- Email: [email protected]
Evolved navigation theory and horizontal visual illusions
Cognition 119 (2011) 288–294
Contents lists available at ScienceDirect
Cognition journal homepage: www.elsevier.com/locate/COGNIT
Brief article
Evolved navigation theory and horizontal visual illusions Russell E. Jackson ⇑, Chéla R. Willey Psychology Department, California State University San Marcos, United States
a r t i c l e
i n f o
Article history: Received 8 July 2010 Revised 31 October 2010 Accepted 5 November 2010 Available online 27 November 2010 Keywords: Distance perception Evolution Evolved navigation theory Illusion Navigation
a b s t r a c t Environmental perception is prerequisite to most vertebrate behavior and its modern investigation initiated the founding of experimental psychology. Navigation costs may affect environmental perception, such as overestimating distances while encumbered (Solomon, 1949). However, little is known about how this occurs in real-world navigation or how it may have evolved. We manipulated the most commonly navigated surfaces with a non-intuitive cost derived from evolved navigation theory. Observers in realistic settings unknowingly overestimated horizontal distances that contained a risk of falling and did so by the relative degree of falling risk. This manipulation produced previously unknown, large magnitude illusions in everyday vision in the environments most commonly navigated by humans. These results bear upon predictions from multiple fundamental theories of visual cognition. Ó 2010 Elsevier B.V. All rights reserved.
1. Introduction Environmental perception occurs throughout most animal behavior and nearly constantly during all human waking hours. Environmental distance perception research shaped the foundation of experimental psychology (see Hicks & Rivers, 1906; Wundt, cited by Winslow (1933)) and its specificity suggests design typical of adaptation by natural selection (Tooby & Cosmides, 1992; Williams, 1966). Unfortunately, there are fundamental inconsistencies in environmental perception. For example, humans perceive horizontal distances roughly accurately, but overestimate vertical distances (Chapanis & Mankin, 1967; Higashiyama, 1996; Jackson & Cormack, 2008; Wu, Ooi, & He, 2004). Here we address this fundamental inconsistency by testing broad cognitive theories of distance estimation. Many cognitive scientists suggest that navigational costs shape distance perception. Navigational costs include energetic demand, injury risk, and time investment. Overestimation of routes with high navigational costs has been thought to prevent the observer from incurring those ⇑ Corresponding author. Address: Psychology Department, California State University San Marcos, 333 South Twin Oaks Valley Road, San Marcos, CA 92096, United States. Tel.: +1 760 750 8568. E-mail address: [email protected] (R.E. Jackson). 0010-0277/$ - see front matter Ó 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.cognition.2010.11.003
costs because observers tend to navigate the shortest of otherwise equivalent routes (Jackson, in preparation). Use of such logic appears as early as Solomon’s (1949) findings that weighted backpacks may induce distance overestimation and it continues today (Howard & Templeton, 1966; Jackson, 2005; Proffitt, Bhalla, Gossweiler, & Midgett, 1995; Sadalla & Magel, 1980). Navigation costs are particularly important on vertical surfaces, where investigation of falling risks led to the discovery of some of the largest known real-world distance illusions. Whereas classic illusions (Müller–Lyer, vertical– horizontal, Ponzo) exhibit magnitudes of roughly 10%, illusions in response to falling regularly exceed 30%. For example, the environmental vertical illusion (magnitude up to 51%) occurs such that individuals overestimate surfaces that pose falling risks, but do not overestimate retinally equivalent surfaces without falling risks (Jackson & Cormack, 2008). The magnitude of these illusions relates to the likelihood and severity of a fall: the descent illusion (magnitude up to 84%) occurs in situations where the observer is most likely to fall to the greatest injury (Jackson, 2005; Jackson & Cormack, 2007). These illusions may produce fear of heights (Jackson, 2009) and they disappear when falling risks are removed (Jackson & Cormack, 2010).
R.E. Jackson, C.R. Willey / Cognition 119 (2011) 288–294
Researchers predicted the above illusions from a research approach titled evolved navigation theory (ENT), which focuses on how navigation costs over evolutionary time may shape environmental cognition and navigation (Jackson, 2005; Jackson & Cormack, 2007). Although ENT has been applied recently to the navigation cost of falling, it encompasses all sources of navigation costs, such as energetic and time demands. Most research on real-world distance illusions focuses on perception of vertical or inclined surfaces (Dominguez, 1954; Hicks & Rivers, 1906; Higashiyama & Ueyama, 1988; Hoover, Bridgeman, & Thomas, in preparation; Jackson, 2009; Kammann, 1967; Raudsepp, 2002; Wober, 1972). Unfortunately, this excludes the surfaces most commonly encountered and navigated—those environmentally horizontal or nearly so. This limits generalizability of this broad research area in a foundational component to cognition. The current research applies the most significant identified navigational costs to the most commonly navigated environments. This is not intuitive because it applies falling risks to horizontal surfaces. However, if such navigational costs truly generate the large magnitude distance illusions as suggested, then such costs might also increase the distance perceived from horizontal surfaces. This would affect the perception of the majority of environments navigated by terrestrial organisms, including humans. One method for applying falling costs to a horizontal surface is to use a horizontal surface that borders a cliff. The navigation of such a surface poses a falling risk, even though the surface is horizontal. If falling costs affect horizontal distance perception (ENT), then observers should overestimate such a surface, but not a similar one without falling risk.
