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Color illusion as a spatial binding problem
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ScienceDirect Color illusion as a spatial binding problem Arthur G Shapiro1,2,3 and Laysa Hedjar3 Illusions are often considered to be a misperception of the physical world. We present a different framework for illusions: in non-illusory conditions, healthy brains construct a single, consistent representation from the physiological processes that encode the world; illusions, in contrast, are conditions where the brain constructs conflicting representations of the world. We contend that the conditions for illusions often arise for color vision because of the multifaceted aspects of color in relation to space, and that many color illusions arise from the juxtaposition and selective recombination (i.e. the binding) of these aspects of color/spatial information. We discuss three spatial aspects of color: modes of appearance, color versus color contrast, and information at different spatial scales. Addresses 1 Department of Psychology, American University, Washington, D.C. 20016, United States 2 Department of Computer Science, American University, Washington, D.C. 20016, United States 3 Program in Behavior, Cognition and Neuroscience, American University, Washington, D.C. 20016, United States Corresponding author: Shapiro, Arthur G ([email protected])
Current Opinion in Behavioral Sciences 2019, 30:149–155 This review comes from a themed issue on Visual perception Edited by Hannah Smithson and John S Werner
https://doi.org/10.1016/j.cobeha.2019.08.004 2352-1546/ã 2019 Elsevier Ltd. All rights reserved.
Introduction What is a color illusion? The answer seems straightforward, particularly since recent high-profile phenomena (e.g. the dress) have helped reify the concept. However, the term ‘illusion’ has recently (or once again) become controversial, with many researchers claiming that the term is not useful and is misleading [1–3,4]. We will therefore first review past and current concerns about the definition of ‘illusion’; we will then reframe the definition in light of current ideas about the brain’s construction of reality. We will examine color illusions from the vantage of the new framework we present: our contention is that illusions are conditions where the brain constructs conflicting representations of the world, and that such conditions often arise when manipulating color because of the multifaceted aspects of color in relation to www.sciencedirect.com
space, which, in our view, are not often given adequate attention in studies of color perception. The standard definition of ‘illusion,’ and its critics
According to the standard definition, an illusion represents a misperception of the factual world [5]. In a general schematic of this definition (Figure 1a), the left side depicts the information in the external world (physics, chemistry, objects, etc.), and the right side depicts a perceptual representation that tries to mirror reality after the eyes and brain transduce and process external information. The framework assumes a correspondence theory of truth, in which our perceptions are more or less accurate descriptions of the world, and illusions represent deviations or misalignments where we see things that are not so. For instance, an illusion would be a straight line that appears bent, two identical colors that appear unequal, or a physically present but unseen gorilla. Not surprisingly, this definition of ‘illusion’ has been problematic for almost the entire history of the field of Psychology. Boring’s [6] statement about illusions is representative: ‘[S]trictly speaking, the concept of illusion has no place in psychology because no experience actually copies reality.’ All color, then, is an illusion because color is not the same as the physical property of light: ‘“[C]olor is ‘in us’ and the external world consists only of light of varying wavelengths’ (Boring [6], discussing Lotze [7]). This idea can be traced at least to Newton’s [8] statement ‘that the rays themselves are not coloured.’ We have known for some time that our senses are far too limited to transduce most of the external world (e.g. objects in the external world can be too small, too fast, or outside perceptible energy range, like ultraviolet light). More than that, we also know that there can never be a one-to-one mapping between photons in the external world and the way neurons represent photons. The standard definition of ‘illusion’ is therefore ‘practically meaningless’ [6] since our percepts never precisely mirror the stimulus: ‘[T] here is no satisfactory way of distinguishing between those aspects of our perception that we regard as veridical and those we label as illusions’ [9]. A number of vision scientists have recently added to this criticism of the standard definition, claiming that the term ‘illusion’ has outlived its usefulness. They state: 1. Perception has a functional purpose with biological utility. Perception should therefore recover not the properties of the current stimulus, but rather aspects of the world that are ‘behaviorally useful’ ([3]; see also Ref. [10]); 2. Our understanding of the reasons illusions occur is very good. Current Opinion in Behavioral Sciences 2019, 30:149–155
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(a) The standard definition is that illusions are misperceptions of reality. The framework for the standard definition can be depicted as three interacting areas: physical world, biology, and a resulting perception. According to this framework, perception mirrors reality under non-illusory conditions, and illusions represent conditions where perception is an inaccurate representation of the physical world. (b) An updated framework of perception is that the brain encodes the physical world via many processing channels, which could lead to a number of potential representations. In non-illusory conditions, the brain is able to settle on a single perceptual representation of the world. (c) Illusions arise from the conflict between plausible constructions of perceptual reality. So, one representation holds that the image is stationary, while another holds that the object on the page moves.
