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On the 'Dynamic Brain' Metaphor

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Brain and Mind

Abstract

Dynamic systems theory offers conceptual andmathematical tools for describing the performance ofneural systems at very different levels oforganization. Three aspects of the dynamic paradigmare discussed, namely neural rhythms, neural andmental development, and macroscopic brain theories andmodels.

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References

  • Amari, S., 1974: A method of statistical neurodynamics, Kybernetik 14, 201–225.

    PubMed  Google Scholar 

  • Aradi, I., Barna, G., Érdi, P., Gröbler, T., 1995: Chaos and learning in the olfactory bulb, Int. J. Intel. Syst. 10, 89–117.

    Google Scholar 

  • Arbib, M. A., 1989: The Metaphorical Brain 2: Neural Networks and Beyond, Wiley-Interscience, New York.

    Google Scholar 

  • Arbib, M. A., Bischoff, A., Fagg, A. H. and Grafton, S. T., 1995: Synthetic PET: Analyzing largescale properties of neural networks, Human Brain Mapping 2, 225–233.

    Google Scholar 

  • Arbib, M. and Êrdi, P., 2000: Structure, function and dynamics: An integrated approach to neural organization, Behav. Brain Sci. (in press).

  • Arbib, M., Érdi, P. and Szentágotai, J., 1997: Neural Organization: Structure, Function and Dynamics, MIT Press, Cambridge, MA.

    Google Scholar 

  • Arbib, M. A., Fagg, A. H. and Grafton, S. T. (in press): Synthetic PET imaging for grasping: From primate neurophysiology to human behavior.

  • Babloyantz, A. and Destexhe, A., 1986: Low-dimensional chaos in an instance of epilepsy, Proc. Natl. Acad. Sci. USA 83, 3513–3517.

    PubMed  Google Scholar 

  • Barna, G. and Érdi, P., 1986: Pattern formation in neural systems II. Noise-induced selective mechanisms for the ontogenetic formation of ocular dominance columns, in R. Trappl (ed.), Cybernetics and Systems' 86, D. Reidel, pp. 343–350.

  • Barna, G., Gröbler, T. and Érdi, P., 1998: Statistical model of the hippocampal CA3 region, II. The population framework: model of rhythmic activity in the CA3 slice, Biol. Cybernetics 79, 309–321.

    Google Scholar 

  • Barto, A. G., 1995: Reinforcement learning, in The Handbook of Brain Theory and Neural Networks, MIT Press, Cambridge, MA, pp. 804–809.

    Google Scholar 

  • Bazsó, F., Kepecs, Á., Lengyel, M., Payrits, Sz., Szalisznyó, K., Zalányi, L., and Érdi, P., 1999: Single cell and population activities in cortical-like systems, Reviews in the Neurosciences 10, 201–212.

    PubMed  Google Scholar 

  • Bazsó, F., Szalisznyó, K., Payrits, Sz. and Érdi, P., 1999: A statistical approach to neural population dynamics: Theory, algorithms, simulations, Neurocomputing 26–27, 329–334.

    Google Scholar 

  • Bloedel, J. R., Ebner, T. J. and Wise, S. P. (eds), 1996: The Acquisition of Motor Behavior in Vertebrates, MIT Press, Cambridge, MA.

    Google Scholar 

  • Bower, J. M. and Beeman, D., 1994: The Book of GENESIS. Exploring Realistic Neural Models with the GEneral NEural Simulation System, TELOS, Springer-Verlag, New York.

    Google Scholar 

  • Bragin, A., Engel, J. Jr., Wilson, C. L., Fried, I. and Buzsaki, G. 1999: High-frequency oscillations in human brain, Hippocampus 9(2), 137–142.

    PubMed  Google Scholar 

  • Bremer, F., 1938: Effets de la déafferentation compléte d'une région de lcore cérébrale sur son activité électrique spontaneé, C.R. Soc. Biol. (Paris) 127, 355–359.

    Google Scholar 

  • Buzsáki, G., 1986: Hippocampal sharp waves: Their origin and significance, Brain Res. 398, 242–252.

    Article  PubMed  Google Scholar 

  • Buzsáki, G., 1991: The thalamic clock: Emergent properties, Neuroscience 2(3), 351–364.

    Google Scholar 

  • Buzsáki, G., 1996: The hippocampo-neocortical dialogue, Cerebral Cortex 6, 81–92.

