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Computation Through Neuronal Oscillations

  • Chapter
The Message of Quantum Science

Part of the book series: Lecture Notes in Physics ((LNP,volume 899))

Abstract

Some of us believe that natural sciences are governed by simple and predictive general principles. This hope has not yet been fulfilled in physics for unifying gravitation and quantum mechanics. Epigenetics has shaken the monopoly of the genetic code to determine inheritance (Alberts et al., Molecular Biology of the Cell. Garland, New York, 2008). It is therefore not surprising that quantum mechanics does not explain consciousness or more generally the coherence of the brain in perception, action and cognition. In an other context, others (Tegmark, Phys Rev E 61:4194–4206, 2000) and we (Koch and Hepp, Nature 440:611–612, 2006; Koch and Hepp, Visions of Discovery: New Light on Physics, Cosmology, and Consciousness. Cambridge University Press, Cambridge, 2011) have strongly argued against the absurdity of such a claim, because consciousness is a higher brain function and not a molecular binding mechanism. Decoherence in the warm and wet brain is by many orders of magnitude too strong. Moreover, there are no efficient algorithms for neural quantum computations. However, the controversy over classical and quantum consciousness will probably never be resolved (see e.g. Hepp, J Math Phys 53:095222, 2012; Hameroff and Penrose, Phys Life Rev 11:39–78, 2013).

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References

  1. Aaronson, S.: Quantum Computing Since Democritus. Cambridge University Press, Cambridge (2013)

    MATH  Google Scholar 

  2. Adrian, E.D.: Olfactory reactions in the brain of the hedgehog. J. Physiol. 100, 459–473 (1942)

    Google Scholar 

  3. Ainsworth, et al.: Rates and rhythms: a synergistic view of frequency and temporal coding in neuronal networks. Neuron 75, 572–583 (2012)

    Google Scholar 

  4. Alberts, B., et al.: Molecular Biology of the Cell, 5th edn. Garland, New York (2008)

    Google Scholar 

  5. Alivisatos, A.P., et al.: The brain activity map. Science 339, 2084–2085 (2013)

    Google Scholar 

  6. Alonso, J.-M., Chen, Y.: Receptive field. Scholarpedia 4(1), 5393 (2009)

    ADS  Google Scholar 

  7. Anastassiou, C.A., et al.: Ephaptic coupling of cortical neurons. Nat. Neurosci. 14, 217–223 (2011)

    MathSciNet  Google Scholar 

  8. Bardeen, J., et al.: Theory of superconductivity. Phys. Rev. 108, 1175–1204 (1957)

    ADS  MATH  MathSciNet  Google Scholar 

  9. Barone, P., et al.: Laminar distribution of neurons in extrastriate areas projecting to visual areas V1 and V4 correlates with the hierarchical rank and indicates the operation of a distance rule. J. Neurosci. 20, 3263–3281 (2000)

    Google Scholar 

  10. Bastos, A.M., et al.: Visual areas exert feedforeward and feedback influences through distinct frequency channels. Neuron 85, 1–12 (2015)

    Google Scholar 

  11. Bastos, A.M., et al.: Communication through coherence with interareal delays. Curr. Opin. Neurobiol. 31, 173–180 (2015)

    Google Scholar 

  12. Berényi, A., et al.: Large scale, high density (up to 512 channels) recording of local circuits in behaving animals. J. Neurophysiol. 111, 1132–1143 (2013)

    Google Scholar 

  13. Bichot, N.P., et al.: Parallel and serial mechanisms for visual search in macaque area V4. Science 308, 529–534 (2005)

    ADS  Google Scholar 

  14. Blanchard, P., Fröhlich, J.: Message from Quantum Science. Springer, Heidelberg (2015)

    Google Scholar 

  15. Borjigin, J., et al.: Surge of neurophysiological coherence and connectivity in the dying brain. Proc. Natl. Acad. Sci. 110, 14432–14437 (2013)