Why should we call a perception an illusion if we are giving a description of how the visual system works [2,4,11]?; or 3. Illusions are a collection of disparate phenomena without a common mechanism [1]. So, while illusions certainly seem to illustrate something important about perception, recent criticism of the term suggests that defining the phenomenon is superfluous since all perception is illusory, or images classified as illusions Current Opinion in Behavioral Sciences 2019, 30:149–155
should not be considered ‘illusions’ once their mechanisms are understood. An alternative definition of ‘illusion’
What, then, makes images classified as illusions special or worth investigating? The problematic issue, from our point of view, is not with the illusions themselves, but rather with the physics-biology-perception framework www.sciencedirect.com
Color illusion as a spatial binding problem Shapiro and Hedjar 151
from Figure 1a, which circumscribes discussions of illusions ([3] also criticize this framework). It is more useful to consider a current neuroscience perspective, in which the brain is a ‘reality engine’ [12] that constructs a perceptual world by integrating the responses from many subprocesses, each of which encodes limited aspects of the physical environment. According to this perspective, as pictured in Figure 1b, the physical world contains the same information as in Figure 1a; and, similar to 1a, the early visual system encodes small slices of the available information through numerous processing streams. The brain could conceivably use this information to construct multiple types of representations of the world, but as a ‘reality engine,’ the brain often seems to settle on a single perceptual ‘story’ that integrates the multiple physiological subprocesses. For our purposes, there are two remarkable aspects of this framework: 1. Under nonillusory conditions, healthy brains construct a single, consistent representation from the information encoded about the world; and 2. The brain’s selected representation is so convincing that without physiological or philosophical reflection, most people will consider the representation to be in one-to-one correspondence with reality. From this vantage, illusions can be redefined to represent conditions, in which there is a conflict between possible constructions of perceptual reality — that is, conditions where a single consistent representation is not the only satisfactory way to understand the images. For instance, for the Hering illusion, we may (or may not) have reasonable explanations for why a line can be perceived as straight under some conditions and bent under others, but that does not remove the conflicting ways of interpreting the line. Similarly, simultaneous contrast displays are classified as illusions not because the surrounds shift the color of the center object but rather because of the conflict between representations: one representation holds that objects maintain a constant color, and another representation shows that backgrounds can shift the color appearance of the center object (Figure 1c). Once such a conflict arises, observers often label one representation as ‘illusory’ and the other as ‘real,’ but this distinction depends on the ‘reality engine’ and prior interactions with a statistically reliable physical world; from the standpoint of neurophysiology, both representations are ‘real’ since both can be used to infer separate physiological processes. Illusions of color and space
For color vision, illusions often arise from conflicts in spatial information. One reason is that color and space are inextricably linked [13]. Colors always have spatial extent: colors are attached to specific objects or image regions; colors cut across objects, as in the case of illuminants; or colors float apart from objects, as in endogenous images. Conversely, each point of the perceptual www.sciencedirect.com
world can be described as a color, a fact that allows our visual world to be simulated by changing pixels on a monitor or paints on a canvas. Vision science has a long history of studying how space affects color. However, most color vision models do not include spatial parameters — and are therefore ‘space blind’ — or account for spatial factors in terms of lateral inhibition or other gain controls that influence color signals. In contrast, recent physiological research emphasizes that retinal spatial processing is complex, sending multiple types of spatial signals to the brain [14,15]; some visual cortex processes seem sensitive to color, while others seem sensitive to color/luminance contrast [16,17]; and color in the dorsal and ventral pathways seems to serve different functions [18,19]. The resolution of the separate spatial responses leads to what has been termed ‘the spatial frequency binding problem’ [20]. That is, the early visual system encodes information at different spatial scales, and the later visual system combines the encoded information in ways appropriate for particular visual tasks. Because of the interdependence of color and space, selection of the appropriate spatial information greatly influences how color is perceived. Here, we discuss three spatial aspects of color: modes of appearance, color versus color contrast, and information at different spatial scales. Modes of appearance
Color often takes on multiple modes of appearance (brightness, lightness, saturation, transparency, scission, shininess, etc.) that can occur in the same spatial location: Figure 2
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Current Opinion in Behavioral Sciences
Color can have multiple modes of appearance. In the Long-Range Argyles stimulus [23,24], a uniform field is divided by three columns of small black and white triangles. Area (a) is between the left column and center column; area (b) is between the center column and the right column. The uniform field does not appear uniform; rather, the area labeled (a) appears as a dark surface in bright illumination, and the area labeled (b) appears as a light surface in shadow. Current Opinion in Behavioral Sciences 2019, 30:149–155
152 Visual perception
‘“[T]wo different colour appearances can be simultaneously present at the same ‘location’ as distinctive aspects of the percept’ [21,22]. For instance, Figure 2, Long-Range Argyles [23,24], shows the complexity of translating multiple perceptual modes into a single perceptual term. Three columns of black and white triangles are placed on a uniform gray background, but
the background does not appear uniform; rather, region A appears as a dark surface under bright illumination, and region B appears as a bright surface in shadow. Curiously, when asked which region is brighter, about 1/3 of respondents report region A while 2/3 report region B (personal observations suggest that this ratio could be highly variable). So, each pixel can be represented on multiple
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Points on a center/surround stimulus can be described in terms of color and rectified color contrast. (a) The center disks have the same pixel value; the disk on the left is yellow with high contrast relative to the surround, and the disk on the right is yellow with low contrast relative to the surround. (b) A basic Contrast Asynchrony paradigm [26]: one disk with a bright surround, and the other with a dark surround; the color/luminance levels of the disks are identical (as in Figure 3(a)) but change from dark to light over time; therefore, the luminance values modulate in phase, and the contrast values modulate in antiphase. (c) The Contrast Asynchrony stimuli represented in a contrast versus luminance plane. (d) Hedjar et al. [28] Remote Controls illusion: thin edges cause the asynchronous appearance to disappear or reappear. (e) Takahashi [30] Curvature Blindness illusion: contrast information can lead to different interpretations of shape and direction. Current Opinion in Behavioral Sciences 2019, 30:149–155
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Color illusion as a spatial binding problem Shapiro and Hedjar 153
perceptual dimensions, and translation to a single perceptual dimension may prove to be a source of discrepancy.
Figure 4
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Any point in a visual image can be described along multiple physical dimensions. For instance, in a simple disk and ring configuration (Figure 3a), each pixel on the disk has both a luminance/chromaticity value and a contrast value relative to the surround (a spatial derivative, [25]). The Contrast Asynchrony paradigm [26,27] places these two dimensions in opposition. In the basic version of the paradigm (Figure 3a), one disk is surrounded by a dark ring, and the other by a light ring. When disk luminance is modulated sinusoidally in time (Figure 3b), the luminance values modulate in phase, and the contrast values modulate in antiphase; the stimulus therefore traces two different lines in a color versus color contrast plane (Figure 3c). The two physical dimensions (luminance and contrast) correspond to two different perceptual modes: the disks appear to get light and dark at the same time (luminance) and appear to alternate out of phase (contrast). The way the visual system seems to resolve the conflict between these two dimensions depends upon subtle contextual differences. For instance, Hedjar et al.’s ([28]; also Ref. [29]) Remote Controls illusion (Figure 3d) shows that minute changes at points distant from the modulating bars can lead to sudden switches from in-phase perception to out-ofphase perception. Furthermore, contrast information can lead to different interpretations of shape and direction. Takahashi’s [30] Curvature Blindness illusion (Figure 3e) shows massive changes in direction based on contrast. The directional interpretation may be related to individual processing units [31], but even if so, the inputs to these units will have at least two different physical dimensions. Information at different spatial scales
Each pixel value in an image can also be considered as the sum of multiple spatial frequency components. Indeed, many aspects of most — not all [32] — standard color and brightness illusions can be explained simply by considering the image at a particular spatial bandwidth (e.g. Refs. [13,33,34–36]). In Figure 4a, the colors of the hearts in Kitaoka’s [37] assimilation illusion are identical at a pixel level but physically different in the low spatial frequency range, whereas the two squares in Purves and Lotto’s [38] Rubik’s cube are identical at a pixel level but physically different in the high spatial frequency range. The spatial frequency ranges can be interchanged across images to show that different spatial bands carry different types of information. In Figure 4b, evening and morning images of Monet’s Rouen cathedral have been decomposed into high and low spatial frequency components. When the low spatial frequency is swapped, the resulting images appear as the morning cathedral painted under www.sciencedirect.com
Original illiusion
After application of spatial filter (b)
Rouen in daylight
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Decompose into high and low frequency components Swap low frequency components Reconstruct image Current Opinion in Behavioral Sciences
In most standard color and brightness illusions, test patches have the same pixel value yet are physically different at some spatial bandwidth. (a) Kitaoka [37] ‘Blue-to-purple heart and green-to-orange heart’ illusion: an assimilation illusion in which the hearts are physically different in the low spatial frequency components. And Purves and Lotto [38] Rubik’s cube illusion: an assimilation illusion, in which the test squares are different in the high spatial frequency components. (b) Evening and morning images of Monet’s cathedral at Rouen decomposed into high and low spatial frequency components: when the low spatial frequency is swapped, the resulting images appear as the morning cathedral painted under evening illumination, and the evening cathedral painted under morning illumination.