    PubMed  Google Scholar 

  • Buzsáki, G., Bragin, A., Chrobak, J. J., Nádasdy, Z., Síik, A., Hsu, M. and Ylinen, A., 1994: Oscillatory and intermittent synchrony in the hippocampus: relevance to memory trace formation, in G. Buzsáki, R. Llinás, W. Singer, A. Berthoz and Y. Chrisen (eds), Temporal Coding in the Brain, Springer-Verlag, Berlin, pp. 145–172.

    Google Scholar 

  • Buzsáki, G. and Traub, R. D., 1997: Physiological basis of EEG activity, in J. Engel and T. A. Pedley (eds), Epilepsy: A Comprehensive Textbook, Lippincott-Raven Publ., Philadelphia, pp. 819–830.

    Google Scholar 

  • Changeux, J. P., 1985: Neuronal Man, Oxford University Press, New York.

    Google Scholar 

  • Changeux, J. P., 1997: Letter to the editors, Trends in Neurosci. 20, 291–293.

    Google Scholar 

  • Changeux, J. P., Courrege, O. and Danchin, A., 1973: A theory of epigenesis of neuronal networks by selective stabilization of synapses, Proc. Natl. Acad. Sci. USA 70, 2974–2978.

    PubMed  Google Scholar 

  • Changeux, J. P. and Danchin, A., 1976: Selective stabilization of developing synapses as a mechanism for the specification of neuronal networks, Nature 264, 705–712.

    PubMed  Google Scholar 

  • Churchland, P. S. and Sejnowski, T. J., 1992: The Computational Brain,MIT Press, Cambridge, MA.

    Google Scholar 

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

    Google Scholar 

  • Collins, J. J. and Stewart, I., 1993b: Hexapodal gaits and coupled nonlinear oscillator models, Biol. Cybernetics 68, 287–298.

    Google Scholar 

  • Collins, J. J. and Stewart, I., 1994: A group-theoretic approach to rings of coupled biological oscillators, Biol. Cybernetics 71, 95–103.

    Google Scholar 

  • Crick, F. and Koch, C., 1990: Towards a neurobiological theory of consciousness, Seminars Neurosci. 2, 263–275.

    Google Scholar 

  • Dean J. and Cruse, H., 1995: Motor pattern generation, in The Handbook of Brain Thory and Neural Networks, MIT Press, Cambridge, MA, pp. 600–605.

    Google Scholar 

  • Decety, J., 1999: The perception of actions: Its putative effect on neural plasticity, in J. Grafman and Y. Christen (eds), Neuoronal Plasticity: Building a Bridge from the Laboratory to the Clinic, Springer, Berlin, pp. 109–130.

    Google Scholar 

  • Destexhe, A., Contreras, D., Sejnowski, T. J. and Steriade, M., 1994: A model of spindle rhythmicity in the isolated thalamic reticular nucleus, J. Neurophysiol. 72, 803–818.

    PubMed  Google Scholar 

  • Drabkin, G. M. and Sbitnev, V. I., 1975: Propagation of spikes in statistical neuron ensembles. I. Concept of phase transitions, Biofizika 20(4), 699–702

    PubMed  Google Scholar 

  • Eckhorn, R., Bauer, R., Jordan, W., Brosch, M., Kruse, W., Munk, M., Reitboek, H. J., 1988: Coherent oscillations: a mechanism of feature linking in the visual cortex? Biol. Cybern. 60, 121–130.

    PubMed  Google Scholar 

  • Edelman, G. M., 1978: Group selection and phasic reentrant signalling: A theory of higher brain function, in G. M. Edelman and V. B. Mountcastle (eds), The Mindful Brain: Cortical Organization and the Group-Selective Theory of Higher Brain Function, MIT Press, Cambridge MA, pp. 55–100.

    Google Scholar 

  • Elman, J. L., Bates, E. A., Johnson, M. H., Karmiloff-Smith, A., Parisi, D. and Plunkett, K., 1996: Rethinking Innateness. A Connectionist Perspective on Development, MIT Press, Cambridge, MA.

    Google Scholar 

  • Érdi, P., 1983: Hierarchical thermodynamic approach to the brain, Int. J. Neurosci. 20, 193–216

    PubMed  Google Scholar 

  • Érdi P., 1993: Neurodynamic system theory, Theoretical Medicine 14, 137–152.

