Vision Research 93 (2013) 54–61

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Vision Research journal homepage: www.elsevier.com/locate/visres

The effect of age upon the perception of 3-D shape from motion J. Farley Norman a,⇑, Jacob R. Cheeseman b, Jessica Pyles b, Michael W. Baxter b, Kelsey E. Thomason b, Autum B. Calloway b a b

Department of Psychology & Center for the Study of Lifespan Development, Western Kentucky University, Bowling Green, KY 42101-1030, USA Department of Psychology, Western Kentucky University, Bowling Green, KY 42101-1030, USA

a r t i c l e

i n f o

Article history: Received 25 July 2013 Received in revised form 1 October 2013 Available online 21 October 2013 Keywords: Aging Perceived shape from motion Shape discrimination

a b s t r a c t Two experiments evaluated the ability of 50 older, middle-aged, and younger adults to discriminate the 3-dimensional (3-D) shape of curved surfaces defined by optical motion. In Experiment 1, temporal correspondence was disrupted by limiting the lifetimes of the moving surface points. In order to discriminate 3-D surface shape reliably, the younger and middle-aged adults needed a surface point lifetime of approximately 4 views (in the apparent motion sequences). In contrast, the older adults needed a much longer surface point lifetime of approximately 9 views in order to reliably perform the same task. In Experiment 2, the negative effect of age upon 3-D shape discrimination from motion was replicated. In this experiment, however, the participants’ abilities to discriminate grating orientation and speed were also assessed. Edden et al. (2009) have recently demonstrated that behavioral grating orientation discrimination correlates with GABA (gamma aminobutyric acid) concentration in human visual cortex. Our results demonstrate that the negative effect of age upon 3-D shape perception from motion is not caused by impairments in the ability to perceive motion per se, but does correlate significantly with grating orientation discrimination. This result suggests that the age-related decline in 3-D shape discrimination from motion is related to decline in GABA concentration in visual cortex. Ó 2013 Elsevier B.V. All rights reserved.

1. Introduction It has been appreciated for decades (e.g., Andersen, 1996; Braunstein, 1966; Green, 1961; Lappin & Craft, 2000; Norman & Lappin, 1992; Rogers & Graham, 1979; Todd, 1984; Wallach & O’Connell, 1953) that patterns of optical motion contain significant amounts of information that enable and support the perception of three-dimensional (3-D) shape. Mathematical analyses (e.g., Koenderink & van Doorn, 1991; also see Lind et al., 2013) have identified the types of geometrical information about 3-D shape that can be recovered from projected patterns of object motion (e.g., affine geometrical information can be obtained from two views of an apparent motion sequence and Euclidean metric information can potentially be obtained from three successive views in a motion sequence). In addition, psychophysical research has demonstrated that motion is as perceptually informative about 3-D object shape as binocular disparity (e.g., Cornilleau-Pérès & Droulez, 1993; Norman & Raines, 2002; Norman, Todd, & Phillips, 1995; Norman et al., 2012).

⇑ Corresponding author. Address: Department of Psychology, 1906 College Heights Blvd. #21030, Western Kentucky University, Bowling Green, KY 421011030, USA. Fax: +1 2707456934. E-mail address: [email protected] (J.F. Norman). 0042-6989/$ - see front matter Ó 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.visres.2013.10.012

Older adults can perceive 3-D shape from motion (Andersen & Atchley, 1995; Norman, Bartholomew, & Burton, 2008; Norman et al., 2004; Norman, Dawson, & Butler, 2000; Norman & Wiesemann, 2007; Norman et al., 2012). Nevertheless, significant age differences do exist. For example, Norman, Bartholomew, and Burton (2008) asked younger and older adults to discriminate the 3-D shape of textured solid objects; those authors found that while their older participants’ shape discrimination performance was facilitated by motion (rotation in depth), the magnitude of the facilitation was significantly reduced relative to that obtained for the younger participants (see their Fig. 6). In a different study, Norman, Dawson, and Butler (2000, Experiment 4), asked younger and older participants to discriminate the shapes (hemispheres, hyperboloids, vertically-oriented cylinders, & horizontally-oriented cylinders) of dotted surfaces rotating in depth. Norman et al. found that when the individual points defining the surfaces survived across all 15 views of the apparent motion sequences (no disruption of temporal correspondence of moving points across frames), their older participants performed well. In contrast, when individual points defining the curved surfaces only survived for 2 successive views in the 15 view apparent motion sequences (large disruption in temporal correspondence), the older participants’ 3-D shape discrimination performance fell to chance levels while the younger participants’ performance levels remained high. In that 2-view point lifetime condition, the older adults experienced

