Varying test-pattern duration to explore the dynamics of contrast-comparison and contrast-normalization processes
Norma V. Graham & S. Sabina Wolfson (2023)
Vision Research, Vol 23, Issue 1, pages 1-22, https://doi.org/10.1167/jov.23.1.15
Abstract: In this paper, we examine the dynamics of contrast-comparison and contrast-normalization processes. Observers adapted (for 1 second) to a grid of Gabor patches at one contrast; then a test pattern (which varied in duration from 12 ms to 3012 ms) was shown; and then the adapt pattern was shown again (1 second). All the Gabor patches in all the adapt patterns had 50% contrast. The test pattern was the same as the adapt pattern except that the Gabor patches in the test pattern had two different contrasts; the test contrasts varied from row to row (horizontal test pattern) or column to column (vertical test pattern). The task was to identify the orientation of the contrast variation in the test pattern (in other words, the observer performed a second-order orientation identification task). The two contrasts in each test pattern were varied while keeping the difference between the two contrasts constant. We have previously found that the observer's performance is poor for test patterns containing contrasts both above and below the adapt patterns' contrast (what we have called the "straddle effect") when the test duration is approximately 100 ms. Here, we find the straddle effect persists at all test durations we used. Other features of the results varied dramatically with test duration. We find that a simple model containing contrast-comparison and contrast-normalization processes provides a good explanation for the psychophysical results. The results provide some insight into the dynamics of these processes.
Spatial characteristics of a contrast-comparison process
Wolfson, S. S. and Graham, N. (2018)
J. M. Brown (Ed.) Pioneer Visual Neuroscience: A Festschrift for Naomi Weisstein, Routledge, pp. 104-117.
Abstract: Some time ago, while trying to study something else, we found a surprising effect of contrast adaptation: the visibility of some contrast-defined patterns was dramatically increased while that of other patterns was dramatically decreased following an adaptation pattern. We initially nicknamed this effect "Buffy Adaptation" but now call it the Straddle Effect. To study the Straddle Effect we present the observer with an adapt pattern for a very short length of time, then replace it with a test pattern, and then replace that with a post-test pattern which is identical to the adapt pattern. Finally, the observer answers a simple question about the perceived appearance of the test pattern. We find that when the spatial characteristics of the adapt and test patterns are identical, there is always a Straddle Effect. But when the adapt and test patterns differ in orientation, phase, or position, the Straddle Effect is much diminished. The Straddle Effect can be explained by a process (which we call contrast comparison) in which the sign of a contrast change is lost (or very degraded), but the size of that contrast change is preserved. It is possible that this contrast-comparison process occurs at the output to something as localized as a typical V1 receptive field.
Is the straddle effect in contrast perception limited to second-order spatial vision?
Graham, N. and Wolfson, S. S. (2018)
Journal of Vision, 18(5):15, 1-43, https://doi.org/10.1167/18.5.15
Abstract: Previous work on the straddle effect in contrast perception (Foley, 2011; Graham & Wolfson, 2007; Wolfson & Graham, 2007, 2009) has used visual patterns and observer tasks of the type known as spatially second-order. After adaptation of about 1 s to a grid of Gabor patches all at one contrast, a second-order test pattern composed of two different test contrasts can be easy or difficult to perceive correctly. When the two test contrasts are both a bit less (or both a bit greater) than the adapt contrast, observers perform very well. However, when the two test contrasts straddle the adapt contrast (i.e., one of the test contrasts is greater than the adapt contrast and the other is less), performance drops dramatically. To explain this drop in performance -- the straddle effect -- we have suggested a contrast-comparison process. We began to wonder: Are second-order patterns necessary for the straddle effect? Here we show that the answer is "no". We demonstrate the straddle effect using spatially first-order visual patterns and several different observer tasks. We also see the effect of contrast normalization using first-order visual patterns here, analogous to our prior findings with second-order visual patterns. We did find one difference between first- and second-order tasks: Performance in the first-order tasks was slightly lower. This slightly lower performance may be due to slightly greater memory load. For many visual scenes, the important quantity in human contrast processing may not be monotonic with physical contrast but may be something more like the unsigned difference between current contrast and recent average contrast.
Two visual contrast processes: One new, one old
Graham, N. and Wolfson, S. S. (2013)
C. Chubb, B. Dosher, Z. Lu, and R. Schiffrin (Eds.), Vision, Memory, and Attention, American Psychological Association, pp. 13-27.
