Archives of Gerontology and Geriatrics 58 (2014) 226–230
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Assessment of mental chronometry (MC) in healthy subjects Johanna Greiner a, Mircea Ariel Schoenfeld a,b,c, Joachim Liepert a,* a
Department of Neurorehabilitation, Kliniken Schmieder, 78476 Allensbach, Germany Department of Neurology, Otto-von-Guericke University, 39120 Magdeburg, Germany c Department of Behavioural Neurology, Leibniz Institute for Neurobiology, 39118 Magdeburg, Germany b
A R T I C L E I N F O
A B S T R A C T
Article history: Received 24 March 2013 Received in revised form 1 August 2013 Accepted 21 September 2013 Available online 18 October 2013
Objective: This study examined the temporal congruency between real and imagined movements and explored intermanual transfer effects in healthy subjects. Methods: Seventy-six right-handed healthy subjects were allocated to three age groups and tested with a modified version of the Box and Block Test (BBT). We focussed on two aspects. First, the BBT was evaluated with respect to its ability to assess MC. Second, we were interested whether performance of motor imagery (MI) and real execution with one hand would modify performance with the other hand. To explore MC, we measured motor execution (ME) time as the time needed to perform the BBT, and MC time as the time difference between ME and the time needed for imagination of task execution. The BBT was performed with both hands consecutively to study transfer effects from one hand to the other and then repeated with the first hand for practice effects. Results: The age group with the oldest subjects exhibited a slower BBT performance and a less precise MC than the other 2 age groups. Irrespective of the age, MC abilities could be transferred to the other hand, whereas ME only improved when repeating the task with the same hand. Conclusions: The BBT was able to demonstrate an age-related decline of dexterity and MC. Intermanual transfer of MI abilities occurred even after a single run. ß 2013 Elsevier Ireland Ltd. All rights reserved.
Keywords: Mental chronometry Motor execution Age-dependent changes Box and Block Test Intermanual transfer
1. Introduction MI may be defined as ‘‘a dynamic state during which the representation of a given motor act is internally rehearsed within working memory without any overt motor output’’ (Decety & Gre`zes, 1999). The imagination of complex movements is an important element of training in competitive sports. From the sports literature it is well known that MI, when applied in addition to real execution, is more effective than MI or functional training alone (e.g., Feltz & Petlichkoff, 1983; Coelho, De Campos, Da Silva, Okazaki, & Keller, 2007; Olsson, Jonsson, & Nyberg, 2008). MI abilities can be tested by different approaches. One might explore how vividly a movement can be imagined. This aspect can be addressed by subjective questionnaires. However, this approach has been questioned (Lotze & Halsband, 2006; Sharma, Pomeroy, & Baron, 2006), because an external validation is not possible in these tests (Lequerica, Rapport, Axelrod, Telmet, & Whitman, 2002). Another approach deals with spatial aspects, e.g., by asking the subjects to perform mental rotations of a hand or other threedimentional objects (e.g., Johnson, 1999; Johnson, Sprehn, &
* Corresponding author at: Department of Neurorehabilitation, Kliniken Schmieder, Zum Tafelholz 8, D-78476 Allensbach, Germany. Tel.: +49 7533 808 1236; fax: +49 7533 808 1441. E-mail address: [email protected] (J. Liepert). 0167-4943/$ – see front matter ß 2013 Elsevier Ireland Ltd. All rights reserved. http://dx.doi.org/10.1016/j.archger.2013.09.003
Saykin, 2002) or by estimation of reachability of an object (Gabbard, Cac¸ola, & Cordova, 2011). A third approach focuses on chronometrical aspects by studying time differences between physical execution of a movement and imagination of the same movement. Thus, MC allows measuring the congruency between MI and ME in an objective way. Typically, the duration of imagined movements correlates with the duration of real movements in healthy individuals (Bakker, de Lange, Stevens, Toni, & Bloem, 2007; Decety, Jeannerod, & Prablanc, 1989) but may be impaired in stroke patients (De Vries & Mulder, 2007; Liepert, Greiner, Nedelko, & Dettmers, 2012; Malouin, Richards, Desrosiers, & Doyon, 2004; Sabate, Gonzales, & Rodriguez, 2007; Sirigu et al., 1996). The tasks used in preceding studies were quite different, e.g., pointing tasks (Malouin et al., 2004) or complex sequences of finger movements (Sabate et al., 2007). Our aim was to apply a simple and widely-used method which would enable scientists all over the world to perform studies with the same standardized equipment. The BBT is a frequently used method in neurological rehabilitation to test dexterity and has been shown to provide a valid and reliable measure in healthy subjects (Desrosiers, Bravo, He´bert, Dutil, & Mercier, 1994; Mathiowetz, Volland, Kashman, & Weber, 1985) and stroke patients (Chen, Chen, Hsueh, Huang, & Hsieh, 2009; Platz et al., 2005). We used this test not only for physical performance but also for MI to explore MC abilities. It’s main features are (1) easy administration, (2) close relation to
