Quantum Brain and Cognition

  • Vladimir G. IvancevicEmail author
  • Tijana T. Ivancevic
Part of the Intelligent Systems, Control and Automation: Science and Engineering book series (ISCA, volume 40)


Quantum Brain and Cognition presents various aspects of the current research in quantum brain area. It includes the following sections:

  1. 5.1

    Biochemistry of Microtubules

    This section presents neuronal microtubules (MT)—the “quantum seat of human consciousness”—from a biochemical point of view.

  2. 5.2

    Kink Soliton Model of MT-Dynamics

    This section presents a mean-field solitary model of microtubular dynamics.

  3. 5.3

    Fractal Neurodynamics

    This section presents a self-similar model of neurodynamics on both macroscopic (classical) and microscopic (quantum) levels.

  4. 5.4

    Dissipative Quantum Brain Model

    This section reviews a current research in a dissipative quantum brain model.

  5. 5.5

    QED Brain Model

    This section presents a quantum electrodynamics brain model.

  6. 5.6

    Stochastic NLS-Filtering and Robotic Eye Tracking

    This section presents a practical engineering application of a quantum neural network (QNN).

  7. 5.7

    QNN-Based Neural Motor Control

    This section presents a neuro-physiological control of human muscular dynamics. It models human cerebellum as an adaptive path integral controller, which is an infinite-dimensional QNN.

  8. 5.8

    Quantum Cognition in the Life Space Foam

    This section presents a modern research in human cognition based on quantum-probability rooted path integral. It briefs on the Life Space Foam concept and its psychological and robotic applications.

  9. 5.9

    Quantum Cognition in Crowd Dynamics

    This section presents recent geometrical research in crowd behaviour dynamics based on the entropic quantum cognition concept.



Lyapunov Exponent Wave Packet Coherent State Topology Change Ricci Soliton 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  1. 1.Department of DefenceDefence Science & Technology Organisation (DSTO)EdinburghAustralia
  2. 2.School of Electrical & Information EngineeringUniversity of South AustraliaAdelaideAustralia

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