Barbara Blakeslee

A multiscale spatial filtering account of the White effect, simultaneous brightness contrast and grating induction

Blakeslee and McCourt ((1997) Vision Research, 37, 2849-2869) demonstrated that a multiscale array of two-dimensional difference-of-Gaussian (DOG) filters provided a simple but powerful model for explaining a number of seemingly complex features of grating induction (GI), while simultaneously encompassing salient features of brightness induction in simultaneous brightness contrast (SBC), brightness assimilation and Hermann Grid stimuli. The DOG model (and isotropic contrast models in general) cannot, however, account for another important group of brightness effects which includes the White effect (White (1979) Perception, 8, 413-416) and the demonstrations of Todorovic ((1997) Perception, 26, 379-395). This paper introduces an oriented DOG (ODOG) model which differs from the DOG model in that the filters are anisotropic and their outputs are pooled nonlinearly. The ODOG model qualitatively predicts the appearance of the test patches in the White effect, the Todorovic demonstration, GI and SBC, while quantitatively predicting the relative magnitudes of these brightness effects as measured psychophysically using brightness matching. The model also accounts for both the smooth transition in test patch brightness seen in the White effect (White & White (1985) Vision Research, 25, 1331-1335) when the relative phase of the test patch is varied relative to the inducing grating, and for the spatial variation of brightness across the test patch as measured using point-by-point brightness matching. Finally, the model predicts intensive aspects of brightness induction measured in a series of Todorovic stimuli as the arms of the test crosses are lengthened (Pessoa, Baratoff, Neumann & Todorokov (1998) Investigative Ophthalmology and Visual Science, Supplement, 39, S159), but fails in one condition. Although it is concluded that higher-level perceptual grouping factors may play a role in determining brightness in this instance, in general the psychophysical results and ODOG modeling argue strongly that the induced brightness phenomena of SBC, GI, the White effect and the Todorovic demonstration, primarily reflect early-stage cortical filtering operations in the visual system.

Synaptic limitations to contrast coding in the retina of the blowfly Calliphora

We investigate the effects of synaptic transmission on early visual processing by examining the passage of signals from photoreceptors to second order neurons (LMCS). We concentrate on the roles played by three properties of synaptic transmission: (1) the shape of the characteristic curve, relating pre- and postsynaptic signal amplitudes, (2) the dynamics of synaptic transmission and (3) the noise introduced during transmission. The characteristic curve is sigmoidal and follows a simple model of synaptic transmission (Appendix) in which transmitter release rises exponentially with presynaptic potential. According to this model a presynaptic depolarization of 1.50–1.86 mV produces an e-fold increase in postsynaptic conductance. The characteristic curve generates a sigmoidal relation between postsynaptic (LMC) response amplitude and stimulus contrast. The shape and slope of the characteristic curve is unaffected by the state of light adaptation. Retinal antagonism adjusts the characteristic curve to keep it centred on the mean level of receptor response generated by the background. Thus the photoreceptor synapses operate in the mid-region of the curve, where the slope or gain is highest and equals approximately 6. The dynamics of transmission of a signal from photoreceptor to second-order neuron approximates to the sum of two processes with exponential time courses. A momentary receptor depolarization generates a postsynaptic hyperpolarization of time constant 0.5–1.0 ms, followed by a slower and weaker depolarization. Light adaptation increases the relative amplitude of the depolarizing process and reduces its time constant from 80 ms to 1.5 ms. The hyperpolarizing process is too rapid to bandlimit receptor signals. The noise introduced during the passage of the signal from receptor to second-order neuron is measured by comparing signal: noise ratios and noise power spectra in the two cell types. Under daylight conditions from 50 to 70% of the total noise power is generated by events associated with the transmission of photoreceptor signals and the generation of LMC responses. According to the exponential model of transmitter release, the effects of synaptic noise are minimized when synaptic gain is maximized. Moreover, both retinal antagonism and the sigmoidal shape of the characteristic curve promote synaptic gain. We conclude that retinal antagonism and nonlinear synaptic amplification act in concert to protect receptor signals from contamination by synaptic noise. This action may explain the widespread occurrence of these processes in early visual processing.

