On how the computational paradigm can help us to model and interpret the neural function

Natural Computing

Volumn 6, Issue 3, 2007, Pages 211-240

  Mira, J Mira ^a   Delgado Garcia A E ^a  

^a UNIVERSIDAD NACIONAL DE EDUCACIÓN A DISTANCIA   (Spain)

Author keywords

Abstraction processes; Causality levels; Computational paradigm; External observer; Nested organizations; Symbolsin neurophysiology

Indexed keywords

ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; BRAIN FUNCTION; COGNITION; CONCEPTUAL FRAMEWORK; CONFERENCE PAPER; HUMAN; INFORMATION PROCESSING; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; NEUROPHYSIOLOGY; NEUROSCIENCE; NONHUMAN; OBSERVER VARIATION; QUALITATIVE ANALYSIS; SEMANTICS; SENSORIMOTOR FUNCTION; THEORETICAL STUDY;

EID: 34547652474     PISSN: 15677818     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11047-006-9008-6     Document Type: Conference Paper

References (49)

1. Brooks R (1991) Intelligence Without Reason. A.i. memo, MIT
2. Cariani P (2001) Symbols and dynamics in the brain. Biosystems, p. 60
3. Chalmers D (1993) A Computations Foundation for the Study of Cognition. http://www.ling.ucsc.edu/chalmers/papers/computation.html
4. Clancey W (1997) Situated Cognition. On Human Knowledge and Computer Representation. Univ. Press, Cambridge
5. Clancey W. (1999) Conceptual Coordination. Lawrence Erlbaum Associates, pub. mahwah edition, New Jersey
6. Craik K (1943) The Nature of Explanation. Cambridge University Press, Cambridge
7. Dayan P and Abbott L (2001) Theoretical Neuroscience. The MIT Press, Cambridge, MA
8. Dreyfus H. (1994) What Computers Still Can't do. The MIT Press, Cambridge, MA
9. Edelman G (1987) Neural Darwinism. Basic Books Inc., New York
10. Fodor J (1984) El Lenguaje del Pensamiento. Alianza Editorial, Madrid
11. Gibson J (1979) The Ecological Approach to Visual Perception. Houghton Mifflin, Boston
12. Gould S (1987) An Urchin in the Storm. Norton, NY
13. Grobstein P (1990) Strategies for analyzing complex organization in the nervous system. I. Lesion experiments. In: Schwartz E (eds) Computational Neuroscience, pp. 19-35. MIT Press, Cambridge, MA
14. Johnson-Laird P (1988) How could consciousness arise from computations of the brain. In: Blakemore C and Greenfiels S (eds) Mindwaves, pp. 247-257. Basil Blackwell
15. Kandel E, Schwartz J and Jessell T (1991) Principles of Neural Science. Prentice Hall
16. Kleene S (1956) Representation of events in nerve nets and finite automata. In: Shannon and McCarty J (eds) Automata Studies, pp. 3-42. Princeton Univ. Press, Princenton, NJ
17. Kuhn T (1971) La Estructura de las Revoluciones Científicas. Fondo de Cultura Económica Fondo de Cultura Económica, México
18. Lashley K (1950) In Search of the Engram, Society of Experimental Biology Symposium nž Vol. 4. Physiological Mechanisms in Animal Behaviour, pp. 454-480. University Press, Cambridge MA
19. Lettvin J, Maturana H, McCulloch W and Pitts W (1959) What the frog's eye tells the frog's brain. Proceedings of the IRE 47(11): 1940-1951
20. Luria A (1974) Cerebro y Lenguaje. Ed. Fontanella, Barcelona
21. Marr D (1982) Vision. Freeman, New York
22. Maturana H. (1975) The organization of the living: A theory of the living organization. International Journal of Man-Machine Studies 7: 313-332
23. Maturana H (2002) Ontology of observing. The biological foundations of self consciousness and the physical domain existence. http://www.inteco.cl/biology/ontology/.
