INT’L. J. AGING AND HUMAN DEVELOPMENT, Vol. 78(3) 277-297, 2014

SPATIAL PERSPECTIVE TAKING IS ROBUST IN LATER LIFE MASAYUKI WATANABE* Shiga University MIDORI TAKAMATSU Japanese Red Cross Otsu School of Nursing

ABSTRACT

In developmental studies of spatial perspective taking, it is important to clearly distinguish imagining body movement from other related cognitive information processing, to capture the genuine features of this ability in aging. This study examined the characteristics of these abilities in the older adults by comparing differences among age groups. A video game task was devised to evaluate response times from various angles of rotation. Four hundred twenty-eight healthy individuals aged 6 to 79 years (eight age groups at 10-year intervals) participated. Average response times for each age group confirmed a curvilinear change that accelerated from childhood to early adulthood and decelerated in later life. However, older participants did not display inferior performance compared with the younger adults on the response times to rotate an imaginary self to a 180° position. These results confirm previous findings that spatial perspective taking, particularly imagining body movement, remains robust in normal aging.

*This study was supported by a Grant-in-Aid for Scientific Research (C), Japan Society for the Promotion of Science, 22530700, to the first author.

277 Ó 2014, Baywood Publishing Co., Inc. doi: http://dx.doi.org/10.2190/AG.78.3.d http://baywood.com

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Spatial perspective taking is the ability to visualize an object from the vantage point of an imaginary observer at some other point in space and update the position of a target relative to the self (Huttenlocher & Presson, 1979). This cognitive process plays a basic yet essential role in supporting spatial orientation in everyday life. Studies on spatial perspective taking originated with Piaget and Inhelder’s (1956) research on children; this was followed by several other developmental studies that used the “three mountains task” (e.g., McDonald & Stuart-Hamilton, 2002), in which children seated at a table facing three different mountains were asked to show how the mountains would look from another point of view. It was revealed that this ability comprises different functions, and should be fully developed by late childhood. These findings give rise to a few questions—namely, what are the essential components of spatial perspective taking, and how do they change over the lifespan? However, tasks like the three mountains task are not suitable for assessing the true nature of spatial perspective taking (Flavell, 1974). This is because the information processing abilities involved in these spatial perspective taking tasks vary and considerably influence the accuracy of task performance (Newcombe, 1989). Information processing can refer to the perception of object features (Rosser, Ensing, Mazzeo, & Horan, 1985), object-manipulation ability (Kozhevnikov & Hegarty, 2001), inhibitory functions (Hasher & Zacks, 1988), or working memory (Yamadori, Ashina, Fujii, Tsukiura, Okuda, & Osaka, 1999). Hegarty and Waller (2004) proposed a mental model of spatial perspective taking in which imagining oneself reoriented at another point in space should be separated from the other information processing abilities that eventually generate the view from this new vantage point. Further, it is possible that imagining body movement to different positions in space is central to spatial perspective taking, while the range of information processing that varies between tasks is subsidiary (Qureshi, Apperly, & Samson, 2010). Some recent neuroscientific studies have sought to verify the view that spatial perspective taking is composed of imagining body movement and other types of cognitive information processing. Researchers presume that the same brain regions govern both imagining body movement and physical movement. Ruby and Decety (2001) measured brain activity using positron emission tomography while participants imagined mimicking an act from their own or another’s perspective. Their results showed deep connections between participants’ own perspectives and regions involved with somatic sensation (e.g., the inferior parietal lobe, precuneus, and postcentral gyrus) but this was not seen when participants took another’s perspective. Wraga, Shepherd, Churcha, Inati, and Kosslyn (2005) recorded brain activity and observed activation in the left supplementary motor area, which contributes to the control of body movement during voluntary spatial perspective taking. These

