Structure and dynamics of recurrent neuromodules

Theory in Biosciences

Volumn 117, Issue 1, 1998, Pages 1-17

  Pasemann, Frank ^a  

^a MAX PLANCK INSTITUTE FOR MATHEMATICS IN THE SCIENCES   (Germany)

Author keywords

Bifurcation analysis; Brain theory; Neurodynamics; Recurrent neural network; Synchronization

Indexed keywords

ARTICLE; ARTIFICIAL NEURAL NETWORK; BRAIN FUNCTION; COGNITION; HYSTERESIS; INFORMATION PROCESSING; OSCILLATION; STRUCTURE ACTIVITY RELATION;

EID: 0031972143     PISSN: 14317613     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (32)

1. Abraham, R.H.; Shaw, C.D. (1992) Dynamics - The Theory of Behavior, 2nd. ed., Addison-Wesley, Redwood City.
2. Buzsáki, G.; Llinás, R.; Singer, W.; Berthoz, A.; Christen, Y. (eds.) (1994) Temporal Coding in the Brain, Springer, Berlin.
3. Cohen, M. A.; Grossberg, S.; Pribe, C. A. (1993) Quadruped gait transitions from a neural pattern generator with arousel modulated interactions. In: Proceedings of the World Congress on Neural Networks, Portland, Oregon July, 1993, Vol. II. pp. 610-613.
4. Duke, W.; Pritchard, W.S. (eds.) (1991) Proceedings of the Conference on Measuring Chaos in the Human Brain, World Scientific, Singapore.
5. Eckhorn, R.; Bauer, R.; Jordan, W.; Brosch, M.; Kruse, W.; Munk, M.; Reitboeck H. J. (1988) Coherent oscillations: a mechanism for feature linking in the visual cortex. Biol. Cybern. 60: 121-130.
6. Elbert, T.; Ray, W.J.; Kowalik, Z.J.; Skinner, J.E.; Graf, K.E.; Birbaumer, N. (1994) Chaos and physiology: Deterministic chaos in excitable cell assemblies. Physiological Review 74: 1-47.
7. Engel, A. K.; Roelfsema, P. R.; Fries, P.; Brecht, M.; Singer, W. (1997) Binding and response selection in the temporal domain - a new paradigm forneurobiological research? Theory in Biosciences 116: 241-266.
8. Freeman, W. J. (1992) Tutorial on neurobiology: From single neurons to brain chaos. Int. J. Bif. and Chaos 2: 451-482.
9. Gray, C. M.; König, P.; Engel, A. K.; Singer, W. (1989) Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties. Nature 338: 334-337.
10. Guckenheimer, J.; Holmes, P. (1983) Nonlinear Oscillations, Dynamical Systems and Bifurcations of Vector Fields, Springer Verlag, New York.
11. Harth, E. (1993) The Creative Loop - How the Brain makes a Mind. Addison-Wesley, Reading.
12. Hertz, J. A.; Krogh, A.; Palmer, R.G. (1991) Introduction to the Theory of Neural Computation, Addison-Wesley, Redwood City.
13. Herz A. V. M. (1996) Global analysis of recurrent neural networks. In: Domany, E.; van Hemmen, J.L.; Schulten, K. (eds.) Models of Neural Networks, Vol. III. Springer Verlag, New York.
14. Hirsch, M. (1989) Convergent activation dynamics in continuous time networks. Neural Networks 2: 331-350.
15. Jackson, E.A. (1991) Perspectives of Nonlinear Dynamics, Cambridge University Press, Cambridge.
16. Johannesma, P.; Aertsen, A.; van den Boogaard, H.; Eggermont, J.; Epping, W. (1986) From synchrony to harmony: ideas on the function of neural assemblies and on the interpretation of neural synchrony. In: Palm, G.; and Aertsen, A. (eds.) Brain Theory. Springer Verlag, Berlin.
17. Kelso, J. A. S. (1995) Dynamic Patterns - The Self-Organization of Brain and Behavior, MIT Press, Cambridge.
18. Krüger, J. (ed.) (1991) Neural Cooperativity, Springer Verlag, Berlin.
19. Langton, C. G. (1990) Computation at the edge of chaos: Phase transitions and emergent computation. Physica D 42: 12-37.
20. Mallot, H. A. (1997) Behavior-oriented approaches to cognition: Theoretical perspectives. Theory in Biosciences 116: 196-220.
21. Nagashino, H; Kelso, J. A. S. (1992) Phase transitions in oscillatory neural networks. Science of Artificial Neural Networks, SPIE 1710: pp.279-287.
22. Ott, E. (1993) Chaos in Dynamical Systems, Cambridge University Press, Cambridge.
23. Pantev, C.; Elbert, T.; Lutkenhöhner B. (eds.) (1995) Oscillatory event-related brain dynamics, Plenum Press, London.
24. Pasemann, F. (1993) Dynamics of a single model neuron. Int. J. Bif. and Chaos 3: 271-278.
25. Pasemann, F. (1995a) Characteristics of periodic attractors in neural ring networks. Neural Networks 8: 421-429.
26. Pasemann, F. (1995b) Neuromodules: A dynamical systems approach to brain modeling. In: Herrmann, H. J.; Wolf, D. E.; Pöppel, E. (eds.) Supercomputing in Brain Research: From Tomography to Neural Networks. World Scientific, Singapore, pp. 331-348.
27. Pasemann, F. (1996) Repräsentation ohne Repräsentation - Überlegungen zu einer Neurodynamik modularer kognitiver Systeme. In: Rusch, G.; Schmidt, S. J.; Breidbach, O. (eds.) Interne Repräsentationen - Neue Konzepte der Hirnforschung. Suhrkamp Verlag, Frankfurt.
28. Pasemann, F. (1997), A simple chaotic neuron, Physica D 104: 205-211.
29. Port, R. F.; van Gelder, T. (eds.) (1995) Mind as Motion - Explorations in the Dynamics of Cognition, MIT Press, Cambridge.
30. Singer, W. (1994) Time as coding space in neocortical processing. In: Buzsáki, G.; Llinás, R.; Singer, W.; Berthoz, A.; Christen, Y. (eds.) Temporal Coding in the Brain. Springer, Berlin, pp. 51-80.
31. von Foerster, H. (1969) What is memory that it may have hindsight and foresight as well? In: Bogoch, S. (ed.) The Future of the Brain Sciences. Plenum Press, New York; in german: Was ist Gedächtnis - daß es Rückschau und Vorschau ermöglicht?. In: Schmidt, S. J. (ed.) Heinz von Foerster: Wissen und Gewissen. Versuch einer Brücke, Suhrkamp, Frankfurt.
32. Wennekers, T.; Pasemann, F. (1996) Synchronous chaos in high-dimensional modular neural networks. International Journal of Bifurcation and Chaos 6: 2055-2067.