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Traversing Scales of Brain and Behavioral Organization III: Theoretical Modeling

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Analysis of Neurophysiological Brain Functioning

Part of the book series: Springer Series in Synergetics ((SSSYN))

Abstract

In coordinated movements typically several states related to different behavioral patterns can be found, e.g. different gaits of horses (Collins and Stewart 1993, Schöner et al. 1990) or different configurations among the joints for trajectory formation tasks (Buchanan et al. 1997, Kelso et al. 1991). These states have different stabilities dependent on external or internal control parameters. When such control parameters are manipulated, coordination states may become unstable and the system exhibits a transition from one state to another. These phenomena have intensively been investigated experimentally and theoretically and mathematical models have been set up reproducing the experimentally observed coordination behavior as well as predicting new effects (see (Haken 1996, Kelso 1995) for reviews). On the other hand, recent MEG and EEG experiments (Kelso et al. 1992, Wallenstein et al. 1995) have investigated the spatiotemporal brain dynamics during coordination of finger movements with external periodic stimuli. To accommodate these results, a mathematical phenomenological model was developed describing the on-going brain activity (Jirsa et al. 1994). In (Jirsa and Haken 1996a, 1996b) [Jirsa and Haken 1996a, Jirsa and Haken 1996b] a neurophysiologically motivated field theory of the spatiotemporal brain dynamics was elaborated which combined properties of neural ensembles, including their short- and long-range connections in the cortex, in addition to describing the interaction of functional units embedded into the neural sheet. This approach was applied to the brain-coordination experiment (Kelso et al. 1992) where the subject’s task was to coordinate rhythmic behavior of a finger with an external acoustic stimulus. During the experiment the MEG of the subject was recorded. Complex systems, such as the brain, have the general property that they perform low-dimensional behavior during transitions from one macroscopic state to another (Cross and Hohenberg 1993, Haken 1983, 1987). This type of behavior has also been found in the analyses (Fuchs et al. 1992, Jirsa et al. 1995) of the brain data from the coordination experiment in (Kelso et al. 1992). On the basis of these analyses the phenomenological model in (Jirsa et al. 1994) describing the brain activity was derived qualitatively from the neurophysiologically motivated theory in (Jirsa and Haken 1996a, 1997).

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References

  • Abeles M. (1991), Corticonics, Cambridge University Press

    Google Scholar 

  • Braitenberg V., Schüz A. (1991), Anatomy of the cortex. Statistics and geometry, Springer, Berlin

    Google Scholar 

  • Buchanan J.J., Kelso J.A.S., de Guzman G.C. (1997), The selforganization of trajectory formation: I. Experimental evidence, Biol. Cybern. 76, 257 – 273

    Article  MATH  Google Scholar 

  • Carson R., Byblow W., Goodman D. (1994), The dynamical substructure of bimanual coordination, in: Swinnen S., Heuer H., Massion J., Casaer P., eds., Interlimb coordination: Neural, Dynamical and Cognitive Constraints, pp. 319 – 337, Academic Press, San Diego

    Google Scholar 

  • Collins J.J., Stewart I.N. (1993), Coupled nonlinear oscillators and the symmetries of animal gaits, J. Nonlinear Sci. 3, 349 – 392

    Article  MathSciNet  ADS  MATH  Google Scholar 

  • Cross M.C., Hohenberg P.C. (1993), Pattern formation outside of equilibrium, Rev. Mod. Phys. 65, 851

    Article  ADS  Google Scholar 

  • Fellemam D.J., Van Essen D.C. (1991), Distributed hierarchical processing in the primate cerebral cortex, Cerebral Cortex 1, 1 – 47

    Article  Google Scholar 

  • Freeman W.J. (1992), Tutorial on neurobiology: From single neurons to brain chaos, Inter. J. Bif. Chaos 2, 451 – 482

    Article  MATH  Google Scholar 

  • Friedrich R., Fuchs A., Haken H. (1991), Spatiotemporal EEG patterns, in: Haken H., Koepchen H.P., eds., Rhythms in Physiological Systems, Springer, Berlin

    Google Scholar 

  • Fuchs A., Haken H. (1988), Pattern recognition and associative memory as dynamical processes in a synergetic system I+II, Erratum, Biol. Cybern. 60, 17–22, 107 – 109, 476

    Article  MathSciNet  Google Scholar 

  • Fuchs A., Kelso J.A.S., Haken H. (1992), Phase Transitions in the Human Brain: Spatial Mode Dynamics, Inter. J. Bif. Chaos 2, 917 – 939

    Article  MATH  Google Scholar 

  • Haken H., Kelso J.A.S., Bunz H. (1985), A Theoretical Model of Phase transitions in Human Hand Movements, Biol. Cybern. 51, 347– 356

    Google Scholar 

  • Haken H. (1983), Synergetics. An Introduction, 3rd ed., Springer, Berlin

    MATH  Google Scholar 

  • Haken H. (1987), Advanced Synergetics, 2nd ed., Springer, Berlin

    Google Scholar 

  • Haken H. (1991), Synergetic Computers and Cognition, A Top-Down Approach to

    Google Scholar 

  • Neural Nets, Springer, Berlin

    Google Scholar 

  • Haken H. (1996), Principles of brain functioning, Springer, Berlin

    MATH  Google Scholar 

  • 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 – 35

    Article  MATH  Google Scholar 

  • Jirsa V.K., Friedrich R., Haken H. (1995), Reconstruction of the spatio-temporal dynamics of a human magnetoencephalogram, Physica D 89, 100 – 122

