Physics of decision processes

  • F. T. ArecchiEmail author
Regular Article


We provide evidence that information processing in linguistic elaboration entails an uncertainty relation and entangled states, without having to strictly rely on quantum processes. Thus far, reported evidences of quantum effects in human brain processes lack a plausible framework, since either no assignment of an appropriate quantum constant had been associated, or speculating on microscopic processes dependent on Planck’s constant resulted in unrealistic de-coherence times. In the human brain formulation of linguistic processes, a word coded as a neuron spike sequence is compared with a previous word retrieved via the short term memory; comparison yields a judgment. Synchronization of the finite neuron spike sequences (SFSS), coding the two words, is the way two brain regions compare their content and extract the most suitable sequence. It consists of an inverse Bayes procedure. In SFSS, an uncertainty relation emerges between the bit size of a word and its duration. This uncertainty affects the task of synchronizing spike trains of different duration representing different words, entailing the occurrence of entangled sequences (ES). ES justifies the inverse Bayes inference that connects different words in a linguistic task. ES decays after a finite de-coherence time. The behavior here exhibited provides an explanation for the previously reported evidences of quantum effects in decision processes.


  1. 1.
    D. Aerts, S. Aerts, Found. Sci. 1, 85 (1995)MathSciNetCrossRefGoogle Scholar
  2. 2.
    D. Aerts, J. Math. Psychol. 53, 314 (2009)CrossRefGoogle Scholar
  3. 3.
    A. Khrennikov, Ubiquitous Quantum Structure: From Psychology to Finance (Springer, 2010)Google Scholar
  4. 4.
    J.R. Busemeyer, P.D. Bruza, Quantum models of cognition and decision (Cambridge University Press, 2012)Google Scholar
  5. 5.
    M. Ashtiani, M.A. Azgomi, Math. Social Sci. 75, 49 (2015)MathSciNetCrossRefGoogle Scholar
  6. 6.
    R. Penrose, Shadows of the Mind (Oxford University Press, Oxford, 1994)Google Scholar
  7. 7.
    S. Hagan, S.R. Hameroff, J.A. Tuszyński, Phys. Rev. E 65, 061901 (2002)ADSCrossRefGoogle Scholar
  8. 8.
    M. Tegmark, Phys. Rev. E 61, 4194 (2000)ADSCrossRefGoogle Scholar
  9. 9.
    C. Koch, K. Hepp, Nature 440, 611 (2006)ADSCrossRefGoogle Scholar
  10. 10.
    F.T. Arecchi, Quantum effects in linguistic endeavors, in Towards a Post-Bertelanffy Systemics, edited by G. Minati, Mario R. Abram, E. Pessa (Springer, 2015) pp. 3--13Google Scholar
  11. 11.
    P.J. Uhlhaas, G. Pipa, B. Lima, L. Meloni, S. Neuschwander, D. Nikolic, W. Singer, Front. Integr. Neurosci. 3, 1 (2009)CrossRefGoogle Scholar
  12. 12.
    W. Singer, Phil. Trans. R. Soc. London 353, 1829 (2015)Google Scholar
  13. 13.
    F.T. Arecchi, Nonlinear Dyn., Psychol. Life Sci. 15, 359 (2011)Google Scholar
  14. 14.
    E. Rodriguez, N. George, J.-P. Lachaux, J. Martinerie, B. Renault, F.J. Varela, Nature 397, 430 (1999)ADSCrossRefGoogle Scholar
  15. 15.
    P. Fries, Trends Cogn. Sci. 9, 474 (2005)CrossRefGoogle Scholar
  16. 16.
    P. Fries, D. Nikolic, W. Singer, Trends Neurosci. 30, 309 (2007)CrossRefGoogle Scholar
  17. 17.
    O. Jensen, L.L. Colgin, Trends Cogn. Sci. 11, 267 (2007)CrossRefGoogle Scholar
  18. 18.
    J.E. Lisman, O. Jensen, Neuron 77, 1002 (2013)CrossRefGoogle Scholar
  19. 19.
    F.T. Arecchi, Uncertainty domains associated with time limited perceptual tasks: fuzzy overlaps or quantum entanglement?, in Decoherence and Entropy in Complex Systems (Springer, 2004) pp. 327--340Google Scholar
  20. 20.
    D. Debanne, E. Campanac, A. Bialowas, E. Carlier, G. Alcaraz, Physiol. Rev. 91, 555 (2011)CrossRefGoogle Scholar
  21. 21.
    F.T. Arecchi, Physica A 338, 218 (2004)ADSCrossRefGoogle Scholar
  22. 22.
    C. von der Malsburg, The correlation theory of brain function, Internal Report 81-2, Dept. of Neurobiology, Max-Planck-Inst. for Biophysical Chemistry, Göttingen, Germany (1981)Google Scholar
  23. 23.
    W. Singer, C.M. Gray, Annu. Rev. Neurosci. 18, 555 (1995)CrossRefGoogle Scholar
  24. 24.
    B.J. Baars, A Cognitive Theory of Consciousness (Cambridge University Press, 1993)Google Scholar
  25. 25.
    S. Dehaene, C. Sergent, J.P. Changeux, Proc. Natl. Acad. Sci. U.S.A. 100, 8520 (2003)ADSCrossRefGoogle Scholar
  26. 26.
    K. Doya, S. Ishii, A. Pouget (Editors), Bayesian Brain: Probabilistic Approaches to Neural Coding (MIT Press, 2007)Google Scholar
  27. 27.
    F.T. Arecchi, Complexity, information loss and model building: from neuro- to cognitive dynamics, in SPIE Noise and Fluctuation in Biological, Biophysical, and Biomedical Systems (SPIE, 2007) Paper 6602-36Google Scholar
  28. 28.
    E. Poeppel, Acta Neurobiol. Exp. 64, 295 (2004)Google Scholar
  29. 29.
    R. Raussendorf, H.J. Briegel, Phys. Rev. Lett. 86, 5188 (2001)ADSCrossRefGoogle Scholar
  30. 30.
    H.J. Briegel, D.E. Browne, W. Dür, R. Raussendorf, M. Van den Nest, Nat. Phys. 5, 19 (2009)CrossRefGoogle Scholar
  31. 31.
    A.R. Damasio, The Feeling of What Happens: Body and Emotion in the Making of Consciousness (Random House, 2000)Google Scholar
  32. 32.
    R.W. Gibbs jr., Embodiment and Cognitive Science (Cambridge University Press, 2005)Google Scholar
  33. 33.
    S. Zeki, J. Nash, Inner Vision: An Exploration of Art and the Brain, Vol. 415 (Oxford University Press, Oxford, 1999)Google Scholar
  34. 34.
    F.T. Arecchi, J. Psychophysiol. 24, 141 (2010)CrossRefGoogle Scholar

Copyright information

© Società Italiana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Emeritus of PhysicsUniversity of FirenzeFirenzeItaly
  2. 2.INO-CNRLargo E. Fermi-6FirenzeItaly

Personalised recommendations