    ADS  Google Scholar 

  16. Bosman, C.A., et al.: Attentional stimulus selection through selective synchronization between monkey visual areas. Neuron 75, 875–888 (2012)

    Google Scholar 

  17. Buffalo, E.A., et al.: A backward progression of attentional effects in the ventral stream. Proc. Natl. Acad. Sci. 107, 361–367 (2010)

    ADS  Google Scholar 

  18. Buffalo, E.A., et al.: Laminar differences in gamma and alpha coherence in the ventral stream. Proc. Natl. Acad. Sci. 108, 11262–11267 (2011)

    Google Scholar 

  19. Burns, S.P., et al.: Is gamma-band activity in the local field potential of V1 cortex a “clock” or “filtered noise”? J. Neurosci. 31, 9658–9664 (2011)

    Google Scholar 

  20. Buschman, T.J., Miller, E.K.: Top-down versus bottom-up control of attention in the prefrontal and posterior parietal cortices. Science 315, 1860–1862 (2007)

    ADS  Google Scholar 

  21. Buzsaki, G.: Hippocampus. Scholarpedia 6(1), 1468 (2011)

    ADS  Google Scholar 

  22. Buzsaki, G., Wang, X.-J.: Mechanisms of gamma oscillation. Ann. Rev. Neurosci. 35, 203–225 (2012)

    Google Scholar 

  23. Carandini, M.: Area V1. Scholarpedia 7(7), 12105 (2012)

    ADS  Google Scholar 

  24. Cardin, J.A., et al.: Driving fast-spiking cells induces gamma rhythm and controls sensory responses. Nature 459, 663–666 (2009)

    ADS  Google Scholar 

  25. Carnevale, N.T., Hines, M.L.: The NEURON Book. Cambridge University Press, Cambridge (2006)

    Google Scholar 

  26. Chalk, M., et al.: Attention reduces stimulus-driven gamma frequency oscillations and spike-field coherence in V1. Neuron 66, 114–125 (2010)

    Google Scholar 

  27. Courtin, J., et al.: Prefrontal parvalbumin interneurons shape neuronal activity to drive fear expression. Nature 505, 92–96 (2014)

    ADS  Google Scholar 

  28. Da Costa, N.M., Martin, K.A.C.: Sparse reconstructions of brain circuits: or, how to survive without a microscopic connectome. NeuroImage 80, 27–36 (2013)

    Google Scholar 

  29. Devoret, M.H., Schoelkopf, R.J.: Superconducting circuits for quantum information: an outlook. Science 339, 1169–1174 (2013)

    ADS  MathSciNet  Google Scholar 

  30. DiCarlo, J.J., et al.: How does the brain solve visual object recognition? Neuron 73, 415–434 (2012)

    Google Scholar 

  31. Douglas, R.J., Martin, K.A.: Neural circuits of the neocortex. Ann. Rev. Neurosci. 27, 419–451 (2004)

    Google Scholar 

  32. Eckhorn, R., et al.: Coherent oscillations: a mechanism of feature linking in the visual cortex? Biol. Cybern. 60, 121–130 (1988)

    Google Scholar 

  33. El-Shamayleh, Y., et al.: Visual response properties of V1 neurons projecting to V2 in macaque. J. Neurosci. 33, 16594–16605 (2013)

    Google Scholar 

  34. Engelhard, B., et al.: Inducing gamma oscillations and precise spike synchrony by operant conditioning via brain-machine interface. Neuron 77, 361–375 (2013)