From the introduction to this chapter:
In everyday life, we occasionally look at blank, un-textured regions of the world around us, a blue unclouded sky for example. But most of the time our eyes see regions occupied by spatial patterning -- by texture, form or patterns -- as when looking at a person to whom we are talking or at the text on this page. Further, there is constant temporal change as well as spatial patterning -- if only as a result of eye movements. Thus, the eye is usually looking at a visual scene where different parts of the scene are characterized by different levels of visual contrast, and, from moment to moment, the contrast at any point on the retina is changing. (Visual contrast in any region of the scene is the difference between the lightest and darkest parts of that region, relative to some measure of overall intensity in that region.) So one might wonder how the spatial patterning an observer has just seen affects the visual processing of the spatial patterning that an observer sees now. And, more specifically, one might wonder how the visual contrast one has just seen in a region affects the processing of visual contrast there now.
The first part of this chapter is about an effect of contrast adaptation discovered rather recently, nicknamed Buffy adaptation. (For the origin of the nickname, see Graham and Wolfson, 2007. We are using the term adaptation here only to mean the effect of preceding contrast on the processing of subsequent visual contrast. Our procedure, which will be described in Fig. 1, might also be called masking or a procedure to study temporal processing.) This recently discovered effect of contrast adaptation dramatically increases the visibility of some contrast-defined patterns and dramatically decreases that of others. The second part of the chapter briefly places this new effect in the context of a previously known effect (called the old effect here), which exhibits more conventional Weber-law-like behavior.Pre-print of manuscript text and manuscript figures.
Beyond multiple pattern analyzers modeled as linear filters (as classical V1 simple cells): Useful additions of the last 25 years
Graham, N. (2011)
Vision Research, Vol 51, Issue 13, pages 1397-1430.
Abstract: This review briefly discusses processes that have been suggested in the last 25 years as important to the intermediate stages of visual processing of patterns. Five categories of processes are presented: (1) Higher-order processes including FRF structures; (2) Divisive contrast nonlinearities including contrast normalization; (3) Subtractive contrast nonlinearities including contrast comparison; (4) Non-classical receptive fields (surround suppression, cross-orientation inhibition); (5) Contour integration.
Two contrast adaptation processes: Contrast normalization and shifting, rectifying contrast comparison
Wolfson, S. S. and Graham, N. (2009)
Journal of Vision, Vol 9, Num 4, Article 30.
Abstract: We present psychophysical results demonstrating the interaction of two contrast adaptation processes in human vision: (1) A contrast-gain-control process of the normalization type and (2) a recently-discovered shifting, rectifying contrast-comparison process. Observers adapted (for 1 s) to a grid of Gabor patches at one contrast, then a brief (94 ms) test pattern was shown, and then the adapt pattern was shown again (1 s). The test pattern was the same as the adapt pattern except that the Gabor patches had two different contrasts arranged to create vertical or horizontal contrast-defined stripes. Observers identified the orientation of the test pattern's stripes. Performance is a complicated ("butterfly shaped") function of the average test contrast, centered at the adapt contrast. This shape is a consequence of the interaction of the two contrast adaptation processes. At the ends of the function are "Weber zones" in which the contrast-gain-control process dominates, and at the center of the function is a "Buffy zone" in which the recently-discovered contrast-comparison process dominates.
PDF & HTML of this article. Also the Supplementary Material in PDF format.
Page 14 and 15 of this paper refers reader to Fig. 14 of Graham and Sutter 2000. Please also see the errata for that paper.
Exploring contrast-controlled adaptation processes in human vision (with help from Buffy the Vampire Slayer)
Graham, N. and Wolfson, S. S. (2007)
In Computational Vision in Neural and Machine System, eds Michael Jenkin & Laurence Harris, pp. 9-47.
From the introduction to this chapter:
Two sets of psychophysical experiments and the models they were used to generate and test are described in this chapter. The first is described briefly and the second at length.
The first set was designed to investigate behaviorally the dynamics of luminance-controlled processes like light adaptation in the retina or LGN. Strictly speaking, these processes are lower than the level that we have been most interested in (and were done with a third major collaborator, Don Hood, who is very interested in that level). Further, this set is already published for the most part. Thus we will describe it quite briefly. However, we do describe it because it both inspired the second set and also gave us distinct expectations about how the second set would turn out.
