Abstract
We are still a long way from understanding the organization and functioning of the Nervous Systems. At the same time there is a large disparity between the richness and fineness of the nervous phenomenology and the crudeness of the point neuron simplistic models we use in its modeling. This distances neuroscience from computation in an almost irreversible fashion.
To contribute to the posing and partially solving of these problems we present in this paper a summary of our work that has been marked by two recurrent themes: (i) the search for a methodology of the natural, with the introduction of distinct levels and domain of description (ii) the search for inspiration in neuroscience seeking new ideas for a more realistic model of neural computation. The final purpose is to move computation a step closer to neuroscience and vice versa.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
References
Kuhn, T.S. (1970). “The Structure of Scientific Revolutions”. The Univ. of Chicago Press, Chicago.
Marr, D. (1982). “Vision”. Freeman, New York.
Maturana, H.R. (1975).“The Organization of the Living: A theory of the Living Organization”. Int. J. Man-Machine Studies, 7, 313–332.
McCulloch, W.S. (1965). “Embodiments of Mind”. The MIT Press. Cambridge, Mass.
Mira, J. Delgado, A.E. (1986). “On Some Fresh Air in Neural Modelling”. Cybernetics and Systems'86. R. Trappl, ed. 311–318. D. Reidel Pub. Comp. Dordrecht.
Mira, J. and Delgado, A.E., (1987) “Some Comments on the Antropocentric Viewpoint in the Neurocybernetic Methodology”. Proc. of the Seventh International Congress of Cybernetics and Systems, Vol. 2, pp. 891–895. London (1987).
Mira, J. and Delgado, A.E. (1995). “Aspectos Metodológicos en IA”. Aspectos Básicos de la IA. J. Mira et al. (Eds.) 53–84. Sanz y Torres. Madrid.
Mira, J. (1995). “Reverse Neurophysiology: The “Embodiments of Mind” Revisited”. Brain Processes, Theories and Models. R. Moreno-Díaz and J. Mira-Mira (eds.) 37–49. The MIT Press, Mass.
Newell, A., “The Knowledge Level”. AI Magazine, summer (1981) 1–20.
Rakic, P. (1975). “Neuroscience Research Program Bulletin on L.C.N.”, 13, 3, 299–314. Boston.
Rumelhart, D.E., Hinton, G.E., and Williams, R.J. (1986). “Learning Internal Representations by Error Propagation”. Parallel Distributed Processing: Explorations in the Microstucture of Cognition, Rumelhart, D.E., and McClelland, J.L. (Eds.), Vol. 1: Foundations. 318–362, MIT Press, Cambridge, Mass.
Segev, I. (1992). “Single Neurone Models: Oversimple, Complex and Reduced”. Trends in Neurosciences, Vol. 15, No. 11, 414–421.
Shannon, C.E. and McCarthy, J. eds., (1956). Automatas Studies, Princeton University Press, N. Jersey.
Shepher, G.M. (1975). “Neuroscience Research Program Bulletin on L.C.N. “, 13, 3, 344–352. Boston.
Shepherd G.M.(ed). (1990) The Synaptic Organization of the Brain. Oxford Univ. Press.
Varela, F.J. (1979). “Principles of Biological Autonomy”. North-Holland. New York.
Wiener, N. (1947). “Cybernetics”. MIT Press and J. Wiley, New York.
Yovits, M.C. and Cameron, S. (1960). “Self-Organizing Systems”, Pergamon Press, Oxford.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1997 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Mira, J., Delgado, A.E. (1997). Some reflections on the relationships between neuroscience and computation. In: Mira, J., Moreno-Díaz, R., Cabestany, J. (eds) Biological and Artificial Computation: From Neuroscience to Technology. IWANN 1997. Lecture Notes in Computer Science, vol 1240. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0032459
Download citation
DOI: https://doi.org/10.1007/BFb0032459
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-63047-0
Online ISBN: 978-3-540-69074-0
eBook Packages: Springer Book Archive