J. Greiner et al. / Archives of Gerontology and Geriatrics 58 (2014) 226–230
activities of daily life (e.g., object manipulation) and (3) rapid execution. We focussed on the investigation of two different aspects: (1) evaluation of the BBT as a tool to detect age-related or genderrelated effects of MC and (2) aspects of practice by task repetition. The latter aspect particularly addressed the question of an intermanual motor skill transfer. It has been shown repeatedly that motor practice with one hand also improves motor functions of the other, untrained hand (e.g., Andree & Maitra, 2002; Lee, Hinder, Gandevia, & Carroll, 2010; Perez, Wise, Willingham, & Cohen, 2007; Schulze, Lu¨ders, & Ja¨ncke, 2002). We were interested whether performance of MC and ME with one hand would result in an improvement of ME and MC abilities for the other hand and whether such an intermanual skill transfer would be agedependent. 2. Methods 2.1. Subjects Seventy-six subjects gave written consent and participated in the study. The study was approved by the Ethical Committee of Constance University. Exclusion criteria were neurological or psychiatric diseases as well as any other diseases involving movement problems. All participants were free of physical or cognitive impairments and were able to understand the instructions given to perform the test. Most subjects were recruited in the hospital. Those aged 65 were spouses of patients currently treated in the hospital. None of the subjects reported any MC involvement or practice ever before the testing. The subjects were allocated into three age groups: Group A: n = 25 (range: 18–34 years, 12 males; age 24.5; 4.2 years [mean standard deviation]), Group B: n = 24 (range: 35–54 years, 8 males; age 43.5 6.6 years) and Group C: n = 27 (range: 55–83 years, 11 males; age 68.3 8.5 years). The age ranges were chosen for 2 reasons. First, we wanted to generate age groups that can be defined as ‘‘young’’, ‘‘middle-aged’’, and ‘‘aged’’. Second, we wanted to gather a similar number of subjects in each group. The study was performed within a single session and had no dropouts to be reported. 2.2. Measures 2.2.1. Edinburgh Handedness Inventory (EHI) Prior to the administration of the chronometric test, the hand dominance was assessed using the EHI as a reliable measure of hand performance (Oldfield, 1971). 2.2.2. BBT The BBT involves grasping and moving 1-in. square wooden blocks from one side of an 8-in. square box to the other, by passing them over a wooden partition 5 in. high using one hand only. Each hand is tested separately. The critical measure is the number of blocks that can be transported within 1 min. Higher scores of transported blocks indicate a better manual dexterity. We used the same standardized setting of the BBT apparatus but positioned fifteen blocks in one compartment of the box. Before starting the MC task subjects were allowed to hold and manipulate one block in order to get a proper evaluation of the weight, surface and haptic properties of the blocks. First, subjects were instructed to imagine grasping each block one after the other and moving it to the other side of the compartment. Subjects were asked to perform the imagery task from the first person perspective as fast and as realistic as possible. They were told to imagine how they grasp the block with thumb and index finger, move it across the partition, release it and return with the hand to
