Do Gabor functions provide appropriate descriptions of visual cortical receptive fields?

Several recent theoretical models for human spatial vision posit that cortical receptive fields act to minimize simultaneously the product of the standard deviation of the sensitivities to position (delta chi) and to spatial frequency (delta omega) in accord with the uncertainty principle from Fourier analysis. The receptive-field functions resulting from this approach--one-dimensional or two-dimensional Gabor elementary functions--have been shown by others to fit measured receptive fields adequately in some species. However, only complex-valued Gabor functions minimize this product, and these cannot be fitted to single-cell receptive fields. We point out that the derivations of others have an implied metric or measure of positional and spatial-frequency uncertainties and that there is an infinitely large class of such metrics, many of which yield other receptive-field functions that are quite plausible biologically. We review neurophysiological measurements of others and analyze psychophysical masking data and find that in many cases receptive-field functions other than Gabor functions fit better. We conclude that there are insufficient theoretical demonstrations and experimental data to favor Gabor functions over any of a number of other plausible receptive-field functions.

[1]  J. Daugman Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters. , 1985, Journal of the Optical Society of America. A, Optics and image science.

[2]  J. Daugman Two-dimensional spectral analysis of cortical receptive field profiles , 1980, Vision Research.

[3]  R Linsker,et al.  From basic network principles to neural architecture: emergence of spatial-opponent cells. , 1986, Proceedings of the National Academy of Sciences of the United States of America.

[4]  D S Falk,et al.  Receptive-field symmetry probed using converging gratings. , 1985, Journal of the Optical Society of America. A, Optics and image science.

[5]  H. Wechsler,et al.  Joint spatial/spatial-frequency representation , 1988 .

[6]  A. Parker,et al.  Spatial properties of neurons in the monkey striate cortex , 1987, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[7]  D J Field,et al.  Relations between the statistics of natural images and the response properties of cortical cells. , 1987, Journal of the Optical Society of America. A, Optics and image science.

[8]  DG Stork,et al.  Receptive fields and the optimal stimulus , 1982 .

[9]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[10]  J. Movshon,et al.  Spatial summation in the receptive fields of simple cells in the cat's striate cortex. , 1978, The Journal of physiology.

[11]  J. P. Jones,et al.  An evaluation of the two-dimensional Gabor filter model of simple receptive fields in cat striate cortex. , 1987, Journal of neurophysiology.

[12]  D. Pollen,et al.  Phase relationships between adjacent simple cells in the visual cortex. , 1981, Science.

[13]  Hugh R. Wilson,et al.  Development of spatiotemporal mechanisms in infant vision , 1988, Vision Research.

[14]  H. Wilson,et al.  Spatial frequency tuning of orientation selective units estimated by oblique masking , 1983, Vision Research.

[15]  J. P. Jones,et al.  Periodic simple cells in cat area 17. , 1984, Journal of neurophysiology.

[16]  R A Young,et al.  The Gaussian derivative model for spatial vision: I. Retinal mechanisms. , 1988, Spatial vision.

[17]  J. Daugman Spatial visual channels in the fourier plane , 1984, Vision Research.

[18]  J. Robson,et al.  Grating summation in fovea and periphery , 1978, Vision Research.

[19]  G. Turin,et al.  An introduction to matched filters , 1960, IRE Trans. Inf. Theory.

[20]  S Marcelja,et al.  Mathematical description of the responses of simple cortical cells. , 1980, Journal of the Optical Society of America.

[21]  D. Hubel,et al.  Receptive fields, binocular interaction and functional architecture in the cat's visual cortex , 1962, The Journal of physiology.

[22]  H. Pollak,et al.  Prolate spheroidal wave functions, fourier analysis and uncertainty — III: The dimension of the space of essentially time- and band-limited signals , 1962 .

[23]  A B Watson,et al.  Efficiency of a model human image code. , 1987, Journal of the Optical Society of America. A, Optics and image science.

[24]  D. V. van Essen,et al.  The representation of the visual field in parvicellular and magnocellular layers of the lateral geniculate nucleus in the macaque monkey , 1984, The Journal of comparative neurology.

[25]  Ralph Linsker,et al.  Self-organization in a perceptual network , 1988, Computer.

[26]  D. Pollen,et al.  Relationship between spatial frequency selectivity and receptive field profile of simple cells. , 1979, The Journal of physiology.

[27]  R Linsker,et al.  From basic network principles to neural architecture: emergence of orientation-selective cells. , 1986, Proceedings of the National Academy of Sciences of the United States of America.