A unified theory of brightness contrast and assimilation incorporating oriented multiscale spatial filtering and contrast normalization.

Brightness induction includes both contrast and assimilations effects. Brightness contrast occurs when the brightness of a test region shifts away from the brightness of adjacent regions. Brightness assimilation refers to the opposite situation in which the brightness of the test region shifts toward that of the surrounding regions. Interestingly, in the White effect [Perception 8 (1979) 413] the direction of the induced brightness change does not correlate with the amount of black or white border in contact with the gray test patch. This has led some investigators to reject spatial filtering explanations not only for the White effect but for brightness perception in general. Instead, these investigators have offered explanations based on a variety of junction analyses and/or perceptual organization schemes. Here, these approaches are challenged with a critical set of new psychophysical measurements that determined the magnitude of the White effect, the shifted White effect [Perception 10 (1981) 215] and the checkerboard illusion [R.L. DeValois, K.K. DeValois, Spatial Vision, Oxford University Press, NY, 1988] as a function of inducing pattern spatial frequency and test patch height. The oriented difference-of-Gaussians (ODOG) computational model of Blakeslee and McCourt [Vision Res. 39 (1999) 4361] parsimoniously accounts for the psychophysical data, and illustrates that mechanisms based on junction analysis or perceptual inference are not required to explain them. According to the ODOG model, brightness induction results from linear spatial filtering with an incomplete basis set (the finite array of spatial filters in the human visual system). In addition, orientation selectivity of the filters and contrast normalization across orientation channels are critical for explaining some brightness effects, such as the White effect.

The Intracellular Pupil Mechanism and Photoreceptor Signal: Noise Ratios in the Fly Lucilia cuprina

The function of the intracellular pupil mechanism is examined by comparing the responses of photoreceptors in normal flies with those from white-eyed flies that lack the pupil. In white-eyed flies the response to an intensity increment of fixed contrast decreases at high background intensities. There is a smaller decrease in noise amplitude so that the signal: noise ratio falls. The intensity dependence of the photoreceptor signal: noise ratio fits a simple model in which activated photopigment molecules compete for 3 x 104 tranduction units. The signal: noise ratio decreases at high intensities because the transduction units are saturated. This model is supported by a noise analysis, which provides three estimates of the number of events generating photoreceptor responses. In white-eyed flies the event number saturates at high background intensities, suggesting that a maximum of 2 x 104 events can be simultaneously active. Wild-type flies do not exhibit saturation effects over the range of intensities studied. The signal: noise ratio rises with intensity to reach a stable asymptote, close to the maximum observed for white-eyed flies. Pupil attenuation is calculated from measurements of signal: noise ratio in white-eyed and wild-type flies. The pupil is progressively activated over a two log unit intensity range and when fully closed attenuates the effective intensity by 99%. The threshold of this pupil effect coincides with the threshold of pupil activation measured optically. We conclude that the intracellular pupil attenuates the light flux to prevent receptor saturation and to extend the range of intensities at which fly photoreceptors operate close to their maximum signal: noise ratio. This upper limit is determined by the number of transduction units generating a cell’s response.

Similar mechanisms underlie simultaneous brightness contrast and grating induction.

The experiments explore whether the mechanism(s) underlying grating induction (GI) can also account for simultaneous brightness contrast (SBC). At each of three test field heights (1, 3 and 6 deg), point-by-point brightness matches were obtained from two subjects for test field widths of 32 deg (GI condition), 14, 12, 8, 6, 3 and 1 deg. The point-by-point brightness matches were quantitatively compared, using GI condition matches as a standard, to assess systematic alterations in the structure and average magnitude of brightness and darkness induction within the test fields as a function of changing test field height and width. In the wider test fields induction structure was present and was generally well-accounted for by the GI condition sinewave predictions. As test field width decreased the sinewave amplitude of the induced structure in the test field decreased (i.e., flattened), and eventually became negative (i.e., showed a reverse cusping) at the narrower test field widths. As expected, both subjects showed a decrease in overall levels of brightness and darkness induction with increasing test field height. For any particular test field height, however, relative brightness increased with decreasing test field width. This brightness increase began at larger test field widths as test field height increased. The results are parsimoniously accounted for by the output of a weighted, octave-interval array of seven difference-of-gaussian filters. This array of filters differs from those previously employed to model various aspects of spatial vision in that it includes filters tuned to much lower spatial frequencies. The two-dimensional output of this same array of filters also accounts for the GI demonstrations of Zaidi [(1989) Vision Research, 29, 691-697], Shapley and Reids [(1985) Proceedings of the National Academy of Sciences USA, 82, 5983-5986] contrast and assimilation demonstration, and the induced spots seen at the street intersections of the Hermann Grid. The physiological plausibility of the filter array explanation of brightness induction is discussed, along with a consideration of its relationship to other models of brightness perception.

