Aging Clin Exp Res DOI 10.1007/s40520-013-0184-9
ORIGINAL ARTICLE
Task requirements and their effects on imagined walking in elderly Michael Kalicinski • Markus Raab
Received: 19 August 2013 / Accepted: 27 November 2013 Ó Springer International Publishing Switzerland 2013
Abstract Background and aims Mental training has the potential to enhance motor performance and behavior in older adults. Yet several studies have revealed age-related alteration of motor imagery (MI) ability, suggesting that mental training is not applicable for older adults. The purpose of the present study was to estimate MI performance in older adults, taking into account task requirements. Methods MI performance of 20 older (mean age 70.75 ± 3.68 years) and 22 younger (mean age 24.31 ± 1.25 years) adults was estimated with the mental chronometry paradigm from the first-person perspective. Participants completed four walking tasks with different requirements, walking (A) in a straight line; (B) with two changes of direction; (C) on uneven ground; and (D) while additionally flipping switches. Path length and width were constant across tasks. MI ability was also measured with the Controllability of Motor Imagery Test, in which body parts have to be controlled and manipulated mentally. In addition, participants reported self-rated clarity of their MI in both tests after each trial. Results Our data suggest no generalized alteration in MI of walking with different task requirements among older adults. A significant Age 9 Condition 9 Task interaction emerged, but this result could not be attributed to a specific task requirement in post-hoc tests. For controllability of MI, older adults showed alterations in imagining body postures. These results showed dissociation with the selfrated clarity in both tests. Conclusion The present findings suggest that older adults show no age-related alterations in MI for familiar M. Kalicinski (&) M. Raab Institute of Psychology, German Sport University Cologne, Am Sportpark Mu¨ngersdorf 6, 50933 Cologne, Germany e-mail: [email protected]
movements. Mental Training of familiar movements could therefore be feasible for older adults and enables promising intervention strategies. Keywords Aging Motor imagery Mobility Mental chronometry
Introduction Imagine yourself standing at the bottom of a staircase with 20 steps of regular height and a handrail on the right. Now imagine climbing the steps to the top. This mental exercise illustrates that humans can produce images of real environments—mainly based on previous experience and verbal descriptions—and can imagine moving through these environments without executing real movements. This skill is defined as motor imagery (MI) and is based on the internal reproduction of action representations within working memory without any overt output [1, 2]. How does MI work? Jeannerod’s [3] simulation theory states that during covert simulation of motor actions, the neural networks that are activated are similar to those activated during overt (real) execution, because execution and imagery share the same action representations [4]. The representations of motor action do not simply rely on memorized actions but also depend on the immediate task requirement [3]. It is therefore not surprising that actions with specific task requirements elicit similar vegetative responses [5] and have similar temporal characteristics [6] under covert and overt movement conditions. The temporal congruence of these conditions is particularly accurate for usual and familiar movements such as writing and walking [7]. It has been suggested [6] that temporal accuracy depends on individual capabilities (e.g., higher in elite
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athletes), movement focus (e.g., lower for movements with variation of postural constraints), environmental constraints (e.g., lower during competition), and task difficulty (e.g., lower for rapid and attention-demanding movements). Yet these results were obtained in studies in the sports domain; it remains unclear how more everyday task requirements affect temporal accuracy. In the last decades, research on MI has expanded to investigate if mental training is also applicable and beneficial for older adults (for a recent review, see [8]). For effective use of mental training, such as fostering specific movement skills or routines, a preserved MI ability is considered a prerequisite [9]. A recent review on MI ability in older adults stressed that older adults are in general able to perform MI accurately and vividly but show difficulty in the simulation of unusual movements [10]. Several studies documented an age-related decline in the ability to mentally reproduce the temporal characteristics of movements accurately. Tasks such as walking [11–14], arm pointing [15–17], and arm lifting [18] were studied. A decline in temporal accuracy was shown for all of the above movements without systematically manipulating task requirements. Factors that have been found to affect accuracy include task familiarity [16, 19] and spatiotemporal task constraints [17], such as track length [13, 14] and width [12]. The latter study reported that older adults systematically overestimated actual walking durations on MI trials, more so for narrower walking tracks, and concluded that age-related MI deficits increase when the constraints become more difficult. In other words, decreasing track width was equated with increasing difficulty. Thus, it has been shown that spatiotemporal constraints influence MI performance, but it remains unclear whether more everyday task requirements also elicit MI deficits in older adults. The main aim of the present study was to explore the potential relationship between MI deficits and task difficulty by varying the tasks along other dimensions besides path length and width. Specifically, difficulty was manipulated by adding requirements to the walking task. We hypothesized (a) that MI performance would show an agerelated alteration and (b) that this age-related alteration would differ among tasks. In addition we explored if MI deficits would also emerge for the controllability of MI and asked participants to verbalize their self-rated MI ability.
