본문 바로가기
KERD
논문KCI 등재

The Neuro-Symbolic Code of Perception

0

조회

0

다운로드

0

인용

0

참고문헌

키워드

초록

Perceptual research has so far been tackled on two different levels: the neural and the cognitive (symbolic) level. These two levels have so far mainly been investigated separately from each other and little is known about their correlations. Here, we present a coding scheme (neuro-symbolic coding) and a cognitive architecture (a neuro-symbolic network), which make it possible to unify these two levels. Based on this, hypotheses are presented for how the activation of millions of sensory receptors results in a unified, complex, multimodal perception,what the function of feedbacks in perception is, what influence focus of attention and knowledge have, and how binding is solved in perception. Furthermore, a hypothesis for the mechanisms involved in perceptual learning is proposed.

Abstract

Perceptual research has so far been tackled on two different levels: the neural and the cognitive (symbolic) level. These two levels have so far mainly been investigated separately from each other and little is known about their correlations. Here, we present a coding scheme (neuro-symbolic coding) and a cognitive architecture (a neuro-symbolic network), which make it possible to unify these two levels. Based on this, hypotheses are presented for how the activation of millions of sensory receptors results in a unified, complex, multimodal perception,what the function of feedbacks in perception is, what influence focus of attention and knowledge have, and how binding is solved in perception. Furthermore, a hypothesis for the mechanisms involved in perceptual learning is proposed.

참고문헌 (43)