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studies show that imagining body movement is a process similar to physical movements governed by the motion control system in the brain. Meanwhile, other cognitive information processing may be managed by different parts of the brain: visual attention by the temporoparietal junction (Coslett & Saffran, 1991) and transformation of mental representations by the intraparietal sulcus (Zacks, 2008). The failure to investigate these processes separately, however, will cause us to overlook the developmental features of spatial perspective taking, relying exclusively on response accuracy and using insufficient procedures to separate imagining body movements from other information processing modes. Even if participants correctly perform imagining body movements, their responses to a spatial perspective taking task could still contain errors if the information processing abilities demanded by that task are inadequate. Many spatial perspective taking tasks require additional information processing abilities that are not central to imagining body movement. A decline in spatial perspective taking ability has been frequently found in older adults. Inagaki et al. (2002) revealed that in older participants, including those over 75 years, the percentage of correct responses was much lower and the number of egocentric errors (i.e., responses reflecting the participant’s own perspective) was much higher than in the two younger age groups (18 to 29 and 33 to 58 years). However, their study could have been insensitive to identifying the essential elements of spatial perspective taking (i.e., imagining body movement) because their task required additional information processing abilities and could not strictly separate them from imagining body movement; thus, low performance on their task cannot be explained on the basis of either process. Although some other studies have also observed reduced performance in older adults on spatial perspective taking tasks (e.g., Hetman & Coyne, 1980), this may not necessarily indicate a substantial decline in spatial perspective taking abilities. Simply increasing task complexity might obscure the process of moving an imaginary self to another point in space (imagining body movement) by increasing cognitive demands inessential to spatial perspective taking (other cognitive information processing). To address this issue, Watanabe (2011) designed a task that elicited voluntary imagining of body movement apart from other cognitive information processing by using the alignment effect, in which both maps and participants are mentally coded in their current orientation (Levine, 1982). First, participants were given a map of a town in which eight buildings (from A to H) surrounded a circular hill; they were then told that icons numbered 1 to 8 displayed on a monitor represented the buildings in the miniature town depicted in the map they were holding. Next, they were asked to state the icon numbers corresponding to the letters of the buildings on the map, imagining

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that the map and town were in different orientations; for example, “On the map, which building would be at C if A were positioned where the number 3 building is located?” The direction of the town displayed on the monitor was changed for every trial. This procedure made it possible to teach participants that it was crucial to imagine themselves moving around the town holding the map (i.e., imagining body movement), rather than mentally rotating the town to a particular angle. The response times to rotate one’s own body image to the 180° position did not differ among older adults, university students, and children. Thus, it was concluded that imagining body movement might be preserved in normal aging. In that study, however, most of the older adult participants were in their 60s, and the children’s group was limited to older children (9 to 11 years); this could have somewhat limited the generalizability of the results. If the age range had been expanded over the lifespan and clear differences had been revealed between age groups, the extent of older adults’ imagining body movement might have been more distinct. To compare performances of imagining body movement among age groups across the lifespan, task procedures must be simple enough to be accurately completed; however, those used by Watanabe (2011) were complex and challenging for younger children because they simulated a spatial orientation activity using a map, and such a situation was unfamiliar to children. Therefore, in this study, we introduced a more familiar situation by designing a simple video game task to be accessible to a broad range of ages. The task was designed to imitate a game of hide-and-seek, in which the object was to find a child character hiding in a rotating house. At the beginning of the game, nine different child characters simultaneously enter a symmetrical house with two windows to signify that the question will be repeated nine times. One of the characters appears at one of the windows, and then hides behind the window frame. Participants are asked, “Which window was the child hiding behind, right or left? Indicate your choice immediately after the “START” signal appears in the center of the screen.” Just before the appearance of the START signal, the house is rotated very quickly in the picture plane at an visual angle randomized by the program, while the background remains stationary. This simple procedure enabled even younger children and older adults to easily play the game. By its nature, this procedure will stimulate the use of a spatial perspective taking strategy. Is spatial perspective taking ability in older adults robust in normal aging, as suggested in Watanabe (2011), or inferior to that of younger people, as generally assumed until now? A comparative study with a few age groups or one utilizing an insensitive measure of spatial perspective taking ability would not be sufficient to answer this question accurately. Thus, the current study utilized the video game task with a broad range of ages in an attempt to

