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Mental Representations: A Computational-Neuroscience Scheme

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Understanding Representation in the Cognitive Sciences

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Abstract

We discuss a series of problems facing referential theories of mental representations and we propose a scheme based on neurophysiological principles that avoids previous limitations. According to this scheme, mental representations are brain traces linked to stimuli in the environment, via a causal but probabilistic process of categorical perception, and fluctuations in activity reflect fluctuations in the confidence-level of perceptual and cognitive hypotheses. The scheme provides an explanation for cases of misrepresentation and is consistent with the abundance of recurrent connections in the cortex, which play an important role in mediating a process of interpretation and of binding of relational properties via temporal synchronisation.

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References

  • Allman, J., Miezin, R, & McGuinness, E. (1985) Direction-and velocity-specific responses from beyond the classical receptive field in the middle temporal visual area (MT). Perception 14: 105–126.

    Article  PubMed  CAS  Google Scholar 

  • Amit, D. J. (1989) Modelling Brain Function. Cambridge: Cambridge University Press.

    Google Scholar 

  • Amit, D. J., Sagi, D., & Usher, M. (1990) Architecture of attractor neural Networks performing cognitive fast scanning. Network 2: 189–216.

    Article  Google Scholar 

  • Anderson, J. A., Silverstein, J. W., Ritz, S. A., & Jones, R. S. (1977) Distinctive features, categorical perception and probability learning: Some applications of a neural model. Psychological Review 84: 413–451.

    Article  Google Scholar 

  • Arieli, A., Sterkin, A., Grinvald, A., & Aertsen, A. (1996) Dynamics of ongoing activity: explanation of the large variability in evoked cortical responses. Science 273: 1868–1871.

    Article  PubMed  CAS  Google Scholar 

  • Barlow, H. B. (1972) Single units and sensation: a neuron doctrine for perceptual psychlogy?. Perception 1: 371–394.

    Article  PubMed  CAS  Google Scholar 

  • Brentano, R. (1973, orig. published 1874) Psychology from an empirical standpoint (translated by A. Pancurello and D. Terrell and L. McAlister). New York: Humanities.

    Google Scholar 

  • Collins, A. M., & Loftus, E. F. (1975) A spreading activation theory of semantic processing. Psychological Review 5: 85–88.

    Google Scholar 

  • Collins, A. M, & Quillian, M. R. (1969) Retrieval time from semantic memory. Journal of Verbal Learning and Verbal Behavior 8: 240–247.

    Article  Google Scholar 

  • Cover, T. M., & Thomas, J. A. (1991) Elements of Information Theory. New York: Wiley.

    Google Scholar 

  • Crane, T. (1995) The mechanical mind. London, UK: Penguin.

    Google Scholar 

  • Crick, F., & Koch, C. (1990a) Some reflections on visual awareness. Cold Spring Harbor Symp. Quant. Biol. 55: 953–962.

    PubMed  CAS  Google Scholar 

  • Crick, F., & Koch, C. (1990b) Towards a neurobiological theory of consciousness. Seminars in the Neurosciences 2: 263–275.

    Google Scholar 

  • Cummins, R. (1991) Meaning and metal represen tation. A Bradford Book. Cambridge, MA: MIT Press.

    Google Scholar 

  • Decharms, R. C, & Merzenich, M. M. (1996) Primary cortical representation of sounds by the coordination of action potential timing. Nature 381: 610–613.

    Article  PubMed  CAS  Google Scholar 

  • Douglas, R. J., & Martin, K. A. C. (1991) A functional microcircuit for cat visual cortex. J. Physiologic. 440: 735–769.

    CAS  Google Scholar 

  • Douglas, R. J., Martin, K. A. C, & Whitteridge, D. (1988) Selective responses of visual cortical cells do not depend on shunting inhibition. Nature 332: 642–644.

    Article  PubMed  CAS  Google Scholar 

  • Dretske, F. (1981) Knowledge and the flow of information. Oxford: Blackwell.

    Google Scholar 

  • Dretske, F. (1983) Précis of Dretske Knowledge and the Flow of Information. Behavioral and Brain Sciences 6(1): 55–63.

    Article  Google Scholar 

  • Eells, E. (1991) Probabilistic causality. Cambridge, UK: Cambridge University Press.

    Google Scholar 

  • Elman, J. (1990) Finding Structure in Time. Cognitive Science 14: 179–211.

