The Search for Consciousness in the Brain

  • John G. Taylor
Chapter
Part of the Springer Series in Cognitive and Neural Systems book series (SSCNS, volume 9)

Abstract

If consciousness is created by brain activity, either solely or in part, then the traces of the relevant brain activity should be able to be observed by suitably subtle experiments and sensitive enough experimental apparatus. Such is the route that has been followed over the last few decades by increasing numbers of neuroscientists to search for what are called the ‘neural correlates of consciousness (NCC) but, however, with rather uncertain results. The main feature of this uncertainty is, I suspect, due to the lack of clarity as to what precisely is to be discovered. In other words there is the difficulty of what exactly the brain activity represents as part of the upcoming conscious experience of a given subject?

Keywords

Nerve Cell Parietal Lobe Spike Train Object Representation Central Representation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Amari S-I (1977) Dynamics of pattern formation in lateral-inhibition type neural fields. Biol Cybern 27:77–87PubMedCrossRefGoogle Scholar
  2. Awh E, Smith EE, Jonides J (1995) Human rehearsal processes and the frontal lobes: PET evidence. Ann N Y Acad Sci 769:97–117PubMedCrossRefGoogle Scholar
  3. Corbetta M, Shulman GL (2002) Control of goal-directed and stimulus-driven attention in the brain. Nat Rev Neurosci 3:201–215PubMedGoogle Scholar
  4. Crick F (1994) The astonishing hypothesis. Scribner, New YorkGoogle Scholar
  5. Crick F, Koch C (1990) Towards a neurobiological theory of consciousness. Semin Neurosci 2:263–275Google Scholar
  6. Damasio A (2000) The feeling of what happens: body and emotion in the making of consciousness. Mariner Books, New YorkGoogle Scholar
  7. Dehaene S, Naccache L, Le Clec HG et al (1998) Imaging unconscious semantic priming. Nature 395(6702):597–600PubMedCrossRefGoogle Scholar
  8. DeYoe EA, Van Essen DC (1988) Concurrent processing streams in monkey visual cortex. TINS 11(5):219–226PubMedGoogle Scholar
  9. Driver J, Mattingley JB (1998) Parietal neglect and visual awareness. Nat Neurosci 1(1):17–22PubMedGoogle Scholar
  10. Fellenz W, Taylor JG (2000) Establishing retinotopy by lateral-inhibition-type homogeneous neural fields. Neurocomputing 48:313–322CrossRefGoogle Scholar
  11. Fragopanagos N, Kockelkoren S, Taylor JG (2005) A neurodynamic model of the attentional blink. Brain Res Cogn Brain Res 24(3):568–586PubMedCrossRefGoogle Scholar
  12. Giese MA (1998) Dynamic neural field theory for motion perception. Kluwer Academic Publishers, BostonGoogle Scholar
  13. Miall RC, Wolpert D (1996) Forward models for physiological motor control. Neural Netw 9:1265–1279PubMedCrossRefGoogle Scholar
  14. Ohyama T, Nores WL, Murphy M, Mauk MD (2003) What the cerebellum computes. Trend Neurosci 26:222–227PubMedCrossRefGoogle Scholar
  15. Panksepp J (2005) Affective consciousness: core emotional feelings in animals and humans. Conscious Cogn 14:30–80PubMedCrossRefGoogle Scholar
  16. Pessoa L, McKenna M, Gutierrez E, Ungerleider LG (2002) Neural processing of emotional faces requires attention. Proc Natl Acad Sci U S A 99(17):11458–11463PubMedCrossRefGoogle Scholar
  17. Petersen R (1997) Modelling learning in the brain. Ph.D. thesis, University of London, (unpublished)Google Scholar
  18. Petersen RS, Taylor JG (1996) Reorganization of somato-sensory cortex after tactile training. In: Touretsky DS, Mozer MC, Hasselmo ME (eds) Advances in neural information processing systems. MIT Press, Cambridge, MA, pp 82–88Google Scholar
  19. Stringer SM, Rolls ET, Trappenberg TP, de Araujo IET (2003a) Self-organising continuous attractor networks and motor function. Neural Netw 16:161–182PubMedCrossRefGoogle Scholar
  20. Stringer SM, Rollls ET, Trappenberg TP (2003b) Self-organizing continuous attractor networks with multiple active packets, and the representation of space. Neural Netw 17(1):5–27CrossRefGoogle Scholar
  21. Takeuchi A, Amari S-I (1999) Formation of topographic maps and columnar microstructures in nerve fields. Biol Cybern 35(2):63–72CrossRefGoogle Scholar
  22. Taylor JG (1997) Perception by neural networks. Neural Netw World 7:363–395Google Scholar
  23. Taylor JG (1999) Towards the networks of the brain: from brain imaging to consciousness. Neural Netw 12:943–959PubMedCrossRefGoogle Scholar
  24. Taylor JG (2000a) The central representation: the where, how and what of consciousness. In: White KE (ed) The emergence of mind. Fondazione Carlo Erba, Milan, pp 117–148Google Scholar
  25. Taylor JG (2000b) A control model for attention and consciousness. Soc Neurosci Abstr, 26, 2231#839.3Google Scholar
  26. Taylor JG (2000c) Neural ‘bubble’ dynamics in two dimensions: foundations. Biol Cybern 80:393–409CrossRefGoogle Scholar
  27. Taylor JG (2001) The central role of the parietal lobes in consciousness. Conscious Cogn 10:379–417PubMedCrossRefGoogle Scholar
  28. Taylor JG (2003) Paying attention to consciousness. Prog Neurobiol 41:305–335CrossRefGoogle Scholar
  29. Taylor JG, Alavi FN (1995) A global competitive neural network. Biol Cybern 72:233–248PubMedCrossRefGoogle Scholar
  30. Taylor JG, Fragopanagos N (2005) The interaction of attention and emotion. Neural Netw 18(4):353–369PubMedCrossRefGoogle Scholar
  31. Taylor JG, Rogers M (2002) A control model of the movement of attention. Neural Netw 15:309–326PubMedCrossRefGoogle Scholar
  32. Taylor JG, Fragopanagos N, Cowie R, Douglas-Cowie E, Fotinea S-E, Kollias S (2003) An emotional recognition architecture based on human brain structure. In: Proceedings of ICANN/ICONIP 2003. Springer, Berlin, pp 1133–1140Google Scholar
  33. Trappenberg TP, Dorris M, Klein RM, Munroe DP (2001) A model of saccade initiation based on the competitive integration of exogenous and endogenous signals from the superior colliculus. J Cognit Neurosci 13:256–271CrossRefGoogle Scholar
  34. van Essen DC, Deyoe EA (2008) Concurrent processing in the primate visual cortex. In: Gazzaniga M (ed) Cognitive neuroscience. MIT Press, Cambridge, MAGoogle Scholar
  35. Wolpert DM, Miall RC, Kawato M (1998) Internal models in the cerebellum. Trend Cognit Sci 2:338–347CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • John G. Taylor
    • 1
  1. 1.Department of MathematicsUniversity of LondonLondonUK

Personalised recommendations