evening illumination, and the evening cathedral painted under morning illumination.
Conclusion The standard definition of the term ‘illusion’ is problematic because our perception is never an exact copy of reality. Here, we base our definition of ‘illusion’ on the idea that a single representation of the physical environment is not always the only solution, and the brain is therefore sometimes forced either to oscillate between representations or to privilege one source of physiological response over others; under non-illusory conditions, the brain selects as ‘reality’ a single consistent representation that ‘best’ integrates information from multiple processes. Current Opinion in Behavioral Sciences 2019, 30:149–155
154 Visual perception
Illusions arise from the conflict between possible representations. The role of conflict in perception has a long history [39]: a stick in semi-submerged water looks bent but feels straight when we touch it with our hands; the experience is compelling since the interpretations of vision and touch conflict with each other, which suggests a need for resolution. It is reasonable to suppose that our appreciation of an ‘illusion’ represents the brain’s response to stimuli that activate one or more of the brain’s several systems that seem to respond to mismatches between different encodings (e.g. Refs. [40–42]).
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Purves D, Wojtach WT, Lotto RB: Why the concept of “visual Illusions” is misleading. In The Oxford Compendium of Visual Illusions. Edited by Shapiro AG, Todorovic D. Oxford University Press; 2017:139-143.
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Every point in an image can be considered in terms of multiple physical dimensions (e.g. luminance/chromaticity; color and color contrast; low, mid-range and high spatial frequencies). Low spatial frequency content tends to carry information about global illumination; mid-range spatial frequency content tends to carry illuminationinvariant information about object color (particularly when there is a single illuminant, and interreflection isn’t present); and high spatial frequency content tends to carry illumination-invariant information about edges [33]. Luminance and luminance contrast correspond to different types of invariance in the environment: contrast between an object and its background remains constant as illumination changes, whereas luminance remains constant when an object moves from one background to another [43,44]. It is truly remarkable that the brain manages to encode and seamlessly integrate information from across all these dimensions as often as it does.
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Boring EG: Sensation and Perception in the History of Experimental Psychology. 1942.
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Lotze RH: Medical Psychology, or, Physiology of the Soul. Leipzig: Weidmann; 1852. 4.
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Rogers B: Delusions about illusions. Perception 2014, 43:840845.
The definition for ‘illusion’ proposed here suggests that many color illusions are examples of the spatial frequency binding problem [20] — that is, the visual system is capable of encoding color information at different spatial scales and contrasts; color illusions often arise because the brain combines spatial information differently depending on the visual tasks; and these combinations often conflict with our idea of color as invariant and separate from space. We believe that by examining how the visual system resolves or fails to resolve spatial binding, researchers can develop potential solutions to practical problems concerning individual differences (e.g. Ref. [33]) and concerning perception in healthy and unhealthy visual systems.
Conflict of interest statement Nothing declared.
References and recommended reading Papers of particular interest, published within the period of review, have been highlighted as: of special interest of outstanding interest 1.
Braddick O: Illusion research: an infantile disorder? Perception 2018, 47:805-806.
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10. Purves D, Wojtach WT, Lotto RB: Understanding vision in wholly empirical terms. Proc Natl Acad Sci U S A (108 Suppl 3):2011:15588-15595. 11. Morgan MJ: Visual illusions. In Unsolved Mysteries of the Mind: Tutorial Essays in Cognition. Edited by Bruce V. Psychology Press; 1996:29-58. 12. Hoffman DD: Human Vision as a Reality Engine. . Retrieved from Washington, DC: Foundation for the Advancement of Behavioral and Brain Sciences; 2010 http://www.cogsci.uci.edu/ddhoff/ HoffmanFABBS.pdf. 13. Shapley R, Nunez V, Gordon J: Cortical double-opponent cells and human color perception. Curr Opin Behav Sci 2019, 30:1-7 A paper published in this issue of COBEHA. The article discusses other options for the integration of color and space, stressing the role of singleopponent and double-opponent cortical cell substrates. The argument the authors put forward is extraordinarily important because it emphasizes the interactions between color and space, the multivariate responses of the cortical color response, and adaptation levels. 14. Masland RH, Martin PR: The unsolved mystery of vision. Curr Biol 2007, 17:R577-R582. 15. Turner MH, Schwartz GW, Rieke F: Receptive field center surround interactions mediate context-dependent spatial contrast encoding in the retina. eLife 2018, 7 http://dx.doi.org/ 10.7554/eLife.38841 Center-surround receptive fields are — in effect — adaptive spatial bandpass filters: changes in the size of the center increase/decrease the high spatial frequency response; changes in the size of the surround increase/ decrease the low spatial frequency response (this fact seems well understood in the signal processing literature, but less so in the physiological/ behavioral literature). This paper shows that receptive field ‘architecture has an important consequence for spatial contrast encoding in the macaque monkey retina: the surround can control sensitivity to fine spatial structure by changing the way the center integrates visual information over space.’ The authors conclude that ‘the surround plays unappreciated roles in shaping ganglion cell sensitivity to natural inputs.’ 16. Johnson EN, Hawken MJ, Shapley R: The orientation selectivity of color-responsive neurons in macaque V1. J Neurosci 2008, 28:8096-8106. 17. Johnson EN, Hawken MJ, Shapley R: The spatial transformation of color in the primary visual cortex of the macaque monkey. Nat Neurosci 2001, 4:409-416. 18. Conway BR: Color signals through dorsal and ventral visual pathways. Visual Neurosci 2014, 31:197-209. 19. Liu J, Wandell BA: Specializations for chromatic and temporal signals in human visual cortex. J Neurosci 2005, 25:3459-3468. www.sciencedirect.com