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a total failure of the ability to perceive 3-D shape from motion: the older participants reported that they only saw a collection of ‘‘blinking points’’ (no perceived rotation in depth, no perception of surface curvature, etc.). Similar results were also obtained by Norman et al. (2004) in a study of 3-D shape discrimination utilizing head-movement produced motion parallax (cf., Rogers & Graham, 1979). We know from previous research (e.g., Norman, Bartholomew, & Burton, 2008; Norman, Dawson, & Butler, 2000; Norman et al., 2004, 2012) that adults between the ages of 62 and 85 years generally exhibit a reduced ability to perceive and discriminate 3-D object shape from motion when compared to younger adults in their 20s. At this point in time, however, nothing is known about the nature of this age-related decline. Is the decline linear with increasing age so that middle-aged adults possess modest deficits? Or is the ability to perceive 3-D shape from motion well preserved and maintained during middle age and only deteriorates after the age of 60? One important purpose of the current study (Experiment 1) was to investigate this issue by evaluating the shape discrimination abilities of middle-aged adults in addition to younger and older adults. We also know from our previous research that while older adults can effectively perceive 3-D shape from motion when individual surface points survive for 15 views, that they cannot perceive 3-D shape when individual surface points survive for only 2 views. An additional important purpose of the current study was to determine exactly how much disruption of temporal correspondence can be tolerated by older adults’ visual systems. For example, can older adults perceive 3-D shape from motion when individual surface points survive for fewer than 15 views in an apparent motion sequence? How does shape discrimination performance change as surface point lifetime is directly manipulated (e.g., 2, 4, 6, 8, 12 views, etc.)? At the moment, very little is known about the sensitivity of older shape-from-motion neural systems to disruptions in temporal correspondence. In a pioneering study by Andersen and Atchley (1995), younger and older adults’ ability to detect 3-D surfaces from motion was evaluated along with the participants’ ability to discriminate 2-D motion. Andersen and Atchley found that while there were significant effects of age for both the 2-D motion task and the detection of 3-D shape from motion task, their participants’ individual performances for these two tasks were uncorrelated. They thus noted that (p. 657) ‘‘performance on 2-D motion tasks is not necessarily predictive of performance on more complex 3-D motion tasks’’. Andersen and Atchley concluded their article by saying (p. 657) ‘‘an important goal of future research will be to determine whether similar results are obtained with other tasks involving integration of different velocities (e.g., 3-D surface discrimination and identification).’’ A third purpose of the current study was to follow up on this suggestion. Do the results of Andersen and Atchley extend to the discrimination of 3-D surface shape from motion? To answer this, we compared (in the current Experiment 2) individual participants’ abilities to discriminate both 2-D motion and 3-D surface shape from motion.

2. Experiment 1 2.1. Method 2.1.1. Apparatus The motion patterns were created by an Apple PowerMacintosh G4 computer and displayed on a 22-inch Mitsubishi Diamond Plus 200 color monitor (resolution was 1280  1024 pixels). The viewing distance was 100 cm. The participants viewed the experimental stimuli monocularly using a viewing hood (e.g., see Norman, Bartholomew, & Burton, 2008; Norman et al., 2012).

