Relationship between spatial frequency selectivity and receptive field profile of simple cells.

Abstract

Maffei & Fiorentini (1976).3. Our data suggest that the simple cell may perform approximately linear spatial summation of inputs to the visual system. However, the output of the simple cell is generally non-linear as reflected in its truncated responses to gratings.

Computational models of visual neurons specialised in the detection of periodic and aperiodic oriented visual stimuli: bar and grating cells

“…The ratio σ/λ determines the spatial frequency bandwidth 3 Valois et al (1982) proposed that this spread is due to the gradual sharpening of the orientation and spatial frequency bandwidth at consecutive stages of the visual system and that the input to higher processing stages is provided by the more narrowly tuned simple cells with half-response spatial frequency bandwidth of approximately one octave. This value of the half-response spatial frequency bandwidth corresponds to the value 0.56 of the ratio σ/λ which is used in the simulations of this study.…”

“…3 The half-response spatial frequency bandwidth b (in octaves) of a linear filter with an impulse response according to (2) is the following function of the ratio σ/λ: b = log 2…”

Motion detection, noise reduction, texture suppression, and contour enhancement by spatiotemporal Gabor filters with surround inhibition

“…Computational models were developed aiming at simulating the function of these neurons for understanding and predicting their responses to more complex visual stimuli. The spatial summation properties of simple cells were modeled by linear filters followed by half-wave rectification (Movshon et al 1978b;Andrews and Pollen 1979;Glezer et al 1980;Kulikowski and Bishop 1981) and Gabor functions proved to be particularly well suited for this purpose (Marcelja 1980;Daugman 1985;Jones and Palmer 1987). Complex cells needed more intricate modeling, which included linear filtering, half-wave rectification and subsequent local spatial summation, or quadrature pair summation of linear filter responses (Movshon et al 1978a;Spitzer and Hochstein 1985;Morrone and Burr 1988;Petkov and Kruizinga 1997;Kruizinga and Petkov 1999;Grigorescu et al 2002, Grigorescu et al 2003.…”

Computational model of dot-pattern selective cells

“…In contrast to other orientation selective cells, grating cells respond very weakly or not at all to single bars, that is, bars that are isolated and are not part of a grating. This behaviour of grating cells cannot be explained by linear ®ltering followed by half-wave recti®cation as in the case of simple cells (Movshon et al 1978b;Andrews and Pollen 1979;Ma ei et al 1979;Glezer et al 1980;Kulikowski and Bishop 1981), nor by three-stage models of the type used for complex cells (Movshon et al 1978a;Spitzer and Hochstein 1985;Morrone and Burr 1988). The nonlinear processing properties of grating cells were reproduced by a computational model based on an AND-type non-linear combination of the responses of a group of simple cells (Kruizinga andPetkov 1995, 1999;Petkov and Kruizinga 1997;Kruizinga 1999).…”