Skip to main content
SpringerLink
Log in

A model for the neuronal implementation of selective visual attention based on temporal correlation among neurons

  • Published:
Journal of Computational Neuroscience Aims and scope Submit manuscript

Abstract

We propose a model for the neuronal implementation of selective visual attention based on temporal correlation among groups of neurons. Neurons in primary visual cortex respond to visual stimuli with a Poisson distributed spike train with an appropriate, stimulus-dependent mean firing rate. The spike trains of neurons whose receptive fields donot overlap with the “focus of attention” are distributed according to homogeneous (time-independent) Poisson process with no correlation between action potentials of different neurons. In contrast, spike trains of neurons with receptive fields within the focus of attention are distributed according to non-homogeneous (time-dependent) Poisson processes. Since the short-term average spike rates of all neurons with receptive fields in the focus of attention covary, correlations between these spike trains are introduced which are detected by inhibitory interneurons in V4. These cells, modeled as modified integrate-and-fire neurons, function as coincidence detectors and suppress the response of V4 cells associated with non-attended visual stimuli. The model reproduces quantitatively experimental data obtained in cortical area V4 of monkey by Moran and Desimone (1985).

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Bair, W., Koch, C, Newsome, W., and Britten, K. (1993). Power spectrum analysis of MT neurons in the awake monkey. In Bower J. and Eeckman F., editors, Computation and Neural Systems. Kluwer, Norwell, MA.

    Google Scholar 

  • Bair, W., Koch, C., Newsome, W., and Britten, K. (1994). Power spectrum analysis of bursting cells in area MT in the behaving monkey.

  • Baldi, P. and Meir, R. (1990). Computing with arrays of coupled oscillators: an application to preattentive texture discrimination. Neural Computation, 2:458–471.

    Google Scholar 

  • Bialek, W., Rieke, F., De Ruyter Van Stevenick, R.R., and Warland D. (1991). Reading a neural code. Science, 252:1854–1857.

    Google Scholar 

  • Braun, J. and Sagi, D. (1990). Vision outside the focus of attention. Perception and Psychophysics, 48:45–58.

    Google Scholar 

  • Colby, C.L. (1991). The neuroanatomy and neurophysiology of attention. J. Child Neurology, 6:S90-S118.

    Google Scholar 

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

    Google Scholar 

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

    Google Scholar 

  • Desimone, R. (1992). Neural circuits for visual attention in the primate brain. In Carpenter G. and Grossberg S., editors,Neural networks for vision and image processing. MIT Press, Cambridge.

    Google Scholar 

  • Desimone, R. and Ungerleider, L.G. (1989). Neural mechanisms of visual processing in monkeys. In Boller F. and Graffman J., editors,Handbook of Neuropsychology, pages 267–299. Elsevier, Amsterdam.

    Google Scholar 

  • Desimone, R., Wessinger, M., Thomas, L., and Schneider, W. (1991). Attentional control of visual perception: cortical and subcortical mechanisms Symp. Quant. Biol., 55:963–971.

    Google Scholar 

  • Eckhorn, R., Bauer, R., Jordan, W., Brosch, M, Kruse, W, Munk, M., and Reitboeck, H.J. (1988). Coherent oscillatios: a mechanism of feature linking in the visual cortex? Biol. Cybern., 60:121–130.

    Google Scholar 

  • Engel, A.K., König, P., Kreiter, A.K., Schillen, Th.B., and Singer, W. (1992). Temporal coding in the visual system: new vistas on integration in the nervous system. Trends in Neurosciences, 15:218–226.

    Google Scholar 

  • Engel A.K., König, P., Kreiter, A.K., and Singer, W. (1991a). Interhemispheric synchronization of oscillatory neuronal responses in cat visual cortex. Science, 252:1177–1179.

    Google Scholar 

  • Engel, A.K., König, P., Kreiter, A.K., and Singer, W. (1991b). Synchronization of oscillatory neuronal responses between striate and extrastriate visual cortical areas of the cat. Proc. Nat. Acad. Sci., USA, 88:6048–6052.

    Google Scholar 

  • Gray, C.M., Engel, A.K., König, P., and Singer, W. (1933). Synchronization of oscillatory neuronal responses in cat striate cortex: temporal properties. Visual Neurosci., 8:337–347.

    Google Scholar 

  • Gray, C.M., Engel, A.K., König, P., and Singer, W. (1990). Stimulus-dependent neuronal oscillations in cat visual cortex: receptive field properties and feature dependence. Europ. J. Neurosci., 2:607–619.

    Google Scholar 

  • Gray, C.M. and Singer, W. (1989). Stimulus-specific neuronal oscillations in orientation columns of cat visual cortex. Proc. Nat. Acad. Sci., USA, 86:1698–1702.

    Google Scholar 

  • Horn, D., Sagi, D., and Usher, M. (1991). Segmentation, binding and illusory conjunctions. Neural Computation, 3:510–525.

    Google Scholar 

  • Julesz, B. (1991). Early vision and focal attention. Rev. Mod. Physics, 63:735–772.

    Google Scholar 

  • Kanwisher, N. and Driver, J. (1992). Objects, attributes and visual attention: which, what, and where. Current Directions in Psychological Science, 1:26–31.

    Google Scholar 

  • Keele, S.W., Cohen, A., Ivry, R., Liotti, M., and Yee, P. (1988). Test of a temporal theory of attentional binding J. Experimental Psychology: Human Perception and Performance, 14:444–452.