The second set of experiments was designed to investigate the dynamics of contrast-controlled processes. We started out to study one such process that had proved necessary to explain our previous results with textured patterns (done in collaboration with other investigators, in particular Jacob Beck and Anne Sutter). But the results of this second set of experiments ended up suggesting the existence of an entirely different contrast-controlled process, and one that we had not previously even imagined. This second set of experiments and the new process they suggested will be the focus of most of this chapter.
PDF (page proofs) of this chapter.
An unusual kind of contrast adaptation: shifting a contrast-comparison level
Wolfson, S. S. and Graham, N. (2007)
Journal of Vision, Vol 7, Num 8, Article 12.
Abstract: We have found an unusual kind of contrast adaptation in human pattern vision that seems fundamentally different from previously reported effects. As the observer adapts to different levels of contrast, the visibility of some contrast-defined (second-order) patterns dramatically increases and that of others dramatically decreases. Oddly, visibility is poor for patterns containing contrasts both above and below the recent average contrast. To explain these effects, we hypothesize a new kind of process acting in concert with a known contrast-gain-control of the normalization type. The new process compares current contrast to an adaptable comparison level; this level reflects the recent average contrast. Such a process existing at an early stage of visual processing is likely to have widespread effects at higher stages.
Forty-four years of studying light adaptation using the probed-sinewave paradigm
Wolfson, S. S. and Graham, N. (2006)
Journal of Vision, 6(10), 1026-1046.
Abstract: Here we examine results from 44 years of probed-sinewave experiments investigating the dynamics of light adaptation. We also briefly examine four models that have been tested against the results. In these experiments, detection threshold is measured for a test stimulus superimposed at various times (phases) on a sinusoidally flickering homogeneous background. The results can be plotted as probe-threshold versus phase curves. Overall, the curves from different laboratories are remarkably similar given the substantial differences in experimental parameters. However, at medium frequencies of background flicker, there are some differences between the majority of the studies and a minority of two. An examination of the full set of results suggests that the differences are not as significant as they first appear and that the experimental condition leading to the differences is the use of long wavelength light in the two minority studies. Of the four models that have been tested, two fail to predict important features of the results, another is critically dependent on a mechanism unlikely to exist in the appropriate physiology, and the last seems quite promising.
PDF & HTML of this article. Also the Supplementary Material in PDF format.
Contrast-response functions for the multifocal visual evoked potentials (mfVEP): A test of a model relating V1 activity to mfVEP activity.
Hood, D. C., Ghadiali, Q., Zhang, J. C., Graham, N., Wolfson, S. S., and Zhang, X. (2006)
Journal of Vision, 6(5), 580-593.
Abstract: The multifocal visual evoked potential (mfVEP) is largely generated in V1. To relate the electrical activity recorded from humans to recordings from single cells in nonhuman primate (V1) cortex, contrast–response functions for the human mfVEP were compared to predictions from a model of V1 activity (D. J. Heeger, A. C. Huk, W. S. Geisler, & D. G. Albrecht, 2000) based upon single-cell recordings from monkey V1 (e.g., D. G. Albrecht, 1995; D. G. Albrecht, W. S. Geisler, R. A. Frazor, & A. M. Crane, 2002; D. G. Albrecht & D. B. Hamilton, 1982; W. S. Geisler & D. G. Albrecht, 1997). A second purpose was to fully articulate the assumptions of this model to better understand the implications of this comparison. Finally, as the third purpose, one of these assumptions was tested. Monocular mfVEPs were obtained from normal subjects with a contrast-reversing dartboard pattern. The display contained 16 sectors each with a checkerboard. Both the sectors and the checks were scaled approximately for cortical magnification. In Experiment 1, there were 64 checks per sector. The contrast–response functions were fitted well up to 40% contrast by the theoretical population curve for V1 neurons; there was a systematic deviation for higher contrasts. The model, as articulated here, predicts that the contrast–response function should be the same and independent of the size of the elements in the display. Varying the size of the elements by varying the viewing distance in Experiment 2 produced similar results to those in Experiment 1. In Experiment 3, the viewing distance and sector size were held constant, but the size of the elements (and therefore the number of checks per sector) was varied. Changing check size by a factor of 16 had relatively little effect on the contrast–response function. In general, the mfVEP results were consistent with the model based upon the V1 neuron population. However, two aspects of the results require further exploration. First, there was a systematic deviation from the model's contrast–response function for higher contrasts. This deviation suggests that one or more of the model's assumptions may be violated. Second, the latency of the mfVEP changed far less than expected based upon single-cell data.