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ENT Prediction 1: Observers will estimate accurately the distance of the surface without falling risks. ENT Prediction 2: Observers will overestimate the distance of the surface with falling risks. We plot predictions simultaneously with observed data below. The proposed method also tests the predictions of other clusters of visual cognition theories. From effortbased theories (see Solomon, 1949; Yang, Dixon, & Proffitt, 1999), we predict no distance perception differences across the surfaces tested here due to invariant navigation effort. From direct perception or ecological approaches, we predict no illusions because the surfaces consist of full cue, real-world conditions (see Gibson, 1966, p. 313; Michaels & Carello, 1981, p. 92). From retinal image and probabilistic approaches (see Geisler, Perry, Super, & Gallogly, 2001; Yang & Purves, 2003), we predict no distance estimation difference due to the roughly invariant retinal image across conditions. All of these competing theories convergently predict no distance perception differences across horizontal surfaces that contain variable falling risks.
2. Experiment 1 2.1. Method Fifty-seven participants volunteered in order to fulfill undergraduate research participation requirements. Participants estimated, via distance matching, a 5.48 m distance across two horizontal surfaces: one with, and one without, falling risks.
Fig. 1. Overhead view of Experiment 1. Both estimated distances measured 5.48 m. A indicates the falling risk surface estimate located on a 6.07 0.23 m board 1.07 m above the ground. B indicates the non-falling risk surface estimate on solid ground. An open circle indicates observer positions while making each estimate (the upper circle for the falling risk surface and the lower circle of the non-falling risk surface). X indicates the point of origin and a dashed arrow indicates the direction that the researcher walked for an observer’s estimates. Observers directed the researcher to walk out until the distance from the point of origin to the researcher looked the same as the distance being estimated (either A or B).
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2.1.1. Distance matching Participants indicated a distance that looked equal to the length of the estimated surface. They directed (via hand signals) a researcher to walk out until the distance from the researcher to a fixed dot looked the same as the length of the estimated surface. Participants received unlimited time to make as many adjustments as they liked. Researchers use similar distance matching methods widely in studies with realistic outdoor settings because such methods likely provide the clearest analog to the percept (Chapanis & Mankin, 1967; Higashiyama, 1996; Jackson & Cormack, 2006; Yang et al., 1999). 2.1.2. Falling risk surface The falling risk surface appeared along a board that spanned a 5.48 m gap across two stages 1.07 m above
ground. The board measured 6.07 0.23 m, with the 5.48 m estimated distance occupying the center of the board between two painted dots. An aluminum ladder kept the length of the board level. The surface upon which participants stood and gave estimates was a 12.19 1.22 m stage oriented perpendicular to the board. Participants stood at the end of the board and near the end of the stage (Fig. 1). 2.1.3. Non-falling risk surface The non-falling risk surface appeared along solid ground facing away from the stage. Two painted dots indicated the 5.48 m distance to estimate. The surface upon which participants estimated was solid ground perpendicular to the length of the non-falling risk surface. Participants stood at the intersection of the estimated surface and the surface over which they made their estimates (Fig. 1).
Fig. 2. Experiment 1 predicted (top) and observed estimates (bottom, mean ± 95% CI). Predictions (top) consist of relative magnitudes, with those of ENT appearing in white and those of competing theories in black. Dashed lines represent actual distance.
R.E. Jackson, C.R. Willey / Cognition 119 (2011) 288–294
We alternated estimate order across participants, with roughly half first estimating the non-falling risk surface and half the falling risk surface. The current method of estimating the same distance across two surfaces without seeing previous estimates resolved an artificial interdependency present in a pilot study in which we used a board for the falling risk surface and then, within view of the participant, moved that same board to the ground for them to estimate as the non-falling risk surface. Participants also made estimates unrelated to the current study and completed a demographic questionnaire. 2.2. Results Participants overestimated the length of the falling risk surface, but not the non-falling risk surface (Fig. 2). Falling risk surface estimates (M = 6.60 ± 0.29 m [95% CI]) significantly differed from actual distance (5.48 m), t (56) = 7.69, p < 0.001. Non-falling risk surface estimates (M = 5.34 ± 0.30 m) did not significantly differ from actual distance, t (56) = 0.96, p = 0.34. Estimates of the two surfaces significantly differed from one another, t (56) = 6.748, p < 0.001. Participants overestimated the falling risk surface by 1.26 m (23.7%, d = 1.12) more than the non-falling risk surface. Participants who first estimated the falling risk surface gave slightly longer estimates for the falling risk and non-falling risk surfaces (0.95 and 0.50 m, respectively) than participants who first estimated the non-falling risk surface. This effect was small in comparison to the distances estimated and did not bear upon any experimental predictions.
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ENT Prediction 3: Horizontal overestimation magnitude will correspond to the relative degree of falling risk. In addition to the unique effects proposed under this prediction, any method of testing it also tests Predictions 1 and 2—making it increasingly difficult to support by random chance. Further, a high falling cost surface must be estimated to be, not only longer than a moderate falling cost surface, but also longer than low and non-falling cost surfaces. This increases the random chance of violating this prediction exponentially by the number of comparisons, posing a very high threshold for support. The three clusters of competing theories (effort-based, direct perception, and retinal/probabilistic approaches) again predict a null effect. Participants should not overestimate any distance, certainly not by the relative degree of falling risk, according to these theories. 3.1. Method Seventy-nine participants volunteered for the study in order to fulfill college course-participation requirements. Participants estimated a 4.39 m distance via distance matching across four horizontal surfaces of high, moderate, low, and no falling risks (Fig. 3). 3.1.1. High falling risk Spanned the width (4.39 m) of a dry ditch 1.16 m deep. Two painted dots on the edges of the ditch indicated the 4.39 m distance to estimate. This surface posed relatively high falling costs due the depth of the ditch and lack of alternative routes for navigating the distance.