    PubMed  Google Scholar 

  • Érdi, P., 1996a: The brain as a hermeneutic device, Bio Systems 38, 179–189.

    PubMed  Google Scholar 

  • Érdi P., 1996b: The complexity of the brain: Structure, function, dynamics, in R. Moreno-Diaz and J. Mira-Mira (eds), Brain Processes, Theories and Models, MIT Press, Cambridge, MA, pp. 88–97.

    Google Scholar 

  • Érdi P., 1996c: Levels, models, and brain activities: neurodynamics is pluralistic, Behavioral and Brain Sciences 19, 296–297.

    Google Scholar 

  • Érdi P, 1999: Neural and mental development: Selectionsim, constructivism, hermeneutics, in C. Taddei-Ferrati (ed.), Neuronal Bases and Pscychological Aspects of Consciousness, World Scientific, pp. 507–518.

  • Érdi, P. and Barna, G., 1984: Self-organizing mechanism for the formation of ordered neural mappings, Biol. Cybernetics 51, 93–101.

    Google Scholar 

  • Érdi, P. and Barna, G., 1985: Self-organization of neural networks: Noise-induced transition, Phys. Lett. 107A, 287–290.

    Google Scholar 

  • Érdi, P. and Barna, G. 1991: 'Neural' model for the formation of the ocularity domains, in Kohonen et al. (eds), Artificial Neural Networks, Vol. 1, North-Holland, pp. 513–518.

  • Érdi, P., Aradi, I. and Gröbler, T., 1997: Rhythmogenesis in single cells and population models: Olfactory bulb and hippocampus, BioSystems 40, 45–53.

    PubMed  Google Scholar 

  • Érdi, P., Gröbler, T. and Tóth, J., 1992: On the classification of some classification problems, in Int. Symp. on Information Physics, Kyushu Inst. Technol., Iizuka, pp. 110–117.

    Google Scholar 

  • Fodor, J. A., 1983: TheModularity of Mind. An Essay on Faculty Psychology,MIT Press, Cambridge, MA.

    Google Scholar 

  • Freeman, W. J., 1978: Spatial properties of an EEG event in the olfactory bulb and cortex, Elect. Clin. Neurophys. 44, 585–605.

    Google Scholar 

  • Freeman, W. J., 1995: Societies of Brains: A study in the Neuroscience of Love and Hate, Erlbaum.

  • Freeman, W. J. and Kozma, R., 2000: Local-global interactions and the role of mesoscopic (intermediate-range) elements in brain dynamics, Behav. Brain Sci.(in press).

  • Freeman, W. J. and Skarda, C. A., 1985: Spatial EEG patterns, nonlinear dynamics and perception. The neo-Sherringtonian view, Brain Res. Rev. 10, 47–175.

    Google Scholar 

  • Friston, K. J., 1994: Functional and effective connectivity in neuroimaging: A synthesis, Human Brain Mapping 2, 56–78.

    Google Scholar 

  • van Gelder, T., 1998. The dynamical hypothesis in cognitive science, Behav. Brain Sci. 21, 40–47.

    Google Scholar 

  • Gerstner, W., 1999: Spiking neurons, in W. Maas and C. M. Bishop (eds), Pulsed Neural Networks, MIT Press, Cambridge, MA.

    Google Scholar 

  • Gevins, A., 1994: Dynamic cognitive networks in the human brain, in G. Buzsáki, R. Llinás, W. Singer, A. Berthoz and Y. Chrisen (eds), Temporal Coding in the Brain, Springer-Verlag, Berlin, pp. 273–290.

    Google Scholar 

  • Gould, S. J., 1977: Ontogeny and Phylogeny, Harvard Univ. Press, Cambridge MA.

    Google Scholar 

  • Grafman J. and Christen Y. (eds), 1999: Neuronal Plasticity: Building a Bridge from the Laboratory to the Clinic, Springer, Berlin.

    Google Scholar 

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

    Article  PubMed  Google Scholar 

  • Gray, C. M. and McCormick, D. A., 1996: Chattering cells: Superficial pyramidal neurons contributing to the generation of synchronous oscillations in the visual cortex, Science 274, 109–113.

    Article  PubMed  Google Scholar 

  • Greenough, W. T., Cohen, N. J. and Juraska, J.M., 1999: New neurons in old brains: Learning to survive? Nature Neuroscience 2, 203–205.