Element-arrangement textures in multiple objective tasks
Wolfson, S. S. and Graham, N. (2005)
Spatial Vision, 18(2), 209-226.
Abstract: In his long years of studying visual perception, Jacob Beck made many contributions. This article is a short review of one line of his research -- that we shared in -- and then a presentation of some results from on-going research down the same line. In the 1980s Beck and his colleagues introduced a new kind of visual stimulus: element-arrangement texture patterns. A series of studies with these patterns has shown that a model containing spatial-frequency and orientation-selective channels can explain many aspects of texture perception as long as two kinds of nonlinear processes are also included; the published studies are briefly summarized. The new results come from multiple objective tasks requiring the observerto make simple discriminations between second-order element-arrangement textures. Results with the objective tasks replicate previously published results using subjective ratings, and the use of the objective tasks allows us to explore several more fine-grained questions about complex (second-order) channels and normalization.
Is there opponent-orientation coding in the second-order channels of pattern vision?
Graham, N. and Wolfson, S. S. (2004)
Vision Research, 44(27), 3145-3175.
Abstract: Is there opponency between orientation-selective processes in pattern perception, analogous to opponency between color mechanisms? Here we concentrate on possible opponency in second-order channels. We compare several possible second-order structures: SIGN-opponent-only channels in which there is no opponency between orientations (also called complex channels or filter-rectify- filter mechanisms); three structures we group under the name ORIENTATION-opponent; and finally BOTH-opponent channels which combine features of both SIGN-opponent-only and ORIENTATION-opponent channels but lead to predictions that are distinct from either of theirs. We measured observers' ability to segregate textures composed of checkerboard and striped arrangements of vertical and horizontal Gabor grating patches. The observers' performance was compared to model predictions from the alternative opponent structures. The experimental results are consistent with SIGN-opponent-only channels. The results rule out the ORIENTATION-opponent and BOTH-opponent structures. Further, when the models were expanded to include a contrast gain-control (inhibition among channels in a normalization network) the SIGN-opponent-only model was also able to explain a contrast-dependent effect we found, thus providing another piece of evidence that such normalization is an important process in human texture perception.
PRESENTATIONS WITH PUBLISHED ABSTRACTS:
Graham, N., Wolfson, S. S., and Patterson, C. (2013) Temporal characteristics of the Straddle Effect (Buffy Contrast Adaptation) and modeling with On-Off Neurons Vision Sciences Society. PDF handout
Graham, N. and Wolfson, S. S. (2012). The Straddle (Buffy) Effect in temporal contrast processing (adaptation) is spatially very local. Vision Sciences Society. PDF handout
Graham, N., Wolfson, S. S., Kwok, I., and Grinshpun, B. (2010). "Buffy contrast adaptation" with a single Gabor patch. Vision Sciences Society. HTML Abstract
Graham, N., Wolfson, S. S., Pan, S., Wable, G., Kwok, I., and Grinshpun, B. (2009). Modeling the interaction of two rapid adaptation processes: contrast comparison and contrast normalization. Society for Neuroscience. HTML Abstract & PDF Handout
Wolfson, S. S., Pan. S., Wable, G., and Graham, N. (2009). Contrast-modulated noise shows an adaptable, rectifying, contrast-comparison process ("Buffy adaptation"). Vision Sciences Society, May 2009. HTML Abstract& PDF Handout
Wolfson, S. S. , Graham, N., and Pan, S. (2008). Two contrast-adaptation processes: One old, one new. Vision Sciences Society, May 2008. HTML Abstract & PDF Handout
Wolfson, S. S. and Graham, N (2007). More about "Buffy adaptation". Vision Sciences Society, May 2007. HTML Abstract & PDF Handout
Graham, N. and Wolfson, S. S. (2006) Complex channels become more complex: Modeling a contrast adaptation process. Journal of Vision, 6(6), abstract 694. Vision Sciences Society, May 2006. HTML Abstract
Wolfson, S. S. and Graham, N. (2005) Dynamics of contrast-gain controls in Human Vision Nournal of Vision 5(8), abstract 760. Vision Sciences Society, May 2005. HTML Abstract & PDF Handout