Methods Participants Participants were 20 older (mean age 70.75 ± 3.68 years) and 22 younger (mean age 24.31 ± 1.25 years) adults. The
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older participants all lived independently in the community. All participants who filled out a custom-made questionnaire were all indicated to have normal or corrected-tonormal vision, and all reported being free of orthopedic or muscular impairment. Because all participants arrived without help at the agreed-upon time in the agreed-upon place, properly followed our instructions, and completed questionnaire items requiring memory and orientation (e.g., address, date of birth, medications used), we deemed them to be free of gross cognitive impairment. Each participant reported having regularly participated in sports or other physical activities. All gave their written consent to participate in this study, which was preapproved by the local ethics committee. Mental chronometry paradigm To investigate MI performance, we had participants engage in four walking tasks: walking (A) in a straight line; (B) with changes of direction; (C) on uneven ground; and (D) while additionally flipping switches. The spatial constraints were constant for the four tasks (track length 600 cm; track width 50 cm). Setting and paths are illustrated in Fig. 1. In the first condition, all participants imagined walking without actual execution. In the second condition, they actually walked. Participants were asked to execute walking for each task one time to get familiar with the spatial constraints and requirements. The four tasks were then presented in randomized order with six repetitions per task in the first (imagined) condition (i.e., a total of 24 trials) and three repetitions in the second (executed) condition (i.e., a total of 12 trials). A rest period of 3 min was provided between conditions. We always started with the imagined condition to prevent the use of strategies such as step counting or replication of remembered durations. In the imagined condition, participants had to stand in front of the required walking path, which was intended to provide a body posture that was congruent with the imagined movements. Participants were then asked to get in the starting position, which meant lifting the forward section of the right foot over an electronic pressure mat. They could start MI of walking independently by bringing the foot down on the pressure mat. They were instructed to complete each trial at a self-paced walking speed, to imagine their movements from the first-person perspective, and to lift the foot when their shoulders crossed the finish line. Duration for the MI was measured by stopwatch software using the contact with the pressure mat as start and the lift off as stop. Participants did not get feedback on the elapsed time for each trial. Procedural training on a separate walking track occurred before data collection started. During training trials for the imagined condition, participants were verbally questioned about the vividness
Aging Clin Exp Res Fig. 1 A three-dimensional model of the experimental setting for the four tasks of the mental chronometry test: walking (A) in a straight line; (B) with direction change; (C) on uneven ground; and (D) while additionally flipping switches. The checkered pattern highlights the target area
and clarity of their mental images and whether they had succeeded in using the first-person perspective. The procedure for the executed condition was identical, except that contact with an additional pressure mat at the end of the path was used as stop for time measurement. Controllability of Motor Imagery test To get a comprehensive estimation of MI ability participants engaged in an additional MI test. For the Controllability of Motor Imagery (CMI) test [14, 20], participants must create a mental picture of themselves and afterward assume a body position that was reached at the end of the MI. Participants stand with their eyes closed on a cross marked on the floor and receive six consecutive instructions for moving a body part into a specific position. They are asked to remain physically still and only to imagine moving their body parts as requested. After the sixth instruction, participants open their eyes and arrange themselves in the assumed final body configuration. Participants score one point for each correct instruction, thus earning up to five points per trial (the first instruction is a standardized home position and is not awarded a point). In addition, one point is given for the correct overall final body configuration. The test consists of ten trials, and the maximum score therefore is 50 for the elements and 10 for the final postures. The test shows a high level of internal consistency with a = .93 [14]. Clarity of MI To get an evaluation of self-rated MI clarity, participants were asked to rate each MI trial in both tests using the rating scale of the Kinesthetic and Visual Imagery Questionnaire (KVIQ). The scale consists of a five-point Likert scale in two imagery modalities: visual (1, no image to 5, image as clear as really seen) and kinesthetic (1, no feeling to 5, feeling as really executed). For the mental chronometry test a mean score was calculated for each task. In
addition a mean score over all tasks was calculated for the mental chronometry and CMI tests. Data analysis To test the hypotheses we ran a 2 (Age: older, younger) 9 2 (Condition: imagined, executed) 9 4 (Task: A, B, C, D) analysis of variance (ANOVA) on the mean durations across repetitions, with age as the between-subjects factor and repeated measures on condition and task. For the additional questions, CMI scores for the final and elements analysis were compared between age groups with a t test. For the self-rated clarity measures we used the kinesthetic and visual scores as dependent variables and ran a 2 (Age: older, younger) 9 2 (Modality: visual, kinesthetic) 9 4 (Task: A, B, C, D) ANOVA with age as the betweensubjects factor and repeated measures on modality and task, as well as a 2 (Age: older, younger) 9 2 (Modality: visual, kinesthetic) 9 2 (Method: Mental chronometry, CMI) ANOVA with age as the between-subjects factor and repeated measures on modality and method. Significant effects of the ANOVAs where the factor age was included were explored by Fisher’s LSD post-hoc analyses. A significance criterion of a = 0.05 was adopted for all results reported. Effect sizes are reported for F values larger than 1 to avoid reporting unreliable effect sizes. Effect sizes for the results of the ANOVA were estimated by calculating the g2. Thereby g2 of [0.01 indicate a small, [0.06 a medium and [0.14 a large effect (Cohen). Effect sizes for the results of the t tests were estimated by calculating the Cohens d. Thereby d [ 0.2 indicate a small, d [ 0.5 a medium, and d [ 0.8 a large effect (Cohen).