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20. Burge J, Rodriguez-Lopez V, Dorronsoro C: Monovision and the misperception of motion. Curr Biol 2019, 29:2586-2592 http:// dx.doi.org/10.1016/j.cub.2019.06.070 Burge et al. show that blurring the image to one eye leads to an unexpected ‘reverse’ Pulfrich effect — reversed because blur reduces contrast and therefore should lead to a Pulfrich effect in the opposite direction. The authors account for this by proposing ‘i) blur reduces the contrast of high-frequency image components more than low-frequency image components, and ii) high spatial frequencies are processed more slowly than low spatial frequencies, all else equal.’ The paper proposes the idea of a ‘spatial frequency binding problem,’ which we consider fundamental to understanding many aspects of visual function, including those that lead to color illusions. 21. Katz D: The World of Colour. Routledge. (1935/2013). 22. Mausfeld R: The dual coding of colour: “Surface colour” and “illumination colour” as constituents of the representational format of perceptual primitives. In Colour: Mind and the Physical World. Edited by Mausfeld R, Heyer D. Oxford University Press. [RM]; 2003 . Retrieved from http://citeseerx.ist.psu.edu/ viewdoc/download?doi=10.1.1.134.306&rep=rep1&type=pdf. 23. Flynn OJ, Shapiro AG: A note concerning the relationship between Adelson’s argyle illusion and Cornsweet edges. Psihologija 2014, 47:353-358. 24. Shapiro AG, Todorovic D: Introduction. In The Oxford Compendium of Visual Illusions. Edited by Shapiro AG, Todorovic D. Oxford University Press; 2017:xix-xxiii. 25. Rose-Henig A, Shapiro AG: Contrast–contrast asynchronies. JOSA A 2014, 31:A232-A238. 26. Shapiro AG: Separating color from color contrast. J Vis 2008, 8:8.1-18. 27. Shapiro AG, D’Antona A, Smith JB, Belano LA, Charles JP: Induced contrast asynchronies may be useful for luminance photometry. Visual Neurosci 2004, 21:243-247. 28. Hedjar L, Cowardin V, Shapiro AG: Remote controls illusion: strange interactions across space cannot be explained by simple contrast filters. J Opt Soc Am A Opt Image Sci Vis 2018, 35:B152-B164 Another paper from our lab presents dramatic variations on the Contrast Asynchrony paradigm, which demonstrate 1) a separation of color and color contrast, and 2) that small edges — sometimes at some distance from the modulation fields — can make the asynchronous appearance disappear. The visual system’s weighting of color and color contrast information can therefore be affected by small contextual changes in the stimulus. 29. Shapiro AG, Leaver AM: Edges can eliminate the appearance of the contrast asynchrony. Ophthalmic Physiol Opt 2010, 30:534544. 30. Takahashi K: Curvature blindness illusion. I-Perception 2017, 8 2041669517742178 The paper presents a new illusion, in which wavy lines on different backgrounds appear to take on different shapes and orientations. The illusion is important because it demonstrates the effects of contrast polarity on shape — that is, that the discontinuity of contrast polarity
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at the turning point of the wavy line affects some but not all curvatures. Anderson and Burr (‘Visual Perception: To Curve or Not to Curve’ 2018, Current Biology, 28, 4R150-R152) argue that the illusion demonstrates segmentation mechanisms of human vision. 31. Anderson BL, Burr DC: Visual perception: to curve or not to curve. Curr Biol 2018, 28:R150-R152. 32. Betz T, Shapley R, Wichmann FA, Maertens M: Noise masking of White’s illusion exposes the weakness of current spatial filtering models of lightness perception. J Vis 2015, 15:1. 33. Dixon EL, Shapiro AG: Spatial filtering, color constancy, and the color-changing dress. J Vis 2017, 17:7 A paper from our lab concerning the color-changing dress. Unlike other papers that propose that individual differences arise from color constancy strategies, this paper suggests that there are individual differences for processing low spatial frequency content, just as there are individual differences for processing high spatial frequency content. A demo included in the paper shows that for simple conditions, global illumination is entirely contained in an image’s low spatial frequency range; thus, in such conditions, the removal of low spatial frequency content leads directly to color constancy. 34. Shapiro A, Hedjar L, Dixon E, Kitaoka A: Kitaoka’s tomato: two simple explanations based on information in the stimulus. IPerception 2018, 9 2041669517749601. 35. Shapiro A, Lu Z-L: Relative brightness in natural images can be accounted for by removing blurry content. Psychol Sci 2011, 22:1452-1459. 36. Zeman A, Brooks KR, Ghebreab S: An exponential filter model predicts lightness illusions. Front Hum Neurosci 2015, 9:368. 37. Kitaoka A: “Blue-to-purple heart and green-to-orange heart” from The latest works 60 website. 2019 http://www.psy.ritsumei.ac.jp/ akitaoka/saishin61e.html. 38. Purves D, Lotto RB: Why We See What We Do: An Empirical Theory of Vision. 1st edition. Sinauer Associates; 2003. 39. Burnyeat M: Conflicting appearances. In Proceedings of the British Academy 1981, vol 6569-111: 1979. 40. Alexander WH, Brown JW: The role of the anterior cingulate cortex in prediction error and signaling surprise. Top Cogn Sci 2019, 11:119-135. 41. Mansouri FA, Tanaka K, Buckley MJ: Conflict-induced behavioural adjustment: a clue to the executive functions of the prefrontal cortex. Nat Rev Neurosci 2009, 10:141-152. 42. Popa LS, Ebner TJ: Cerebellum, predictions and errors. Front Cell Neurosci 2018, 12:524. 43. Brown RO: Background and illuminants: the yin and yang of colour constancy. In Colour Perception: Mind and the Physical World. Edited by Mausfeld R, Heyer D. Oxford University Press; 2003:247-272. 44. Whittle P, Mausfeld R, Heyer D: Contrast colours. Colour Percept: Mind Phys World 2003:115-138.
