Advertisement

Traversing Scales of Brain and Behavioral Organization I: Concepts and Experiments

  • J. A. Scott Kelso
  • Armin Fuchs
  • Viktor K. Jirsa
Part of the Springer Series in Synergetics book series (SSSYN)

Abstract

In this paper, and the ones following, we will present an approach to understanding behavior, brain and the relation between them. The present contribution provides a sketch of the strategy we have adopted toward the brain-behavior relation, notes its main tenets and applies them to a new and very specific experiment that uses large scale SQuID arrays to determine how the human brain times individual actions to environmental events. A second paper (Fuchs, Jirsa and Kelso this volume) will describe in more detail the various methods we and others have used to analyze and visualize the spatiotemporal activity of the brain and to extract relevant features from experimental data. Finally, in a third paper (Jirsa, Kelso and Fuchs this volume) we will spell out a theory, grounded in the neuroanatomy and neurophysiology of the cerebral cortex, that serves to connect neural and behavioral levels of description for the paradigmatic case of bimanual coordination. Our collective goal in these three papers is to set the stage for a principled move from phenomenological laws at the behavioral level to the specific neural mechanisms that underlie them. With respect to the history of science our approach is entirely conventional. Fundamentally, it begins with the identification of the macroscopic behavior of a system and attempts to derive it from a level below. Even for physical systems, however, the derivation of the “macro” from the “micro” is nontrivial. Only in the 70’s, for example, was it first possible to derive the behavior of ferromagnets (as described by Landau’s mean field theory) from more fundamental grounds using the so-called renormalization group method that earned Kenneth Wilson the Nobel Prize in 1982. Likewise, it took the genius of Hermann Haken to derive the behavior of a far from equilibrium system like the laser from quantum mechanics (Haken 1970). Thus, some 70 years after atoms were discovered did it become possible to derive macroscopic properties of certain materials and optical devices from a more microscopic basis, and only then using rather sophisticated mathematical techniques.