2.3. Discussion Participants accurately estimated horizontal surface length without falling costs, but clearly overestimated an equal horizontal surface with falling costs. These data are indistinguishable from ENT predictions (Fig. 2) and contradict predictions from other theories. This is a novel finding. The most common surfaces navigated by humans appear subject to large illusions and from a previously unanticipated source. Given the pervasiveness of navigation in most other behaviors, these findings bear upon broad human activity and potentially most non-human terrestrial animal behavior.
3.1.2. Moderate falling risk Spanned the ground bordering the end of the ditch where the ditch passed into a drainage pipe. Two painted dots indicated the 4.39 m distance to estimate. This surface posed relatively moderate falling costs due to flat ground
3. Experiment 2 The magnitude of (vertical) distance illusions proposed under ENT reflects the likelihood or severity of a fall (Jackson, 2009; Jackson & Cormack, 2007, 2008, 2010). Observers most overestimate vertical surfaces the navigation of which are most likely to result in a fall. Given that observers overestimate vertical surfaces proportionate to falling risk, and given the current observation that falling risks affect horizontal estimation, we predicted that observers should overestimate a horizontal surface by the degree to which it poses falling costs. Observers should overestimate surfaces with low and high falling risks by small and large amounts, respectively.
Fig. 3. Overhead view of Experiment 2. All estimated distances measured 4.39 m. High falling risk surface (A) spanning the 1.16 m deep ditch. Moderate falling risk surface (B) along the edge of the ditch. Low falling risk surface (C) along the top of a .15 m tall freestanding curb. Non-falling risk surface (D) along solid ground. The open circle indicates observer position during all four estimates. The dashed arrow indicates the direction that the researcher walked for all four estimates.
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Fig. 4. Experiment 1 predicted (top) and observed estimates (bottom, mean ± 95% CI). Predictions (top) consist of relative magnitudes, with those of ENT appearing in white and those of competing theories in black. Dashed lines represent actual distance.
on one side of the surface, but the deep ditch on the other side of the surface. 3.1.3. Low falling risk Spanned a length of nearby curb 0.15 m tall. Two painted dots on top of the curb indicated the 4.39 m distance to estimate. This posed relatively low falling costs due to the short height on either side of this freestanding curb. 3.1.4. Non-falling risk Appeared along solid ground parallel to, but apart from, the length of the ditch. The ditch did not appear in participants’ visual field while estimating this surface. Two painted dots indicated the 4.39 m distance to estimate. This surface posed no falling costs due to its location on level ground. Participants stood at the same fixed point for all estimates. The surface upon which participants estimated
extended in front of them and posed no falling costs. Estimate order was high falling risk surface, low falling risk surface, moderate falling risk surface, non-falling risk surface. We were able to order estimates differently than the predicted magnitude sequency in order to partially control for order effects. Order effects have not impacted similar predicted effects in similar previous studies (Jackson, 2009; Jackson & Cormack, 2007, 2008; Jackson & Willey, submitted for publication). Estimates were part of a larger study. 3.2. Results Participants only overestimated surfaces with falling risks. Overestimation magnitude increased as the falling risk magnitude increased (Fig. 4). Compared to the non-falling risk surface, participants overestimated the low falling risk surface by 0.37 m (9.0%,
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d = 0.54), moderate falling risk surface by 0.67 m (16.2%, d = 0.82), and high falling risk surface by 1.92 m (46.5%, d = 1.46). All estimates differed significantly from one another, F (3234) = 54.74, p < 0.001. Non-falling risk surface estimates significantly differed from estimates of the low falling risk surface, t (78) = 3.79, p < 0.001. Low falling risk surface estimates significantly differed from estimates of the moderate falling risk surface, t (78) = 2.89, p = 0.005. Moderate falling risk surface estimates significantly differed from estimates of the high falling risk surface, t (78) = 6.48, p < 0.001. High falling risk surface estimates (M = 6.05 ± 0.40 m [95% CI]) significantly differed from the actual distance (4.39 m), t (78) = 8.26, p < 0.001. Moderate falling risk surface estimates (M = 4.80 ± 0.23 m) significantly differed from the actual distance, t (78) = 3.54, p = 0.001. Low falling risk surface estimates (M = 4.50 ± 0.18 m) did not significantly differ from the actual distance, t (78) = 1.19, p = 0.24. Non-falling risk surface estimates (M = 4.13 ± 0.12 m) significantly differed from the actual distance, t (78) = 4.46, p < 0.001. 3.3. Discussion Participants’ distance estimates corresponded with each surface’s relative falling risk without exception. These data coincide with ENT Prediction 3. Observers overestimated surface length to the extent that the surface posed falling risks—even in the most common natural surfaces viewed, and navigated, by humans. Observed estimates fell slightly below predicted estimates (Fig. 4). Given the overall excellent fit with the predicted multi-parameter function, this slight potential underestimate likely stems from a minor methodological component such as anchoring. Many distance perception researchers observe such slight deviations from the intended estimate in natural settings (Bridgeman & Hoover, 2008; Chapanis & Mankin, 1967; Hansen & Essock, 2004; Mankin, 1969; Taylor, 1961). These estimates may also reflect a logarithmic, instead of linear, function—the shape of which nonetheless corresponds to ENT predictions. Comparison across both experiments reinforces the interpretation that falling risk produces overestimates of horizontal surfaces by degree of falling risk. The Experiment 1 falling risk surface most resembled the Experiment 2 open gap (high falling risk) condition. The magnitude of overestimation across these conditions increased from Experiment 1 to 2. This is exactly what one would expect from the current predictions, given that the plank in Experiment 1 facilitates navigating the gap, while the lack of such a surface in Experiment 2 increases falling risk. Comparison across other studies reinforces this interpretation. The magnitude of falling risk illusions on vertical surfaces mirrors the magnitude of horizontal illusions discovered here. Current participants did not overestimate surfaces without falling risk and ranged from 9% overestimation at low falling risks to 47% at high falling risks. This is nearly the exact range found for the corresponding situations in vertical surfaces (Jackson & Cormack, 2008). Environments (and individuals) exhibiting even greater
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falling risk or avoidance are the exact situations in which overestimation magnitude exceeds the range found here (Jackson, 2009; Jackson & Cormack, 2007).