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grasp the next block. The subjects were given a start signal (go) for the imagery by the experimenter and gave a signal (stop) as soon as they had completed the task. The time between ‘‘go’’ and ‘‘stop’’ signal was measured using a stopwatch and defined as MI time. We deliberately chose this order (first MI, then ME) since the movements (grasping, transferring and releasing an object) are easy and need no explicit training. In the following, subjects physically performed in the BBT. The instruction was to move the blocks one by one as fast as possible to the other side of the compartment. The experimenter gave a go signal. The time until the last block was moved was measured and defined as ME time. The time difference between MI and ME was calculated and called MC. The experiment consisted of three tasks. Each subject participated in all of these tasks. In each task both conditions (MI and ME) were measured. In task 1, the subject started the test with one hand. The side (right or left hand) was chosen randomly. In task 2, the subject performed the test with the other hand and in task 3 the subject repeated the test with the same hand he had used in task 1. 2.3. Procedure An experienced physiotherapist familiar with the procedures tested all subjects. The duration of the whole session was about 15 min. The subjects were seated in front of a table, sitting on a chair with backrest. The wooden box was placed on the table in front of the subjects. 3. Data analysis The statistical analysis was performed using SPSS V16.0. In the analysis, the level of significance was assumed at 5%. An analysis of variance (ANOVA) with the factors AGE (3 levels), GENDER (2 levels), TASK (3 levels) and ORDER (2 levels [right hand first or left hand first]) was calculated with the ME data and with the MC data. In case of significant main effects or interactions, univariate ANOVAs were employed to further investigate the effects. Prior to the analysis, a sign-test was performed on the data and revealed that the distribution of the data was not different from the normal distribution. For analysing the MC data, the time difference between MI and ME was taken as an absolute error, irrespective of whether MI duration was shorter than real execution time or vice versa. Then, the MC data was normalized by the formula (real performance MC/real performance), to eliminate the difference in performance (older participants being slower than younger participants). For calculation of effect sizes we chose Cohen’ d. By convention, an effect size of 0.2 is termed small, an effect size of 0.5 is termed medium and a value of 0.8 is termed large. 4. Results 4.1. EHI Out of 79 subjects assessed with the EHI, three subjects were identified as left-handed and 76 subjects were identified as righthanded. In order to avoid a handedness-related influence on the data, the analysis was performed with the right-handed subjects only. 4.2. ME performance The ANOVA indicated significant differences for the main factors task type (F(2, 210) = 4.243; p = 0.016), and age (F(2, 210) = 21.527; p < 0.001). However, no significant differences
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J. Greiner et al. / Archives of Gerontology and Geriatrics 58 (2014) 226–230
Table 1 BBT results: task types. Task type
ME
MC
1. Task (first hand)
Ratio
2.3 1.9 [TD$INLE]
3. Task (first hand again)
[TD$INLE]
1.8 1.4 1.3 1.1
2. Task (other hand) ME: real performance time measured in seconds. MC: time difference between ME and MI, time measured in seconds. Ratio: ME minus MI, divided by ME. *p < 0.05.
were found for the factors gender (F(1, 210) = 0.07; p = 0.82) or order (right hand first versus left hand first) (F(1, 210) = 0.386; p = 0.58), in the absence of any significant interaction. There was no significant difference between task 1 and 2 (first hand and second hand) (F(1, 156) = 0.607; p = 0.437; d = 0.12)), but a significant difference between task type 1 and 3 (first hand and first hand again) (F(1, 156) = 10.416; p = 0.002; d = 0.52)), and between task type 2 and 3 (second hand and first hand again) (F(1,156) = 4.865; p = 0.029; d = 0.35)). This pattern indicates that there was no difference in real performance between the first hand and the second hand, but motor performance with the first hand improved with repetition (Table 1). There was a significant difference between the youngest age group ‘‘A’’ and the oldest age group ‘‘C’’ (F(1, 154) = 27.341; p < 0.0001; d = 0.7), and between the intermediate group ‘‘B’’ and group ‘‘C’’ (F(1, 151) = 18.237; p < 0.0001; d = 0.56). There was no significant difference between group ‘‘A’’ and group ‘‘B’’ (F(1, 145) = 0.580; p = 0.475; d = 0.11). Thus, age group ‘‘C’’ was slower in the real execution performance compared to the other two age groups (Table 2). 4.3. MC For the first task, MI time was shorter than real execution performance time (ME) in 41 subjects, and vice versa in 25 subjects. 10 subjects did not misestimate themselves and showed an identical time for MC. Concerning time difference (MC) between MI and ME, the ANOVA indicated no significant difference for the factor gender (F(1, 210) = 0.614; p > 0.05)). However, significant differences were observed for the factors age (F(2, 210) = 5.113; p = 0.002)), and task type (F(2, 210) = 9.823; p < 0.0001)) in the absence of a significant interaction. Further analyses indicated a significant difference between task types 1 and 3 (first hand and first hand again) (F(1, 156) = 15.278; p < 0.0001; d = 0.63), a significant difference between task type 1 and 2 (first hand and second hand) (F(1, 156) = 5.302; p = 0.023; d = 0.37), and a marginally significant difference between task type