    Article  Google Scholar 

  • Fahle, M. (1993) Figure ground discrimination for temporal information. Proceedings of the Royal Soc. London 254: 199–203.

    Article  CAS  Google Scholar 

  • Ferster, D., & Spruston, N. (1995) Cracking the neuronal code. Science 270: 756–757.

    Article  PubMed  CAS  Google Scholar 

  • Fodor, J. (1987) Psychosemantics. Cambridge, MA: MIT Press.

    Google Scholar 

  • Fodor, J. (1990) A theory of content and other essays. Cambridge, MA: MIT Press.

    Google Scholar 

  • Georgopoulos, A. P., Kettner, R. E., & Schwartz, A. B. (1986) Neuronal population coding of movement direction. Science 233: 1416–1419.

    Article  PubMed  CAS  Google Scholar 

  • Gray, C., König, P., Engel, A., & Singer, W. (1989) Oscillatory responses in cat visual cortx exhibit inter-columnar synchronization which reflects global stimulus properties. Nature 338: 334–337.

    Article  PubMed  CAS  Google Scholar 

  • Gregory, R. L. (1998) Eye and Brain: The psychology of seeing (5 edition). Oxford: Oxford University Press.

    Google Scholar 

  • Hansel, D., & Sompolinsky, H. (1996) Chaos and synchrony in a model of a hypercolumn in visual cortex. Journal of Computational Neuroscience 3(1): 7–34.

    Article  PubMed  CAS  Google Scholar 

  • Harnad, S. (1987) Categorical perception: The groundwork of cognition. Cambridge, UK: Cambridge University Press.

    Google Scholar 

  • Hopfield, J. J. (1984) Neurons with Graded Responses Have Collective Computational Properties Like Those of Two-State Neurons. Proc. Nat. Acad. Sci., USA 81.

    Google Scholar 

  • Knierim, J. J., & Van Essen, D. C. (1992) Neuronal responses to static texture patterns in area VI of the alert macaque monkey. J. Neurophysiology 67(4): 961–980.

    CAS  Google Scholar 

  • LaMotte, R. H., & Mountcastle, V. B. M. (1979) Discorders in somethesis following lesions of parietal lobe. J. Neurophysiology 42(2): 400–419.

    Google Scholar 

  • Leonards, U., Singer, W., & Fahle, M. (1996) The Influence of Temporal Phase Differences on Texture Segmentation. Vision Res. 36(17): 2689–2697.

    Article  PubMed  CAS  Google Scholar 

  • McClelland, J., Rumelhart, & Hinton, G. (1986a) The appeal of parallel distributed processing.In: Rumelhart, D., & McClelland, J. (eds.) Parallel Distributed Processing, Vol.1. Cambridge: MIT Press, pp. 3–44.

    Google Scholar 

  • McClelland, J., Rumelhart, D., & the PDP Research Group (1986b) Parallel Distributed Processing: Explorations in the Microstructure of Cognition, Vol. 2. Cambridge: MIT Press.

    Google Scholar 

  • Milner, P. (1974) A model for visual shape recognition. Psychol. Rev. 81: 521–535.

    Article  PubMed  CAS  Google Scholar 

  • Mirollo, R., & Strogatz, S. (1990) Synchronization of pulse-coupled biological oscillators. SIAM J. on Applied Mathematics 50(6): 1645–1662.

    Article  Google Scholar 

  • Miyashita, Y., & Chang, H. (1988) Neural correlate of pictorial short term memory in primate temporal cortex. Nature 331: 68–70.

    Article  PubMed  CAS  Google Scholar 

  • Niebur, E., & Koch, C. (1994) A model for the neuronal implementation of selective visual attention based on temporal correlation among neurons. Journal of Computational Neuroscience 1(1): 141–158.

    Article  PubMed  CAS  Google Scholar 

  • Putnam, H. (1981) Reason, truth, and history. New York: Cambridge University Press.

    Google Scholar 

  • Searle, J. R. (1983) Intentionality: An essay in the philosophy of mind. Cambridge: CUP.

    Google Scholar 

  • Shadlen, M. N., & Newsome, W. T. (1995) Is there a signal in the noise? Current Opinion in Neurobiology 5: 248–250.

    Article  PubMed  CAS  Google Scholar 

  • Singer, W., & Gray, C. M. (1995) Visual feature integration and the temporal correlation hypothesis. Annu. Rev. Neurosci. 18: 555–586.

    Article  PubMed  CAS  Google Scholar 

  • Softky, W. (1995) Simple codes versus efficient codes. Current Opinion in Neurobiology 5: 239–247.