4. General discussion Participants overestimated the most commonly navigated surfaces only when those surfaces posed a risk of falling. Overestimation magnitude reflected the degree of falling risk present in the surface. Horizontal surfaces far outnumber vertical surfaces in human environments and so this research explains a previously unknown factor present in most human navigation. Horizontal surfaces in general, and those with falling risks in particular, are exceedingly common in human and non-human terrestrial navigation. The frequency that an average person traverses stairs, a sloped path, or a curb numbers tens to hundreds or thousands of times in an average day. Counting the number of hand railings, graded surface angles, and fences bordering vertical surfaces identifies a vast number of such safety devices intended to prevent the costs resulting from navigating a world full of horizontal surfaces with falling costs. Without such safety devices in the environments in which humans evolved, horizontal surfaces with falling costs were likely ubiquitous. The illusions identified here explain how we interpret these exceedingly common surfaces in ways previously unknown. Only from an inclusive navigation theory that includes risk of falling (ENT) did we predict the observed data. We do not suggest that this replaces probabilistic approaches to vision, nor replaces the idea that retinal information is essential in distance perception. Instead, these data expand probabilistic approaches by identifying non-retinal information required for realistic vision. This appears essential for integrating previously independent visual domains. The logic from which we derived the current predictions appears in multiple sources several years prior to these experiments (Jackson, 2005, 2009, in preparation; Jackson & Cormack, 2007, 2008, 2010). This strength in prediction may stem from evolution by natural selection imposing additional criteria not normally utilized in this domain. In order for the adaptations discovered here to have evolved as specified by ENT, (1) there must have been sufficient distance estimation variation over evolutionary time that was, (2) heritable and, (3) tied to differential reproduction—implying that, (4) falling risks must have been present in horizontal surfaces over sufficient evolutionary time, (5) there must have been sufficient costs from falling, and (6) sufficient adaptive benefits from the observed illusion. Finding the predicted adaptation(s) in the current study lends support to the above conditions, each of which now creates further testable predictions. The high predictive specificity of evolution by natural selection may generate more information than non-evolutionary approaches. Environmental interpretation and distance perception are precursors to most human and non-human animal behavior. Nonetheless, we predicted and then discovered a novel phenomenon that occurs throughout the majority
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of human navigation and environmental cognition. The earliest modern research in these fields (Fick 1851, cited in Finger and Spelt (1947)) precedes the founding of experimental psychology. However, the theory-driven nature of this investigation integrated previously disparate researches and poses previously unavailable inroads into this fundamental area of cognitive science.
Acknowledgements We thank Theresa Cook, Erin Drasil, Ryan Sulman, and David Vazquez for gathering data. We also thank two anonymous reviewers for their comments.
References Bridgeman, B., & Hoover, M. (2008). Processing spatial layout by perception and sensorimotor interaction. The Quarterly Journal of Experimental Psychology, 61(6), 851–859. doi:10.1080/ 17470210701623712. Chapanis, A., & Mankin, D. A. (1967). The vertical–horizontal illusion in a visually-rich environment. Perception & Psychophysics, 2(6), 249–255. Dominguez, K. E. (1954). A study of visual illusions in the monkey. Journal of Genetic Psychology, 85, 105–127. Finger, F. W., & Spelt, D. K. (1947). The illustration of the horizontal– vertical illusion. Journal of Experimental Psychology, 37, 243–250. Geisler, W., Perry, J., Super, B., & Gallogly, D. (2001). Edge co-occurrence in natural images predicts contour grouping performance. Vision Research, 41, 711–724. Gibson, J. J. (1966). The senses considered as perceptual systems. Boston: Houghton Mifflin Company. Hansen, B. C., & Essock, E. A. (2004). A horizontal bias in human visual processing of orientation and its correspondence to the structural components of natural scenes. Journal of Vision, 4, 1044–1060. doi:10.1167/4.12.5. Hicks, G. D., & Rivers, W. H. R. (1906). The illusion of compared horizontal and vertical lines. British Journal of Psychology, 2, 243–260. doi:10.1037/h0063886. Higashiyama, A. (1996). Horizontal and vertical distance perception: The discorded-orientation theory. Perception & Psychophysics, 58(2), 259–270. Higashiyama, A., & Ueyama, E. (1988). The perception of vertical and horizontal distances in outdoor settings. Perception & Psychophysics, 44, 151–156. Hoover, M., Bridgeman, B., & Thomas, K. (in preparation). Slope perception in near and far space. Howard, I. P., & Templeton, W. B. (1966). Human spatial orientation. New York: Wiley. Jackson, R. E. (2005). Falling towards a theory of the vertical–horizontal illusion. Studies in Perception and Action, 8, 241–244.