Factors governing the adaptation of cells in area-17 of the cat visual cortex

Neurons in area 17 of the cat visual cortex adapt when stimulated by drifting patterns of optimal orientation, spatial frequency and temporal frequency (Ohzawa et al. 1982; Albrecht et al. 1984; Ohzawa et al. 1985). A component of this adaptation has been attributed to a contrast gain-control mechanism, rather than to neural fatigue, and results in enhanced differential sensitivity around the adapting contrast level (Ohzawa et al. 1982; Albrecht et al. 1984; Ohzawa et al. 1985). Experiments described here suggest that neural response rate, the directional selectivity of the cell, and the temporal frequency of the stimulus, are the principal determinants of adaptation, irrespective of other stimulus parameters such as contrast, velocity, or spatial frequency. The present results can nevertheless accommodate the results of previous studies of adaptation, and additionally provide scope for the resolution of apparent contradictions between results from psychophysical and neurophysiological studies of adaptation.

A multiscale spatial filtering account of the Wertheimer–Benary effect and the corrugated Mondrian

Blakeslee and McCourt [Blakeslee, B., & McCourt, M.E. (1997). Similar mechanisms underlie simultaneous brightness contrast and grating induction. Vision Research, 37, 2849-2869] demonstrated that a multiscale array of two-dimensional difference-of-Gaussian (DOG) filters provided a simple but powerful model for explaining a number of seemingly complex features of grating induction (GI), while simultaneously encompassing salient features of brightness induction in simultaneous brightness contrast (SBC), brightness assimilation and Hermann Grid stimuli. The DOG model (and isotropic contrast models in general) cannot, however, account for another important group of brightness effects including the White effect [White, M. (1997). A new effect of pattern on perceived lightness. Perception, 8, 413-416] and a variant of SBC [Todorovic, D. (1997). Lightness and junctions. Perception, 26, 379-395]. Blakeslee and McCourt [Blakeslee, B., McCourt, M.E. (1999). A multiscale spatial filtering account of the White effect, simultaneous brightness contrast and grating induction. Vision Research, 39, 4361-4377] developed a modified version of the model, an oriented (ODOG) model, which differed from the DOG model in that the filters were anisotropic and their outputs were pooled nonlinearly. Using this model, they were able to account for both groups of induction effects. The present paper examines two additional sets of brightness illusions that cannot be explained by isotropic contrast models. Psychophysical brightness matching is employed to quantitatively measure the size of the brightness effect for two Wertheimer-Benary stimuli [Benary, W. (1924). Beobachtungen zu einem experiment uber helligkeitskontrast. Psychologische Forschung, 5, 131-142; Todorovic, D. (1997). Lightness and junctions. Perception, 26, 379-395] and for low- and high-contrast versions of corrugated Mondrian stimuli [Adelson, E.H. (1993). Perceptual organization and the jugdement of brightness. Science, 262, 2042-2044; Todorovic, D. (1997). Lightness and junctions. Perception, 26, 379-395]. Brightness matches are obtained on both homogeneous and checkerboard matching backgrounds. The ODOG model qualitatively predicts the appearance of the test patches in the Wertheimer-Benary stimuli and corrugated Mondrian stimuli. In addition, it quantitatively predicts the relative magnitudes of the corrugated Mondrian effects in the various conditions. In general, the psychophysical results and ODOG modeling argue strongly that like SBC, GI, the White effect and Todorovics SBC demonstration, induced brightness in Wertheimer-Benary stimuli and in the corrugated Mondrian primarily reflects early-stage filtering operations in the visual system.

