Skip to main content
Book cover

Advances in Cognitive Neurodynamics (IV) pp 127–136Cite as

Advanced Models of Cortical Dynamics in Perception

Part of the Advances in Cognitive Neurodynamics book series (ICCN)

Abstract

Here the phenomenon of interest is the flash of recognition and accompanying emotion one experiences when one receives a familiar stimulus. We explain the speed and richness of the event by postulating phase transitions in cortical neuropil: condensation from a gas-like phase to a liquid-like phase followed by evaporation. We model the process with a Carnot-like thermodynamic cycle at three successive levels of complexity: primary sensory cortices; limbic system; global neocortex. We replace the thermodynamic state variables of pressure, volume and temperature with neurodynamic variables, respectively mean beta-gamma power, pattern stability (negentropy), and neural feedback gain (mean interaction strength). We cite evidence that all sensory cortices use this cycle, necessarily so for two reasons. They all evolved from the primordial forebrain of vertebrates dominated by olfaction; they all transmit the same form of perceptual information, wave packets, so signals in all modalities armodel by linear matrix concatenation.

Keywords

  • Carnot cycle
  • Criticality
  • Ephapsis
  • Hebbian assembly
  • Memory
  • Phase transition
  • Wave packet

This is a preview of subscription content, access via your institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-94-017-9548-7_17
  • Chapter length: 10 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   189.00
Price excludes VAT (USA)
  • ISBN: 978-94-017-9548-7
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   249.99
Price excludes VAT (USA)
Hardcover Book
USD   299.99
Price excludes VAT (USA)
Learn about institutional subscriptions
Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

References

  1. Freeman WJ, Quian Quiroga R (2013) Imaging Brain Function with EEG: Advanced Temporal and Spatial imaging of Electroencephalographic Signals. New York: Springer.

    CrossRef  Google Scholar 

  2. Fuster, J.M. (2006) The cognit: a network model of cortical representation. International Journal of Psychophysiology 60:125–132.

    CrossRef  PubMed  Google Scholar 

  3. Taylor JG (1998) Neural ‘bubble’ dynamics in two dimensions: foundations. Biol Cybern 80: 393–409.

    CrossRef  Google Scholar 

  4. Tononi G (2004) An information integration theory of consciousness. BMC Neurosci. 5: 42.

    CrossRef  PubMed Central  PubMed  Google Scholar 

  5. Freeman WJ (1975) Mass Action in the Nervous System New York: Academic. http://sulcus.berkeley.edu/MANSWWW/MANSWWW.html

  6. Capolupo A, Freeman WJ, Vitiello G (2013) Dissipation of ‘dark energy’ by cortex in knowledge retrieval. Physics of Life Reviews, on-line. DOI: 10.1016/j.plrev.2013.01.001

    Google Scholar 

  7. Capolupo A, Freeman WJ, Vitiello G (this volume) The dissipative many-body model and phase transitions in brain nonlinear dynamics.

    Google Scholar 

  8. Freeman WJ. Deep analysis of perception through dynamic structures that emerge in cortical activity from self-regulated noise. Cognitive Neurodynamics (2009) 3(1): 105–116.

    CrossRef  PubMed Central  PubMed  Google Scholar 

  9. Rice SO. Mathematical analysis of random noise. Technical publications monographs, vol. B-1589. New York: Bell Telephone Labs (1950).

    Google Scholar 

  10. Freeman WJ, Livi R, Obinata M, Vitiello G (2012) Cortical phase transitions, non-equilibrium thermodynamics and the time-dependent Ginzburg-Landau equation. Int J Mod Phys B 26 (6): 1250035. DOI: 10.1142/S021797921250035Xx

    CrossRef  Google Scholar 

  11. Kozma, R, Puljic M, Freeman WJ (this volume) Thermodynamic model of criticality in the cortex based on EEG/ECoG Data. Chapter 1 in: Plenz D (ed), “Criticality in Neural Systems”. NY: Wiley, (2012) 1–28

    Google Scholar 

  12. Quian Quiroga R. Concept cells: The building blocks of declarative memory functions. Nature Rev Neuroscience 13 (2012): 587–597.

    Google Scholar 

  13. Quian Quiroga R (this volume) Concept cells in the human brain

    Google Scholar 

  14. Ruiz Y, Pockett S, Freeman WJ, Gonzales E, Li Guang (2010) A method to study global spatial patterns related to sensory perception in scalp EEG. J Neuroscience Methods 191: 110–118. doi:10.1016/j.jneumeth.2010.05.021

    CrossRef  Google Scholar 

  15. Brockmeier AJ, Hazrati MK, Freeman WJ, Li L, Principe JC (2012) Locating spatial patterns of waveforms during sensory perception in scalp EEG. EMBC Ann Intern Conf IEEE, pp. 2531–2534, doi: 10.1109/EMBC.2012.6346479

  16. Zhang T, Dai L, Wang Y, Freeman WJ, Li G (this volume) EEG spatiotemporal pattern classification of the stimuli on different fingers

    Google Scholar 

  17. Arvanitaki A (1942) Effects evoked in an axon by the activity of a contiguous one. J Neurophysiol 5(2):89–108. (first use of ‘ephapsis’)

    Google Scholar 

  18. Wall PD, Lidierth M (1997) Five sources of a dorsal root potential: their interactions and origins in the superficial dorsal horn. Neurophysiol 78(2): 860–871.

    CAS  Google Scholar 

  19. Steriade M, Amzica F (1994) Dynamic coupling among neocortical neurons during evoked and spontaneous spike-wave seizure activity. J Neurophysiol 72(5): 2051–2069.

    CAS  PubMed  Google Scholar 

  20. Anastassiou CA, Perin R, Markram H, Koch C (2011) Ephaptic coupling of cortical neurons. Nature Neurosci 14: 217–223. doi:10.1038/nn.2727

    CrossRef  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Division of Neurobiology, Department of Molecular and Cell Biology, University of California, Berkeley, CA, 94720, USA

    Walter J. Freeman

  2. Department of Mathematical Sciences, University of Memphis, Memphis, TN, 38152, USA

    Robert Kozma

  3. Department of Control Science and Engineering, State Key Lab of Industrial Control Technology, Zhejiang University, 38 Zheda Road, Hangzhou, 310027, People’s Republic of China

    Guang Li & Tinglin Zhang

  4. Centre for Systems Neuroscience, University of Leicester, LE1 7RH, Leicester, UK

    Rodrigo Quian Quiroga

  5. Dipartimento di Fisica, University of Salerno, 84084, Fisciano, (Salerno), Italy

    Giuseppe Vitiello

Authors
  1. Walter J. Freeman
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Robert Kozma
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Guang Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Rodrigo Quian Quiroga
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Giuseppe Vitiello
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Tinglin Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Walter J. Freeman .

Editor information

Editors and Affiliations

  1. SLU and Agora for Biosystems, Sigtuna, Sweden

    Hans Liljenström

Rights and permissions

Reprints and Permissions

Copyright information

© 2015 Springer Science+Business Media Dordrecht

About this paper

Cite this paper

Freeman, W.J., Kozma, R., Li, G., Quiroga, R.Q., Vitiello, G., Zhang, T. (2015). Advanced Models of Cortical Dynamics in Perception. In: Liljenström, H. (eds) Advances in Cognitive Neurodynamics (IV). Advances in Cognitive Neurodynamics. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-9548-7_17

Download citation