Jackson, R. E. (2009). Individual differences in distance perception. Proceedings of the Royal Society B: Biological Sciences, 276, 1665–1669. doi:10.1098/rspb.2009.0004. Jackson, R. E. (in preparation). Preference for the nearer of otherwise equivalent goals. Jackson, R. E., & Cormack, L. K. (2006). Previously unknown illusion predicted by evolved navigation theory [Abstract]. Journal of Vision, 6(6), 962. Jackson, R. E., & Cormack, L. K. (2007). Evolved navigation theory and the descent illusion. Perception & Psychophysics, 69(3), 353–362. Jackson, R. E., & Cormack, L. K. (2008). Evolved navigation theory and the environmental vertical illusion. Evolution and Human Behavior, 29(5), 299–304. doi:10.1016/j.evolhumbehav.2008.03.001. Jackson, R. E., & Cormack, L. K. (2010). Reducing the presence of navigation risk eliminates strong environmental illusions. Journal of Vision, 10(5), 1–8. doi:10.1167/10.5.9. Jackson, R. E. & Willey, C. R. (submitted for publication). Learning, exposure, and evolved navigation costs: Testing competing theories. Kammann, R. (1967). The overestimation of vertical distance and slope and its role in the moon illusion. Perception & Psychophysics, 2(12), 585–589. Mankin, D. A. (1969). The influence of perceptual anchors and visual noise on the vertical–horizontal illusion. Perception & Psychophysics, 5(3), 149–154. Michaels, C. F., & Carello, C. (1981). Direct perception. Englewood Cliffs, NJ: Prentice-Hall. Proffitt, D. R., Bhalla, M., Gossweiler, R., & Midgett, J. (1995). Perceiving geographical slant. Psychonomic Bulletin & Review, 2(4), 409–428. Raudsepp, J. (2002). Horizontal–vertical illusion: Continuous decrement or the deviant first guess? Perceptual & Motor Skills, 94(2), 599–604. doi:10.2466/PMS.94.2.599-604. Sadalla, E. K., & Magel, S. G. (1980). The perception of traversed distance. Environment and Behavior, 12(1), 65–79. doi:10.1177/ 0013916580121005. Solomon, R. L. (1949). The role of effort in the performance of a distance discrimination. Journal of Experimental Psychology, 39(1), 73–83. Taylor, M. M. (1961). Effect of anchoring and distance perception on the reproduction of forms. Perceptual and Motor Skills, 12, 203–230. Tooby, J., & Cosmides, L. (1992). The psychological foundations of culture. In J. H. Barkow, J. Tooby, & L. Cosmides (Eds.), The adapted mind: Evolutionary psychology and the generation of culture (pp. 19–136). New York: Oxford. Williams, G. C. (1966). Adaptation and natural selection. Princeton, NJ: Princeton University Press. Winslow, C. N. (1933). Visual illusions in the chick. Archives of Psychology, 153, 83. Wober, M. (1972). Horizons, horizontals, and illusions about the vertical. Perceptual & Motor Skills, 34(3), 960. Wu, B., Ooi, T. L., & He, Z. J. (2004). Perceiving distance accurately by a directional process of integrating ground information. Nature, 428(6978), 73–77. doi:10.1038/nature02350. Yang, T. L., Dixon, M. W., & Proffitt, D. R. (1999). Seeing big things: Overestimation of heights is greater for real objects than for objects in pictures. Perception, 28, 445–467. doi:10.1068/p2854. Yang, Z., & Purves, D. (2003). A statistical explanation of visual space. Nature Neuroscience, 6(6), 632–640.
Contents lists available at ScienceDirect
Cognition journal homepage: www.elsevier.com/locate/COGNIT
Brief article
Evolved navigation theory and horizontal visual illusions Russell E. Jackson ⇑, Chéla R. Willey Psychology Department, California State University San Marcos, United States
a r t i c l e
i n f o
Article history: Received 8 July 2010 Revised 31 October 2010 Accepted 5 November 2010 Available online 27 November 2010 Keywords: Distance perception Evolution Evolved navigation theory Illusion Navigation
a b s t r a c t Environmental perception is prerequisite to most vertebrate behavior and its modern investigation initiated the founding of experimental psychology. Navigation costs may affect environmental perception, such as overestimating distances while encumbered (Solomon, 1949). However, little is known about how this occurs in real-world navigation or how it may have evolved. We manipulated the most commonly navigated surfaces with a non-intuitive cost derived from evolved navigation theory. Observers in realistic settings unknowingly overestimated horizontal distances that contained a risk of falling and did so by the relative degree of falling risk. This manipulation produced previously unknown, large magnitude illusions in everyday vision in the environments most commonly navigated by humans. These results bear upon predictions from multiple fundamental theories of visual cognition. Ó 2010 Elsevier B.V. All rights reserved.
1. Introduction Environmental perception occurs throughout most animal behavior and nearly constantly during all human waking hours. Environmental distance perception research shaped the foundation of experimental psychology (see Hicks & Rivers, 1906; Wundt, cited by Winslow (1933)) and its specificity suggests design typical of adaptation by natural selection (Tooby & Cosmides, 1992; Williams, 1966). Unfortunately, there are fundamental inconsistencies in environmental perception. For example, humans perceive horizontal distances roughly accurately, but overestimate vertical distances (Chapanis & Mankin, 1967; Higashiyama, 1996; Jackson & Cormack, 2008; Wu, Ooi, & He, 2004). Here we address this fundamental inconsistency by testing broad cognitive theories of distance estimation. Many cognitive scientists suggest that navigational costs shape distance perception. Navigational costs include energetic demand, injury risk, and time investment. Overestimation of routes with high navigational costs has been thought to prevent the observer from incurring those ⇑ Corresponding author. Address: Psychology Department, California State University San Marcos, 333 South Twin Oaks Valley Road, San Marcos, CA 92096, United States. Tel.: +1 760 750 8568. E-mail address: [email protected] (R.E. Jackson). 0010-0277/$ - see front matter Ó 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.cognition.2010.11.003
costs because observers tend to navigate the shortest of otherwise equivalent routes (Jackson, in preparation). Use of such logic appears as early as Solomon’s (1949) findings that weighted backpacks may induce distance overestimation and it continues today (Howard & Templeton, 1966; Jackson, 2005; Proffitt, Bhalla, Gossweiler, & Midgett, 1995; Sadalla & Magel, 1980). Navigation costs are particularly important on vertical surfaces, where investigation of falling risks led to the discovery of some of the largest known real-world distance illusions. Whereas classic illusions (Müller–Lyer, vertical– horizontal, Ponzo) exhibit magnitudes of roughly 10%, illusions in response to falling regularly exceed 30%. For example, the environmental vertical illusion (magnitude up to 51%) occurs such that individuals overestimate surfaces that pose falling risks, but do not overestimate retinally equivalent surfaces without falling risks (Jackson & Cormack, 2008). The magnitude of these illusions relates to the likelihood and severity of a fall: the descent illusion (magnitude up to 84%) occurs in situations where the observer is most likely to fall to the greatest injury (Jackson, 2005; Jackson & Cormack, 2007). These illusions may produce fear of heights (Jackson, 2009) and they disappear when falling risks are removed (Jackson & Cormack, 2010).
