Skip to main content
SpringerLink
Log in

Characterization of state transitions in spatially distributed, chaotic, nonlinear, dynamical systems in cerebral cortex

  • Papers
  • Data Types And Results
  • Published:
Integrative Physiological and Behavioral Science Aims and scope Submit manuscript

Abstract

The neurons of cerebral cortex are largely autonomous and generate activity that is manifested in trains of microscopic axonal action potentials. The neurons interact by sparse but numerous synaptic connections to generate macroscopic dendritic activity patterns that are observed in electroencephalographic (EEG) waves. The macroscopic patterns are constructed by the populations and they shape the output of cortical neurons in parallel arrays. Sensory cortexes receive sensory information in the form of microscopic action potentials, which induce state transitions in population dynamics. Each state transition transforms sensory information to perceptual meaning. The EEG reflects both kinds of activity. The sensory input is accessed by time ensemble averaging, whereas the perceptual output is found by spatial ensemble averaging. Spatial phase gradients in the EEG are useful for identifying EEG segments in a sequence of state transitions in response to sensory input. The rapidity and flexibility with which they take place give strong reason to postulate that the mechanism for the construction of these sequences of patterns is a dynamical system operating in a chaotic domain.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Bartlett, F.C. (1932).Remembering. Cambridge, England: University Press.

    Google Scholar 

  • Basar, E. (1980).EEG-Brain Dynamics. Amsterdam: Elsevier.

    Google Scholar 

  • Basar, E. and Bullock, T.H. (Eds.) (1989).Brain Dynamics. Berlin: Springer.

    Google Scholar 

  • Berger, H. (1937). Uber das Elektrenkephalogramm des Menschen. XII.Archiv fur Psychiatrie, 106: 165–187.

    Article  Google Scholar 

  • Bressler, S.L. (1990). The gamma wave: A cortical information carrier?Trends in NeuroScience, 13: 161–162.

    Article  Google Scholar 

  • Bressler, S.L. and Freeman, W.J. (1980). Frequency analysis of olfactory system EEG in cat, rabbit and rat.Electroencephalography and Clinical Neurophysiology, 50: 19–24.

    Article  PubMed  Google Scholar 

  • Crick, F. and Koch, C. (1990). Towards a neurobiological theory of consciousness.Seminars in the Neurosciences, 2: 263–275.

    Google Scholar 

  • Dempsey, E.W. and Morison, R.S. (1942). The electrical activity of thalamocortical relay systems.American Journal of Physiology, 138: 283–289.

    Google Scholar 

  • Eeckman, F.H. and Freeman, W.J. (1991). Asymmetric sigmoid nonlinearity in the rat olfactory system.Brain Research, 557: 13–21.

    Article  PubMed  Google Scholar 

  • Eeckman, F.H. and Freeman, W.J. (1990). Correlations between unit firing and EEG in the rat olfactory system.Brain Research, 528: 238–244.

    Article  PubMed  Google Scholar 

  • Freeman, W.J. (1975).Mass Action in the Nervous System. NY: Academic.

    Google Scholar 

  • Freeman, W.J. (1978). Spatial properties of an EEG event in the olfactory bulb and cortex.Electroencephalography and Clinical Neurophysiology, 44: 586–605.

    Article  PubMed  Google Scholar 

  • Freeman, W.J. (1987a). Techniques used in the search for the physiological basis of the EEG. In Gevins, A., Remond, A. (Eds.),Handbook Electroencephalography and Clinical Neurophysiology, 3A, Pt 2, Ch. 18. Amsterdam: Elsevier, 583–664.

    Google Scholar 

  • Freeman, W.J. (1987b). Simulation of chaotic EEG patterns with a dynamic model of the olfactory system.Biological Cybernetics, 56: 139–150.

    Article  PubMed  Google Scholar 

  • Freeman, W.J. (1988). Strange attractors that govern mammalian brain dynamics shown by trajectories of electroencephalographic (EEG) potential.IEEE Transactions Circuits & Systems, 35: 781–783.

    Article  Google Scholar 

  • Freeman, W.J. (1991). The physiology of perception.Scientific American, 264: 78–85.

    Article  PubMed  Google Scholar 

  • Freeman, W.J. (1992). Tutorial in Neurobiology: From Single Neurons to Brain Chaos.International Journal of Bifurcation and Chaos, 2: 451–482.

    Article  Google Scholar 

  • Freeman, W.J. (1993). The emergence of chaotic dynamics as a basis for comprehending intentionality in experimental subjects. In Pribram, K. (Ed.),Rethinking Neural Networks: Quantum Fields and Biological Data. Hillsdale, NJ: Lawrence Erlbaum Associates, pp. 507–514.

    Google Scholar 

  • Freeman, W.J. and Barrie, J.B. (1994). Chaotic oscillations and the genesis of meaning in cerebral cortex. In Mervaillie, J., Christen, Y. (Eds.),Temporal coding in the brain. Berlin: Springer-Verlag, (in press).

    Google Scholar 

  • Freeman, W.J. and Baird, B. (1987). Relation of olfactory EEG to behavior: Spatial analysis.Behavioral Neuroscience, 101: 393–408.

    Article  PubMed  Google Scholar 

  • Freeman, W.J. and Grajski, K.A. (1987). Relation of olfactory EEG to behavior: Factor analysis.Behavioral Neuroscience, 101: 766–777.