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2.1.2. Experimental stimuli The experimental stimuli were similar to those used by Norman et al. (2004, 2012): three differently-shaped curved surfaces were portrayed through rotation in depth (i.e., using the kinetic depth effect; e.g., see Braunstein, 1976; Green, 1961; Lappin, Doner, & Kottas, 1980). For one of these surfaces (the ‘‘Bulls-Eye’’) depth was modulated sinusoidally as a function of increasing distance from the center of the stimulus, resulting in a series of circular peaks and troughs. A second type of surface (the ‘‘Star’’ or ‘‘Snowflake’’) was characterized by sinusoidal peaks and troughs that radiated outward from the center (if point positions within a stimulus pattern are defined in terms of polar coordinates, r and h, then the depth of these surfaces was modulated sinusoidally as a function of h). In the third surface type (the ‘‘Egg-crate’’), depth was modulated sinusoidally as functions of x- and y-coordinates within the stimulus [i.e., z = sin(x) * sin(y)]: these surfaces possessed arrays of ‘‘bumps’’ and ‘‘dimples’’. The average spatial frequency for all curved surfaces was 0.3 cycles/° visual angle, which coincides with the peak of the modulation transfer function for motion-defined surfaces (e.g., see Fig. 3 of Rogers & Graham, 1982). The phases of the sinusoidal depth modulations were randomly determined for each trial, so that each experimental stimulus was unique; the total amount of simulated front-to-back depth was always 1.0 cm. The 3-D structures of the differently shaped experimental stimuli were defined by the motions of 800 randomly-distributed points (bright white points rendered against a black background). The projection was perspective (see Fig. 1 of Braunstein, 1962), appropriate for the 100 cm viewing distance. The stimulus surfaces oscillated (i.e., rotated) in depth over a 44° range (±22° from a frontal orientation) about a Cartesian vertical axis located in the plane of the computer monitor. The surfaces rotated 2° at every frame transition. The apparent motion sequences consisted of 88 individual frames (2 complete cycles of surface rotation), while the frame update rate was 30 Hz. Each trial’s total stimulus duration was thus 2.93 s (88 frames  33.3 ms/frame). 2.1.3. Procedure There were 5 surface point lifetime conditions for each age group. For the middle-aged and older age groups, we used surface point lifetimes of 2, 4, 8, 12, and 16 views (as the 3-D objects rotated in depth, each surface point would survive for only a limited number of successive views in an apparent motion sequence; when each point reached the end of its individual lifetime, it would be randomly positioned to a new location on the object’s surface). Because it is already known (e.g., Norman, Dawson, & Butler, 2000; Norman et al., 2004; also see van Damme & van de Grind, 1996) that younger adults can reliably discriminate 3-D shape with shorter point lifetimes, we used surface point lifetimes of 2, 3, 4, 6, and 8 views for the younger participants. At the beginning of each trial’s apparent motion sequence, the phase of each surface point’s lifetime would be randomly determined; because of this, only a subset of the 800 surface points would ‘‘die’’ and be randomly repositioned at any particular frame transition – for example, in the 4-view surface point lifetime condition, approximately 25% of the surface points would ‘‘die’’ and be randomly repositioned on any given frame transition (see Figure 6a of Dosher, Landy, & Sperling, 1989; for a graphical depiction of limited surface point lifetime displays). On any given trial, a single one of the three curved surfaces (‘‘Bulls-Eye’’, ‘‘Star’’, or ‘‘Egg-crate’’) would be displayed. The participants’ task on each trial was to identify which of the three surfaces had been presented. Within each experimental session, the participants judged 120 trials [5 surface point lifetime conditions  3 surface shapes (Bulls-Eye, Star, & Egg-crate)  8 replications]. The order of the surface shapes within a session was completely random. Two