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answer this question, elucidating in detail the features of imagining body movement and the other cognitive information processing separately. METHOD Participants Four hundred and twenty-eight healthy individuals aged 6 to 79 years participated in the current study. Participants (or primary caregivers of children) provided informed consent orally and joined the experiment voluntarily after receiving an oral explanation of the experimental purpose and method, any expected discomfort, and their freedom to discontinue their participation. After the experiment, participants were debriefed about the meaning of their task scores, and a randomly selected subset of the sample (n = 49; roughly 12% of the whole) were interviewed about the strategies they had used in the task: “Describe how you found the position of the target window.” Their answers were classified based on criteria for the strategies, which consisted of key phrases for each strategy; for example, “mentally rotated the house” or “placed a rotated image of the house upon a house figure” indicated mental rotation, and “imagined myself moving around” or “pictured myself seeing the house from another view point” indicated perspective taking. Participants under 59 years of age were recruited from public kindergartens, schools, universities (children, students, and their teachers), and relatively large companies (employees) in cities across Japan. Most of the older adult participants were recruited from the Job Centre for Older Workers in Shiga, Japan, an organization that offers older retirees a place of employment; the other older adult participants were recruited through personal connections. For confidentiality reasons, participants’ educational backgrounds were not recorded. Judging from the professional specializations of the adults up to age 59, however, most had probably achieved at minimum a university degree, making the groups largely homogeneous. On the other hand, since many of the older adults registered with the Job Centre were retired craftspeople, self-employed workers, or housewives, and due to the cohort effect of this generation, the proportion of this age group with a university degree was thought to be less than that in the younger adult group. Regardless, as can be seen in the results, no critical difference was observed between the task results of the younger and older groups, leading us to conclude that if there were differences in educational achievement between the age groups, these differences likely had little impact on spatial perspective taking ability. None of the participants suffered from any neurological disabilities that could have materially influenced their performance on the experimental tasks. Furthermore, all the older adult participants were administered the

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Revised Hasegawa Dementia Scale (Hasegawa, 1983), the most commonly used dementia screening test in Japan, to assess their cognitive functioning. Their scores exceeded the cut-off value (20 out of a maximum of 30 points) for dementia symptoms, confirming that our older adult sample did not suffer from excessive cognitive impairment. Polychromous logistic regression analysis was carried out to examine the association between the scores in correct responses (dependent variable) and their frequency (independent variable). Results showed a rapidly ascending curve of frequency with the rise in scores (y = 368.5/(1 + 1367.185e^ – 0.793x); F(1, 6) = 10.20, p < .05, h2 = .10, R2 = .63) and that perfect scores occupied 76.8% of the whole (M = 8.37; SD = 1.34; maximum score was 9). Data from 25 participants (5.8%: eleven 6-year-olds, eight 7-year-olds, one 8-year-old, two 62-year-olds, two 69-year-olds, and one 79-year-old) who scored less than 5 (under 2.5 times the SD to the average) were excluded from the main analysis because, based on findings from the pilot study (Watanabe & Takamatsu, 2012), it was suspected that they were using an inappropriate strategy, such as adhering to one side, or had misunderstood the task. In total, eight age groups separated by 10-year intervals were constructed (Table 1). There was no significant difference in the proportion of males and females among the age groups (c2 (7, N = 403) = 5.78, n.s.); our final sample was 46.4% male and 53.6% female.

Table 1. Numbers and Average Age of Each Age Group Age group 6-9

Male

Female

Average age

Total

6.5

47

19 (14)

28 (6)

10-19

29

30

13.7

59

20-29

30

38

21.8

68

30-39

16

25

35.1

41

40-49

31

34

44.4

65

50-59

18 (2)

19

53.6

37

60-69

13 (2)

20

65.5

33

70-78

31

22 (1)

73.8

53

Total

187

216

403

Note: The numbers for the 25 participants excluded for their low number of correct answers are shown separately in parentheses.

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Apparatus To engage young participants and help them understand the task, we used a video game format. A specialized yet easy-to-use video game controller (XaviX PORT; SSD Company Limited, Japan) compensated for any potential decreases in motor function among our older adult participants. The controller detected a player’s hand movement and projected a virtual palm onto a monitor. Players could progress through the game simply by placing the virtual palm on the icon presented on the screen (labeled “NEXT,” “WAIT HERE,” “YES/NO,” etc.) or on either of the windows of the house for 2000 ms. The controller was set up at abdomen height, at a distance of approximately 30 cm from the participants. The position of the controller was adjusted so that the virtual palm (the circular symbol at the bottom of the screen in Figure 1) could be moved to every corner of the 14” (minimum) color screen when participants moved their palms within a 10-cm circle around their chests. This controller is increasingly being used in recreational games played at facilities for older adults in Japan. Thus, children and older adults were able to perform the video game task in this study without incurring undue confusion or excessive time to acclimatize to the game console.