R.E. Jackson, C.R. Willey / Cognition 119 (2011) 288–294
Researchers predicted the above illusions from a research approach titled evolved navigation theory (ENT), which focuses on how navigation costs over evolutionary time may shape environmental cognition and navigation (Jackson, 2005; Jackson & Cormack, 2007). Although ENT has been applied recently to the navigation cost of falling, it encompasses all sources of navigation costs, such as energetic and time demands. Most research on real-world distance illusions focuses on perception of vertical or inclined surfaces (Dominguez, 1954; Hicks & Rivers, 1906; Higashiyama & Ueyama, 1988; Hoover, Bridgeman, & Thomas, in preparation; Jackson, 2009; Kammann, 1967; Raudsepp, 2002; Wober, 1972). Unfortunately, this excludes the surfaces most commonly encountered and navigated—those environmentally horizontal or nearly so. This limits generalizability of this broad research area in a foundational component to cognition. The current research applies the most significant identified navigational costs to the most commonly navigated environments. This is not intuitive because it applies falling risks to horizontal surfaces. However, if such navigational costs truly generate the large magnitude distance illusions as suggested, then such costs might also increase the distance perceived from horizontal surfaces. This would affect the perception of the majority of environments navigated by terrestrial organisms, including humans. One method for applying falling costs to a horizontal surface is to use a horizontal surface that borders a cliff. The navigation of such a surface poses a falling risk, even though the surface is horizontal. If falling costs affect horizontal distance perception (ENT), then observers should overestimate such a surface, but not a similar one without falling risk.
289
ENT Prediction 1: Observers will estimate accurately the distance of the surface without falling risks. ENT Prediction 2: Observers will overestimate the distance of the surface with falling risks. We plot predictions simultaneously with observed data below. The proposed method also tests the predictions of other clusters of visual cognition theories. From effortbased theories (see Solomon, 1949; Yang, Dixon, & Proffitt, 1999), we predict no distance perception differences across the surfaces tested here due to invariant navigation effort. From direct perception or ecological approaches, we predict no illusions because the surfaces consist of full cue, real-world conditions (see Gibson, 1966, p. 313; Michaels & Carello, 1981, p. 92). From retinal image and probabilistic approaches (see Geisler, Perry, Super, & Gallogly, 2001; Yang & Purves, 2003), we predict no distance estimation difference due to the roughly invariant retinal image across conditions. All of these competing theories convergently predict no distance perception differences across horizontal surfaces that contain variable falling risks.
2. Experiment 1 2.1. Method Fifty-seven participants volunteered in order to fulfill undergraduate research participation requirements. Participants estimated, via distance matching, a 5.48 m distance across two horizontal surfaces: one with, and one without, falling risks.
Fig. 1. Overhead view of Experiment 1. Both estimated distances measured 5.48 m. A indicates the falling risk surface estimate located on a 6.07 0.23 m board 1.07 m above the ground. B indicates the non-falling risk surface estimate on solid ground. An open circle indicates observer positions while making each estimate (the upper circle for the falling risk surface and the lower circle of the non-falling risk surface). X indicates the point of origin and a dashed arrow indicates the direction that the researcher walked for an observer’s estimates. Observers directed the researcher to walk out until the distance from the point of origin to the researcher looked the same as the distance being estimated (either A or B).
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2.1.1. Distance matching Participants indicated a distance that looked equal to the length of the estimated surface. They directed (via hand signals) a researcher to walk out until the distance from the researcher to a fixed dot looked the same as the length of the estimated surface. Participants received unlimited time to make as many adjustments as they liked. Researchers use similar distance matching methods widely in studies with realistic outdoor settings because such methods likely provide the clearest analog to the percept (Chapanis & Mankin, 1967; Higashiyama, 1996; Jackson & Cormack, 2006; Yang et al., 1999). 2.1.2. Falling risk surface The falling risk surface appeared along a board that spanned a 5.48 m gap across two stages 1.07 m above
ground. The board measured 6.07 0.23 m, with the 5.48 m estimated distance occupying the center of the board between two painted dots. An aluminum ladder kept the length of the board level. The surface upon which participants stood and gave estimates was a 12.19 1.22 m stage oriented perpendicular to the board. Participants stood at the end of the board and near the end of the stage (Fig. 1). 2.1.3. Non-falling risk surface The non-falling risk surface appeared along solid ground facing away from the stage. Two painted dots indicated the 5.48 m distance to estimate. The surface upon which participants estimated was solid ground perpendicular to the length of the non-falling risk surface. Participants stood at the intersection of the estimated surface and the surface over which they made their estimates (Fig. 1).
Fig. 2. Experiment 1 predicted (top) and observed estimates (bottom, mean ± 95% CI). Predictions (top) consist of relative magnitudes, with those of ENT appearing in white and those of competing theories in black. Dashed lines represent actual distance.