    PubMed  Google Scholar 

  • Gröbler, T., Barna, G. and Érdi, P., 1998: Statistical model of the hippocampal CA3 region, I. The single cell module: Bursting model of the pyramidal cell, Biol. Cybernetics 79, 301–308.

    Google Scholar 

  • Haken, H., 1977: Introduction to Synergetics. Nonequilibrium Phase Transitions and Self-Organization in Physics, Chemistry and Biology, Springer Verlag, Berlin.

    Google Scholar 

  • Hines, M., 1984: Efficient computation of branched nerve equations, J. Bio-Med. Comp. 15, 69–74.

    Google Scholar 

  • Hines, M., 1993: NEURON-A program for simulation of nerve equations, in F. Eeckman (ed.), Neural Systems: Analysis and Modeling, Kluwer Academic Publishers, Norwell, MA, pp. 127–136.

    Google Scholar 

  • Hinton, G., 1989: Connectionist learning procedures, Artificial Intelligence 40, 185–234.

    Article  Google Scholar 

  • Hodgkin, A. L. and Huxley, A. F., 1952: A quantitative description of membrane current and its application to conduction and excitation in nerve, J. Physiol. London 117, 500–544.

    PubMed  Google Scholar 

  • Horsthemke,W. and Lefever, R., 1984: Noise-induced Transition. Theory and Application in Physics, Chemistry and Biology, Springer, Berlin.

    Google Scholar 

  • Horwitz, B., Tagamets, M.-A. and McIntosh, R., 1999: Neural modeling, functional brain imaging, and cognition, Trends Cognit. Sci. 3, 91–98.

    Google Scholar 

  • Joliot, M., Ribary, U. and Llinás, R., 1994: Human oscillatory brain activity near 40 Hz coexists with cognitive temporal binding, Proc. Natl. Acad. Sci. USA 91(24), 11748–11751.

    PubMed  Google Scholar 

  • Karmiloff-Smith, A., 1992: Beyond Modularity: A Developmental Perspective on Cognitive Science, MIT Press, Cambridge, MA.

    Google Scholar 

  • Katchalsky, A. K., Rowland, V. and Blumenthal, R., 1974: Dynamic patterns of brain cell assemblies, NRP Bull. 12(1).

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

    Google Scholar 

  • Kolb, B., 1999: Towards an ecology of cortical organization, in J. Grafman and Y. Christen (eds), Neuronal Plasticity: Building a Bridge from the Laboratory to the Clinic, Springer, Berlin, pp. 17–34.

    Google Scholar 

  • Leung, L. S. and Yu, H. W., 1998: Theta-frequency resonance in hippocampal CA1 neurons in vitro demonstrated by sinusoidal current injection, J. Neurophysiol. 79, 1592–1596.

    PubMed  Google Scholar 

  • Liley, D. T., Alexander, D. M., Wright, J. J. and Aldous, M. D., 1999: Alpha rhythm emerges from large-scale networks of realistically coupled multicompartmental model cortical neurons, Network 10: 79–92.

    PubMed  Google Scholar 

  • Llinás, R., Ribary, U., Joliot, M. and Wang, X.-J., 1994: Content and context in temporal thalamocortical binding, in G. Buzsáki, R. Llinás, W. Singer, A. Berthoz and Y. Christen (eds), Temporal Coding in the Brain, Springer-Verlag, Berlin, pp. 251–272.

    Google Scholar 

  • Lopes da Silva, F. H., Pijn, J. P. and Wadman, W. J., 1994: Dynamics of local neuronal networks: Control parameters and state bifurcations in epileptogenesis, Prog. Brain Res. 102, 359–370.

    PubMed  Google Scholar 

  • Lytton, W. W., Hellman, K. M. and Sutula, T. P., 1998: Computer models of hippocampal circuit changes of the kindling model of epilepsy, Artif. Intell. Med. 13(1–2), 81–97.

    PubMed  Google Scholar 

  • Meyer-Lindenberg, A., Ziemann, U., Hajak, Cohen L, and Berman, K., 1999: A direct demonstration of nonlinear dynamics in the human brain using PET and transcranial magnetic stimulation (TMS), in Fifth International Conference on Functional Mapping of the Human Brain, Poster 287: http://www.apnet.com/hbm99/methphyscog.htm

  • Mitchell, M., Crutchfield, J. P. and Hraber, P. T., 1994: Dynamics, computation, and the "edge of chaos": A re-examination, in G. Cowan, D. Pines and D. Melzner (eds), Complexity: Metaphors, Models, and Reality. Santa Fe Institute Studies in the Sciences of Complexity, Proceedings Volume 19, Addison-Wesley, Reading, MA.