Results To investigate the performance in mental chronometry, we focus on the analyses of the condition effect, as it
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Aging Clin Exp Res old MDI
old MDE
young MDI
young MDE
dual task tasks requirements
Fig. 2 Mean durations ± standard error of both age groups for both conditions separated by tasks
ground
bend
basic 0
represents the difference between imagined and executed movement durations, and its interactions with age and tasks. The mean duration of both age groups for each condition and task are illustrated in Fig. 2. Both age groups overestimated the duration in the imagined condition. Respectively, ANOVA of durations revealed significant effect of Condition. For our first hypothesis, the ANOVA revealed no significant effect of Age 9 Condition, although older adults showed a tendency for higher differences. The predicted age-related alteration of MI performance could therefore not be confirmed in the present study. For our second hypothesis, we found a significant effect of Age 9 Condition 9 Task, suggesting that group differences, as predicted, show an interaction with different task requirements. Further post-hoc analyses showed significant condition differences for each task in both age groups (all p \ 0.001). In both conditions task differences in the old group emerged between task A and the other tasks, and B and the other tasks (all p \ 0.001). Thereby durations of task C and D were longer than for task A and B. No significant differences were observed between task C and D. A significant effect was also found for Condition 9 Task. Further main and interaction effects, p and F values, and eta squared are illustrated in Table 1. An additional aim was to explore if MI alteration emerged in other MI tests. For the CMI test (final), we found a mean score of 2.1 (SD = 1.89) for the older group and a three times higher mean score of 7.09 (SD = 2.1) for the younger group. A t test yielded significant group differences, t (40) = 8.086; p \ 0.001; d = 2.55. For the CMI test (elements) a mean of 35 (SD = 5.64) for the older group and a mean of 46.23 (SD = 2.65) for the younger group were calculated. A t test yielded significant group differences, t (40) = 8.281; p \ 0.001; d = 2.65. Table 2 shows the mean scores for self-rated visual and kinesthetic MI clarity for the four tasks in the mental chronometry test and for the CMI test. In the mental chronometry
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2
4 6 duration in seconds + SE
8
10
Table 1 Results of the analyses of variance Factors
F
g2
p
Mental chronometry Age
F (1, 40) = 1.660
[0.05
Condition
F (1, 40) = 24.130
\0.001
0.376
Task
F (3, 120) = 83.758 \0.001
0.676
Age 9 condition
F (1, 40) = 0.248
[0.05
Age 9 task
F (3, 120) = 3.005
0.033
0.069
Condition 9 task
F (3, 120) = 5.425
0.001
0.119
Age 9 condition 9 task
F (3, 120) = 2.762
0.045
0.064
Motor imagery clarity in walking Age
F (1, 40) = 5.715
0.022
0.125
Modality Task
F (1, 40) = 1.645 F (3, 120) = 3.370
[0.05 0.020
0.077
Age 9 modality
F (1, 40) = 1.645
[0.05
Age 9 task
F (3, 120) = 0.586
[0.05
Modality 9 task
F (3, 120) = 6.248
\0.001
0.135
Age 9 modality 9 task
F (3, 120) = 4.459
0.005
0.100
Motor imagery clarity in methods [0.05
Age
F (1, 40) = 0.731
Modality
F (1, 40) = 8.023
Method
F (1, 40) = 5.564
Age 9 modality
F (1, 40) = 0.242
Age 9 method
F (1, 40) = 11.507
Modality 9 method
F (1, 40) = 0.599
[0.05
Age 9 modality 9 method
F (1, 40) = 1.697
[0.05
0.007
0.167
0.023
0.122
[0.05 0.002
0.223
test, the older adults rated their clarity significantly higher than the younger adults. Whereas we found this main effect of age, no significant interaction of Age 9 Modality or Age 9 Task was revealed. The ANOVA further revealed a significant main effect of Task. Post-hoc analysis showed that the rating of task D was significantly higher than in the other tasks. In the CMI test the two groups showed similar ratings of their MI clarity. Comparing the average scores for
Aging Clin Exp Res Table 2 Means of MI rating and Standard Deviation, separately for tasks in the MC test and for method (MC and CMI), by age group (older, younger) and modality (visual, kinesthetic) Task or method
Older Visual
Younger a
Kinesthetic
b
Visuala
Kinestheticb
Task Straight
4.11 (±0.72)
3.97 (±1.01)
3.84 (±0.67)
3.62 (±0.90)
Direction change Uneven ground
4.03 (±0.74) 4.03 (±0.70)
3.88 (±0.86) 3.93 (±0.77)
3.78 (±0.75) 3.70 (±0.49)
3.53 (±0.75) 3.70 (±0.56)
Dual task
4.15 (±0.58)
4.07 (±0.67)
3.96 (±0.51)
3.77 (±0.68)
MCc
4.08 (±0.63)
3.96 (±0.77)
3.82 (±0.52)
3.65 (±0.66)
CMId
3.61 (±0.90)
3.45 (±0.95)
3.61 (±0.63)
3.49 (±0.62)
Method
a
Visual scale: 1 (no image) to 5 (image as clear as really seen)
b
Kinesthetic scale: 1 (no feeling) to 5 (feeling as really executed)
c
Mental chronometry
d
Controllability of motor imagery
mental chronometry and CMI, we found a significant Age 9 Method interaction. Post-hoc analysis showed that significant method differences only emerged in the old group (p \ 0.001) with a higher rating for the imagined walking. Group difference only emerged for the rating of MI in the mental chronometry test differences (p = 0.035) with a higher rating among older adults. Results of the ANOVAs for MI clarity in walking and MI clarity in different methods are illustrated in Table 2. Summarizing the main results and in contrast to our predictions no significant interaction of Age 9 Condition was confirmed, but a significant three-way interaction of Age 9 Condition 9 Task and a main effect of condition were established. Whereas in the mental chronometry test no age-related alteration of MI was found, the CMI revealed significant age-group differences in MI ability. The differences in MI were not reflected in the ratings of the participants, but differed age-related.
Discussion The main aim of this study was to explore MI performance of walking in older adults and to determine if it varied with task requirements. Therefore, we first discuss the main finding, which is the effect of age and condition and its interactions with tasks of various degrees of difficulty. We predicted that age-related deficits would emerge and that these deficits would show an interaction with tasks of different degrees of difficulty. In the second part of the discussion we will focus on our additional findings on CMI and self-rated clarity in older adults. Finally, we will give some implications for future research and discuss potentials for interventions.