2 and 3 (second hand and first hand again) (F(1, 156) = 3.733; p = 0.055; d = 0.31). This pattern shows that the MC performance improves when performed with the other hand, and improves even more with repetition of the same hand. In addition there was a significant difference between age group ‘‘A’’ and age group ‘‘C’’ (F(1, 154) = 9.228; p = 0.003; d = 0.22), and a significant difference between group ‘‘B’’ and group ‘‘C’’ (F(1, 151) = 9.311; p = 0.002; d = 0.31). No significant difference (F(1, 145) = 0.055; p > 0.05; d = 0.11) was observed between groups ‘‘A’’ and ‘‘B’’. Thus, the oldest age group ‘‘C’’ showed the worst MC performance. 5. Discussion The main results of this study are that, (1) the group with the oldest subjects was slower in real execution performance than the other two groups, (2) the group with the oldest subjects had a less precise MC ability than the other two groups and (3) based on the whole group of subjects, task performance with the ‘‘second’’ hand (task type 2) was associated with an improvement of MC but not with an improved execution performance and (4) in task type 3, repeated use with the same hand (used hand) showed improvement in ME. The age-dependent decline in the ME performance with the BBT indicates a partial loss of dexterity with increasing age. This is in agreement with other publications (Marneweck, Loftus, & Hammond, 2011; Mathiowetz et al., 1985). The reasons for this impaired execution remain speculative. A slowing of processing in motor areas of the brain as well as a subclinical dysfunction of joints, tendons and muscles might be responsible for our finding. Functional imaging studies have shown repeatedly that older adults compared with young adults had more widespread movement-associated brain activations involving motor and nonmotor areas. These changes were interpreted as a compensatory effect required by older adults to perform the motor task at the same level (e.g., Heuninckx, Wenderoth, Debaere, Peeters, & Swinnen, 2005). These age-related differences can also be found in MI tasks
Table 2 BBT results: age groups. Age groups
ME
Group B (35–54 years)
MC
Ratio
1.4 1.2
Group A (18–34 years) [TD$INLE]
Group C (55–83 years) Group A: (n = 25); Group B: (n = 24); Group C: (n = 27). ME: real performance time measured in seconds. MC: time difference between ME and MI, time measured in seconds. Ratio: ME minus MI, divided by ME. *p < 0.05.
1.4 1.2 2.4 1.8
[TD$INLE]
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(Zapparoli et al., 2013). The findings underscore the necessity to match for the factor ‘‘age’’ when comparing patients and healthy subjects in their ME. Our group of elderly subjects also showed a less precise MC in the test. Since we had eliminated the influence of longer execution times, the MC results cannot be attributed to a longer performance time per se, but rather indicate that old persons have both, a loss of dexterity and an impairment of MC ability when tested with the BBT. An age-related decline of MI has also been shown in other studies (e.g., Skoura, Papaxanthis, Vinter, & Pozzo, 2005). Saimpont, Pozzo, and Papaxanthis (2009) used the Hand Rotation Task to demonstrate an impaired ability of elderly subjects to implicitly simulate movements of the upper limbs. In another study (Personnier, Kubicki, Laroche, & Papaxanthis, 2010) it was shown that the temporal feature of imagined precision on gait was declined in the older age group. Similar findings were reported by Schott (2012). In that study, impaired MC was found for a walking test. Subjects aged 70 years or older were affected whereas no significant impairment of MC was observed in subjects aged 60–69 years. A correlation with the intactness of working memory was reported. In a study by Malouin, Richards, and Durand (2010) an impaired visual MI ability was associated with a decline in visuospatial and kinesthetic working memory. Saimpont, Malouin, Tousignant, and Jackson (2013) concluded that age-related MI ability declines depend