Computational Methods in Neural Modeling: 7th International by L.M. Ricciardi, G. Esposilo, V. Giorno, C. Valerio (auth.),

By L.M. Ricciardi, G. Esposilo, V. Giorno, C. Valerio (auth.), José Mira, José R. Álvarez (eds.)

The two-volume set LNCS 2686 and LNCS 2687 represent the refereed complaints of the seventh foreign Work-Conference on man made and ordinary Neural Networks, IWANN 2003, held in Ma?, Menorca, Spain in June 2003.

The 197 revised papers awarded have been rigorously reviewed and chosen for inclusion within the booklet and handle the subsequent issues: mathematical and computational tools in neural modelling, neurophysiological information research and modelling, structural and sensible versions of neurons, studying and different plasticity phenomena, advanced platforms dynamics, cognitive strategies and synthetic intelligence, methodologies for internet layout, bio-inspired structures and engineering, and functions in a vast number of fields.

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Additional info for Computational Methods in Neural Modeling: 7th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2003 Maó, Menorca, Spain, June 3–6, 2003 Proceedings, Part I

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2. M. A. Whittington, R. D. Traub, J. G. R. Jefferys, “Synchronised oscillations in interneuron networks driven by metabotropic glutamate receptor activation”, Nature, vol. 373, pp. 612-615,1995. 3. X. J. Wang, J. , vol. 4, pp. 84-97, 1992. 4. X. Wang and G. Buzsaki, “Gamma oscillations by synaptic inhibition in an interneuronal network model”, J. , vol. 16, 6402-6413, 1996. 5. C. van Vreeswijk, L. F. Abbott, B. Ermentrout, “When inhibition not excitation synchronizes neural firing”, J. Comput.

Cybernetics and Systems, An International Journal, 18: (1987) 319-349 8. : Neural Modeling in Cerebral Dynamics. Mathematical Biosciences. Special number ecl. by L. Ricciarcli, 2003 (pencl. ) 9. : Neurosymbolic Integration: The Knowledge Level Approach. R. Moreno-Diaz et al ( 4 s ) Cast and Tools for Complexity in Biological, Physical and Engineering Systems. Extended Abstracts of EUROCAST (2003) 10. , Prieto, A. ): Connectionist Models of Neurons, Learning Processes, and Artiiicia1 Intelligence.

Besides, both experimental and theoretical evidences relate the synchronous discharge of a population of inhibitory interneurons to some features of their coupling, like the duration and intensity of the synaptic current [2-7]. Recently two classes of neocortical inhibitory interneurons – Fast Spiking (FS) and Low Threshold Spiking cells (LTS) – were found to interact by electrical synapses too [8, 9]. FS cells exhibit a higher level of inhibitory connections, among them, while a lower level is found for the LTS group.

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