Unlike in earlier studies that found temporal accuracy of MI deteriorates across the life span [11–14], in the present study we found no significant age-related differences in executed versus imagined walking durations. In a recent study, Saimpont et al. [21] came to the conclusion that agerelated differences decrease when MI is performed in a body posture congruent with the imagined action, which was also the case in the present study. The present findings might therefore confirm the role of a congruent body posture in accurate MI performance, especially for older adults. The importance of a congruent body posture should therefore also be considered when applying mental training for older adults. Furthermore, the additional task requirements may not have caused as much difficulty as the spatial constraints used in other studies, such as decreasing track length [14] or width [12]. More precisely, neither Schott [14] nor Personnier et al. [12] found age-related deficits in their walking tasks with similar spatial constraints to those used in the present study. The significant Age 9 Condition 9 Task interaction shows that the task requirements had different effects on performance across age groups, although spatial constraints were the same for all four tasks. There is some early evidence by Kalicinski, Kempe, and Bock [22] that age differences emerge only in walking tasks with more difficult task requirements. In the current study, post-hoc analysis showed that condition differences were present for all tasks in both age groups suggesting that there was no specific task that was more difficult to imagine than others. The significant three-way interaction effect might be due to the fact that in both conditions task differences emerged, except between tasks C and D. However the significant Age 9 Condition 9 Task provides first tentative evidence, that task requirements have an effect on MI performance.
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This issue deserves further empirical research. Classification of task requirements and their impact on MI performance is needed to fully understand age-related alterations and could further help to apply effective MI interventions. The significant effect of condition indicates that some participants of both age groups had difficulty in representing the temporal characteristic of the present walking tasks. It should be noted that younger adults might also have difficulties in mental chronometry tasks. In a recent study on individual differences in temporal accuracy of imagined walking in younger adults, participants were categorized as ‘‘good’’ or ‘‘bad’’ imagers [23]. The authors found correlations for differential performance in MI of walking, such that ‘‘good’’ imagers appeared to be better in recruiting brain networks that are generally recruited during MI, such as the primary motor cortex, right thalamus, and bilateral cerebellum. Further empirical research is needed to determine if these results are generalizable to older populations. An additional aim of this study was to investigate if group differences are sensitive to the MI paradigms used (controllability and self-rated clarity). Whereas for the temporal accuracy of imagined walking no age-related difference emerged, the older participants exhibited deficits in the CMI test, which is in accordance with earlier findings [14, 20]. Such deficits have been ascribed to the meditational role of working memory [14]. Working memory is a cognitive function known to be involved in MI [24–26]. As working memory is distinctly affected by old age [27], working memory should be taken into account in future investigations on MI in older age, testing the interaction effects found in the present study. The results of the rating of MI clarity showed a significant effect of age but in a surprising direction: Older adults rated clarity higher than younger participants. No significant interaction of Age 9 Modality was found, which is in contrast to the findings of Malouin et al. [25], who found that older adults showed no dominance of visual or kinesthetic MI modality, whereas younger adults exhibited a dominance of visual MI. To the best of our knowledge, the current experiment is the first to use the KVIQ scale to rate clarity of MI for different walking tasks. It should be noted that walking is a highly familiar and usual movement, which might explain the different findings. The significant task effect shows that the imagined walking with difficult task requirements were rated differently concerning the clarity of MI. More precisely, participants rated the clarity of task D significantly higher than the other tasks. A possible explanation could be that the switches in task D might serve as visual cues. This result provides further evidence that task requirements might play an important role in imagined walking.
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Finally, comparing the two methods, the significant Age 9 Method interaction shows that the self-rated clarity of MI in different methods differs across age groups. More precisely whereas older adults show a significant higher rating for the more familiar walking task (mental chronometry) in comparison to the non-familiar task of imagining body posters (CMI), no method differences were observed for the young group. Moreover, older adults rated their clarity in the mental chronometry higher than younger adults, whereas no significant group differences were observed for the CMI. The latter finding is somewhat surprising. Considering that for CMI test large group effects emerged, one could argue that older adults were not aware of these internal representation alterations. Overestimation of individual abilities in older adults could have consequences for risk of falling, as they might not afford adequate protection in risky situation. The results of the present study indicate that more work needs to be done supporting the explanations proposed by the simulation theory. First, it remains unclear why and when the task requirements have an impact on the temporal congruency of imagined and executed walking. Second, the explanatory power of the simulation theory could be systematically tested on different age groups in multiple-task designs such as ours to explore the limits of MI based on individual skills and abilities. Third, the simulation theory could be extended to the subjective sensation during MI regardless of MI performance. So what if older adults are asked to imagine themselves climbing the 20 steps of a staircase? Based on the present study, one could draw the conclusion that they would be able to produce an image of a real staircase and imagine themselves moving on it as well as younger adults, although they show alterations in other MI ability tests. It might be more difficult for older adults when the difficulty of the task increases (e.g., steps of changing height). Older adults may not have any difficulty achieving high clarity of MI for usual and familiar movements, such as climbing stairs. It remains to be seen why some people are able to represent the temporal characteristics of the task accurately while others cannot. Although with our design we are unable to make evidence-based recommendations for mental training, the present findings might have some implications for mental training interventions for older adults, for instance to prevent falls. Results of the mental chronometry test have indicated that older adults show similar MI performance in walking tasks to that of younger adults, suggesting that mental training is also beneficial for the elderly. Older adults might benefit from mental training of movement skills related to gait quality or even specific movements to prevent falls (e.g., a wide sidestep with external rotation in the hip joint). Therefore, it should be taken into account
Aging Clin Exp Res
that familiar movements such as walking with low spatial constraints might facilitate clear and accurate MI, which is crucial for mental training. Task requirements, such as uneven ground, could be used to simulate relevant situations for falling prevention without loss of accuracy and clarity of the movement representation. Spatial constraints, such as track width or requirements, such as changing direction, could be further used to progressively challenge participants regarding their MI performance. Finally, in regard to falling prevention, MI gives older adults the opportunity to gain experience, learn, and train in methods for coping with risky situations without being exposed to the risk. It has been already shown that mental training with MI is effective for improving dynamic balance ability in younger adults [28]. Future research should attempt to clarify if MI is efficient for older adults by conducting controlled intervention studies.