    Google Scholar 

  35. ETH Board Blue Brain Project: Internationale Begutachtung www.ethrat.ch/en/node/1361 (2013)

  36. Fenno, L., et al.: The development and application of optogenetics. Ann. Rev. Neurosci. 35, 389–412 (2011)

    Google Scholar 

  37. Fetz, E.E.: Volitional control of cortical oscillations and synchrony. Neuron 77, 216–218 (2013)

    Google Scholar 

  38. Findlay, J., Walker, R.: Human saccadic eye movements. Scholarpedia 7(7), 5095 (2012)

    Google Scholar 

  39. Freund, T., Kali, S.: Interneurons. Scholarpedia 3(9), 4720 (2008)

    ADS  Google Scholar 

  40. Friederici, A.D.: The brain basis of language: from structure to function. Physiol. Rev. 91, 1357–1392 (2011)

    Google Scholar 

  41. Fries, P.: Modulation of oscillatory neuronal synchronization by selective visual attention. Science 291, 1560–1563 (2001)

    ADS  Google Scholar 

  42. Fries, P.: A mechanism for cognitive dynamics: neuronal communication through neuronal coherence. Trends Cogn. Sci. 9, 474–480 (2005)

    Google Scholar 

  43. Fries, P., et al.: The effects of visual stimulation and selective visual attention on rhythmic neuronal synchronization in macaque area V4. J. Neurosci. 28, 4823–4835 (2008)

    Google Scholar 

  44. Friston, K.J., et al.: DCM for complex-valued data: cross spectra, coherence and phase delays. NeuroImage 59, 439–455 (2012)

    Google Scholar 

  45. Gaillard, R., et al.: Converging intracranial markers of conscious access. PLoS Biol. 7, e1000061 (2009)

    Google Scholar 

  46. Gray, C.M., Singer, W.: Stimulus-specific neuronal oscillations in the cat visual cortex: a cortical functional unit. SfN Abstr. 13, 404.3 (1987)

    Google Scholar 

  47. Gregoriou, G.G., et al.: High-frequency, long-range coupling between prefrontal and visual cortex during attention. Science 324, 1207–1210 (2009)

    ADS  Google Scholar 

  48. Gregoriou, G.G., et al.: Cell-type-specific synchronization of neural activity in FEF with V4 during attention. Neuron 73, 581–594 (2012)

    Google Scholar 

  49. Grothe, I., et al.: Switching neuronal inputs by differential modulations of gamma-band phase-coherence. J. Neurosci. 32, 16172–16180 (2012)

    Google Scholar 

  50. Hameroff, S., Penrose, R.: Conciousness in the universe: A review of the ‘Orch OR’ theory. Phys. Life Rev. 11, 39–78 (2013)

    ADS  Google Scholar 

  51. Helmstaedter, M., et al.: Connectomic reconstruction of the inner plexiform layer in the mouse retina. Nature 500, 168–174 (2013)

    ADS  Google Scholar 

  52. Hepp, K.: Two models for Josephson oscillators. Ann. Phys. 90, 285–294 (1975)

    ADS  MathSciNet  Google Scholar 

  53. Hepp, K.: Coherence and decoherence in the brain. J. Math. Phys. 53, 095222 (2012)

    ADS  MathSciNet  Google Scholar 

  54. Hill, S.L., et al.: Statistical connectivity provides a sufficient foundation for specific functional connectivity in neocortical neural microcircuits. Proc. Natl. Acad. Sci. 109, 16772–16773 (2012)

    Google Scholar 

  55. Histed, M.H., Maunsell, J.H.R.: Cortical neural populations can guide behavior by integrating inputs linearly, independent of synchrony. Proc. Natl. Acad. Sci. 111, E178–E187 (2013)

    Google Scholar 

  56. James, W.: The Principles of Psychology, p 403. H. Holt, New York (1890)

    Google Scholar 

  57. Jia, X., et al.: Stimulus selectivity and spatial coherence of gamma components of the local field potential. J. Neurosci. 31, 9390–9403 (2011)

    Google Scholar 

  58. Jia, X., et al.: No consistent relationship between gamma power and peak frequency in macaque primary visual cortex. J. Neurosci. 33, 17–25 (2013)

