScience + QuantumPhysics> NeuroQuantology :: Copyright 2001-2019