on task difficulty. In summary, the existing literature suggests that different types of MI are affected with increasing age. This suggests a more generalized decline of MI abilities and not the loss of one particular function. The level of cognitive and, in particular, memory function may play an important role. In our study, we did not specifically address this issue. In future studies working memory abilities should be considered. Interestingly, MC was already improved when performing the BBT-MC task with the other hand without preceding ME. This suggests that subjects had some benefit from the preceding task execution even if it was not the same hand. It indicates that MC abilities are independent of whether the same or the other hand has been the subject of imagery. We therefore hypothesize that MC knowledge is stored in a brain area that is accessible by both hemispheres. A recent analysis of effective connectivity between different brain areas evoked by MI of unilateral hand movements has shown that the MI task not only activated areas in the contralateral but also in the ipsilateral hemisphere, mainly the supplementary motor area (SMA), the dorsal premotor cortex (PMd), the inferior parietal lobule (IPL) and the superior parietal lobule (SPL) (Gao, Duan, & Chen, 2011). SMA, PMd, IPL and SPL form a MI network that is activated in both hemispheres by unilateral MI. Information stored in this network is therefore accessible by each hemisphere. However, since the MI task employed by Gao et al. (2011) was not a MC task, our hypothesis is not proven yet. The MC skill transfer was independent of age, suggesting that this ability is less age-related than dexterity and MC per se. Our results are in accordance with a study in which a tapping sequence paradigm was used to train subjects either by motor performance or MI of the task (Amemiya, Ishizu, Ayabe, & Kojima, 2010). The authors reported that imagery was effective for both trained movement and intermanual transfer whereas execution was effective especially for the trained movement. Independent of age or gender, the real performance of the BBT task with the untrained hand did not result in an improved performance time, suggesting that there was no practice or knowledge transfer from one hand to the other. One could argue that the task was too simple or that subjects already were at ceiling with their performance. However, repetition of the task with the trained hand did result in a faster execution of the task. Thus, task
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performance could still be improved. A possible explanation of this finding is that an intermanual transfer of the motor skill requires a much higher number of repetitions. Schulze et al. (2002) have demonstrated in a study with healthy subjects that participated in a pegboard task for 120 min that such an intense motor training can transfer a motor function improvement from the trained hand to the untrained hand. In our study, the modified version of the BBT was easy to administer and took a maximum of 15 min including all task repetitions. None of the subjects reported any difficulties when performing the MC task. We suggest that the comparison between MI and real execution performance of the BBT provides relevant information about the individual dexterity and MI abilities. Thus, this test might be suitable for patients with neurological diseases participating in MI studies. Several studies have explored MI as a treatment in stroke patients. Two reviews concluded that MI might be helpful as an additional training to physical training (Barclay-Goddard, Stevenson, Poluha, & Thalman, 2011; De Vries & Mulder, 2007; Sharma et al., 2006; Zimmermann-Schlatter, Schuster, Puhan, Siekierka, & Steurer, 2008). However, a recent controlled trial with 121 stroke patients was unable to demonstrate a beneficial effect of MI (Ietswaart et al., 2011). Our own pilot study in which the BBT was used in stroke patients to test their MC abilities has not only demonstrated its feasibility in such a patient group. The BBT results also indicated that patients with severe sensory deficits were much more compromised in their MC ability than patients with pure motor stroke (Liepert et al., 2012). In future studies, it should be explored if this test is able to predict the effectiveness of MI training. Moreover, the intermanual transfer of MI abilities might offer an interesting treatment perspective in stroke patients. The hypothesis is that intense MI training with the unaffected hand could also improve MI skills for the affected side. Conflict of interest