    Google Scholar 

  59. Jia, X., et al.: Gamma and the coordination of spiking in early visual cortex. Neuron 77, 762–774 (2013)

    Google Scholar 

  60. Josephson, B.: Possible new effects in superconductive tunneling. Phys. Lett. 1, 251–253 (1962)

    ADS  MATH  Google Scholar 

  61. Kajikawa, Y., Schroeder, C.E.: How local is the local field potential? Neuron 72, 847–858 (2011)

    Google Scholar 

  62. Kandel, E.R., et al.: Principles of Neural Science, 5th edn. McGraw-Hill, New York (2013)

    Google Scholar 

  63. Katzner, S., et al.: Local origin of field potentials in visual cortex. Neuron 61, 35–41 (2009)

    Google Scholar 

  64. Khawaja, F.A., et al.: Pattern motion selectivity of spiking outputs and local field potentials in macaque visual cortex. J. Neurosci. 29, 13702–13709 (2009)

    Google Scholar 

  65. Koch, C.: Biophysics of Computation: Information Processing in Single Neurons. Oxford University Press, New York (1999)

    Google Scholar 

  66. Koch, C., Hepp, K.: Quantum mechanics in the brain. Nature 440, 611–612 (2006)

    ADS  Google Scholar 

  67. Koch, C., Hepp, K.: In: Chiao, R.J., Cohen, M.L., Legget, A.J., Phillips, W.D., Harper, jr C.L. (eds.) Visions of Discovery: New Light on Physics, Cosmology, and Consciousness. Cambridge University Press, Cambridge (2011)

    Google Scholar 

  68. Kreiter, A.K., Singer, W.: Stimulus-dependent synchronization of neuronal responses in the visual cortex of the awake macaque monkey. J Neurosci. 16, 2381–2396 (1996)

    Google Scholar 

  69. Lashgari, R., et al.: Response properties of local field potentials and neighboring single neurons in awake primary visual cortex. J. Neurosci. 32, 11396–11413 (2012)

    Google Scholar 

  70. Lepousez, G., Lledo, P.-M.: Odor discrimination requires proper olfactory fast oscillations in awake mice. Neuron 80, 1–15 (2013)

    Google Scholar 

  71. Lewis, D.A.: Inhibitory neurons in human cortical circuits: Substrate for cognitive dysfunction in schizophrenia. Curr. Opin. Neurobiol. 26, 22–26 (2014)

    Google Scholar 

  72. Lima, B., et al.: Synchronization dynamics in response to plaid stimuli in monkey V1. Cereb. Cortex 20, 1556–1573 (2010)

    Google Scholar 

  73. Lucero, E., et al.: Computing prime factors with a Josephson phase qubit quantum processor. Nat. Phys. 8, 719–723 (2012)

    Google Scholar 

  74. Markov, T., et al.: A weighted and directed interareal connectivity matrix for macaque cerebral cortex. Cereb. Cortex 24, 17–36 (2013)

    Google Scholar 

  75. Markov, T., et al.: The anatomy of hierarchy: feedforward and feedback pathways in macaque visual cortex. J. Comp. Neurol. 522, 225–259 (2013)

    Google Scholar 

  76. Markov, T., et al.: Cortical high-density counterstream architectures. Science 342, 1238406 (2013)

    Google Scholar 

  77. Markram, H.: The blue brain project. Nat. Rev. Neurosci. 7, 153–160 (2006)

    Google Scholar 

  78. Marshall, L., et al.: Boosting slow oscillations during sleep potentiates memory. Nature 444, 610–613 (2006)

    ADS  Google Scholar 

  79. Miller, E.K., Buschman, T.J.: Cortical circuits for the control of attention. Curr. Opin. Neurobiol. 23, 216–222 (2013)

    Google Scholar 

  80. Moratti, S., et al.: Dynamic gamma frequency feedback coupling between higher and lower order visual cortex underlies perceptual completion in humans. Neuroimage 86, 470–479 (2013)