    Google Scholar 

  • Koch, C. and Ullman, S. (1985). Shifts in selective visual attention: towards the underlying neural circuitry. Human Neurobiol., 4:219–227.

    Google Scholar 

  • Kreiter, A.K. and Singer, W. (1992). Oscillatory neuronal response in the visual-cortex of the awake macaque monkey. Europ. J. Neurosci., 4(4):369–375.

    Google Scholar 

  • LaBerge, D. and Buchsbaum, M.S. (1990). Positron emission tomographic measurements of pulvinar activity during an attention task. J. Neurosci., 10:613–619.

    Google Scholar 

  • Livingstone, M.S. (1991). Visually-evoked oscillations in monkey striate cortex. Soc. Neurosci. Abstr., 17(1):176.

    Google Scholar 

  • Llinas, R.R., Grace, A.A., and Yarom, Y. (1991). In vitro neurons in mammalian cortical layer 4 exhibit intrinsic oscillatory activity in the 10- to 50-hz frequency range. Proc. Natl. Acad. Sci. USA, 88:987–901.

    Google Scholar 

  • McClurkin, J.W., Optican, L.M., Richmond, B.J., and Gawne, T.J. (1991). Concurrent processing and complexity of temporally encoded neuronal messages in visual perception. Science, 253:675–677.

    Google Scholar 

  • Moran, J. and Desimone, R. (1985). Selective attention gates visual processing in the extrastriate cortex. Science, 229:782–784.

    Google Scholar 

  • Motter, B.C. (1993). Focal attention produces spatially selective processing in visual cortical areas V1, V2, and V4 in the presence of competing stimuli. J. Neurophysiology, 70(3):909–919.

    Google Scholar 

  • Mountcastle, V.B., Anderson, R.A., and Motter, B.C. (1981). The influence of attentive fixation upon the excitability of the light-sensitive neurons of the posterior parietal cortex. J. Neurosci., 1:1218–1232.

    Google Scholar 

  • Nakamura, H., Gattass, R., Desimone, R., and Ungerleider, L.G. (1993). The modular organization of projections from area V1 and area V2 to area V4 and TEO in macaques. J. Neuroscience, 13(9):3681–3691.

    Google Scholar 

  • Niebur, E., Koch, C., and Rosin, C. (1993). An oscillation-based model for the neural basis of attention. Vision Research, 33:2789–2802.

    Google Scholar 

  • Olshausen, B., Andersen, C., and Van Essen, D. (1993). A neural model of visual attention and invariant pattern recognition. J. Neuroscience, 13:4700–4719.

    Google Scholar 

  • Petersen, S.E., Robinson, D.L., and Morris, J.D. (1987). Contributions of the pulvinar to visual spatial attention. Neuropsychologia, 25:97–105.

    Google Scholar 

  • Posner, M.I. and Driver, J. (1992). The neurobiology of selective attention. Current Opinion in Neurobiology, 2:165–169.

    Google Scholar 

  • Posner, M.I. and Petersen S.E. (1990). The attention system of the human brain. Ann. Rev. Neurosci., 13:25–42.

    Google Scholar 

  • Rafal, R.D. and Posner, M.I. (1987). Deficits in human visual spatial attention following thalamic lesions. Proc. Nat. Acad. Sci., USA, 84:7349–7353.

    Google Scholar 

  • Robinson, D.L. and Petersen, S.E. (1992). The pulvinar and visual salience. Trends in Neurosciences, 15(4):127–132.

    Google Scholar 

  • Saarinen, J. and Julesz, B. (1991). The speed of attentional shifts in the visual field. Proc. Nat. Acad. Sci., USA, 88:1812–1814.

    Google Scholar 

  • Singer, W. (1993). Synchronization of cortical activity and its putative role in information processing and learning. Annu. Rev. Physiol., 55:349–74.

    Google Scholar 

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

    Google Scholar 

  • Tovee, M.J. and Rolls, E.T. (1992). Oscillatory activity is not evident in the primate temporal visual cortex with static stimuli. Neuro Report, 3:369–372.

    Google Scholar 

  • Treisman, A. (1988). Features and Objects: the fourteenth Bartlett memorial lecture. Quant. J. Exp. Psychol., 40A:201–237.

    Google Scholar 

  • von der Malsburg, C. (1981). The correlation theory of brain function. Technical Report 81-2, Max-Planck-Institute for Biophysical Chemistry, D-3400 Goettingen, Germany.

    Google Scholar 

  • von der Malsburg, C. and Schneider, W. (1986). A neural cocktail party processor. Biol. Cybern., 54:29–40.

    Google Scholar 

  • Young, M.P., Tanaka, K., and Yamane, S. (1992). On oscillating neuronal responses in the visual cortex of the monkey. J. Neurophysiol., 67:1464–1474.

    Google Scholar 

Download references

Author information

Author notes

  1. Ernst Niebur

    Present address: Caltech, 139-74, 91125, Pasadena, CA, USA

Authors and Affiliations

  1. Computation and Neural Systems Program, California Institute of Technology, 91125, Pasadena, CA, USA

    Ernst Niebur & Christof Koch

Authors
  1. Ernst Niebur
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Christof Koch
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

About this article

Cite this article

Niebur, E., Koch, C. A model for the neuronal implementation of selective visual attention based on temporal correlation among neurons. J Comput Neurosci 1, 141–158 (1994). https://doi.org/10.1007/BF00962722

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF00962722

Keywords

Search

Navigation