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ScienceDirect Color illusion as a spatial binding problem Arthur G Shapiro1,2,3 and Laysa Hedjar3 Illusions are often considered to be a misperception of the physical world. We present a different framework for illusions: in non-illusory conditions, healthy brains construct a single, consistent representation from the physiological processes that encode the world; illusions, in contrast, are conditions where the brain constructs conflicting representations of the world. We contend that the conditions for illusions often arise for color vision because of the multifaceted aspects of color in relation to space, and that many color illusions arise from the juxtaposition and selective recombination (i.e. the binding) of these aspects of color/spatial information. We discuss three spatial aspects of color: modes of appearance, color versus color contrast, and information at different spatial scales. Addresses 1 Department of Psychology, American University, Washington, D.C. 20016, United States 2 Department of Computer Science, American University, Washington, D.C. 20016, United States 3 Program in Behavior, Cognition and Neuroscience, American University, Washington, D.C. 20016, United States Corresponding author: Shapiro, Arthur G ([email protected])
Current Opinion in Behavioral Sciences 2019, 30:149–155 This review comes from a themed issue on Visual perception Edited by Hannah Smithson and John S Werner
https://doi.org/10.1016/j.cobeha.2019.08.004 2352-1546/ã 2019 Elsevier Ltd. All rights reserved.
Introduction What is a color illusion? The answer seems straightforward, particularly since recent high-profile phenomena (e.g. the dress) have helped reify the concept. However, the term ‘illusion’ has recently (or once again) become controversial, with many researchers claiming that the term is not useful and is misleading [1–3,4]. We will therefore first review past and current concerns about the definition of ‘illusion’; we will then reframe the definition in light of current ideas about the brain’s construction of reality. We will examine color illusions from the vantage of the new framework we present: our contention is that illusions are conditions where the brain constructs conflicting representations of the world, and that such conditions often arise when manipulating color because of the multifaceted aspects of color in relation to www.sciencedirect.com
space, which, in our view, are not often given adequate attention in studies of color perception. The standard definition of ‘illusion,’ and its critics
According to the standard definition, an illusion represents a misperception of the factual world [5]. In a general schematic of this definition (Figure 1a), the left side depicts the information in the external world (physics, chemistry, objects, etc.), and the right side depicts a perceptual representation that tries to mirror reality after the eyes and brain transduce and process external information. The framework assumes a correspondence theory of truth, in which our perceptions are more or less accurate descriptions of the world, and illusions represent deviations or misalignments where we see things that are not so. For instance, an illusion would be a straight line that appears bent, two identical colors that appear unequal, or a physically present but unseen gorilla. Not surprisingly, this definition of ‘illusion’ has been problematic for almost the entire history of the field of Psychology. Boring’s [6] statement about illusions is representative: ‘[S]trictly speaking, the concept of illusion has no place in psychology because no experience actually copies reality.’ All color, then, is an illusion because color is not the same as the physical property of light: ‘“[C]olor is ‘in us’ and the external world consists only of light of varying wavelengths’ (Boring [6], discussing Lotze [7]). This idea can be traced at least to Newton’s [8] statement ‘that the rays themselves are not coloured.’ We have known for some time that our senses are far too limited to transduce most of the external world (e.g. objects in the external world can be too small, too fast, or outside perceptible energy range, like ultraviolet light). More than that, we also know that there can never be a one-to-one mapping between photons in the external world and the way neurons represent photons. The standard definition of ‘illusion’ is therefore ‘practically meaningless’ [6] since our percepts never precisely mirror the stimulus: ‘[T] here is no satisfactory way of distinguishing between those aspects of our perception that we regard as veridical and those we label as illusions’ [9]. A number of vision scientists have recently added to this criticism of the standard definition, claiming that the term ‘illusion’ has outlived its usefulness. They state: 1. Perception has a functional purpose with biological utility. Perception should therefore recover not the properties of the current stimulus, but rather aspects of the world that are ‘behaviorally useful’ ([3]; see also Ref. [10]); 2. Our understanding of the reasons illusions occur is very good. Current Opinion in Behavioral Sciences 2019, 30:149–155
150 Visual perception
Figure 1
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Motion Current Opinion in Behavioral Sciences
(a) The standard definition is that illusions are misperceptions of reality. The framework for the standard definition can be depicted as three interacting areas: physical world, biology, and a resulting perception. According to this framework, perception mirrors reality under non-illusory conditions, and illusions represent conditions where perception is an inaccurate representation of the physical world. (b) An updated framework of perception is that the brain encodes the physical world via many processing channels, which could lead to a number of potential representations. In non-illusory conditions, the brain is able to settle on a single perceptual representation of the world. (c) Illusions arise from the conflict between plausible constructions of perceptual reality. So, one representation holds that the image is stationary, while another holds that the object on the page moves.