    Google Scholar 

  81. Murthy, V.N., Fetz, E.E.: Coherent 25- to 35-Hz oscillations in the sensorimotor cortex of awake behaving monkeys. Proc. Natl. Acad. Sci. 89, 5670–5674 (1992)

    ADS  Google Scholar 

  82. Nicolic, D., et al.: Gamma oscillations: precise temporal coordination without a metronome. Trends Cogn. Sci. 17, 54–55 (2013)

    Google Scholar 

  83. Palanca, B.J.A., DeAngelis, G.C.: Does neural synchrony underlie visual feature grouping? Neuron 46, 333–346 (2005)

    Google Scholar 

  84. Pannasch, U., Rouach, N.: Emerging role for astroglial networks in information processing: from synapse to behavior. Trends Neurosci. 36, 405–417 (2013)

    Google Scholar 

  85. Poggio, T., Serre, T.: Models of visual cortex. Scholarpedia 8(4), 3516 (2013)

    ADS  Google Scholar 

  86. Ray, S., Maunsell, J.H.R.: Differences in gamma frequencies across visual cortex restrict their possible use in computation. Neuron 67, 885–898 (2010)

    Google Scholar 

  87. Rey, H.G., et al.: Timing of single-neuron and local field potential responses in the human medial temporal lobe. Curr. Biol. 24, 299–304 (2014)

    Google Scholar 

  88. Reimann, M.W., et al.: A biophysically detailed model of neocortical LFPs predicts the critical role of active membrane currents. Neuron 79, 375–390 (2013)

    Google Scholar 

  89. Roberts, M.J., et al.: Robust gamma coherence between macaque V1 and V2 by dynamic frequency matching. Neuron 78, 523–536 (2013)

    Google Scholar 

  90. Roelfsema, P.R., et al.: Synchrony and covariation of firing rates in the primary visual cortex during contour grouping. Nat. Neurosci. 7, 982–991 (2004)

    Google Scholar 

  91. Roelfsema, P.R., et al.: Alpha and gamma oscillations as markers of feedforward and feedback processing in areas V1 and V4 of monkey visual cortex. SfN Abstr. 1, 623.03 (2012)

    Google Scholar 

  92. Saalmann, Y.B., et al.: The Pulvinar regulates information transmission between cortical areas on attention demands. Science 337, 753–756 (2012)

    ADS  Google Scholar 

  93. Schafer, R.J., et al.: Visual and attentional functions of the lateral pulvinar. SfN Abstr. 673.10 (2012)

    Google Scholar 

  94. Seung, S.: I am my connectome (2010). Video on TED.com

    Google Scholar 

  95. Shafranjuk, S.E., Ketterson, J.B.: Principles of josepson-junction-based quantum computation. In: Bennemann, K.H., Ketterson, J.B., (eds.) Superconductivity, vol 1. Spinger, Berlin (2008)

    Google Scholar 

  96. Shadlen, M.N., Movshon, J.A.: Synchrony unbound: a critical evaluation of the temporal binding hypothesis. Neuron 24, 67–77 (1999)

    Google Scholar 

  97. Shepherd, G., (ed.): The Synaptic Organization of the Brain. Oxford University Press, Oxford (2004)

    Google Scholar 

  98. Shimamoto, S.A., et al.: Subthalamic nucleus neurons are sychronized to primary motor cortex local field potentials in Parkinson’s disease. J. Neurosci. 33, 7220–7233 (2013)

    Google Scholar 

  99. Singer, W.: Time as coding space in neocortical processing: a hypothesis. In: Gazzaniga, M.S. (ed.) The Cognitive Neurosciences, pp. 91–104. MIT, Cambridge, MA (1997)