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Conflict of interest On behalf of all authors, the corresponding author states that there is no conflict of interest.
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ORIGINAL ARTICLE
Task requirements and their effects on imagined walking in elderly Michael Kalicinski • Markus Raab
Received: 19 August 2013 / Accepted: 27 November 2013 Ó Springer International Publishing Switzerland 2013
Abstract Background and aims Mental training has the potential to enhance motor performance and behavior in older adults. Yet several studies have revealed age-related alteration of motor imagery (MI) ability, suggesting that mental training is not applicable for older adults. The purpose of the present study was to estimate MI performance in older adults, taking into account task requirements. Methods MI performance of 20 older (mean age 70.75 ± 3.68 years) and 22 younger (mean age 24.31 ± 1.25 years) adults was estimated with the mental chronometry paradigm from the first-person perspective. Participants completed four walking tasks with different requirements, walking (A) in a straight line; (B) with two changes of direction; (C) on uneven ground; and (D) while additionally flipping switches. Path length and width were constant across tasks. MI ability was also measured with the Controllability of Motor Imagery Test, in which body parts have to be controlled and manipulated mentally. In addition, participants reported self-rated clarity of their MI in both tests after each trial. Results Our data suggest no generalized alteration in MI of walking with different task requirements among older adults. A significant Age 9 Condition 9 Task interaction emerged, but this result could not be attributed to a specific task requirement in post-hoc tests. For controllability of MI, older adults showed alterations in imagining body postures. These results showed dissociation with the selfrated clarity in both tests. Conclusion The present findings suggest that older adults show no age-related alterations in MI for familiar M. Kalicinski (&) M. Raab Institute of Psychology, German Sport University Cologne, Am Sportpark Mu¨ngersdorf 6, 50933 Cologne, Germany e-mail: [email protected]
movements. Mental Training of familiar movements could therefore be feasible for older adults and enables promising intervention strategies. Keywords Aging Motor imagery Mobility Mental chronometry
Introduction Imagine yourself standing at the bottom of a staircase with 20 steps of regular height and a handrail on the right. Now imagine climbing the steps to the top. This mental exercise illustrates that humans can produce images of real environments—mainly based on previous experience and verbal descriptions—and can imagine moving through these environments without executing real movements. This skill is defined as motor imagery (MI) and is based on the internal reproduction of action representations within working memory without any overt output [1, 2]. How does MI work? Jeannerod’s [3] simulation theory states that during covert simulation of motor actions, the neural networks that are activated are similar to those activated during overt (real) execution, because execution and imagery share the same action representations [4]. The representations of motor action do not simply rely on memorized actions but also depend on the immediate task requirement [3]. It is therefore not surprising that actions with specific task requirements elicit similar vegetative responses [5] and have similar temporal characteristics [6] under covert and overt movement conditions. The temporal congruence of these conditions is particularly accurate for usual and familiar movements such as writing and walking [7]. It has been suggested [6] that temporal accuracy depends on individual capabilities (e.g., higher in elite
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athletes), movement focus (e.g., lower for movements with variation of postural constraints), environmental constraints (e.g., lower during competition), and task difficulty (e.g., lower for rapid and attention-demanding movements). Yet these results were obtained in studies in the sports domain; it remains unclear how more everyday task requirements affect temporal accuracy. In the last decades, research on MI has expanded to investigate if mental training is also applicable and beneficial for older adults (for a recent review, see [8]). For effective use of mental training, such as fostering specific movement skills or routines, a preserved MI ability is considered a prerequisite [9]. A recent review on MI ability in older adults stressed that older adults are in general able to perform MI accurately and vividly but show difficulty in the simulation of unusual movements [10]. Several studies documented an age-related decline in the ability to mentally reproduce the temporal characteristics of movements accurately. Tasks such as walking [11–14], arm pointing [15–17], and arm lifting [18] were studied. A decline in temporal accuracy was shown for all of the above movements without systematically manipulating task requirements. Factors that have been found to affect accuracy include task familiarity [16, 19] and spatiotemporal task constraints [17], such as track length [13, 14] and width [12]. The latter study reported that older adults systematically overestimated actual walking durations on MI trials, more so for narrower walking tracks, and concluded that age-related MI deficits increase when the constraints become more difficult. In other words, decreasing track width was equated with increasing difficulty. Thus, it has been shown that spatiotemporal constraints influence MI performance, but it remains unclear whether more everyday task requirements also elicit MI deficits in older adults. The main aim of the present study was to explore the potential relationship between MI deficits and task difficulty by varying the tasks along other dimensions besides path length and width. Specifically, difficulty was manipulated by adding requirements to the walking task. We hypothesized (a) that MI performance would show an agerelated alteration and (b) that this age-related alteration would differ among tasks. In addition we explored if MI deficits would also emerge for the controllability of MI and asked participants to verbalize their self-rated MI ability.