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experimental sessions were run for each participant, both conducted on the same day. Therefore, by the end of the experiment, each participant had judged a total of 240 stimulus presentations. Before beginning the experiment, we ensured that all of the participants completely understood the experimental task. The participants were presented with sample trials depicting the three surface shapes defined by motion (Bulls-Eye, Star, & Egg-crate). There was no disruption of temporal correspondence for these introductory sample trials: all 800 of the individual surface points survived across the entire 88-view apparent motion sequences. Only after each participant could reliably and accurately identify the surface shapes (with no manipulation of surface point lifetime) were they allowed to begin the first experimental block of trials. 2.1.4. Participants Thirty adults participated in the experiment. The younger participants were in their 20s and 30s (mean age = 27.3 years, SD = 6.4), while the middle-aged participants were in their 40s and 50s (mean age = 50.9, SD = 4.4). The older participants were aged 60 or older (mean age was 75.1 years, SD = 5.7). Informed consent was obtained from all participants, and the methods and procedures were approved by the Human Subjects Review Board at Western Kentucky University. The participants’ acuities were assessed with a standard ETDRS eye chart (Precision Vision catalog number 2195) at a distance of 1 meter. The younger, middle-aged, and older participants all possessed good visual acuity: the younger, middle-aged, and older participants’ average acuity was 0.14, 0.08, and 0.02 LogMAR (log minimum angle of resolution). A zero value of LogMAR indicates ‘‘normal’’ acuity, while negative and positive values indicate ‘‘better than average’’ and ‘‘less than average’’ acuity, respectively (the 0.02 average logMAR acuity possessed by the older participants is slightly worse than 20/20, but much better than 20/25, thus our older participants’ visual acuity was quite good). Despite the fact that all of our participants possessed good overall visual acuity, the small differences in acuity that did exist were statistically significant (F(2, 27) = 9.0, p = .001, g2p = 0.4). A subsequent Fisher LSD (least significant difference) test revealed that the older participants’ acuity was significantly different from that of both the younger and middle-aged participants (the acuity of the younger and middle-aged participants, however, was not significantly different). It is well known that aging affects visual acuity (e.g., Elliott, Yang, & Whitaker, 1995); it is also well known, however, that such variations in acuity do not affect the ability to perceive 3-D shape from motion (e.g., see Andersen & Atchley, 1995; Norman, Beers, Holmin, & Boswell, 2010; Norman et al., 2000). All 30 participants were naïve and had no knowledge of the previous literature, exact hypotheses under test, etc. 3. Results and discussion Various aspects of the results are shown in Figs. 1–3. Fig. 1 illustrates results obtained for a representative younger participant, a representative older participant, and one older participant whose discrimination performance failed to reach threshold levels. A logistic function (Macmillan & Creelman, 1991; pp. 186–190) was fit to each participant’s individual results (solid curves in Fig. 1). These best-fitting logistic functions were then used to identify each participant’s surface point lifetime threshold (i.e., the point lifetime needed to reliably discriminate 3-D surface shape). In particular, the threshold was defined as that surface point lifetime that led to 66.7% correct shape discrimination performance (because chance performance is 33.3% correct in this experiment, 66.7% correct represents a level of performance that is halfway between chance and perfectly accurate responding). As can be seen in Fig. 1, a few older participants (n = 3, see for example, the individual results of

participant 7) could not discriminate 3-D shape at above threshold levels of performance. These older participants’ shape discrimination performances, however, were significantly higher than chance (e.g., for participant 7, v2(4) = 39.7, p < .000001). For purposes of statistical analysis we set the threshold surface point lifetime to 16 views (the longest surface point lifetime used in the experiment) for these three older participants. The resulting age difference in the thresholds, plotted in Fig. 2, is therefore an underestimate. Even so, the age difference in point lifetime thresholds between the older and younger adults was statistically significant using a non-parametric analysis of variance (Kruskal–Wallis ANOVA of ranks, H = 8.8, p = .0125; see Siegel, 1956). It is readily apparent from an inspection of Fig. 2 that there were large differences in surface point lifetime thresholds between the older and younger age groups. However, one can also see from this figure that the thresholds obtained for the middle-aged and younger participants were very similar; there was no significant difference between these age groups (Wilcoxon rank-sum test, Wx = 103, p = .88; see Wilcoxon, 1945 and Siegel & Castellan, 1988). One can also see from Fig. 2 that the average point lifetime threshold for the middle-aged and younger participants was approximately 4 views (i.e., on average, the younger and middleaged adults needed the surface points to survive for approximately 4 successive views in the apparent motion sequences in order to reliably discriminate 3-D shape from motion). Fig. 3 is especially informative, because it plots all of the participants’ shape discrimination accuracies for the 4-view point lifetime condition as a function of their individual ages (from 19 to 84 years). The bilinear curve shown in Fig. 3 indicates the best quantitative fit to the participants’ data; this bilinear curve was a better fit (according to a least-squares analysis; e.g., see Hamming, 1973) to the participants’ performance than either a pure linear fit or other monotonic function. For example, the sum of the squared residuals (7912.5) for the depicted bilinear curve (y = 66.557 + 0.075x for younger and middle-aged adults; y = 157.693 1.498x for older adults) is much smaller, indicating a better fit to the data, than the sum of the squared residuals (9559.7) obtained for the best-fitting linear regression (y = 86.446 0.490x). One can see from Fig. 3 that although there is considerable individual variability at any particular age, that the ability to reliably discriminate 3-D shape from moving patterns with limited point lifetimes is generally maintained throughout young adulthood and middle age, and begins to decline after the age of 60 years. After the age of 60, the ability to discriminate 3-D shape from limited lifetime motion patterns declines at a steady linear rate. When considering these results (those illustrated in Fig. 3), however, it is important to keep in mind that these data are for the challenging 4-view surface point lifetime condition – the older adults performed considerably better on the shape discrimination from motion task (average discrimination accuracy was 83.1% correct) when the surface points survived for 16 views in the apparent motion sequences.