Why should we call a perception an illusion if we are giving a description of how the visual system works [2,4,11]?; or 3. Illusions are a collection of disparate phenomena without a common mechanism [1]. So, while illusions certainly seem to illustrate something important about perception, recent criticism of the term suggests that defining the phenomenon is superfluous since all perception is illusory, or images classified as illusions Current Opinion in Behavioral Sciences 2019, 30:149–155
should not be considered ‘illusions’ once their mechanisms are understood. An alternative definition of ‘illusion’
What, then, makes images classified as illusions special or worth investigating? The problematic issue, from our point of view, is not with the illusions themselves, but rather with the physics-biology-perception framework www.sciencedirect.com
Color illusion as a spatial binding problem Shapiro and Hedjar 151
from Figure 1a, which circumscribes discussions of illusions ([3] also criticize this framework). It is more useful to consider a current neuroscience perspective, in which the brain is a ‘reality engine’ [12] that constructs a perceptual world by integrating the responses from many subprocesses, each of which encodes limited aspects of the physical environment. According to this perspective, as pictured in Figure 1b, the physical world contains the same information as in Figure 1a; and, similar to 1a, the early visual system encodes small slices of the available information through numerous processing streams. The brain could conceivably use this information to construct multiple types of representations of the world, but as a ‘reality engine,’ the brain often seems to settle on a single perceptual ‘story’ that integrates the multiple physiological subprocesses. For our purposes, there are two remarkable aspects of this framework: 1. Under nonillusory conditions, healthy brains construct a single, consistent representation from the information encoded about the world; and 2. The brain’s selected representation is so convincing that without physiological or philosophical reflection, most people will consider the representation to be in one-to-one correspondence with reality. From this vantage, illusions can be redefined to represent conditions, in which there is a conflict between possible constructions of perceptual reality — that is, conditions where a single consistent representation is not the only satisfactory way to understand the images. For instance, for the Hering illusion, we may (or may not) have reasonable explanations for why a line can be perceived as straight under some conditions and bent under others, but that does not remove the conflicting ways of interpreting the line. Similarly, simultaneous contrast displays are classified as illusions not because the surrounds shift the color of the center object but rather because of the conflict between representations: one representation holds that objects maintain a constant color, and another representation shows that backgrounds can shift the color appearance of the center object (Figure 1c). Once such a conflict arises, observers often label one representation as ‘illusory’ and the other as ‘real,’ but this distinction depends on the ‘reality engine’ and prior interactions with a statistically reliable physical world; from the standpoint of neurophysiology, both representations are ‘real’ since both can be used to infer separate physiological processes. Illusions of color and space
For color vision, illusions often arise from conflicts in spatial information. One reason is that color and space are inextricably linked [13]. Colors always have spatial extent: colors are attached to specific objects or image regions; colors cut across objects, as in the case of illuminants; or colors float apart from objects, as in endogenous images. Conversely, each point of the perceptual www.sciencedirect.com
world can be described as a color, a fact that allows our visual world to be simulated by changing pixels on a monitor or paints on a canvas. Vision science has a long history of studying how space affects color. However, most color vision models do not include spatial parameters — and are therefore ‘space blind’ — or account for spatial factors in terms of lateral inhibition or other gain controls that influence color signals. In contrast, recent physiological research emphasizes that retinal spatial processing is complex, sending multiple types of spatial signals to the brain [14,15]; some visual cortex processes seem sensitive to color, while others seem sensitive to color/luminance contrast [16,17]; and color in the dorsal and ventral pathways seems to serve different functions [18,19]. The resolution of the separate spatial responses leads to what has been termed ‘the spatial frequency binding problem’ [20]. That is, the early visual system encodes information at different spatial scales, and the later visual system combines the encoded information in ways appropriate for particular visual tasks. Because of the interdependence of color and space, selection of the appropriate spatial information greatly influences how color is perceived. Here, we discuss three spatial aspects of color: modes of appearance, color versus color contrast, and information at different spatial scales. Modes of appearance
Color often takes on multiple modes of appearance (brightness, lightness, saturation, transparency, scission, shininess, etc.) that can occur in the same spatial location: Figure 2
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Current Opinion in Behavioral Sciences
Color can have multiple modes of appearance. In the Long-Range Argyles stimulus [23,24], a uniform field is divided by three columns of small black and white triangles. Area (a) is between the left column and center column; area (b) is between the center column and the right column. The uniform field does not appear uniform; rather, the area labeled (a) appears as a dark surface in bright illumination, and the area labeled (b) appears as a light surface in shadow. Current Opinion in Behavioral Sciences 2019, 30:149–155
152 Visual perception
‘“[T]wo different colour appearances can be simultaneously present at the same ‘location’ as distinctive aspects of the percept’ [21,22]. For instance, Figure 2, Long-Range Argyles [23,24], shows the complexity of translating multiple perceptual modes into a single perceptual term. Three columns of black and white triangles are placed on a uniform gray background, but
the background does not appear uniform; rather, region A appears as a dark surface under bright illumination, and region B appears as a bright surface in shadow. Curiously, when asked which region is brighter, about 1/3 of respondents report region A while 2/3 report region B (personal observations suggest that this ratio could be highly variable). So, each pixel can be represented on multiple
Figure 3
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Out of phase In phase Out of phase Current Opinion in Behavioral Sciences
Points on a center/surround stimulus can be described in terms of color and rectified color contrast. (a) The center disks have the same pixel value; the disk on the left is yellow with high contrast relative to the surround, and the disk on the right is yellow with low contrast relative to the surround. (b) A basic Contrast Asynchrony paradigm [26]: one disk with a bright surround, and the other with a dark surround; the color/luminance levels of the disks are identical (as in Figure 3(a)) but change from dark to light over time; therefore, the luminance values modulate in phase, and the contrast values modulate in antiphase. (c) The Contrast Asynchrony stimuli represented in a contrast versus luminance plane. (d) Hedjar et al. [28] Remote Controls illusion: thin edges cause the asynchronous appearance to disappear or reappear. (e) Takahashi [30] Curvature Blindness illusion: contrast information can lead to different interpretations of shape and direction. Current Opinion in Behavioral Sciences 2019, 30:149–155
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Color illusion as a spatial binding problem Shapiro and Hedjar 153
perceptual dimensions, and translation to a single perceptual dimension may prove to be a source of discrepancy.