    Google Scholar 

  100. Singer, W.: Binding by synchrony. Scholarpedia 2(12), 1657 (2007)

    ADS  Google Scholar 

  101. Spaak, E., et al.: Layer-specific entrainment of gamma-band neural activity by the alpha rhythm in monkey visual cortex. Curr. Biol. 22, 2313–2318 (2012)

    Google Scholar 

  102. Spruston, N.: Pyramidal neuron. Scholarpedia 4(5), 6130 (2009)

    ADS  Google Scholar 

  103. Squire, L.R., et al.: Fundamental Neuroscience. Elsevier, Amsterdam (2013)

    Google Scholar 

  104. Squire, R.F., et al.: Frontal eye field. Scholarpedia 7(10), 5341 (2012)

    ADS  Google Scholar 

  105. Tegmark, M.: Importance of quantum decoherence in brain processes. Phys. Rev. E 61, 4194–4206 (2000)

    ADS  Google Scholar 

  106. Thiele, A., Stoner, G.: Neuronal synchrony does not correlate with motion coherence in cortical area MT. Nature 421, 366–370 (2003)

    ADS  Google Scholar 

  107. Traub, R.D., et al.: Single-column thalamocortical network model exhibiting gamma oscillations, sleep spindles, and epileptogenic bursts. J. Neurophysiol. 93, 2194–2232 (2005)

    Google Scholar 

  108. Van Kerkoerle, et al.: Alpha and gamma oscillations characterize feedback and feedforeward processing in monkey visual cortex. Proc. Natl. Acad. Sci. 111, 14332–14341 (2014)

    Google Scholar 

  109. Vezoli, J., et al.: Extracting structure from function: Inter-areal causal interactions at gamma and beta rhythms reveal cortical hierarchical relationships. SfN Abstr. 723.10 (2012)

    Google Scholar 

  110. Vinck, M., et al.: Attentional modulation of cell-class-specific gamma-band synchronization in awake monkey area V4. Neuron 80, 1077–1089 (2013)

    Google Scholar 

  111. Von der Malsburg, C.: The correlation theory of brain function. In: Domany, E., Van Hemmen, J.L., Schulten, K. (eds.) MPI Biophysical Chemistry, Internal Report 81-2. Reprinted in Models of Neural Networks II (1994). Spinger, Berlin (1981)

    Google Scholar 

  112. Wang, X.-J.: Neurophysiological and computational principles of cortical rhythms in cognition. Physiol. Rev. 90, 1195–1268 (2010)

    Google Scholar 

  113. Womelsdorf, T., et al.: Gamma-band synchronization in visual cortex predicts speed of change detection. Nature 439, 733–736 (2006)

    ADS  Google Scholar 

  114. Womelsdorf, T., et al.: Modulation of neuronal interactions through neuronal synchronization. Science 316, 1609–1612 (2007)

    ADS  Google Scholar 

  115. Xing, D., et al.: Stochastic generation of gamma band activity in the primary visual cortex of awake and anesthetized monkeys. J. Neurosci. 32, 13873–13880 (2012)

    Google Scholar 

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Acknowledgements

I am grateful to my colleagues in the Physics Department of the ETHZ, Jürg Fröhlich, Hans-Ruedi Ott and Thomas Schulthess, for listening to my concerns about the BBP. I have learnt most about neuroscience from the late neurologist Volker Henn and from collaborations in the Institute of Neuroinformatics in Zürich. Constructive remarks by Pascal Fries and Kevan Martin have been very helpful, but all misrepresentations are mine.

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    K. Hepp

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  1. Fakultät für Physik, Universität Bielefeld, Bielefeld, Germany

    Philippe Blanchard

  2. Institute for Theoretical Physics, ETH Zürich, Zürich, Switzerland

    Jürg Fröhlich

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Hepp, K. (2015). Computation Through Neuronal Oscillations. In: Blanchard, P., Fröhlich, J. (eds) The Message of Quantum Science. Lecture Notes in Physics, vol 899. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46422-9_10

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