Oriented multiscale spatial filtering and contrast normalization: a parsimonious model of brightness induction in a continuum of stimuli including White, Howe and simultaneous brightness contrast

The White effect [Perception 8 (1979) 413] cannot be simply explained as due to either brightness contrast or brightness assimilation because the direction of the induced brightness change does not correlate with the amount of black or white border in contact with the gray test patch. This has led some investigators to abandon spatial filtering explanations not only for the White effect but for brightness perception in general. Offered instead are explanations based on a variety of junction analyses and/or perceptual organization schemes which in the case of the White effect are usually based on T-junctions. Recently, Howe [Perception 30 (2001) 1023] challenged T-junction based explanations with a novel variation of Whites effect in which the T-junctions were constant while the brightness effect was eliminated or reversed, and proposed an alternative explanation in terms of illusory contours. The present study argues that an analysis at the level of illusory contours is not necessary and that a much simpler spatial filtering based explanation is sufficient. Brightness induction was measured in a set of stimuli chosen to illustrate the relationship between the Howe stimulus [Perception 30 (2001) 1023], the White stimulus [Perception 8 (1979) 413] and the classical simultaneous brightness contrast (SBC) stimulus. The White stimulus and the SBC stimulus occupy opposite ends of a continuum of stimuli in which the Howe stimulus is the mid-point. The psychophysical measurements were compared with the predictions of the oriented difference-of-Gaussians (ODOG) computational model of Blakeslee and McCourt [Vision Research 39 (1999) 4361]. The ODOG model parsimoniously accounted for both the direction and relative magnitude of the brightness effects suggesting that more complex mechanisms are not required to explain them.

A Multiscale Spatial Filtering Account of Brightness Phenomena

Brightness is a fundamental quality of human vision. A central problem in thestudy of brightness perception is understanding how and when the visual sys-tem is able to separate the physically invariant reflectances of surfaces from theirpotentially changing illumination. Reflectance and illumination are confoundedsince their product determines luminance, the amount of light reaching the eyefrom a particular surface. Before proceeding further, however, we need to cometo terms with several definitional problems currently plaguing the field with con-fusion.Brightness is defined by the CIE (1970)as the attribute accordingto whicha visual stimulus appears to be more or less intense, or to emit more or less light.Thus, unrelated achromatic colors (that is, stimuli presented alone in a dark field)vary only in brightness (CIE, 1970). Variations in brightness range from bright todim. Brightness is highly correlated with the photometric quantity luminance, es-pecially for unrelated stimuli, and therefore another common definition of bright-ness is perceived luminance (the Trieste group uses this definition: see Arend,1993). The CIE adds the property of lightness to related achromatic stimuli (thatis, stimuli presented in a display containing multiple stimuli). Lightness, as de-fined by the CIE, is the attribute according to which a visual stimulus appears toemit more or less light in proportion to that emitted by a similarly illuminatedarea perceived as “white”. Thus, the CIE definition of lightness is actually rel-ative brightness. Variations in lightness range from very light or white, to verydark or black. Although an unrelated color can appear white, only related col-ors have a gray or black component. Related colors thus possess a perceptualdimension (blackness) that does not exist for unrelated colors; this added dimen-sion arises through spatial interactions, revealed in some instances by inductioneffects, that can occur only between related stimuli (Wyszecki and Stiles, 1982;Wyszecki, 1986; Lennie and D’Zmura, 1988; Pokorny, Shevell and Smith, 1991).

Brightness with and without perceived transparency: when does it make a difference?

Subjects matched the brightness of test patches whose inner (adjacent) surrounds appeared either as transparent overlays on a wider background that included the test patch or as regions differing in reflectance from the test patch and the outer surround. In the above configurations the luminance and spatial extent of the inner surround was identical, thus controlling for the effects of surround luminance. Configuration condition had a significant effect on test-patch brightness. In general, test-patch brightness was significantly elevated under conditions favouring the interpretation of the stimulus as including a transparent overlay. The largest effect occurred for the configuration in which the perception of transparency was supported by stereo depth cues. The brightness effect was mediated by the virtual transmittance of the transparent overlay, increasing in magnitude with decreasing transmittance. Further, the effect of transparency on brightness was greatest for test-patch luminances near to those of their immediate surrounds.