Methods Participants Participants were 20 older (mean age 70.75 ± 3.68 years) and 22 younger (mean age 24.31 ± 1.25 years) adults. The
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older participants all lived independently in the community. All participants who filled out a custom-made questionnaire were all indicated to have normal or corrected-tonormal vision, and all reported being free of orthopedic or muscular impairment. Because all participants arrived without help at the agreed-upon time in the agreed-upon place, properly followed our instructions, and completed questionnaire items requiring memory and orientation (e.g., address, date of birth, medications used), we deemed them to be free of gross cognitive impairment. Each participant reported having regularly participated in sports or other physical activities. All gave their written consent to participate in this study, which was preapproved by the local ethics committee. Mental chronometry paradigm To investigate MI performance, we had participants engage in four walking tasks: walking (A) in a straight line; (B) with changes of direction; (C) on uneven ground; and (D) while additionally flipping switches. The spatial constraints were constant for the four tasks (track length 600 cm; track width 50 cm). Setting and paths are illustrated in Fig. 1. In the first condition, all participants imagined walking without actual execution. In the second condition, they actually walked. Participants were asked to execute walking for each task one time to get familiar with the spatial constraints and requirements. The four tasks were then presented in randomized order with six repetitions per task in the first (imagined) condition (i.e., a total of 24 trials) and three repetitions in the second (executed) condition (i.e., a total of 12 trials). A rest period of 3 min was provided between conditions. We always started with the imagined condition to prevent the use of strategies such as step counting or replication of remembered durations. In the imagined condition, participants had to stand in front of the required walking path, which was intended to provide a body posture that was congruent with the imagined movements. Participants were then asked to get in the starting position, which meant lifting the forward section of the right foot over an electronic pressure mat. They could start MI of walking independently by bringing the foot down on the pressure mat. They were instructed to complete each trial at a self-paced walking speed, to imagine their movements from the first-person perspective, and to lift the foot when their shoulders crossed the finish line. Duration for the MI was measured by stopwatch software using the contact with the pressure mat as start and the lift off as stop. Participants did not get feedback on the elapsed time for each trial. Procedural training on a separate walking track occurred before data collection started. During training trials for the imagined condition, participants were verbally questioned about the vividness
Aging Clin Exp Res Fig. 1 A three-dimensional model of the experimental setting for the four tasks of the mental chronometry test: walking (A) in a straight line; (B) with direction change; (C) on uneven ground; and (D) while additionally flipping switches. The checkered pattern highlights the target area
and clarity of their mental images and whether they had succeeded in using the first-person perspective. The procedure for the executed condition was identical, except that contact with an additional pressure mat at the end of the path was used as stop for time measurement. Controllability of Motor Imagery test To get a comprehensive estimation of MI ability participants engaged in an additional MI test. For the Controllability of Motor Imagery (CMI) test [14, 20], participants must create a mental picture of themselves and afterward assume a body position that was reached at the end of the MI. Participants stand with their eyes closed on a cross marked on the floor and receive six consecutive instructions for moving a body part into a specific position. They are asked to remain physically still and only to imagine moving their body parts as requested. After the sixth instruction, participants open their eyes and arrange themselves in the assumed final body configuration. Participants score one point for each correct instruction, thus earning up to five points per trial (the first instruction is a standardized home position and is not awarded a point). In addition, one point is given for the correct overall final body configuration. The test consists of ten trials, and the maximum score therefore is 50 for the elements and 10 for the final postures. The test shows a high level of internal consistency with a = .93 [14]. Clarity of MI To get an evaluation of self-rated MI clarity, participants were asked to rate each MI trial in both tests using the rating scale of the Kinesthetic and Visual Imagery Questionnaire (KVIQ). The scale consists of a five-point Likert scale in two imagery modalities: visual (1, no image to 5, image as clear as really seen) and kinesthetic (1, no feeling to 5, feeling as really executed). For the mental chronometry test a mean score was calculated for each task. In
addition a mean score over all tasks was calculated for the mental chronometry and CMI tests. Data analysis To test the hypotheses we ran a 2 (Age: older, younger) 9 2 (Condition: imagined, executed) 9 4 (Task: A, B, C, D) analysis of variance (ANOVA) on the mean durations across repetitions, with age as the between-subjects factor and repeated measures on condition and task. For the additional questions, CMI scores for the final and elements analysis were compared between age groups with a t test. For the self-rated clarity measures we used the kinesthetic and visual scores as dependent variables and ran a 2 (Age: older, younger) 9 2 (Modality: visual, kinesthetic) 9 4 (Task: A, B, C, D) ANOVA with age as the betweensubjects factor and repeated measures on modality and task, as well as a 2 (Age: older, younger) 9 2 (Modality: visual, kinesthetic) 9 2 (Method: Mental chronometry, CMI) ANOVA with age as the between-subjects factor and repeated measures on modality and method. Significant effects of the ANOVAs where the factor age was included were explored by Fisher’s LSD post-hoc analyses. A significance criterion of a = 0.05 was adopted for all results reported. Effect sizes are reported for F values larger than 1 to avoid reporting unreliable effect sizes. Effect sizes for the results of the ANOVA were estimated by calculating the g2. Thereby g2 of [0.01 indicate a small, [0.06 a medium and [0.14 a large effect (Cohen). Effect sizes for the results of the t tests were estimated by calculating the Cohens d. Thereby d [ 0.2 indicate a small, d [ 0.5 a medium, and d [ 0.8 a large effect (Cohen).