Figure 1. A scene from the video game task. The circular symbol at the bottom left of the screen is the virtual palm. The palm icon at the bottom of the screen indicates the standby region.

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Procedure In order to familiarize the participants with the procedure (Figure 2), a practice session was completed before the experimental session. The youngest (kindergarten-age) participants were introduced to the video game task by observing other children engaged in experimental sessions. In both practice and experimental sessions, a countdown of “3, 2, 1” appeared in the center of the screen for 3000 ms after a child character hid behind any side of the window frames; the countdown was also spoken by a woman’s voice. During the practice session (in which the house was not rotated), the experimenter explained the task procedure to each participant in detail; then, participants were instructed to move the virtual palm to any window in order to find each hiding child, while in the subsequent experimental sessions, the game progressed automatically according to the signs on the screen without any verbal instructions. Between responses, participants were to return the virtual palm to the standby region indicated by the palm icon (Figure 1). If the virtual palm was moved outside the standby region before the “START” signal appeared, an error would occur, and the countdown would be stopped. After returning the virtual palm inside the standby region, the countdown started again from the beginning. Participants were judged to have sufficiently understood the task procedure when they could correctly detect the location of the hiding child three times in a row during the practice session. At the beginning of the experimental session, two trials were presented at the 0-degree position as an introduction (i.e., the house was not rotated in the first two trials); seven other positions were presented in successive trials in which the house was rotated. The angle of rotation (45°, 90°, 135°, 180°, 225°, 270°, and 315° counter-clockwise) was randomized by the computer program. This rotation took a maximum of 300 ms, which was the time taken to turn the house 180°, and was followed immediately by the “START” signal displayed for 1000 ms. Response times were defined as the time that elapsed between the “START” signal and the moment that a player put his or her virtual palm on any window. Players’ response times for each rotation angle and the accuracy of their responses were automatically measured by the video game controller. In this procedure, it was assumed that participants would use spatial perspective taking corresponding to the angle of rotation of the house in order to recognize the house as being upright from the vantage point of an imaginary observer. Design One trial included the process from the appearance of a child character to the response with the virtual palm. In an experimental session, the question was

Figure 2. Schematic of experimental session in the video game task. An example of the house is rotated to 180°. The house was not rotated during a practice session. Response times include the presentation time of the START signal (1000 ms), but exclude the time to detect the virtual palm placing on a window (2000 ms).

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repeated nine times with a different child character each time, while in practice sessions, it continued only until the performance criterion was achieved. Since the younger children required 15 to 20 minutes to complete these two sessions, it was thought that additional experimental sessions would reduce their attention and cause an inordinate emotional burden. In contrast, when two or three experimental sessions were repeated for university students in a pilot study, their results showed a tendency to improve. In order to collect data from all age groups based on equivalent conditions, each participant underwent just one experimental session. RESULTS Two measures of response time were analyzed: imagining body movement and both imagining body movement and the other cognitive information processing. Response time between stimulus presentation and response from each rotation angle was termed the common response time (“RT-C”), encompassing both imagining body movement and the other cognitive processes required to solve the task; only RT-Cs at 0° represented the cognitive information processing ability aside from imagining body movement alone. When plotting such response times against rotation angles in a spatial perspective taking task, a bell-shaped graph, peaking at around 180° and with relatively straight gradients, is typically obtained (Watanabe, 2011); thus, it was expected that the time for imagining body movement increases linearly according to the increase in rotation angle in this study (Figure 3). Rotation angles that were symmetrical to the median line of the participant were at equal distances from the participant (e.g., 90° and 270°). Therefore, data corresponding to rotation angles greater than 180° were included along with data corresponding to angles less than 180°. To confirm this expectation, the linear formulas of each age group considering the four locations between 45° to 180° were calculated; results showed high coefficients of determination ranging from .814 (20- to 29-year-old group) to .997 (6- to 9-year-old group). The linear function formulas on the four locations between 45° to 180° were also calculated for every participant. In the formula y = ax + b (x: degrees of rotations, y: response times), the gradient “a” represents the theoretical time per degree for imagining body movement, and the intercept “b” represents the theoretical time required for other cognitive information processing. Each gradient “a,” which ranged from .4257 to 28.4013, was multiplied by 180 and rounded off to become an integer between 77 (20-year-old woman) and 5112 (6-year-old boy). This gradient-based index was labeled “RT-G” in order to represent the theoretical response time to rotate one’s body mentally to the 180° position (imagining body movement); this did not include the time