statement The authors declare that they have nothing to disclose. References Amemiya, K., Ishizu, T., Ayabe, T., & Kojima, S. (2010). Effects of motor imagery on intermanual transfer: A near-infrared spectroscopy and behavioural study. Brain Research, 1343, 93–103. Andree, M. E., & Maitra, K. K. (2002). Intermanual transfer of a new writing occupation in young adults without disability. Occupational Therapy International, 9(1), 41–56. Bakker, M., de Lange, F. P., Stevens, J. A., Toni, I., & Bloem, B. R. (2007). Motor imagery of gait: A quantitative approach. Experimental Brain Research, 179(3), 497–504. Barclay-Goddard, R. E., Stevenson, T. J., Poluha, W., & Thalman, L. (2011). Mental practice for treating upper extremity deficits in individuals with hemiparesis after stroke. Cochrane Database of Systematic Reviews, CD005950. Chen, H. M., Chen, C. C., Hsueh, I. P., Huang, S. L., & Hsieh, C. L. (2009). Test-retest reproducibility and smallest real difference of 5 hand function tests in patients with stroke. Neurorehabilitation and Neural Repair, 23(6), 435–440. Coelho, R. W., De Campos, W., Da Silva, S. G., Okazaki, F. H., & Keller, B. (2007). Imagery intervention in open and closed tennis motor skill performance. Perceptual and Motor Skills, 105(2), 458–468. Decety, J., & Gre`zes, J. (1999). Neural mechanisms subserving the perception of human actions. Trends in Cognitive Sciences, 3(5), 172–178. Decety, J., Jeannerod, M., & Prablanc, C. (1989). The timing of mentally represented action. Behavioural Brain Research, 34(1–2), 35–42. Desrosiers, J., Bravo, G., He´bert, R., Dutil, E., & Mercier, L. (1994). Validation of the Box and Block Test as a measure of dexterity of elderly people: Reliability, validity and norms studies. Archives of Physical Medicine and Rehabilitation, 75(7), 751–755. De Vries, S., & Mulder, T. (2007). Motor imagery and stroke rehabilitation: A critical discussion. Journal of Rehabilitation Medicine, 39(1), 5–13. Feltz, D. L., & Petlichkoff, L. (1983). Perceived competence among interscholastic sport participants and dropouts. Canadian Journal of Applied Sport Sciences, 8(4), 231–235. Gabbard, C., Cac¸ola, P., & Cordova, A. (2011). Is there an advanced aging effect on the ability to mentally represent action? Archives of Gerontology and Geriatrics, 53(2), 206–209. Gao, Q., Duan, X., & Chen, H. (2011). Evaluation of effective connectivity of motor areas during motor imagery and execution using conditional Granger causality. NeuroImage, 54(2), 1280–1288.
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Archives of Gerontology and Geriatrics journal homepage: www.elsevier.com/locate/archger
Assessment of mental chronometry (MC) in healthy subjects Johanna Greiner a, Mircea Ariel Schoenfeld a,b,c, Joachim Liepert a,* a
Department of Neurorehabilitation, Kliniken Schmieder, 78476 Allensbach, Germany Department of Neurology, Otto-von-Guericke University, 39120 Magdeburg, Germany c Department of Behavioural Neurology, Leibniz Institute for Neurobiology, 39118 Magdeburg, Germany b
A R T I C L E I N F O
A B S T R A C T
Article history: Received 24 March 2013 Received in revised form 1 August 2013 Accepted 21 September 2013 Available online 18 October 2013
Objective: This study examined the temporal congruency between real and imagined movements and explored intermanual transfer effects in healthy subjects. Methods: Seventy-six right-handed healthy subjects were allocated to three age groups and tested with a modified version of the Box and Block Test (BBT). We focussed on two aspects. First, the BBT was evaluated with respect to its ability to assess MC. Second, we were interested whether performance of motor imagery (MI) and real execution with one hand would modify performance with the other hand. To explore MC, we measured motor execution (ME) time as the time needed to perform the BBT, and MC time as the time difference between ME and the time needed for imagination of task execution. The BBT was performed with both hands consecutively to study transfer effects from one hand to the other and then repeated with the first hand for practice effects. Results: The age group with the oldest subjects exhibited a slower BBT performance and a less precise MC than the other 2 age groups. Irrespective of the age, MC abilities could be transferred to the other hand, whereas ME only improved when repeating the task with the same hand. Conclusions: The BBT was able to demonstrate an age-related decline of dexterity and MC. Intermanual transfer of MI abilities occurred even after a single run. ß 2013 Elsevier Ireland Ltd. All rights reserved.