24. Maturana H and Varela F (1990) El Árbol del Conocimiento Humano. Ed. Debate, Madrid
25. McCulloch W (1965) Embodiments of Mind. The MIT Press, Cambridge, MA
26. McCulloch W, Pitts W (1943) A logical calculus of the ideas immanent in nervous activity. Bulletin of Mathematical Biophysics 5: 115-133
27. Mira J (1995) Reverse neurophysiology: The embodiments of mind revisited. In: Moreno-Díaz R and Mira-Mira J (eds) Brain Processes, Theories and Models. The MIT Press, MA
28. Mira J (1998) Operaciones 'inteligentes' en Sistemas Artificiales: La Perspectiva de la inteligencia Artificial en la Comprensión del Sistema Nervioso. Revista de la Real Academia de Medicina de Catalunya 12(1): 87-107
29. Mira J and Delgado A (1987) Some comments on the antropocentric viewpoint in the neurocybernetic methodology. In: Proc of the Seventh International Congress of Cybernetics and Systems, pp. 891-895
30. Mira J and Delgado A (2003a) Neural modeling in cerebral dynamics. BioSystems 71: 133-144
31. Mira J and Delgado A (2003b) Where is knowledge in robotics? Some methodological Issues on symbolic and connectionist perspectives of AI. In: Zhou C, Maravall D and Rua D (eds) Autonomous Robotic Systems, pp. 3-34. Physical-Verlag Springer, Berlin
32. Mira J and Delgado A (2004) From modeling with words to computing with numbers. In: Proceedings ISDA 2004, Budapest, pp. 7-13
33. Mira J, Delgado A, Boticario J, Díez F (1995) Aspectos bÁsicos de la inteligencia artificial. Sanz y Torres, SL, Madrid
34. Montserrat J (1998) La Percepción Visual. Ed Biblioteca Nueva, Madrid
35. Moreno R, Mira J (1996) Logic and neural nets: Variations on themes by W.S. McCulloch. In: Moreno R and Mira J (eds) Brain Processes, Theories and Models, pp. 24-36. The MIT Press, MA
36. Moreno-Diaz R (1971) Deterministic and probabilistic neural nets with loops. Mathematical Biosciences 11: 129-136
37. Newell A (1981) The knowledge level. AI Magazine, 120
38. Newell A and Simon H (1976) Computer science as empirical inquiry: symbols and search. Communications of ACM 19: 113-126
39. Patee H (2001) The physics of symbols: Brining the epistemic cut. Biosystems 60: 5-12
40. Pylyshyn S (1986) Computation and Cognition. Towards a Foundation of Cognitive Science. The MIT Press
41. Schmitt F and Worden F (1979) The Neuroscience Fourth Study Program. The MIT Press, Cambridge, MA
42. Schreiber G, Akkermans H and de Anjo Anjewierden R (1999) Engineering and Managing Knowledge: The CommonKADS Methodology. The MIT Press, Cambridge, MA
43. Searle J (1985) Minds, brains and programs. In: Haugeland J (ed) Mind Design. Philosophy, Psychology, Artificial Intelligence. The MIT Press
44. Searle J (1989) Minds and brains without programs. In: Blakemore C and Greenfield S (eds) Mindwaves. Basil Blackwell
45. Shepherd G (ed) (1990) The Synaptic Organization of the Brain. Oxford Univ. Press
46. Varela F (1979) Principles of Biological Autonomy. The North Holland Series in General Systems Research, New York
47. von Foester H (2003) Understanding Understanding. Springer
48. von Neumann J (1956) Probabilistic logics and the synthesis of reliable organisms from unreliable components. In: Shannon and McCarthy (eds) Automata Studies. Princenton Univ. Press, Princenton, NJ
49. Wiener N (1948) Cybernetics. The Technology Press, John Wiley & Sons, New York