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Figure 3. Average RT-Cs (ms) for each rotation angle in the age groups.

required for any other cognitive information processing. The main results in this study were produced using RT-C and RT-G. Before beginning the analysis, the existence of speed-accuracy trade-offs was examined. Pearson’s correlation coefficients were calculated between RT-C or RT-G and the number of correct responses, including those with low scores, in each age group. Only the 70- to 78-year-old group had a significant negative correlation (r = –.34, n = 54, p < .01), which meant that some were excellent in both speed and accuracy while others were inferior in both. No significant coefficients were found in the other age groups. These results indicate that there was no considerable artifact of trade-offs between speed and accuracy. Furthermore, a one-way analysis of variance (ANOVA) was conducted on the number of correct answers with age group as the independent variable. The results indicated a significant main effect of age group (F(7, 420) = 29.04, p < .01, partial h2 = .326), and Scheffé’s multiple comparisons test on age groups revealed that the 6- to 9-year-old group (M = 6.75) was significantly inferior to the other age groups (p < .01). A one-way ANOVA excluding those with scores less than 5 also indicated a significant main effect of age group (F(7, 395) = 12.04, p < .01, partial h2 = .176), and the inferiority of the 6- to 9-year-old group (M = 7.85) to five age groups between 10 and 59 years old (p < .01). Age groups other than

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the 6- to 9-year-olds showed a ceiling effect; those average scores ranged from 8.34 to 8.93 points. The average RT-Cs of the eight locations from 0° to 315° for each age group displayed a hill-like curve that peaked at approximately 180°. A three-way repeated measures ANOVA was conducted on RT-C with age group and sex as the independent variables and rotation angle as the repeated measure. The results indicated significant main effects of both age group (F(7, 387) = 35.75, p < .01, partial h2 = .393) and rotation angle (F(5.7, 2215.1) = 72.75, p < .01, partial h2 = .158; Greenhouse-Geisser correction). Scheffé’s multiple comparisons test on age groups revealed that the 6- to 9-year-old group was significantly slower than the other age groups (p < .01); and the 70–78- and 60- to 69-year-old groups were significantly slower than the 20- to 29-year-old group (p < .01). The interaction between age group and rotation angle was also significant (F(40.1, 2215.1) = 5.14, p < .01; Greenhouse-Geisser correction). No significant effect of sex was found (F(1, 387) = .001, n.s.). Under Levene’s test, the standard deviations in the average RT-Cs were significantly different between the age groups (F(7, 395) = 14.24, p < .01). The 6- to 9-year-olds (SD = 1094.1) had a larger value than those of the other groups whose SDs ranged from 503.9 to 782.0. Therefore, Kruskal-Wallis’s test was conducted on the average RT-Cs to verify the main effect of age group in the ANOVA, with age group as the independent variable; the result also indicated a significant main effect of age group (c2 (7, N = 403) = 136.05, p < .01). Scheffé’s multiple comparisons test on age group revealed that the 6- to 9-year-old group was significantly slower than the 10- to 19-, 20- to 29-, 30- to 39-, 40- to 49-, and 50- to 59-year-old groups (p < .01); the 10- to 19-year-old group was significantly slower than the 20- to 29-year-old group (p < .01); the 70- to 78-year-old group was significantly slower than the 20- to 29- and 30- to 39-year-old groups (p < .01); and the 50- to 59- and 60- to 69-year-old groups were significantly slower than the 20- to 29-year-old group (p < .01). The average RT-Cs for each age confirmed a curvilinear change wherein response time accelerated from childhood to early adulthood and slowed down in later life (y = .88x2 - 73.6x + 2056; x: age, y: average RT-C; F(2, 400) = 69.73, p < .01, h2 = .26, R2 = .26). Furthermore, a two-way ANOVA was conducted on RT-Cs at 0° (i.e., the house was not rotated) with age group and sex as independent variables to compare the cognitive information processing other than imagining body movement among age groups; while the values of intercept “b” were not used for this purpose because some of them had negative values, indicating an impossible situation in which the virtual palm had begun to move before the “START” signal for the experimental program. The analysis indicated a significant main effect of age group (F(7, 387) = 10.39, p < .01, h2 = .15). Scheffé’s multiple comparisons test revealed that the 6- to