4. Experiment 2 The results of Experiment 1 demonstrate that while older, middle-aged, and younger adults can perceive and discriminate 3-D shape from motion (see Figures 1 and 2), aging nevertheless has adverse effects (see Figures 2 and 3). One obvious possibility of the source of this age-related deterioration in 3-D shape discrimination from motion would be reduced sensitivity to motion itself. A number of studies (e.g., Bidwell, Holzman, & Chen, 2006; Norman, Burton, & Best, 2010; Norman et al., 2003; Raghuram, Lakshminarayanan, & Khanna, 2005; Snowden & Kavanagh, 2006) have previously found older adults to possess a reduced ability to discriminate differences in the speed of moving patterns. It has

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Point Lifetime (views) Fig. 1. Representative results of Experiment 1 for individual participants. The top row illustrates results for one representative younger participant and one representative older participant. The solid curves represent the best-fitting logistic function. The bottom row illustrates results for one of the three older participants who could not discriminate 3-D surface shape (with temporal disruption of surface point correspondence) at above threshold levels of performance. The dashed line in all plots indicates chance levels of shape discrimination performance.

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been suggested (Liang et al., 2010; Schmolesky et al., 2000; Yang et al., 2009a, 2009b; Yu et al., 2006) that age-related reductions in sensitivity to motion are related to deterioration in the functionality of inhibitory (i.e., GABA, gamma-aminobutyric acid) synapses within the brain’s primary visual cortex (V1) and cortical areas MT and V2. Direct support for this hypothesis comes from an experiment performed by Leventhal et al. (2003). In this study, Leventhal et al. demonstrated that it was possible to restore motion selectivity to individual V1 neurons in old monkeys by directly applying GABA or the GABA agonist muscimol. Six years later, Edden et al.

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Age (years) Fig. 3. Results of Experiment 1 plotting the participants’ shape discrimination accuracy for the 4-view surface point lifetime condition as a function of their individual ages.

(2009) showed that the resting concentration of GABA in human primary visual cortex is correlated with individual participants’ abilities to discriminate differences in the orientation of luminance gratings (see their Fig. 3A). In the current experiment, we again replicate the effect of age upon the ability to discriminate 3-D shape from motion, but now also evaluate our participants’ abilities to judge motion per se (i.e., discriminate the speed of motion, see Norman et al., 2003) and to discriminate the orientation of sine-wave luminance gratings (thus behaviorally assessing each participant’s concentration of GABA in primary visual cortex). An important purpose of this experiment is to determine whether the variability in our individual participants’ ability to discriminate