Figure 4
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Any point in a visual image can be described along multiple physical dimensions. For instance, in a simple disk and ring configuration (Figure 3a), each pixel on the disk has both a luminance/chromaticity value and a contrast value relative to the surround (a spatial derivative, [25]). The Contrast Asynchrony paradigm [26,27] places these two dimensions in opposition. In the basic version of the paradigm (Figure 3a), one disk is surrounded by a dark ring, and the other by a light ring. When disk luminance is modulated sinusoidally in time (Figure 3b), the luminance values modulate in phase, and the contrast values modulate in antiphase; the stimulus therefore traces two different lines in a color versus color contrast plane (Figure 3c). The two physical dimensions (luminance and contrast) correspond to two different perceptual modes: the disks appear to get light and dark at the same time (luminance) and appear to alternate out of phase (contrast). The way the visual system seems to resolve the conflict between these two dimensions depends upon subtle contextual differences. For instance, Hedjar et al.’s ([28]; also Ref. [29]) Remote Controls illusion (Figure 3d) shows that minute changes at points distant from the modulating bars can lead to sudden switches from in-phase perception to out-ofphase perception. Furthermore, contrast information can lead to different interpretations of shape and direction. Takahashi’s [30] Curvature Blindness illusion (Figure 3e) shows massive changes in direction based on contrast. The directional interpretation may be related to individual processing units [31], but even if so, the inputs to these units will have at least two different physical dimensions. Information at different spatial scales
Each pixel value in an image can also be considered as the sum of multiple spatial frequency components. Indeed, many aspects of most — not all [32] — standard color and brightness illusions can be explained simply by considering the image at a particular spatial bandwidth (e.g. Refs. [13,33,34–36]). In Figure 4a, the colors of the hearts in Kitaoka’s [37] assimilation illusion are identical at a pixel level but physically different in the low spatial frequency range, whereas the two squares in Purves and Lotto’s [38] Rubik’s cube are identical at a pixel level but physically different in the high spatial frequency range. The spatial frequency ranges can be interchanged across images to show that different spatial bands carry different types of information. In Figure 4b, evening and morning images of Monet’s Rouen cathedral have been decomposed into high and low spatial frequency components. When the low spatial frequency is swapped, the resulting images appear as the morning cathedral painted under www.sciencedirect.com
Original illiusion
After application of spatial filter (b)
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Decompose into high and low frequency components Swap low frequency components Reconstruct image Current Opinion in Behavioral Sciences
In most standard color and brightness illusions, test patches have the same pixel value yet are physically different at some spatial bandwidth. (a) Kitaoka [37] ‘Blue-to-purple heart and green-to-orange heart’ illusion: an assimilation illusion in which the hearts are physically different in the low spatial frequency components. And Purves and Lotto [38] Rubik’s cube illusion: an assimilation illusion, in which the test squares are different in the high spatial frequency components. (b) Evening and morning images of Monet’s cathedral at Rouen decomposed into high and low spatial frequency components: when the low spatial frequency is swapped, the resulting images appear as the morning cathedral painted under evening illumination, and the evening cathedral painted under morning illumination.
evening illumination, and the evening cathedral painted under morning illumination.
Conclusion The standard definition of the term ‘illusion’ is problematic because our perception is never an exact copy of reality. Here, we base our definition of ‘illusion’ on the idea that a single representation of the physical environment is not always the only solution, and the brain is therefore sometimes forced either to oscillate between representations or to privilege one source of physiological response over others; under non-illusory conditions, the brain selects as ‘reality’ a single consistent representation that ‘best’ integrates information from multiple processes. Current Opinion in Behavioral Sciences 2019, 30:149–155
154 Visual perception
Illusions arise from the conflict between possible representations. The role of conflict in perception has a long history [39]: a stick in semi-submerged water looks bent but feels straight when we touch it with our hands; the experience is compelling since the interpretations of vision and touch conflict with each other, which suggests a need for resolution. It is reasonable to suppose that our appreciation of an ‘illusion’ represents the brain’s response to stimuli that activate one or more of the brain’s several systems that seem to respond to mismatches between different encodings (e.g. Refs. [40–42]).
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Every point in an image can be considered in terms of multiple physical dimensions (e.g. luminance/chromaticity; color and color contrast; low, mid-range and high spatial frequencies). Low spatial frequency content tends to carry information about global illumination; mid-range spatial frequency content tends to carry illuminationinvariant information about object color (particularly when there is a single illuminant, and interreflection isn’t present); and high spatial frequency content tends to carry illumination-invariant information about edges [33]. Luminance and luminance contrast correspond to different types of invariance in the environment: contrast between an object and its background remains constant as illumination changes, whereas luminance remains constant when an object moves from one background to another [43,44]. It is truly remarkable that the brain manages to encode and seamlessly integrate information from across all these dimensions as often as it does.
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The definition for ‘illusion’ proposed here suggests that many color illusions are examples of the spatial frequency binding problem [20] — that is, the visual system is capable of encoding color information at different spatial scales and contrasts; color illusions often arise because the brain combines spatial information differently depending on the visual tasks; and these combinations often conflict with our idea of color as invariant and separate from space. We believe that by examining how the visual system resolves or fails to resolve spatial binding, researchers can develop potential solutions to practical problems concerning individual differences (e.g. Ref. [33]) and concerning perception in healthy and unhealthy visual systems.
Conflict of interest statement Nothing declared.
References and recommended reading Papers of particular interest, published within the period of review, have been highlighted as: of special interest of outstanding interest 1.
Braddick O: Illusion research: an infantile disorder? Perception 2018, 47:805-806.