    Google Scholar 

  • Nicolis, G. and Prigogine, I., 1977: Self-Organization in Nonequilibrium Systems, J.Wiley and Sons, New York.

    Google Scholar 

  • Nunez, P. L., 1995: Neocortical Dynamics and Human EEG Rhythms, Oxford University Press, Oxford.

    Google Scholar 

  • O'Keefe, J. and Recce, M., 1993: Phase relationship between hippocampal place units and the EEG theta rhythm, Hippocampus 3, 317–330.

    PubMed  Google Scholar 

  • van Ooyen, A., 1994: Activity-dependent neural network development, Network: Computation in Neural Systems 5, 401–423.

    Google Scholar 

  • van Ooyen, A., van Pelt, J. and Corner, M. A., 1995: Implications of activity-dependent neurite outgrowth for neuronal morphology and network development, J. Theor. Biol. 17(2), 63–82.

    Google Scholar 

  • Palus, M., 1999: Nonlinear dynamics in the EEG analysis: Disappointments and perspectives, in P. E. Rapp, N. Pradhan and R. Sreenivasan (eds), Nonlinear Dynamics and Brain Functioning, Nova Science Publishers.

  • Paton, R., 1992: Towards a metaphorical biology, Biology and Philosophy 7, 279–294.

    Google Scholar 

  • Piaget, J., 1975: L'Equilibration des Structures Cognitives. Probléme Central du Développement, Presses Universitaires de France, Paris.

    Google Scholar 

  • Purves, D., White, L. E. and Riddle, D. R., 1996: Is neural development Darwinian? Trends in Neurosci. 19(11), 460–464.

    Google Scholar 

  • Purves, D., White, L. and Riddle, D., 1997: Reply, Trends in Neurosci. 20, 293.

    Google Scholar 

  • Quartz, S. R. and Sejnowski, T. J., 1997: The neural basis of cognitive development: A constructivist manifesto, Behav. Brain Sci. 20(4), 537–596.

    PubMed  Google Scholar 

  • Rall, W., 1962: Electrophysiology of a dendritic neuron model, Biophys. J. 2, 145–167.

    PubMed  Google Scholar 

  • Rall, W., 1977: Core conductor theory ad cable properties of neurons in E. R. Kandel, J. M. Brookhardt and V. B. Mountcastle (eds), Handbook of Physiology: The Nervous System,William and Wilkins, Baltimore, pp. 39–98.

    Google Scholar 

  • Rosenblueth, A., Wiener, N. and Bigelow, J., 1943: Behavior, purpose and teleology, Philos. Sci. 10, 18–24.

    Google Scholar 

  • Ribary, U., Ioannides, A. A., Singh, K. D., Hasson, R., Bolton, J. P., Lado, F., Mogilner, A. and Llinás, R., 1991: Magnetic field tomography of coherent thalamocortical 40-Hz oscillations in humans. Proc. Natl. Acad. Sci. USA 88(24), 1037–1041.

    Google Scholar 

  • Schaal, 1999: Is imitation learning the route to humanoid robots? Trends Cognit. Sci. 3, 233–242.

    Google Scholar 

  • Selverston, A. I. and Moulins, M., 1987: The Crustacean Stomatogastric System, Springer-Verlag, Berlin.

    Google Scholar 

  • Shatz, C. J., 1996: Emergence of order in visual system development, Proc. Natl. Acad. Sci. USA 23, 602–608.

    Google Scholar 

  • Schiff, S. J., Jerger, K., Duong, D. H., Chang, T., Spano, M. L., and Ditto, W. L., 1994: Controlling chaos in the brain, Nature 370(6491): 615–620.

    PubMed  Google Scholar 

  • Siegelman, H. T. and Fishman, S., 1998: Analog vomputation with dynamic systems, Physica 120D, 214–235.

    Google Scholar 

  • Singer, W., 1998: Consciousness and the structure of neuronal representation, Philos. Trans. R. Soc. London B. Biol. Sci. 353(1377), 1829–1840.

    PubMed  Google Scholar 

  • Skarda, C. A. and Freeman, W. J. 1987: How brains make chaos in order to make sense of the world, Behav. Brain Sci. 10, 161–195.