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3-D shape from motion is related to (i.e., is correlated with) their variability in grating orientation discrimination. If these judgments are correlated (3-D shape discrimination from motion and grating orientation discrimination), this would suggest (cf., Edden et al., 2009) that the observed age-related decline in 3-D shape discrimination from motion is related to resting concentrations of GABA within V1. 4.1. Method 4.1.1. Apparatus The apparatus was the same as that used in Experiment 1. 4.1.2. Experimental stimuli The visual displays for the 3-D shape from motion discrimination task were the same as the 4-view surface point lifetime stimuli used in Experiment 1. The visual displays for the speed discrimination task were similar to those used in Experiment 1 of Norman et al. (2003; also see Todd & Norman, 1995). Two elongated moving strips (each containing 50 bright high-contrast points rendered against a black background) were displayed on every trial. The length and width of each horizontally-oriented strip was 21.0 and 0.57°, respectively. One strip was located 2.86° above the center of the monitor screen, while the other was located 2.86° below the center (a fixation point was provided at the center of the display). The points within the strips moved (i.e., translated) from left to right for 3.0 s; when an individual point reached the rightmost edge of the strip, its position was recycled back to the beginning of the strip to begin its journey again (although its vertical position was randomly changed at the time of ‘‘recycling’’ so that the moving stimulus pattern was constantly changing and never repeated itself at any moment of time). The points within one of the strips always moved at a moderate standard speed (5.48 deg/s), while the points within the other strip moved with a slower speed. On any given trial, whether the standard (i.e., faster) speed was located above or below the center of the monitor screen was randomly determined. The visual displays for the grating orientation discrimination task closely resembled those used by Edden et al. (2009). On any given trial, two sine-wave luminance gratings (4 deg diameter; spatial frequency of 3 cycles/deg; 80% contrast) were sequentially presented; each grating was displayed for 350 ms, separated by a 500 ms inter-stimulus interval (ISI). As in the experiment by Edden et al., the average orientation of the bars of the gratings was oblique (45° clockwise from vertical). 4.1.3. Procedure The basic procedure and task for the 3-D shape from motion judgments was identical to that used in Experiment 1: on any given trial, each participant viewed a single 3-D surface and was required to identify its shape (i.e., whether it was a ‘‘Bulls-Eye’’, ‘‘Star’’, or ‘‘Egg-crate’’). Each participant judged a total of 60 trials, 20 for each of the three surfaces. As in Experiment 1, the older and younger participants were not allowed to begin the 3-D shape judgment task until they could reliably and accurately discriminate the three surface shapes presented with unlimited surface point lifetime (i.e., no disruption in temporal correspondence). For the speed discrimination task, the participant was required to judge on any given trial whether the top or bottom set of points was moving fastest. For the grating orientation task, the participants were required to indicate on any given trial the orientation of the second grating relative to that of the first (i.e., judge whether the grating rotated clockwise or counterclockwise). The thresholds for the speed and grating orientation discrimination tasks were determined by an adaptive procedure developed by Lelkens and Koenderink (1984; also see Norman & Todd, 1994;

Norman, Norman et al., 2008). At the beginning of the speed discrimination task, the speed of the standard strip was twice that of the test (slower) strip. After each correct judgment, the difference in speed between the standard and test strips was reduced by one step size (initially 0.1 deg/s). After each incorrect judgment, the difference in speed was increased by three times the step size. As pointed out by Lelkens and Koenderink, this procedure converges upon the 75th percentage point of a participant’s psychometric function. The step size (initially 0.1 deg/s) was halved after the first, third, and seventh reversals. Each block of trials continued until the occurrence of the tenth reversal. The final estimate of each participant’s threshold was obtained by averaging the speed differences for the last eight reversals. At the beginning of a block of trials for the grating orientation discrimination task, the difference in orientation of the gratings was 10° for the younger participants and 25° for the older participants (pilot testing had revealed that older adults need larger differences in orientation to perform the discrimination task reliably). In order to determine a threshold for one younger participant, a larger initial difference in grating orientation (20 deg) was needed. After each correct judgment, the difference in orientation between the two gratings was reduced by one step size (initially 0.35 deg). After each incorrect judgment, the difference in orientation was increased by three times the step size. The step size (initially 0.35 deg) was halved after the first, third, and seventh reversals. Each block of trials continued until the occurrence of the tenth reversal. The final estimate of each participant’s threshold was obtained by averaging the grating orientation differences for the last eight reversals. 4.1.4. Participants The participants were 20 younger and older adults, none of whom had participated in Experiment 1. Ten of the participants were 66 years of age or older (mean age was 71.3 years, SD = 3.1; ages ranged from 66 to 75 years), while the remaining 10 participants were 33 years of age or younger (mean age was 23.3 years, SD = 4.6; ages ranged from 18 to 33 years). One of the participants (younger adult, age = 24 years) completed the shape-from-motion and speed discrimination tasks, but not the grating orientation task. Two of the student coauthors (JRC & MWB) served as younger participants, while the remaining 18 participants were naive. Informed consent was obtained from all participants, and the methods and procedures were approved by the Human Subjects Review Board at Western Kentucky University. The participants possessed good visual acuity: the younger and older participants’ average acuity was 0.16 and 0.0 LogMAR (log minimum angle of resolution), respectively. As was the case in Experiment 1, the visual acuities of the younger and older participants, while good, were nevertheless significantly different (t(18) = 3.4, p = .003, 2-tailed). 5. Results and discussion The results for the 3-D shape from motion discrimination task are shown in Fig. 4. Once again, there was a significant effect of age (Wilcoxon rank-sum test, Wx = 66, p = .002, 2-tailed; see Siegel & Castellan, 1988), such that the younger participants’ shape discrimination performance was 59.3% higher. Fig. 5 shows the individual younger and older adults’ shape discrimination accuracy plotted as functions of the participants’ grating orientation discrimination (left panel) and speed discrimination (right panel) thresholds. If the effect of age upon 3-D shape from motion discrimination is related to age-related reductions in GABAergic activity in visual cortices, we should expect reduced ability to discriminate shape to correspond with reduced concentrations of GABA as behaviorally measured by Edden et al. (2009). In our study, we did obtain a significant correlation in the hypothesized