    Article  MATH  Google Scholar 

  • Jirsa V.K., Haken H. (1996), Field theory of electromagnetic brain activity, Phys. Rev. Let. 77, 960

    Article  ADS  Google Scholar 

  • Jirsa V.K., Haken H. (1996), Derivation of a field equation of brain activity, J. Biol. Phys. 22, 101 – 112

    Article  Google Scholar 

  • Jirsa V.K., Haken H. (1997), A derivation of a macroscopic field theory of the brain from the quasi-microscopic neural dynamics, Physica D 99, 503 – 526

    Article  MATH  Google Scholar 

  • Kelso J.A.S. (1981), On the oscillatory basis of movement, Bull. Psychon. Soc. 18, 63

    Google Scholar 

  • Kelso J.A.S. (1984), Phase transitions and critical behavior in human bimanual coordination, Am. J. Physiol. 15, R1000 – R1004

    Google Scholar 

  • Kelso J.A.S., Scholz J.P., Schöner G. (1986), Nonequilibrium phase transitions in coordinated biological motion: critical fluctuations, Phys. Let. A 118, 279 – 284

    Article  ADS  Google Scholar 

  • Kelso J.A.S., Buchanan J.J., Wallace S.A. (1991), Order parameters for the neural organization of single, multijoint limb movement patterns, Exp. Brain Res. 85, 432 – 444

    Google Scholar 

  • 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 – 144

    Google Scholar 

  • Kelso J.A.S., Fuchs A., Holroyd T., Cheyne D., Weinberg H. (1994), Bifurcations In human brain and behavior, Society for Neuroscience, 20, 444

    Google Scholar 

  • Kelso J.A.S. (1995), Dynamic Patterns. The Self-Organization of Brain and Behavior, The MIT Press, Cambridge, Massachusetts

    Google Scholar 

  • Kristeva R., Cheyne D., Deecke L. (1991), Neuromagnetic fields accompanying unilateral and bilateral voluntary movements: Topography and analysis of cortical sources, Electroenceph. Clin. Neurophys. 81, 284 – 298

    Google Scholar 

  • Miller R. (1987), Representation of brief temporal patterns, Hebbian synapses, and the left-hemisphere dominance for phoneme recognition, Psychobiology 15, 241– 247

    Google Scholar 

  • Nunez P.L. (1974), The brain wave equation: A model for the EEG, Mathematical Biosciences 21, 279 – 297

    Article  MATH  Google Scholar 

  • Nunez P.L. (1995), Neocortical dynamics and human EEG rhythms, Oxford University Press

    Google Scholar 

  • Scholz J.P., Kelso J.A.S., Schöner G. (1987), Nonequilibrium phase transitions in coordinated biological motion: critical slowing down and switching time, Phys. Let. A 123, 390 – 394

    Article  ADS  Google Scholar 

  • Schöner G., Jiang W.Y., Kelso J.A.S. (1990), A Synergetic Theory of Quadrupedal Gaits and Gait Transitions, J. theor. Biol. 142, 359 – 391

    Article  Google Scholar 

  • Tuller B., Kelso J.A.S. (1989), Environment ally-specified patterns of movement coordination in normal and split-brain subjects, Exp. Brain Res. 75, 306 – 316

    Google Scholar 

  • Wallenstein G.V., Kelso J.A.S., Bressier S.L. (1995), Phase transitions in spatiotem-poral patterns of brain activity and behavior, Physica D 84, 626 – 634

    Article  Google Scholar 

  • Wiesendanger M., Wicki U., Rouiller E. (1994), Are there unifying structures in the brain responsible for interlimb coordination?, in: Swinnen S., Heuer H., Massion J., Casaer P., eds., Interlimb coordination: Neural, Dynamical and Cognitive Constraints, pp. 179 – 207, Academic Press, San Diego

    Google Scholar 

  • Williamson S.J., Kaufman L. (1987), Analysis of neuromagnetic signals, in: Gevins A.S., Remond A., eds., Methods of analysis of brain electrical and magnetic signals. EEG Handbook, Elsevier Science

    Google Scholar 

  • Wilson H.R., Cowan J.D. (1972), Excitatory and inhibitory interactions in localized populations of model neurons, Biophysical Journal 12, pp. 1 – 24

    Article  ADS  Google Scholar 

  • Wilson H.R., Cowan J.D. (1973), A mathematical theory of the functional dynamics of cortical and thalamic nervous tissue, Kybernetik 13, 55 – 80

    Article  MATH  Google Scholar 

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© 1999 Springer-Verlag Berlin Heidelberg

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Jirsal, V.K., Kelsol, J.A.S., Fuchsl, A. (1999). Traversing Scales of Brain and Behavioral Organization III: Theoretical Modeling. In: Uhl, C. (eds) Analysis of Neurophysiological Brain Functioning. Springer Series in Synergetics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-60007-4_6

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  • DOI: https://doi.org/10.1007/978-3-642-60007-4_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-64219-7

  • Online ISBN: 978-3-642-60007-4

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