Keywords

Brain Activity Peak Velocity Movement Rate Movement Velocity Behavioral Level 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. DeGuzman, G., Kelso, J.A.S. (1991): Multifrequency behavioral patterns and the phase attractive circle map, Biol. Cybern. 64, 485 – 495MATHCrossRefGoogle Scholar
  2. DeGuzman, G., Kelso, J.A.S., Buchanan, J.J. (1997): Self-organization of trajectory formation. Biol. Cybern. 76, 275 – 284CrossRefGoogle Scholar
  3. Fuchs, A., Kelso, J.A.S., Haken, H. (1992): Phase Transitions in the Human Brain: Spatial Mode Dynamics, Inter. J. Bifurc. Chaos 2, 917 – 939MATHCrossRefGoogle Scholar
  4. Fuchs, A., Kelso, J.A.S. (1994): A theoretical note on models of interlimb coordination, Journ. Exp. Psych.: Human Perception and Performance, 20, No. 5, 1088 – 1097CrossRefGoogle Scholar
  5. Georgopoulos, A.P. (1997): Neural networks and motor control, Neuroscientist 3, 52 – 60Google Scholar
  6. Haken, H. (1970): Laser theory. Encyclopedia of Physics Vol. XXXV/2C, Springer, BerlinGoogle Scholar
  7. Haken, H. (1983): Synergetics. An Introduction, 3rd ed., Springer, BerlinMATHGoogle Scholar
  8. Haken, H., Kelso, J.A.S., Bunz, H. (1985): A Theoretical Model of Phase Transitions in Human Hand Movements, Biol. Cybern. 51, 347 – 356MathSciNetMATHCrossRefGoogle Scholar
  9. Haken, H., Peper, C.E., Beek, P.J., Daffertshofer, A. (1996): A model for phase transitions in human hand movements during multifrequency tapping, Physica D 90, 179 – 196MATHCrossRefGoogle Scholar
  10. Jirsa, V.K., Friedrich, R., Haken, H., Kelso, J.A.S. (1994): A theoretical model of phase transitions in the human brain, Biol. Cybern. 71, 27 – 35MATHCrossRefGoogle Scholar
  11. Jirsa, V.K., Haken H. (1996): Field theory of electromagnetic brain activity, Phys. Rev. Let. 77, 960–963 Kelso, J.A.S. (1984): Phase transitions and critical behavior in human bimanual coordination, Am. J. Physiol. 15, R1000 – R1004Google Scholar
  12. Kelso, J.A.S. (1995): Dynamic Patterns. The S elf-Organization of Brain and Behavior, MIT Press, Cambridge, MAGoogle Scholar
  13. Kelso, J.A.S., DelColle, J.D., Schöner, G. (1990): Action-perception as a pattern formation process, in: Attention & Performance XIII, Jeannerod, M., ed., 139– 169, Erlbaum, Hillsdale, NJGoogle Scholar
  14. Kelso, J.A.S., Buchanan, J.J., DeGuzman, G.C., Ding, M. (1993): Spontaneous recruitment and annihilation of degrees of freedom in biological coordination. Phys. Let. A 179, 364 – 371ADSCrossRefGoogle Scholar
  15. Kelso, J.A.S., Bressier, S.L., Buchanan, S., DeGuzman, G.C., Ding, M., Fuchs, A., Holroyd, T. (1992): A Phase Transition in Human Brain and Behavior, Phys. Let. A 169, 134 – 144ADSCrossRefGoogle Scholar
  16. Kelso, J.A.S., Bressier, S.L., Buchanan, S., DeGuzman, G.C., Ding, M., Fuchs, A., Holroyd, T. (1991): Cooperative and critical phenomena in the human brain revealed by multiple SQUIDS. In: Measuring chaos in the human brain, Duke D., Pritcard W., eds., World Scientific, NJGoogle Scholar
  17. Kelso, J.A.S., Fuchs, A., Lancaster, R., Holroyd, T., Cheyne, D., Weinberg, H. (1998): Dynamic Cortical Activity in the Human Brain Reveals Motor Equivalence, NATURE 392, 814 – 818ADSCrossRefGoogle Scholar
  18. Kelso, J.A.S., Fuchs, A., Lancaster, R., Holroyd, T., Cheyne, D., Weinberg, H. (1998): Dynamic Cortical Activity in the Human Brain Reveals Motor Equivalence, NATURE 392, 814 – 818ADSCrossRefGoogle Scholar
  19. Rao, S.M., Harrington, D.L., Haaland, K.Y., Bobholz, J.A., Cox, R.W., Binder, J.R. (1997): Distributed neural systems underlying the timing of movements, J. Neurosci. 17, 5528 – 5535Google Scholar
  20. Schöner, G., Haken, H., Kelso, J.A.S. (1986): A Stochastic Theory of Phase Transitions in Human Hand Movement, Biol. Cybern. 53, 247 – 257MATHCrossRefGoogle Scholar
  21. Treffner, P.J., Turvey, M.T. (1996): Symmetry, broken symmetry, and handedness in bimanual coordination dynamics. Exp. Brain Res. 107, 463 – 478Google Scholar
  22. Turvey, M.T. (1994): From Borelli (1680) and Bell (1826) to the dynamics of action and perception. J. of Sport and Exercise Psychology 16, 2, S128 – S157Google Scholar
  23. Uhl, C., Friedrich, R., Haken, H. (1995): Analysis of spatiotemporal signals of complex systems, Phys. Rev. E 51, 3890 – 3900Google Scholar
  24. Wallenstein, G.V., Kelso, J.A.S., Bressier, S.L. (1995): Phase transitions in spatiotemporal patterns of brain activity and behavior, Physica D 84, 626 – 634CrossRefGoogle Scholar
  25. Wilson, K.G. (1979): Problems in Physics with many scales of length. Sci. Am. 241, 158Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • J. A. Scott Kelso
    • 1
  • Armin Fuchs
    • 1
  • Viktor K. Jirsa
    • 1
  1. 1.Program in Complex Systems and Brain Sciences, Center for Complex SystemsFlorida Atlantic UniversityBoca RatonUSA

Personalised recommendations