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9-year-old group’s value was significantly larger (M = 1037.7, SD = 624.3) than the other age groups (p < .05). No significant effect of sex was found (F(1, 387) = .036, n.s.). Under Levene’s test, the standard deviations for the RT-Cs at 0° were also significantly different among the age groups (F(7, 395) = 7.39, p < .01), with 6- to 9-year-olds (SD = 623.3) and 10- to 19-year-olds (SD = 604.3) having a significantly larger value than the other groups (from 290.1 to 406.3). To verify the main effect of age group in the ANOVA, Kruskal-Wallis’s test was conducted on the RT-Cs at 0° with age group as the independent variable; the result also indicated a significant main effect (c2 (7, N = 403) = 61.80, p < .01). Scheffé’s multiple comparisons test on age group revealed that the 6- to 9-year-old group was significantly slower than the 20- to 29-, 30- to 39-, and 40- to 49-year-old groups (p < .01), and the 20- to 29-year-old group was significantly faster than the 40- to 49-, 50- to 59-, and 60- to 69-year-old groups (p < .05). A two-way ANOVA was conducted on RT-Gs with age group and sex as the independent variables, which meant investigating the meaning of the significant interaction between age groups and rotation angles in a three-way repeated measures ANOVA on the average RT-Cs. The analysis indicated a significant main effect of age group (F(7, 387) = 13.60, p < .01, h2 = .20, Figure 4). Scheffé’s multiple comparisons test on the mean RT-Gs revealed that the 6- to 9-year-old group’s value was significantly larger (M = 3374.3) than the other age groups (p < .01). No significant effect of sex was found (F(1, 387) = .034, n.s.). Under Levene’s test, the standard deviations for the RT-Gs were also significantly different among the age groups (F(7, 395) = 12.95, p < .01), with 6- to 9-year-olds (SD = 2671.4) having a significantly larger value than the other groups (from 546.7 to 1505.6). To verify the main effect of age group in the ANOVA, Kruskal-Wallis’s test was conducted on the RT-Gs with age group as the independent variable; the result also indicated a significant main effect (c2 (7, N = 403) = 66.11, p < .01). Scheffé’s multiple comparisons test on age group revealed that the 6- to 9-year-old group was significantly slower than the 20- to 29- and 40- to 49-year-old groups (p < .01). DISCUSSION Before discussing the importance of the results, the validity of the task in this study should be reexamined. In an ordinary reorientation task, five types of strategies can be used: spatial perspective taking, whereby object images are reconstructed from another vantage point different from his or her vantage point; mental rotation, whereby an object image is rotated in one’s mind; perceptual updating, in which object locations are updated across eye tracking;

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Figure 4. Average RT-Gs (ms) and standard deviations (error bars) for each age group.

external allocentric cues, which are used as frame of reference for locating a target object; or logical judgment, whereby the left and right sides of the target object are mentally reversed and then applied to the percept. However, the rapid rotation of the house stimulus in this task prevented perceptual updating, and the simple and symmetrical house figure as an experimental stimulus made it difficult for participants to use external allocentric cues. Additionally, each 45 degrees of rotation produced both the up-down and left-right relationship simultaneously, making it more difficult for participants to judge logically. Thus, we considered the two remaining alternatives: spatial perspective taking and mental rotation. Both mechanisms are used to update the position of a target relative to self, but they differ in that perspective spatial taking moves or rotates one’s body relative to the target, whereas mental rotation moves the target object relative to the body. It is very difficult to strictly distinguish the two in an experimental task; however, we thought it possible to increase the probability that participants would use a spatial perspective taking strategy in this study by considering the following three phenomena. First, of the 49 participants interviewed about their strategies after the experiment, 45 reported using spatial perspective taking: “I imagined as if I