Keywords: Mental chronometry Motor execution Age-dependent changes Box and Block Test Intermanual transfer
1. Introduction MI may be defined as ‘‘a dynamic state during which the representation of a given motor act is internally rehearsed within working memory without any overt motor output’’ (Decety & Gre`zes, 1999). The imagination of complex movements is an important element of training in competitive sports. From the sports literature it is well known that MI, when applied in addition to real execution, is more effective than MI or functional training alone (e.g., Feltz & Petlichkoff, 1983; Coelho, De Campos, Da Silva, Okazaki, & Keller, 2007; Olsson, Jonsson, & Nyberg, 2008). MI abilities can be tested by different approaches. One might explore how vividly a movement can be imagined. This aspect can be addressed by subjective questionnaires. However, this approach has been questioned (Lotze & Halsband, 2006; Sharma, Pomeroy, & Baron, 2006), because an external validation is not possible in these tests (Lequerica, Rapport, Axelrod, Telmet, & Whitman, 2002). Another approach deals with spatial aspects, e.g., by asking the subjects to perform mental rotations of a hand or other threedimentional objects (e.g., Johnson, 1999; Johnson, Sprehn, &
* Corresponding author at: Department of Neurorehabilitation, Kliniken Schmieder, Zum Tafelholz 8, D-78476 Allensbach, Germany. Tel.: +49 7533 808 1236; fax: +49 7533 808 1441. E-mail address: [email protected] (J. Liepert). 0167-4943/$ – see front matter ß 2013 Elsevier Ireland Ltd. All rights reserved. http://dx.doi.org/10.1016/j.archger.2013.09.003
Saykin, 2002) or by estimation of reachability of an object (Gabbard, Cac¸ola, & Cordova, 2011). A third approach focuses on chronometrical aspects by studying time differences between physical execution of a movement and imagination of the same movement. Thus, MC allows measuring the congruency between MI and ME in an objective way. Typically, the duration of imagined movements correlates with the duration of real movements in healthy individuals (Bakker, de Lange, Stevens, Toni, & Bloem, 2007; Decety, Jeannerod, & Prablanc, 1989) but may be impaired in stroke patients (De Vries & Mulder, 2007; Liepert, Greiner, Nedelko, & Dettmers, 2012; Malouin, Richards, Desrosiers, & Doyon, 2004; Sabate, Gonzales, & Rodriguez, 2007; Sirigu et al., 1996). The tasks used in preceding studies were quite different, e.g., pointing tasks (Malouin et al., 2004) or complex sequences of finger movements (Sabate et al., 2007). Our aim was to apply a simple and widely-used method which would enable scientists all over the world to perform studies with the same standardized equipment. The BBT is a frequently used method in neurological rehabilitation to test dexterity and has been shown to provide a valid and reliable measure in healthy subjects (Desrosiers, Bravo, He´bert, Dutil, & Mercier, 1994; Mathiowetz, Volland, Kashman, & Weber, 1985) and stroke patients (Chen, Chen, Hsueh, Huang, & Hsieh, 2009; Platz et al., 2005). We used this test not only for physical performance but also for MI to explore MC abilities. It’s main features are (1) easy administration, (2) close relation to
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activities of daily life (e.g., object manipulation) and (3) rapid execution. We focussed on the investigation of two different aspects: (1) evaluation of the BBT as a tool to detect age-related or genderrelated effects of MC and (2) aspects of practice by task repetition. The latter aspect particularly addressed the question of an intermanual motor skill transfer. It has been shown repeatedly that motor practice with one hand also improves motor functions of the other, untrained hand (e.g., Andree & Maitra, 2002; Lee, Hinder, Gandevia, & Carroll, 2010; Perez, Wise, Willingham, & Cohen, 2007; Schulze, Lu¨ders, & Ja¨ncke, 2002). We were interested whether performance of MC and ME with one hand would result in an improvement of ME and MC abilities for the other hand and whether such an intermanual skill transfer would be agedependent. 2. Methods 2.1. Subjects Seventy-six subjects gave written consent and participated in the study. The study was approved by the Ethical Committee of Constance University. Exclusion criteria were neurological or psychiatric diseases as well as any other diseases involving movement problems. All participants were free of physical or cognitive impairments and were able to understand the instructions given to perform the test. Most subjects were recruited in the hospital. Those aged 65 were spouses of patients currently treated in the hospital. None of the subjects reported any MC involvement or practice ever before the testing. The subjects were allocated into three age groups: Group A: n = 25 (range: 18–34 years, 12 males; age 24.5; 4.2 years [mean standard deviation]), Group B: n = 24 (range: 35–54 years, 8 males; age 43.5 6.6 years) and Group C: n = 27 (range: 55–83 years, 11 males; age 68.3 8.5 years). The age ranges were chosen for 2 reasons. First, we wanted to generate age groups that can be defined as ‘‘young’’, ‘‘middle-aged’’, and ‘‘aged’’. Second, we wanted to gather a similar number of subjects in each group. The study was performed within a single session and had no dropouts to be reported. 2.2. Measures 2.2.1. Edinburgh Handedness Inventory (EHI) Prior to the administration of the chronometric test, the hand dominance was assessed using the EHI as a reliable measure of hand performance (Oldfield, 1971). 