    Article  PubMed  CAS  Google Scholar 

  • Softky, W., & Koch, C. (1993) The highly irregular firing of cortical cells is inconsistent with temporal integration of random EPSPs. J. Neurosci. 13(1): 334–350.

    PubMed  CAS  Google Scholar 

  • Sompolinsky, H., & Kanter, I. (1986) Temporal Association in Asymmetric Neural Networks. Physical Review Letters 57: 2861–2864.

    Article  PubMed  Google Scholar 

  • Stemmler, M., Usher, M., & Niebur, E. (1995) Lateral Interactions in Primary Visual Cortex: A Model Bridging Physiology and Psychophysics. Science 269: 1877–1880.

    Article  PubMed  CAS  Google Scholar 

  • Suppes, P. (1970) A probabilitic theory of causality. Amsterdam: North Holland.

    Google Scholar 

  • Usher, M., & Donnelly, N. (1998) Visual synchrony affects binding and segmentation in perception. Nature 394: 179–182.

    Article  PubMed  CAS  Google Scholar 

  • Usher, M., & Niebur, E. (1995) Stimulus dependent synchronization in a model of orientation-tuned spiking neurons. In: Bower, J. M. (ed.) Computation and Neural Systems, Vol.3. MA: Kluwer, Norwell, pp. 341–346.

    Google Scholar 

  • Usher, M., & Niebur, E. (1999) Firing Patterns And Neural Codes: Models, data and implications. In preparation.

    Google Scholar 

  • Usher, M., Stemmler, M., Koch, C., & Olami, Z. (1994) Network Amplification of Local Fluctuations Causes High Spike Rate Variability, Fractal Firing Patterns and Oscillatory Local Field Potentials. Neural Computation 6(5): 795–836.

    Article  Google Scholar 

  • Usher, M., Stemmler, M., & Niebur, E. (1996) The role of lateral connections in visual cortex: dynamics and information processing. In: Sirosh, J., Mikkulainen, R., & Choe, Y. (eds.) Lateral Interactions in the Cortex. The UTCS Neural Networks Research Group, Austin, Texas. Electronic book, http://www.cs.utexas.edu/users/nn/webpubs/htmlbookn96.

    Google Scholar 

  • Usher, M., Stemmler, M., & Olami, Z. (1995) Dynamic pattern formation leads to 1/f noise in neural populations. Physical Review Letters 74(2): 326–329.

    Article  PubMed  CAS  Google Scholar 

  • von der Malsburg, C. (1981) The correlation theory of brain function. Tech. report 81-2, MaxPlanck-Institute for Biophysical Chemistry, Göttingen, Germany.

    Google Scholar 

  • von der Malsburg, C. (1996) Binding in models of perception and brain function. Current Biology 5: 520–526.

    Google Scholar 

  • Wittgenstein, L. (1958) Philosophical Investigations (Second edition). Oxford: Blackwell.

    Google Scholar 

  • Wyttenbach, R. A., May, M. L., & Hoy, R. R. (1996) Categorical perception of sound frequency by crickets. Science 273:1542–1544.

    Article  PubMed  CAS  Google Scholar 

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Author information

Authors and Affiliations

  1. Dept. of Psychology, Univ. of Kent at Canterbury, Kent, CP2 7NP, UK

    Marius Usher

  2. Krieger Mind/Brain Institute and Dept. of Neuroscience, The Johns Hopkins University, Baltimore, MD, 21218, USA

    Ernst Niebur

Authors
  1. Marius Usher
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  2. Ernst Niebur
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Editor information

Editors and Affiliations

  1. Free University of Brussels, Brussels, Belgium

    Alexander Riegler

  2. University of Vienna, Vienna, Austria

    Markus Peschl

  3. University/ETH Zurich, Zurich, Switzerland

    Astrid von Stein

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© 1999 Kluwer Academic/Plenum Publishers

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Usher, M., Niebur, E. (1999). Mental Representations: A Computational-Neuroscience Scheme. In: Riegler, A., Peschl, M., von Stein, A. (eds) Understanding Representation in the Cognitive Sciences. Springer, Boston, MA. https://doi.org/10.1007/978-0-585-29605-0_15

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  • DOI: https://doi.org/10.1007/978-0-585-29605-0_15

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-0-306-46286-3

  • Online ISBN: 978-0-585-29605-0

  • eBook Packages: Springer Book Archive

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