Results To investigate the performance in mental chronometry, we focus on the analyses of the condition effect, as it
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Aging Clin Exp Res old MDI
old MDE
young MDI
young MDE
dual task tasks requirements
Fig. 2 Mean durations ± standard error of both age groups for both conditions separated by tasks
ground
bend
basic 0
represents the difference between imagined and executed movement durations, and its interactions with age and tasks. The mean duration of both age groups for each condition and task are illustrated in Fig. 2. Both age groups overestimated the duration in the imagined condition. Respectively, ANOVA of durations revealed significant effect of Condition. For our first hypothesis, the ANOVA revealed no significant effect of Age 9 Condition, although older adults showed a tendency for higher differences. The predicted age-related alteration of MI performance could therefore not be confirmed in the present study. For our second hypothesis, we found a significant effect of Age 9 Condition 9 Task, suggesting that group differences, as predicted, show an interaction with different task requirements. Further post-hoc analyses showed significant condition differences for each task in both age groups (all p \ 0.001). In both conditions task differences in the old group emerged between task A and the other tasks, and B and the other tasks (all p \ 0.001). Thereby durations of task C and D were longer than for task A and B. No significant differences were observed between task C and D. A significant effect was also found for Condition 9 Task. Further main and interaction effects, p and F values, and eta squared are illustrated in Table 1. An additional aim was to explore if MI alteration emerged in other MI tests. For the CMI test (final), we found a mean score of 2.1 (SD = 1.89) for the older group and a three times higher mean score of 7.09 (SD = 2.1) for the younger group. A t test yielded significant group differences, t (40) = 8.086; p \ 0.001; d = 2.55. For the CMI test (elements) a mean of 35 (SD = 5.64) for the older group and a mean of 46.23 (SD = 2.65) for the younger group were calculated. A t test yielded significant group differences, t (40) = 8.281; p \ 0.001; d = 2.65. Table 2 shows the mean scores for self-rated visual and kinesthetic MI clarity for the four tasks in the mental chronometry test and for the CMI test. In the mental chronometry
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2
4 6 duration in seconds + SE
8
10
Table 1 Results of the analyses of variance Factors
F
g2
p
Mental chronometry Age
F (1, 40) = 1.660
[0.05
Condition
F (1, 40) = 24.130
\0.001
0.376
Task
F (3, 120) = 83.758 \0.001
0.676
Age 9 condition
F (1, 40) = 0.248
[0.05
Age 9 task
F (3, 120) = 3.005
0.033
0.069
Condition 9 task
F (3, 120) = 5.425
0.001
0.119
Age 9 condition 9 task
F (3, 120) = 2.762
0.045
0.064
Motor imagery clarity in walking Age
F (1, 40) = 5.715
0.022
0.125
Modality Task
F (1, 40) = 1.645 F (3, 120) = 3.370
[0.05 0.020
0.077
Age 9 modality
F (1, 40) = 1.645
[0.05
Age 9 task
F (3, 120) = 0.586
[0.05
Modality 9 task
F (3, 120) = 6.248
\0.001
0.135
Age 9 modality 9 task
F (3, 120) = 4.459
0.005
0.100
Motor imagery clarity in methods [0.05
Age
F (1, 40) = 0.731
Modality
F (1, 40) = 8.023
Method
F (1, 40) = 5.564
Age 9 modality
F (1, 40) = 0.242
Age 9 method
F (1, 40) = 11.507
Modality 9 method
F (1, 40) = 0.599
[0.05
Age 9 modality 9 method
F (1, 40) = 1.697
[0.05
0.007
0.167
0.023
0.122
[0.05 0.002
0.223
test, the older adults rated their clarity significantly higher than the younger adults. Whereas we found this main effect of age, no significant interaction of Age 9 Modality or Age 9 Task was revealed. The ANOVA further revealed a significant main effect of Task. Post-hoc analysis showed that the rating of task D was significantly higher than in the other tasks. In the CMI test the two groups showed similar ratings of their MI clarity. Comparing the average scores for
Aging Clin Exp Res Table 2 Means of MI rating and Standard Deviation, separately for tasks in the MC test and for method (MC and CMI), by age group (older, younger) and modality (visual, kinesthetic) Task or method
Older Visual
Younger a
Kinesthetic
b
Visuala
Kinestheticb
Task Straight
4.11 (±0.72)
3.97 (±1.01)
3.84 (±0.67)
3.62 (±0.90)
Direction change Uneven ground
4.03 (±0.74) 4.03 (±0.70)
3.88 (±0.86) 3.93 (±0.77)
3.78 (±0.75) 3.70 (±0.49)
3.53 (±0.75) 3.70 (±0.56)
Dual task
4.15 (±0.58)
4.07 (±0.67)
3.96 (±0.51)
3.77 (±0.68)
MCc
4.08 (±0.63)
3.96 (±0.77)
3.82 (±0.52)
3.65 (±0.66)
CMId
3.61 (±0.90)
3.45 (±0.95)
3.61 (±0.63)
3.49 (±0.62)
Method
a
Visual scale: 1 (no image) to 5 (image as clear as really seen)
b
Kinesthetic scale: 1 (no feeling) to 5 (feeling as really executed)
c
Mental chronometry
d
Controllability of motor imagery
mental chronometry and CMI, we found a significant Age 9 Method interaction. Post-hoc analysis showed that significant method differences only emerged in the old group (p \ 0.001) with a higher rating for the imagined walking. Group difference only emerged for the rating of MI in the mental chronometry test differences (p = 0.035) with a higher rating among older adults. Results of the ANOVAs for MI clarity in walking and MI clarity in different methods are illustrated in Table 2. Summarizing the main results and in contrast to our predictions no significant interaction of Age 9 Condition was confirmed, but a significant three-way interaction of Age 9 Condition 9 Task and a main effect of condition were established. Whereas in the mental chronometry test no age-related alteration of MI was found, the CMI revealed significant age-group differences in MI ability. The differences in MI were not reflected in the ratings of the participants, but differed age-related.
Discussion The main aim of this study was to explore MI performance of walking in older adults and to determine if it varied with task requirements. Therefore, we first discuss the main finding, which is the effect of age and condition and its interactions with tasks of various degrees of difficulty. We predicted that age-related deficits would emerge and that these deficits would show an interaction with tasks of different degrees of difficulty. In the second part of the discussion we will focus on our additional findings on CMI and self-rated clarity in older adults. Finally, we will give some implications for future research and discuss potentials for interventions.