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had moved to any position around the monitor frame and was looking at the house upright.” The remaining four included two younger children who were not able to describe their strategies, one university student who reported using a perceptual updating strategy (“I could track the movement of the window”), and one middle-aged adult who had used mental rotation for the house figure (“I mentally rotated the original house until it overlapped with the one presented”). This means that most participants imagined that they were looking at the house figure by rotating their bodies, while they were actually forbidden to move during the experiment. Second, the figure of a house used in the current task was not symmetrical on the horizontal axis, whereas it was symmetrical on the vertical axis. This led participants to visualize an upright image of the house throughout the task. Participants should imagine themselves standing in front of the house, simultaneously rotating the image of both themselves and the house. Such imagination was possible only if participants could shift their perspective to different vantage points. Third, experimental objects are not always mentally rotated, even in an ordinary mental rotation task. Adults can use two strategies in attempting to solve a mental rotation task: moving the object or moving oneself around the object (Schultz, 1991). Therefore, even if a linear relation is found, it does not necessarily signal the use of a mental rotation strategy; rather, it might indicate the use of a spatial perspective taking strategy. The second reason above reinforces this possibility. Meanwhile, younger children tend to use simpler strategy such as comparing details of objects without rotating an object image in their mind; thus, their response times may not show a linear relation to the angle of rotation (Quaiser-Pohl, Rohe, & Amberger, 2010). Children who could not describe their strategies in the post-experimental interview may have used inappropriate solutions. For the above three reasons, it is highly probable that participants in this study, especially older children and adults, used a spatial perspective taking strategy. In the results of this study, the pattern of average RT-Cs for each age was approximated by the quadratic curve and similar to the findings of previous studies (e.g., Hasan, Walimuni, Abid, Frye, Ewing-Cobbs, Wolinsky, et al., 2011). However, the middle-aged and older adults did not display performance inferior to the younger adults on RT-Gs. Conversely, children in the 6- to 9-year-old group were generally inferior to the other age groups in terms of both RT-Cs and RT-Gs. To interpret these results appropriately, it is necessary to remember that RT-G represented the theoretical speed of imagining body movement, while RT-C encompassed the combined speed of the imagining body movement and the other cognitive processes required for

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solving the task as a whole. With these assumptions in place, we arrived at the following conclusions. Spatial perspective taking appeared not to be impaired in normal aging, as is often found with working memory (Park, Smith, Lautenschlager, Earles, Frieske, Zwahr, et al., 1996) or sensory functioning speed (Baltes & Lindenberger, 1997). Thus, the often-reported decline in spatial perspective taking might not stem from a failure in the ability to perform imagining body movement, but from deficits in other cognitive information processing abilities. For example, decreased inhibitory function (Hasher & Zacks, 1988) or a decline in working memory capacity (Yamadori et al., 1999) could account for these declines. Older adults also have weaker selective attention than young adults (Hartley, 1993). Any of these factors might hinder the cascade of cognitive processes responsible for good task performance, even if imagining body movement was possible. Of course, it is likely that smooth movement could not be performed if the imaginary body was fixed to its current location. Further, young children exhibited the longest response times on RT-Cs at 0° (and thus the weakest cognitive information processing ability); older adults also appeared to be losing their ability relatively slowly. Therefore, cognitive information processing other than imagining body movement might be acquired during childhood and then decrease gradually in later life. This change is similar to that of executive functions (Lehto, Juujaervi, Kooistra, & Pulkkinen, 2003) or some kinds of cognitive functions (Baltes & Lindenberger, 1997). Based on these considerations, we can conclude that spatial perspective taking, particularly imagining body movement, remained relatively robust in normal aging as suggested by Watanabe (2011). To further reinforce this finding, it is important to verify the sample validity. Our protocol excluded older adults with diseases such as dementia or cerebral vascular disorder by screening with the Revised Hasegawa Dementia Scale (Hasegawa, 1983). As a result, it is possible that the older age groups in this study included only normally aging subjects and that our results, therefore, would not generalize to the wider population. However, the proportion of older adults with dementia or cerebral vascular disorder is not so high that research results on this population must always be qualified. For example, Hankey and Warlow (1999) showed that the stroke onset rate per year is 0.2%. In the present study, some participants (two of 33 people from the 60to 69-year-old group (6.1%) and five of 53 people from the 70- to 78-year-old group (9.4%)) could be classified within the first stage of attenuation in cognitive functions, applying the current results of RT-Gs to the result from Watanabe, Katagi, Ishikawa, and Kawamura (2008) which investigated spatial