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We alternated estimate order across participants, with roughly half first estimating the non-falling risk surface and half the falling risk surface. The current method of estimating the same distance across two surfaces without seeing previous estimates resolved an artificial interdependency present in a pilot study in which we used a board for the falling risk surface and then, within view of the participant, moved that same board to the ground for them to estimate as the non-falling risk surface. Participants also made estimates unrelated to the current study and completed a demographic questionnaire. 2.2. Results Participants overestimated the length of the falling risk surface, but not the non-falling risk surface (Fig. 2). Falling risk surface estimates (M = 6.60 ± 0.29 m [95% CI]) significantly differed from actual distance (5.48 m), t (56) = 7.69, p < 0.001. Non-falling risk surface estimates (M = 5.34 ± 0.30 m) did not significantly differ from actual distance, t (56) = 0.96, p = 0.34. Estimates of the two surfaces significantly differed from one another, t (56) = 6.748, p < 0.001. Participants overestimated the falling risk surface by 1.26 m (23.7%, d = 1.12) more than the non-falling risk surface. Participants who first estimated the falling risk surface gave slightly longer estimates for the falling risk and non-falling risk surfaces (0.95 and 0.50 m, respectively) than participants who first estimated the non-falling risk surface. This effect was small in comparison to the distances estimated and did not bear upon any experimental predictions.
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ENT Prediction 3: Horizontal overestimation magnitude will correspond to the relative degree of falling risk. In addition to the unique effects proposed under this prediction, any method of testing it also tests Predictions 1 and 2—making it increasingly difficult to support by random chance. Further, a high falling cost surface must be estimated to be, not only longer than a moderate falling cost surface, but also longer than low and non-falling cost surfaces. This increases the random chance of violating this prediction exponentially by the number of comparisons, posing a very high threshold for support. The three clusters of competing theories (effort-based, direct perception, and retinal/probabilistic approaches) again predict a null effect. Participants should not overestimate any distance, certainly not by the relative degree of falling risk, according to these theories. 3.1. Method Seventy-nine participants volunteered for the study in order to fulfill college course-participation requirements. Participants estimated a 4.39 m distance via distance matching across four horizontal surfaces of high, moderate, low, and no falling risks (Fig. 3). 3.1.1. High falling risk Spanned the width (4.39 m) of a dry ditch 1.16 m deep. Two painted dots on the edges of the ditch indicated the 4.39 m distance to estimate. This surface posed relatively high falling costs due the depth of the ditch and lack of alternative routes for navigating the distance.
2.3. Discussion Participants accurately estimated horizontal surface length without falling costs, but clearly overestimated an equal horizontal surface with falling costs. These data are indistinguishable from ENT predictions (Fig. 2) and contradict predictions from other theories. This is a novel finding. The most common surfaces navigated by humans appear subject to large illusions and from a previously unanticipated source. Given the pervasiveness of navigation in most other behaviors, these findings bear upon broad human activity and potentially most non-human terrestrial animal behavior.
3.1.2. Moderate falling risk Spanned the ground bordering the end of the ditch where the ditch passed into a drainage pipe. Two painted dots indicated the 4.39 m distance to estimate. This surface posed relatively moderate falling costs due to flat ground
3. Experiment 2 The magnitude of (vertical) distance illusions proposed under ENT reflects the likelihood or severity of a fall (Jackson, 2009; Jackson & Cormack, 2007, 2008, 2010). Observers most overestimate vertical surfaces the navigation of which are most likely to result in a fall. Given that observers overestimate vertical surfaces proportionate to falling risk, and given the current observation that falling risks affect horizontal estimation, we predicted that observers should overestimate a horizontal surface by the degree to which it poses falling costs. Observers should overestimate surfaces with low and high falling risks by small and large amounts, respectively.
Fig. 3. Overhead view of Experiment 2. All estimated distances measured 4.39 m. High falling risk surface (A) spanning the 1.16 m deep ditch. Moderate falling risk surface (B) along the edge of the ditch. Low falling risk surface (C) along the top of a .15 m tall freestanding curb. Non-falling risk surface (D) along solid ground. The open circle indicates observer position during all four estimates. The dashed arrow indicates the direction that the researcher walked for all four estimates.
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Fig. 4. Experiment 1 predicted (top) and observed estimates (bottom, mean ± 95% CI). Predictions (top) consist of relative magnitudes, with those of ENT appearing in white and those of competing theories in black. Dashed lines represent actual distance.