Unlike in earlier studies that found temporal accuracy of MI deteriorates across the life span [11–14], in the present study we found no significant age-related differences in executed versus imagined walking durations. In a recent study, Saimpont et al. [21] came to the conclusion that agerelated differences decrease when MI is performed in a body posture congruent with the imagined action, which was also the case in the present study. The present findings might therefore confirm the role of a congruent body posture in accurate MI performance, especially for older adults. The importance of a congruent body posture should therefore also be considered when applying mental training for older adults. Furthermore, the additional task requirements may not have caused as much difficulty as the spatial constraints used in other studies, such as decreasing track length [14] or width [12]. More precisely, neither Schott [14] nor Personnier et al. [12] found age-related deficits in their walking tasks with similar spatial constraints to those used in the present study. The significant Age 9 Condition 9 Task interaction shows that the task requirements had different effects on performance across age groups, although spatial constraints were the same for all four tasks. There is some early evidence by Kalicinski, Kempe, and Bock [22] that age differences emerge only in walking tasks with more difficult task requirements. In the current study, post-hoc analysis showed that condition differences were present for all tasks in both age groups suggesting that there was no specific task that was more difficult to imagine than others. The significant three-way interaction effect might be due to the fact that in both conditions task differences emerged, except between tasks C and D. However the significant Age 9 Condition 9 Task provides first tentative evidence, that task requirements have an effect on MI performance.
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This issue deserves further empirical research. Classification of task requirements and their impact on MI performance is needed to fully understand age-related alterations and could further help to apply effective MI interventions. The significant effect of condition indicates that some participants of both age groups had difficulty in representing the temporal characteristic of the present walking tasks. It should be noted that younger adults might also have difficulties in mental chronometry tasks. In a recent study on individual differences in temporal accuracy of imagined walking in younger adults, participants were categorized as ‘‘good’’ or ‘‘bad’’ imagers [23]. The authors found correlations for differential performance in MI of walking, such that ‘‘good’’ imagers appeared to be better in recruiting brain networks that are generally recruited during MI, such as the primary motor cortex, right thalamus, and bilateral cerebellum. Further empirical research is needed to determine if these results are generalizable to older populations. An additional aim of this study was to investigate if group differences are sensitive to the MI paradigms used (controllability and self-rated clarity). Whereas for the temporal accuracy of imagined walking no age-related difference emerged, the older participants exhibited deficits in the CMI test, which is in accordance with earlier findings [14, 20]. Such deficits have been ascribed to the meditational role of working memory [14]. Working memory is a cognitive function known to be involved in MI [24–26]. As working memory is distinctly affected by old age [27], working memory should be taken into account in future investigations on MI in older age, testing the interaction effects found in the present study. The results of the rating of MI clarity showed a significant effect of age but in a surprising direction: Older adults rated clarity higher than younger participants. No significant interaction of Age 9 Modality was found, which is in contrast to the findings of Malouin et al. [25], who found that older adults showed no dominance of visual or kinesthetic MI modality, whereas younger adults exhibited a dominance of visual MI. To the best of our knowledge, the current experiment is the first to use the KVIQ scale to rate clarity of MI for different walking tasks. It should be noted that walking is a highly familiar and usual movement, which might explain the different findings. The significant task effect shows that the imagined walking with difficult task requirements were rated differently concerning the clarity of MI. More precisely, participants rated the clarity of task D significantly higher than the other tasks. A possible explanation could be that the switches in task D might serve as visual cues. This result provides further evidence that task requirements might play an important role in imagined walking.
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Finally, comparing the two methods, the significant Age 9 Method interaction shows that the self-rated clarity of MI in different methods differs across age groups. More precisely whereas older adults show a significant higher rating for the more familiar walking task (mental chronometry) in comparison to the non-familiar task of imagining body posters (CMI), no method differences were observed for the young group. Moreover, older adults rated their clarity in the mental chronometry higher than younger adults, whereas no significant group differences were observed for the CMI. The latter finding is somewhat surprising. Considering that for CMI test large group effects emerged, one could argue that older adults were not aware of these internal representation alterations. Overestimation of individual abilities in older adults could have consequences for risk of falling, as they might not afford adequate protection in risky situation. The results of the present study indicate that more work needs to be done supporting the explanations proposed by the simulation theory. First, it remains unclear why and when the task requirements have an impact on the temporal congruency of imagined and executed walking. Second, the explanatory power of the simulation theory could be systematically tested on different age groups in multiple-task designs such as ours to explore the limits of MI based on individual skills and abilities. Third, the simulation theory could be extended to the subjective sensation during MI regardless of MI performance. So what if older adults are asked to imagine themselves climbing the 20 steps of a staircase? Based on the present study, one could draw the conclusion that they would be able to produce an image of a real staircase and imagine themselves moving on it as well as younger adults, although they show alterations in other MI ability tests. It might be more difficult for older adults when the difficulty of the task increases (e.g., steps of changing height). Older adults may not have any difficulty achieving high clarity of MI for usual and familiar movements, such as climbing stairs. It remains to be seen why some people are able to represent the temporal characteristics of the task accurately while others cannot. Although with our design we are unable to make evidence-based recommendations for mental training, the present findings might have some implications for mental training interventions for older adults, for instance to prevent falls. Results of the mental chronometry test have indicated that older adults show similar MI performance in walking tasks to that of younger adults, suggesting that mental training is also beneficial for the elderly. Older adults might benefit from mental training of movement skills related to gait quality or even specific movements to prevent falls (e.g., a wide sidestep with external rotation in the hip joint). Therefore, it should be taken into account
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that familiar movements such as walking with low spatial constraints might facilitate clear and accurate MI, which is crucial for mental training. Task requirements, such as uneven ground, could be used to simulate relevant situations for falling prevention without loss of accuracy and clarity of the movement representation. Spatial constraints, such as track width or requirements, such as changing direction, could be further used to progressively challenge participants regarding their MI performance. Finally, in regard to falling prevention, MI gives older adults the opportunity to gain experience, learn, and train in methods for coping with risky situations without being exposed to the risk. It has been already shown that mental training with MI is effective for improving dynamic balance ability in younger adults [28]. Future research should attempt to clarify if MI is efficient for older adults by conducting controlled intervention studies.
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Conflict of interest On behalf of all authors, the corresponding author states that there is no conflict of interest.
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