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6. General discussion

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direction (Pearson r = 0.392, r2 = 0.154, p < .05, 1-tailed; see left panel of Fig. 5). The correlation, however, was modest – about 15% of the variability in our participants’ shape discrimination performance can be accounted for by variability in grating orientation discrimination, suggesting that resting GABA concentration in V1 is indeed related to the decline in 3-D shape discrimination ability that occurs with increasing age. Likewise, if the effect of age upon 3-D shape from motion discrimination is related to age-related reductions in sensitivity to motion itself, we should expect reduced ability to discriminate shape to correspond with reduced performance on a 2-D motion task (i.e., higher thresholds). This, however, did not occur – we found no significant correlation between 3-D shape from motion discrimination accuracy and speed discrimination thresholds (Pearson r = 0.268, r2 = 0.072, p > .12, 1-tailed; see right panel of Fig. 5). Even if this correlation had been significant, only 7.2% of the variability in our participants’ shape discrimination performance could be accounted for by variations in their individual speed discrimination thresholds.

The results of Experiment 1 demonstrate that while older adults can accurately discriminate 3-D surface shape from motion under favorable circumstances (e.g., 83.1% correct discrimination accuracy in the 16-view point lifetime condition), their performance suffers disproportionately (see Fig. 3) when the surface point lifetime is reduced. Norman, Dawson, and Butler (2000, Experiment 4) had previously found that while older adults could reliably perceive and discriminate 3-D surface shape from motion with 15-view point lifetimes, they could not with only 2-view point lifetimes. The current results (see Fig. 2) extend these previous findings and show that older adults, on average, need a surface point lifetime of 9 views in order to reliably perceive 3-D shape from motion. This is a large effect of age. As Fig. 2 illustrates, younger and middle-aged adults only need a 4-view surface point lifetime to successfully perform the same 3-D shape discrimination task. The current results are useful, because they document for the first time exactly how much temporal correspondence is needed for older visual systems to successfully recover information about 3-D surface shape from patterns of optical motion. The current results also demonstrate that middle-aged adults’ abilities to perceive and discriminate 3-D shape from motion are similar to those of younger adults (see Figs. 2 and 3). It appears, therefore, that the negative effects of increasing age do not become substantive until the age of 65–70 years. None of the previous relevant studies (Andersen & Atchley, 1995; Norman, Dawson, & Butler, 2000; Norman et al., 2004, 2012) included middle-aged participants, so their abilities to perceive and discriminate 3-D shape from motion were unknown until the current investigation. In a pioneering investigation of the effects of aging by Andersen and Atchley (1995), no significant correlation was found between performance on a 3-D surface detection task (surfaces defined by motion) and a 2-D motion discrimination task. Andersen and Atchley therefore concluded (p. 650) that ‘‘different processes underlie the analysis of 2-D and 3-D motion’’. The results of our current Experiment 2 on surface shape discrimination agree with and are analogous to the previous findings of Andersen and Atchley concerning surface detection. In our study, we found no significant or meaningful correlation between participants’ abilities to discriminate 3-D shape from motion and their abilities to discriminate speed (Fig. 5, right panel). In their discussion (p. 657), Andersen and Atchley believed that ‘‘an important goal of future

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Fig. 5. Individual results for Experiment 2. The shape discrimination accuracies for individual younger and older participants are plotted as a function of their grating orientation discrimination (left panel) and speed discrimination (right panel) thresholds. The linear regression line shown in the left panel highlights the significant correlation that was obtained between the participants’ shape discrimination performances and their grating orientation thresholds.