  1. Barlow, H.B., "Single Units and Sensation: A Neuron Doctrine for Perceptual Psychology", Perception, 1, pp.371~394 (1972)
  2. Burgstaller, W., "Interpretation of Situations in Buildings", 박사, pp.2007
  3. Chun, M.M., "Visual Attention, Blackwell’s Handbook of Perception", pp.272~310 (2001), Blackwell
  4. Dietrich, D., "Simulating the Mind. in: A Technical Neuropsychoanalytical Approach" (2008), Springer Verlag
  5. Engel, A. K., "Dynamic Predictions: Oscillations and Synchrony in Top-Down Processing", Nature Reviews Neuroscience, 2 (2001)
  6. Ernst, M.O., "Merging the Senses into a Robust Percept", TRENDS in Cognitive Sciences, 8(4), pp.162~169 (2004)
  7. , (2009), , 2009
  8. Goetzinger, S.O., "Scenario Recognition based on a Bionic Model for Multi-Level Symbolization", 석사, pp.2006
  9. Goldstein, E.B., "Wahrnehmungspsychologie" (2002), Spektrum Akademischer Verlag
  10. Golledge, H.D.R., "Information Processing: A Solution to the Binding Problem?", Current Biology, 6(9), pp.1092~1095 (1996)
  11. Hebb, D.O., "The oranization of behavior: A neuropsychological theory" (2002), Lawrence Erlbaum
  12. Hebb, D.O., "The Mammal and his Environment", Am. J. Psychiatry, 111(11), pp.826~831 (1955)
  13. Hommel, B., "When an Object is more than a Binding of its Features: Evidence for Two Mechanisms of Visual Feature Integration", Visual Cognition, 17, pp.120~140 (2009)
  14. Hubel, D.H., "Brain, and Vision" (1988), W H Freeman and Co
  15. Hubel, D.H., "Receptive Fields, Binocular Interaction and Functional Architecture in the Cats Visual Cortex", J. Physiol., 160, pp.106~154 (1962)
  16. Husserl, E., "The Phenomenology of Internal Time Consciousness. in: Bloomington" (1964), Indiana University Press
  17. Lang, R., "Scenario Recognition in Modern Building Automation", International Journal of Intelligent Systems and Technologies, 4(1), pp.36~44 (2009)
  18. Luria, A.R., "The Working Brain. in: An Introduction in Neuropsychology" (1973), Basic Books
  19. Pulver, S., "Synaptic activity makes fly neurons shape up", Journal of Experimental Biology, 212 (2009)
  20. Quian Quiroga, R., "Invariant Visual Representation by Single Neurons in the Human Brain", Nature, 435, pp.1102~1107 (2007)
  21. Quian Quiroga, R., "Sparse but not ‘Grandmother-cell’ Coding in the Medial Temporal Lobe", Trends in Cognitive Sciences, 12(3), pp.87~91 (2007)
  22. Seric, L., "Observer network and forest fire detection", Information Fusion (2009)
  23. Shatz, C.J., "The developing brain", Sci. Am, 267, pp.60~67 (1992)
  24. Solms, M., "The Brain and the Inner World An Introduction to the Neuroscience of Subjective Experience" (2002), Other Press New York
  25. Tani, J., "The Dynamical Systems Accounts for Phenomenology of Immanent Time: An Interpretation by Revisiting a Robotics Synthetic Study", Journal of Consciousness Studies, 11(9), pp.5~24 (2004)
  26. Treisman, A.M., "A Feature-Integration Theory of Attention", Cognitive Psychology, 12, pp.97~136 (1980)
  27. Treisman, A., "The Binding Problem", Current Opinion in Neurobiology, 6, pp.171~178 (1996)
  28. Triesch, J., "Binding: A proposed experiment and a model", Proceedings of the ICANN 96, pp.685~690 (1996), Springer Verlag
  29. Velik, R., "A Model for Multimodal Humanlike Perception based on Modular Hierarchical Symbolic Information Processing, Knowledge Integration, and Learning", Proceedings of the 2nd International Conference on Bio-Inspired Models of Network, Information, and Computing Systems (2007)
  30. Velik, R., "Neuro-Symbolic Networks: Introduction to a New Information Processing Principle", Proceedings of the 6th International Conference on Industrial Informatics (2008)
  31. Velik, R., "A Bionic Model for Human-like Machine Perception" (2008), SVH Verlag
  32. Velik, R., "A Bionic Model for Human-like Machine Perception", 박사, pp.2008
  33. Velik, R., "A Bionic Approach to Dynamic, Multimodal Scene Perception and Interpretation in Buildings", International Journal of Intelligent Systems and Technologies, 4(1), pp.1~9 (2009)
  34. Velik, R., "Emulating the Perceptual System of the Brain for the Purpose of Sensor Fusion. in: Human-Computer System Interaction: Backgrounds and Applications", pp.2009, Springer Berlin
  35. Velik, R., "Bionic Approach for High-Efficiency Sensor Data Processing in Building Automation", Proceedings of the 35th Annual Conference of the IEEE Industrial Electronics Society (2009)
  36. Velik, R., "From Neuron-firing to Consciousness — Towards the True Solution of the Binding Problem", Neuroscience and Behavioral Review, 34(7), pp.993~1001 (2010)
  37. Velik, R., "Why Machines Cannot Feel", Minds and Machines, 20(1), pp.1~18 (2010), Springer
  38. Velik, R., "Towards Human-like Machine Perception 2.0", International Review on Computers and Software (IRECOS), Special Section on Advanced Artificial Networks (2010)
  39. Velik, R., "Quo Vadis, Intelligent Machine?", Brain (Broad Research in Artificial Intelligence and Neuroscience), 1(4) (2010)
  40. Velik, R., "Autonomous Perception and Decision Making in Buildings", IEEE Transactions on Industrial Electronics, 57(11) (2010)
  41. Velik, R., "Neuro-symbolic Alerting Rules", IEEE Transactions on Industrial Electronics, 57(11) (2010)
  42. von der Malsburg, C., "The What and Why of Binding: The Modelers Perspective", Neuron, 24, pp.95~104 (1999)
  43. Wolfe, J.M., "The Psychophysical Evidence for a Binding Problem", Neuron, 24, pp.11~17 (1999)

관련 논문AI추천

이 간행물의 다른 논문 (4건)