    Article  PubMed  Google Scholar 

  • Freeman, W.J. and Van Dijk, B. (1987). Spatial patterns of visual cortical fast EEG during conditioned reflex in a rhesus monkey.Brain Research, 442: 267–276.

    Article  Google Scholar 

  • Freeman, W.J. and Viana Di Prisco, G. (1986). EEG spatial pattern differences with discriminated odors manifest chaotic and limit cycle attractors in olfactory bulb of rabbits. InBrain Theory, Palm, G., Aertsen, A. (Eds.). Berlin: Springer, 97–119.

    Google Scholar 

  • Gray, C.M., Freeman, W.J., and Skinner, J.E. (1986). Chemical dependencies of learning in the rabbit olfactory bulb: Acquisition of the transient spatial-pattern change depends on norepinephrine.Behavioral Neuroscience, 100: 585–596.

    Article  PubMed  Google Scholar 

  • Gray, C.M., Koenig, P., Engel, K.A. and Singer, W. (1989). Oscillatory responses in cat visual cortex exhibit intercolumnar synchronization which reflects global stimulus properties.Nature, 338: 334–337.

    Article  PubMed  Google Scholar 

  • Gray, C.M. and Skinner, J.E. (1988). Field potential response changes in the rabbit olfactory bulb accompany behavioral habituation during the repeated presentation of unreinforced odors.Experimental Brain Research, 73: 189–197.

    Article  Google Scholar 

  • Haken, H. and Stadler, M. (1990).Synergetics of Cognition. Berlin: Springer.

    Google Scholar 

  • Jasper, H.H. (1960). Unspecific thalamocortical relations. In Magoun, H.W. (Ed.).Neurophysiology Section, Handbook of Physiology Vol. 2. Baltimore, MD: Williams and Wilkins, Chapter 53, pp. 1307–1321.

    Google Scholar 

  • Johnson, B.W., Weinberg, H., Ribary, U., Cheyne, D.O. and Ancill, R. (1988). Topographic distribution of the 40 Hz auditory event-related potential in normal and aged subjects.Brain Topography, 1: 117–121.

    Article  PubMed  Google Scholar 

  • Kelso, J.A.S., Bressler, S.L., Buchanan, S., DeGuzman, G.C., Ding, M., Fuchs, A. and Holroyd, T. (1991). Cooperative and critical phenomena in the human brain revealed by multiple squids. Chapter in Duke, D., Pritchard, W. (Eds.)Chaos in the Human Brain. Teaneck, NJ: World Scientific.

    Google Scholar 

  • Llinas, R., Ribary, U., Capell, J., Yamamoto, T. and Winar, R. (1991). An anatomical localization revealed by MEG recordings of the human somatosensory system.Electroencephalography and Clinical Neurophysiology, 78: 185–196.

    Article  PubMed  Google Scholar 

  • Menon, V., Freeman, W.J., and Gevins, A. (1994).Spatio-temporal correlations in human electrocorticograms compared with multichannel band pass filtered noise. Submitted.

  • Mitra, M., and Skinner, J.E. (1992). Low-Dimensional Chaos Maps Learning in a Model Neuropil (Olfactory Bulb).Integrative Physiological and Behavioral Science, 27:4, 304–322.

    Article  PubMed  Google Scholar 

  • Sheer, D.E. (1989). Sensory and cognitive 40-Hz event-related potentials. In Basar, E., Bullock, T.H. (Eds.), (1989)Brain Dynamics. Berlin: Springer, 339–374.

    Google Scholar 

  • Skinner, J.E. and Lindsley, D.B. (1967). Electrophysiological and behavioral effects of blockade of the nonspecific thalamocortical system.Brain Research, 6: 95–118.

    Article  PubMed  Google Scholar 

  • Skinner, J.E., Martin, J.L., Landisman, C.E., Mommer, M.M., Fulton, K., Mitra, M., Burton, W.D., and Saltzberg, B. (1990). Chaotic attractors in a model of neocortex: Dimensionalities of olfactory bulb surface potentials are spatially uniform and event-related. In E. Basar and T.H. Bullock (Eds.).Brain Dynamics Progress and Perspectives. Berlin: Springer-Verlag, pp. 119–134.

    Google Scholar 

  • Skinner, J.E. and Yingling, C.D. (1977). Central gating mechanisms that regulate event-related potentials and behavior: A neural model for attention.Progress in Clinical Neurophysiology, 1: 30–69.

    Google Scholar 

  • Thompson, J.M.T. and Stewart, H.B. (1986).Nonlinear Dynamics and Chaos. New York: Wiley.

    Google Scholar 

  • Weinberg, H., Robertson, D., Crisp, D. and Johnson, B. (1990). Magnetic fields of the brain resulting from normal and pathological function. Chapter 25 in John, E.R. (Ed.),Machinery of the Mind, Boston: Birkhaeuser, 479–511.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Molecular & Cell Biology, University of California, 94720, Berkeley, CA

    Walter J. Freeman

Authors
  1. Walter J. Freeman
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

About this article

Cite this article

Freeman, W.J. Characterization of state transitions in spatially distributed, chaotic, nonlinear, dynamical systems in cerebral cortex. Integrative Physiological and Behavioral Science 29, 294–306 (1994). https://doi.org/10.1007/BF02691333

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02691333

Keywords

Search

Navigation