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research will be to determine whether similar results are obtained with other tasks involving integration of different velocities (e.g., 3-D surface discrimination and identification)’’. The results of our current study have now extended Andersen and Atchley’s investigation to 3-D shape discrimination and we have verified their conclusion (p. 657) that ‘‘performance on 2-D motion tasks is not necessarily predictive of performance on more complex 3-D motion tasks’’. A variety of adverse effects of increasing age upon visual tasks (e.g., Andersen & Ni, 2008; Betts, Sekuler, & Bennett, 2007; Betts et al., 2005; Blake, Rizzo, & McEvoy, 2008; Norman et al., 2007; Wilson et al., 2011) are hypothesized to occur because of a reduction in inhibitory (i.e., GABA) activity in visual cortex. Such GABA sensitive tasks include (1) binocular rivalry suppression, (2) visual face matching, (3) 2-D shape recognition from dynamic occlusion, (4) motion direction discrimination, and (5) orientation discrimination. Edden et al. (2009) have demonstrated that GABA concentration in human primary visual cortex can be behaviorally measured by assessing participants’ abilities to discriminate luminance grating orientation. In the current Experiment 2, we evaluated our younger and older participants’ abilities to discriminate both 3-D shape from motion and luminance grating orientation. We found (Fig. 5, left panel) a significant correlation between our participants’ grating orientation thresholds and their 3-D shape discrimination abilities; those participants with higher grating orientation thresholds (lower GABA concentration in visual cortex), for example, have reduced abilities to discriminate 3-D shape from motion. This result strengthens the emerging belief that the changes in GABAergic activity that accompany aging (Leventhal et al., 2003; Pinto et al., 2010) are responsible for at least some of the observed age-related declines in visual functioning. Two-view apparent motion sequences are generally adequate for discriminating 3-D shape from motion, for example, when observers can view the two alternating views for a relatively long period of time (i.e., multiple repetitions of the 2-view apparent motion sequence), when there are no disruptions of temporal correspondence, and when the 3-D shapes to be discriminated are not affine equivalent along an observer’s line of sight (e.g., see Norman & Lappin, 1992; Norman & Todd, 1993; Todd & Norman, 1991). In the current study, however, surface point lifetime was manipulated, not the number of views per se. As the lifetime of the surface points in our Experiment 1 was reduced from 16 views to 12, 8, 6, 4, 3, and 2 views, the number of points constituting uncorrelated noise at each frame transition increased from 6.25% of the 800 total points to 8.3%, 12.5%, 16.7%, 25.0%, 33.3%, and 50%. The increasing amounts of noise (i.e., disruption of temporal correspondence) make the shorter surface point lifetime conditions difficult. In conditions similar to ours (manipulation of surface point lifetime, 30 Hz frame update rate), the younger participants of van Damme and van de Grind (1996) also needed surface point lifetimes of 4 views in order to successfully discriminate surface curvature magnitudes defined by motion. In our Experiment 1, we found that while younger and middle-aged participants needed a surface point lifetime of approximately 4 views in order to discriminate shape at threshold levels, older adults needed a surface point lifetime of approximately 9 views. This result demonstrates that older adults’ 3-D shape discrimination ability is especially susceptible to the presence of increasing amounts of uncorrelated noise within apparent motion sequences. It is true that our current Experiments (Figs. 1–4) document large and adverse effects of increasing age upon the ability to perceive and discriminate 3-D shape from motion. However, it is important to keep these results in perspective: all of our older participants were able to reliably and accurately discriminate 3-D shape from motion when there was no, or little, disruption of temporal correspondence. As an example, consider participants 25

(age = 25 years) and 9 (age = 84 years) from the current Experiment 1, whose individual performances are plotted in Fig. 1. These representative younger and older participants’ shape discrimination accuracies for the 4-view point lifetime condition were 77.1% and 50.0% correct, respectively. In this condition, the older adult was obviously much less able to perceive and discriminate 3-D shape than the younger adult. Notice, however, that this older adult (participant 9) could discriminate 3-D shape from motion very effectively (95.8% correct) in the 16-view point lifetime condition (when there was less disruption of temporal correspondence). This pattern occurred for most of the older participants: 7 out of the 10 older participants in Experiment 1 could discriminate 3-D shape from motion at 90% accuracy (or above) in the experimental conditions with the least disruption of temporal correspondence. These findings demonstrate that the neural mechanisms responsible for perceiving 3-D shape from motion in older adults are fragile: they work well under favorable conditions, but become less tolerant and fail (much more than younger visual systems) under difficult circumstances (e.g., when temporal correspondence is disrupted, as in the current experiments).

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