on one side of the surface, but the deep ditch on the other side of the surface. 3.1.3. Low falling risk Spanned a length of nearby curb 0.15 m tall. Two painted dots on top of the curb indicated the 4.39 m distance to estimate. This posed relatively low falling costs due to the short height on either side of this freestanding curb. 3.1.4. Non-falling risk Appeared along solid ground parallel to, but apart from, the length of the ditch. The ditch did not appear in participants’ visual field while estimating this surface. Two painted dots indicated the 4.39 m distance to estimate. This surface posed no falling costs due to its location on level ground. Participants stood at the same fixed point for all estimates. The surface upon which participants estimated
extended in front of them and posed no falling costs. Estimate order was high falling risk surface, low falling risk surface, moderate falling risk surface, non-falling risk surface. We were able to order estimates differently than the predicted magnitude sequency in order to partially control for order effects. Order effects have not impacted similar predicted effects in similar previous studies (Jackson, 2009; Jackson & Cormack, 2007, 2008; Jackson & Willey, submitted for publication). Estimates were part of a larger study. 3.2. Results Participants only overestimated surfaces with falling risks. Overestimation magnitude increased as the falling risk magnitude increased (Fig. 4). Compared to the non-falling risk surface, participants overestimated the low falling risk surface by 0.37 m (9.0%,
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d = 0.54), moderate falling risk surface by 0.67 m (16.2%, d = 0.82), and high falling risk surface by 1.92 m (46.5%, d = 1.46). All estimates differed significantly from one another, F (3234) = 54.74, p < 0.001. Non-falling risk surface estimates significantly differed from estimates of the low falling risk surface, t (78) = 3.79, p < 0.001. Low falling risk surface estimates significantly differed from estimates of the moderate falling risk surface, t (78) = 2.89, p = 0.005. Moderate falling risk surface estimates significantly differed from estimates of the high falling risk surface, t (78) = 6.48, p < 0.001. High falling risk surface estimates (M = 6.05 ± 0.40 m [95% CI]) significantly differed from the actual distance (4.39 m), t (78) = 8.26, p < 0.001. Moderate falling risk surface estimates (M = 4.80 ± 0.23 m) significantly differed from the actual distance, t (78) = 3.54, p = 0.001. Low falling risk surface estimates (M = 4.50 ± 0.18 m) did not significantly differ from the actual distance, t (78) = 1.19, p = 0.24. Non-falling risk surface estimates (M = 4.13 ± 0.12 m) significantly differed from the actual distance, t (78) = 4.46, p < 0.001. 3.3. Discussion Participants’ distance estimates corresponded with each surface’s relative falling risk without exception. These data coincide with ENT Prediction 3. Observers overestimated surface length to the extent that the surface posed falling risks—even in the most common natural surfaces viewed, and navigated, by humans. Observed estimates fell slightly below predicted estimates (Fig. 4). Given the overall excellent fit with the predicted multi-parameter function, this slight potential underestimate likely stems from a minor methodological component such as anchoring. Many distance perception researchers observe such slight deviations from the intended estimate in natural settings (Bridgeman & Hoover, 2008; Chapanis & Mankin, 1967; Hansen & Essock, 2004; Mankin, 1969; Taylor, 1961). These estimates may also reflect a logarithmic, instead of linear, function—the shape of which nonetheless corresponds to ENT predictions. Comparison across both experiments reinforces the interpretation that falling risk produces overestimates of horizontal surfaces by degree of falling risk. The Experiment 1 falling risk surface most resembled the Experiment 2 open gap (high falling risk) condition. The magnitude of overestimation across these conditions increased from Experiment 1 to 2. This is exactly what one would expect from the current predictions, given that the plank in Experiment 1 facilitates navigating the gap, while the lack of such a surface in Experiment 2 increases falling risk. Comparison across other studies reinforces this interpretation. The magnitude of falling risk illusions on vertical surfaces mirrors the magnitude of horizontal illusions discovered here. Current participants did not overestimate surfaces without falling risk and ranged from 9% overestimation at low falling risks to 47% at high falling risks. This is nearly the exact range found for the corresponding situations in vertical surfaces (Jackson & Cormack, 2008). Environments (and individuals) exhibiting even greater
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falling risk or avoidance are the exact situations in which overestimation magnitude exceeds the range found here (Jackson, 2009; Jackson & Cormack, 2007).
4. General discussion Participants overestimated the most commonly navigated surfaces only when those surfaces posed a risk of falling. Overestimation magnitude reflected the degree of falling risk present in the surface. Horizontal surfaces far outnumber vertical surfaces in human environments and so this research explains a previously unknown factor present in most human navigation. Horizontal surfaces in general, and those with falling risks in particular, are exceedingly common in human and non-human terrestrial navigation. The frequency that an average person traverses stairs, a sloped path, or a curb numbers tens to hundreds or thousands of times in an average day. Counting the number of hand railings, graded surface angles, and fences bordering vertical surfaces identifies a vast number of such safety devices intended to prevent the costs resulting from navigating a world full of horizontal surfaces with falling costs. Without such safety devices in the environments in which humans evolved, horizontal surfaces with falling costs were likely ubiquitous. The illusions identified here explain how we interpret these exceedingly common surfaces in ways previously unknown. Only from an inclusive navigation theory that includes risk of falling (ENT) did we predict the observed data. We do not suggest that this replaces probabilistic approaches to vision, nor replaces the idea that retinal information is essential in distance perception. Instead, these data expand probabilistic approaches by identifying non-retinal information required for realistic vision. This appears essential for integrating previously independent visual domains. The logic from which we derived the current predictions appears in multiple sources several years prior to these experiments (Jackson, 2005, 2009, in preparation; Jackson & Cormack, 2007, 2008, 2010). This strength in prediction may stem from evolution by natural selection imposing additional criteria not normally utilized in this domain. In order for the adaptations discovered here to have evolved as specified by ENT, (1) there must have been sufficient distance estimation variation over evolutionary time that was, (2) heritable and, (3) tied to differential reproduction—implying that, (4) falling risks must have been present in horizontal surfaces over sufficient evolutionary time, (5) there must have been sufficient costs from falling, and (6) sufficient adaptive benefits from the observed illusion. Finding the predicted adaptation(s) in the current study lends support to the above conditions, each of which now creates further testable predictions. The high predictive specificity of evolution by natural selection may generate more information than non-evolutionary approaches. Environmental interpretation and distance perception are precursors to most human and non-human animal behavior. Nonetheless, we predicted and then discovered a novel phenomenon that occurs throughout the majority
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of human navigation and environmental cognition. The earliest modern research in these fields (Fick 1851, cited in Finger and Spelt (1947)) precedes the founding of experimental psychology. However, the theory-driven nature of this investigation integrated previously disparate researches and poses previously unavailable inroads into this fundamental area of cognitive science.
Acknowledgements We thank Theresa Cook, Erin Drasil, Ryan Sulman, and David Vazquez for gathering data. We also thank two anonymous reviewers for their comments.
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