    Google Scholar 

  • Sperry, R. W., 1969: A modified concept of consiousness, Psychol. Rev. 76, 532–536.

    PubMed  Google Scholar 

  • Sperry, R. W., 1980: Mind-brain interaction: mentalism yes, dualism no, Neuroscience 5,195–206.

    PubMed  Google Scholar 

  • Sporns, O., 1997: Variation and selection in neural function, Trends Neurosci. 20, 291.

    Google Scholar 

  • Sporns, O. and Tononi, G., 1994: Selectionism and the brain, Int. Rev. Neurobiol., Vol. 37, Academic Press, San Diego.

    Google Scholar 

  • Steriade, M., McCormick, D. A. and Sejnowski, T. J., 1993: Thalamocortical oscillations in the sleeping and aroused brain, Science 262, 679–685.

    PubMed  Google Scholar 

  • Szentágothai, J., 1984: Downward causation?, Ann. Rev. Neurosci. 7, 1–11.

    PubMed  Google Scholar 

  • Szentágothai, J., 1993: Self organization: The basic principle of neural functions, Theoretical Med. 14, 101–116.

    Google Scholar 

  • Szentágothai, J. and Érdi, P., 1983: Outline of a general brain theory, Central Research Institute for Physics of the Hung. Acad. Sci. Report.

  • Szentágothai, J. and Érdi, P., 1989: Self-organization in the nervous system, J. Soc. Biol. Struct. 12, 367–384.

    Google Scholar 

  • Thom, R., 1975: Structural Stability and Morphogenesis, W.A. Benjamin, Reading. MA.

    Google Scholar 

  • Traub, R. D., Jeffreys, G. R. and Whittington, M. A., 1999: Fast Oscillations in Cortical Circuits, MIT Press, Cambridge, MA.

    Google Scholar 

  • Traub, R. D. and Miles, R., 1991: Neuronal Networks of the Hippocampus, Cambridge Univ. Press, Cambridge.

    Google Scholar 

  • Truesdell, C., 1989: Rational Thermodynamics, Springer, Berlin.

    Google Scholar 

  • Tsuda, I., 1996: A new type of self-organization associated with chaotic dynamics in neural networks, Int. J. Neural Systems 7, 451–459.

    Google Scholar 

  • Ventriglia, F., 1974: Kinetic approach to neural systems: I, Bull. Math. Biol. 36, 534–544.

    Google Scholar 

  • Ventriglia, F., 1994: Toward a kinetic theory of cortical-like neural fields, in F. Ventriglia (ed.), Neural Modeling and Neural Networks, Pergamon Press, Oxford, pp. 217–249.

    Google Scholar 

  • Ventriglia, F., 1998: Simulation of CA3 region of hippocampus by kinetic models, Biosystems 48, 247–254.

    PubMed  Google Scholar 

  • Wang, X. J. and Buzsáki, G. Y., 1996: Gamma oscillation by synaptic inhibition in a hippocampal interneuronal network model. J. Neurosci. 16, 6402–6413.

    PubMed  Google Scholar 

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

    PubMed  Google Scholar 

  • Wilson, M. and Bower, J. M., 1989: The simulation of large-scale neural networks, in C. Koch and I. Segev (eds), Methods in Neural Modeling: From Synapses to Networks, MIT Press, Cambridge, MA, pp. 291–334.

    Google Scholar 

  • Whittington, M. A., Traub, R. B. and Jefferys, J., 1995: Synchronized oscillations in interneuron networks driven by metabotropic glutamate receptor activation, Nature 370, 612–615.

    Google Scholar 

  • Wright, J. J. and Liley, D. T. J. 1996: Dynamics of the brain at global and microscopic scales: Neural networks and the EEG, Behav. Brain Sci. 19, 285–320.

    Google Scholar 

  • Ylinen, A., Bragin, A., Nadasdy, Z., Jando, G., Szabo, I., Sík, A. and Buzsáki, G., 1995: Sharp wave-associated high-frequency oscillation (200 Hz) in the intact hippocampus: Network and intracellular mechanisms, J. Neuroscience 15, 30–46.

    Google Scholar 

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Érdi, P. On the 'Dynamic Brain' Metaphor. Brain and Mind 1, 119–145 (2000). https://doi.org/10.1023/A:1010076304410

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