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perspective taking ability in older patients with dementia or cerebrovascular disorder. This suggests that our participants were not a special sample of older adults. A larger problem, if anything, is the small ratio of great age: only 11.3% of valid data came from individuals over 76 years of age in this study. Some research has suggested that such older adults who exhibit a prominent decline in motor function still display relatively well-maintained spatial perspective taking ability (De Beni, Pazzaglia, & Gardini, 2006; Ohta, Walsh, & Krauss, 1981). Inagaki et al. (2002), however, revealed that in older adult participants, including those over 76 years old, the percentage of correct responses was much lower and the number of egocentric errors much higher than in the two younger age groups. When the older adults over 76 years are examined fully, it may be revealed that a commensurate decline in the performance of spatial perspective taking does indeed exist. In sum, it can be concluded that this research is sufficiently diverse to reflect the real population under 80 years old. In addition, it is good to close this argument with suggestions for future research, based on the current study’s limitations. The possibility that our participants used a mental rotation strategy in our task cannot be entirely ruled out, because whether one changes oneself to align with the subject (spatial perspective taking) or changes the subject but not oneself (mental rotation) depends on which function takes precedence under certain conditions (Noda, 2010). Hence, future aging research on imaginary reorientation of objects should examine which function will be well maintained and which will rapidly decline. Future research should also focus on investigating the features of imagining body movement in more detail, the following two points in particular. First, the relationship between imagining body movement and brain activity for motor skills (premotor area, somatosensory area, etc.) should be a high priority. It has been reported that activity in both the premotor area and pre-cingulate gyrus, which regulate actual movements, increased when people imagined mimicking an act from their own perspective (Decety, 1996; Jeannerod, 1995). Further, it has been confirmed that motor sensations occur along with imagined movement, and that activity in somatosensory areas also increases (Jackson, Meltzoff, & Decety, 2006). These reports suggest two possibilities: the domain relevant to cerebral movement participates in imagining body movement, and improvement in motor functions is advantageous to imagining body movement. If these can be confirmed, improvement in motor functions may lead to the development of imagining body movement. Second, imagining body movement can conflict with the somatic sensations generated by a real body. To cancel this conflict and enable smooth

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imagining body movement, it is necessary to detach the imaginary body from the constraints of real body. May (2004) provided evidence in support of this hypothesis. He assumed that conflicts between sensorimotor codes of object location and cognitive codes for the same object locations would occur in imagining body movement when his experimental participants were asked to point to an unseen object location after spatial perspective taking. Larger latency and increased pointing errors were discovered as a function of the disparity between real and imagined perspectives, which reflected the degree of conflict. Anyone lacking sufficient inhibition function (Hasher & Zacks, 1988) to cancel the conflict cannot smoothly take perspectives, because the imaginary body would be fixed to the current location by the somatic sensations generated by the real body. Drastic increases in egocentric errors in the older adults (Inagaki et al., 2002) may be attributable to their inability to cancel the conflict. Despite the acknowledged limitations of this research, the present findings indicate that spatial perspective taking, particularly imagining body movement, remains robust in normal aging. This corroborates other evidence of good spatial orientation functions in the older adults. At the same time, in order to improve the quality of life of disabled elders with diseases such as dementia or cerebral vascular disorder, the mechanism by which these diseases impair spatial perspective taking must be identified. Our results further indicate the presence of different types of developmental factors at work in spatial perspective taking. Some abilities (e.g., imagining body movement) are preserved in later life, but others (e.g., inhibitory functions or working memory) decline easily. Developmental features of these abilities should be investigated carefully one by one; the interactive changes in the cognitive abilities involved in spatial perspective taking could then be examined from a dynamic systems perspective. Finally, considering the impact of drastic changes in physical condition on the older adults, knowledge from medicine and neuronal physiology will advance psychological aging research. ACKNOWLEDGMENT I would like to express my deepest gratitude to Prof. G. J. Bremner whose comments and suggestions were innumerably valuable to my article. REFERENCES Baltes, P. B., & Lindenberger, U. (1997). Emergence of a powerful connection between sensory and cognitive functions across the adult life span: A new window at the study of cognitive aging? Psychology and Aging, 12, 12-21.

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Direct reprint requests to: Masayuki Watanabe Department of School Psychology Shiga University 2-5-1, Hiratsu, Otsu, Shiga, 520-0862 Japan e-mail: [email protected]