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10. Purves D, Wojtach WT, Lotto RB: Understanding vision in wholly empirical terms. Proc Natl Acad Sci U S A (108 Suppl 3):2011:15588-15595. 11. Morgan MJ: Visual illusions. In Unsolved Mysteries of the Mind: Tutorial Essays in Cognition. Edited by Bruce V. Psychology Press; 1996:29-58. 12. Hoffman DD: Human Vision as a Reality Engine. . Retrieved from Washington, DC: Foundation for the Advancement of Behavioral and Brain Sciences; 2010 http://www.cogsci.uci.edu/ddhoff/ HoffmanFABBS.pdf. 13. Shapley R, Nunez V, Gordon J: Cortical double-opponent cells and human color perception. Curr Opin Behav Sci 2019, 30:1-7 A paper published in this issue of COBEHA. The article discusses other options for the integration of color and space, stressing the role of singleopponent and double-opponent cortical cell substrates. The argument the authors put forward is extraordinarily important because it emphasizes the interactions between color and space, the multivariate responses of the cortical color response, and adaptation levels. 14. Masland RH, Martin PR: The unsolved mystery of vision. Curr Biol 2007, 17:R577-R582. 15. Turner MH, Schwartz GW, Rieke F: Receptive field center surround interactions mediate context-dependent spatial contrast encoding in the retina. eLife 2018, 7 http://dx.doi.org/ 10.7554/eLife.38841 Center-surround receptive fields are — in effect — adaptive spatial bandpass filters: changes in the size of the center increase/decrease the high spatial frequency response; changes in the size of the surround increase/ decrease the low spatial frequency response (this fact seems well understood in the signal processing literature, but less so in the physiological/ behavioral literature). This paper shows that receptive field ‘architecture has an important consequence for spatial contrast encoding in the macaque monkey retina: the surround can control sensitivity to fine spatial structure by changing the way the center integrates visual information over space.’ The authors conclude that ‘the surround plays unappreciated roles in shaping ganglion cell sensitivity to natural inputs.’ 16. Johnson EN, Hawken MJ, Shapley R: The orientation selectivity of color-responsive neurons in macaque V1. J Neurosci 2008, 28:8096-8106. 17. Johnson EN, Hawken MJ, Shapley R: The spatial transformation of color in the primary visual cortex of the macaque monkey. Nat Neurosci 2001, 4:409-416. 18. Conway BR: Color signals through dorsal and ventral visual pathways. Visual Neurosci 2014, 31:197-209. 19. Liu J, Wandell BA: Specializations for chromatic and temporal signals in human visual cortex. J Neurosci 2005, 25:3459-3468. www.sciencedirect.com
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20. Burge J, Rodriguez-Lopez V, Dorronsoro C: Monovision and the misperception of motion. Curr Biol 2019, 29:2586-2592 http:// dx.doi.org/10.1016/j.cub.2019.06.070 Burge et al. show that blurring the image to one eye leads to an unexpected ‘reverse’ Pulfrich effect — reversed because blur reduces contrast and therefore should lead to a Pulfrich effect in the opposite direction. The authors account for this by proposing ‘i) blur reduces the contrast of high-frequency image components more than low-frequency image components, and ii) high spatial frequencies are processed more slowly than low spatial frequencies, all else equal.’ The paper proposes the idea of a ‘spatial frequency binding problem,’ which we consider fundamental to understanding many aspects of visual function, including those that lead to color illusions. 21. Katz D: The World of Colour. Routledge. (1935/2013). 22. Mausfeld R: The dual coding of colour: “Surface colour” and “illumination colour” as constituents of the representational format of perceptual primitives. In Colour: Mind and the Physical World. Edited by Mausfeld R, Heyer D. Oxford University Press. [RM]; 2003 . Retrieved from http://citeseerx.ist.psu.edu/ viewdoc/download?doi=10.1.1.134.306&rep=rep1&type=pdf. 23. Flynn OJ, Shapiro AG: A note concerning the relationship between Adelson’s argyle illusion and Cornsweet edges. Psihologija 2014, 47:353-358. 24. Shapiro AG, Todorovic D: Introduction. In The Oxford Compendium of Visual Illusions. Edited by Shapiro AG, Todorovic D. Oxford University Press; 2017:xix-xxiii. 25. Rose-Henig A, Shapiro AG: Contrast–contrast asynchronies. JOSA A 2014, 31:A232-A238. 26. Shapiro AG: Separating color from color contrast. J Vis 2008, 8:8.1-18. 27. Shapiro AG, D’Antona A, Smith JB, Belano LA, Charles JP: Induced contrast asynchronies may be useful for luminance photometry. Visual Neurosci 2004, 21:243-247. 28. Hedjar L, Cowardin V, Shapiro AG: Remote controls illusion: strange interactions across space cannot be explained by simple contrast filters. J Opt Soc Am A Opt Image Sci Vis 2018, 35:B152-B164 Another paper from our lab presents dramatic variations on the Contrast Asynchrony paradigm, which demonstrate 1) a separation of color and color contrast, and 2) that small edges — sometimes at some distance from the modulation fields — can make the asynchronous appearance disappear. The visual system’s weighting of color and color contrast information can therefore be affected by small contextual changes in the stimulus. 29. Shapiro AG, Leaver AM: Edges can eliminate the appearance of the contrast asynchrony. Ophthalmic Physiol Opt 2010, 30:534544. 30. Takahashi K: Curvature blindness illusion. I-Perception 2017, 8 2041669517742178 The paper presents a new illusion, in which wavy lines on different backgrounds appear to take on different shapes and orientations. The illusion is important because it demonstrates the effects of contrast polarity on shape — that is, that the discontinuity of contrast polarity
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at the turning point of the wavy line affects some but not all curvatures. Anderson and Burr (‘Visual Perception: To Curve or Not to Curve’ 2018, Current Biology, 28, 4R150-R152) argue that the illusion demonstrates segmentation mechanisms of human vision. 31. Anderson BL, Burr DC: Visual perception: to curve or not to curve. Curr Biol 2018, 28:R150-R152. 32. Betz T, Shapley R, Wichmann FA, Maertens M: Noise masking of White’s illusion exposes the weakness of current spatial filtering models of lightness perception. J Vis 2015, 15:1. 33. Dixon EL, Shapiro AG: Spatial filtering, color constancy, and the color-changing dress. J Vis 2017, 17:7 A paper from our lab concerning the color-changing dress. Unlike other papers that propose that individual differences arise from color constancy strategies, this paper suggests that there are individual differences for processing low spatial frequency content, just as there are individual differences for processing high spatial frequency content. A demo included in the paper shows that for simple conditions, global illumination is entirely contained in an image’s low spatial frequency range; thus, in such conditions, the removal of low spatial frequency content leads directly to color constancy. 34. Shapiro A, Hedjar L, Dixon E, Kitaoka A: Kitaoka’s tomato: two simple explanations based on information in the stimulus. IPerception 2018, 9 2041669517749601. 35. Shapiro A, Lu Z-L: Relative brightness in natural images can be accounted for by removing blurry content. Psychol Sci 2011, 22:1452-1459. 36. Zeman A, Brooks KR, Ghebreab S: An exponential filter model predicts lightness illusions. Front Hum Neurosci 2015, 9:368. 37. Kitaoka A: “Blue-to-purple heart and green-to-orange heart” from The latest works 60 website. 2019 http://www.psy.ritsumei.ac.jp/ akitaoka/saishin61e.html. 38. Purves D, Lotto RB: Why We See What We Do: An Empirical Theory of Vision. 1st edition. Sinauer Associates; 2003. 39. Burnyeat M: Conflicting appearances. In Proceedings of the British Academy 1981, vol 6569-111: 1979. 40. Alexander WH, Brown JW: The role of the anterior cingulate cortex in prediction error and signaling surprise. Top Cogn Sci 2019, 11:119-135. 41. Mansouri FA, Tanaka K, Buckley MJ: Conflict-induced behavioural adjustment: a clue to the executive functions of the prefrontal cortex. Nat Rev Neurosci 2009, 10:141-152. 42. Popa LS, Ebner TJ: Cerebellum, predictions and errors. Front Cell Neurosci 2018, 12:524. 43. Brown RO: Background and illuminants: the yin and yang of colour constancy. In Colour Perception: Mind and the Physical World. Edited by Mausfeld R, Heyer D. Oxford University Press; 2003:247-272. 44. Whittle P, Mausfeld R, Heyer D: Contrast colours. Colour Percept: Mind Phys World 2003:115-138.
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