2.2.2. BBT The BBT involves grasping and moving 1-in. square wooden blocks from one side of an 8-in. square box to the other, by passing them over a wooden partition 5 in. high using one hand only. Each hand is tested separately. The critical measure is the number of blocks that can be transported within 1 min. Higher scores of transported blocks indicate a better manual dexterity. We used the same standardized setting of the BBT apparatus but positioned fifteen blocks in one compartment of the box. Before starting the MC task subjects were allowed to hold and manipulate one block in order to get a proper evaluation of the weight, surface and haptic properties of the blocks. First, subjects were instructed to imagine grasping each block one after the other and moving it to the other side of the compartment. Subjects were asked to perform the imagery task from the first person perspective as fast and as realistic as possible. They were told to imagine how they grasp the block with thumb and index finger, move it across the partition, release it and return with the hand to
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grasp the next block. The subjects were given a start signal (go) for the imagery by the experimenter and gave a signal (stop) as soon as they had completed the task. The time between ‘‘go’’ and ‘‘stop’’ signal was measured using a stopwatch and defined as MI time. We deliberately chose this order (first MI, then ME) since the movements (grasping, transferring and releasing an object) are easy and need no explicit training. In the following, subjects physically performed in the BBT. The instruction was to move the blocks one by one as fast as possible to the other side of the compartment. The experimenter gave a go signal. The time until the last block was moved was measured and defined as ME time. The time difference between MI and ME was calculated and called MC. The experiment consisted of three tasks. Each subject participated in all of these tasks. In each task both conditions (MI and ME) were measured. In task 1, the subject started the test with one hand. The side (right or left hand) was chosen randomly. In task 2, the subject performed the test with the other hand and in task 3 the subject repeated the test with the same hand he had used in task 1. 2.3. Procedure An experienced physiotherapist familiar with the procedures tested all subjects. The duration of the whole session was about 15 min. The subjects were seated in front of a table, sitting on a chair with backrest. The wooden box was placed on the table in front of the subjects. 3. Data analysis The statistical analysis was performed using SPSS V16.0. In the analysis, the level of significance was assumed at 5%. An analysis of variance (ANOVA) with the factors AGE (3 levels), GENDER (2 levels), TASK (3 levels) and ORDER (2 levels [right hand first or left hand first]) was calculated with the ME data and with the MC data. In case of significant main effects or interactions, univariate ANOVAs were employed to further investigate the effects. Prior to the analysis, a sign-test was performed on the data and revealed that the distribution of the data was not different from the normal distribution. For analysing the MC data, the time difference between MI and ME was taken as an absolute error, irrespective of whether MI duration was shorter than real execution time or vice versa. Then, the MC data was normalized by the formula (real performance MC/real performance), to eliminate the difference in performance (older participants being slower than younger participants). For calculation of effect sizes we chose Cohen’ d. By convention, an effect size of 0.2 is termed small, an effect size of 0.5 is termed medium and a value of 0.8 is termed large. 4. Results 4.1. EHI Out of 79 subjects assessed with the EHI, three subjects were identified as left-handed and 76 subjects were identified as righthanded. In order to avoid a handedness-related influence on the data, the analysis was performed with the right-handed subjects only. 4.2. ME performance The ANOVA indicated significant differences for the main factors task type (F(2, 210) = 4.243; p = 0.016), and age (F(2, 210) = 21.527; p < 0.001). However, no significant differences
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Table 1 BBT results: task types. Task type
ME
MC
1. Task (first hand)
Ratio
2.3 1.9 [TD$INLE]
3. Task (first hand again)
[TD$INLE]
1.8 1.4 1.3 1.1
2. Task (other hand) ME: real performance time measured in seconds. MC: time difference between ME and MI, time measured in seconds. Ratio: ME minus MI, divided by ME. *p < 0.05.
were found for the factors gender (F(1, 210) = 0.07; p = 0.82) or order (right hand first versus left hand first) (F(1, 210) = 0.386; p = 0.58), in the absence of any significant interaction. There was no significant difference between task 1 and 2 (first hand and second hand) (F(1, 156) = 0.607; p = 0.437; d = 0.12)), but a significant difference between task type 1 and 3 (first hand and first hand again) (F(1, 156) = 10.416; p = 0.002; d = 0.52)), and between task type 2 and 3 (second hand and first hand again) (F(1,156) = 4.865; p = 0.029; d = 0.35)). This pattern indicates that there was no difference in real performance between the first hand and the second hand, but motor performance with the first hand improved with repetition (Table 1). There was a significant difference between the youngest age group ‘‘A’’ and the oldest age group ‘‘C’’ (F(1, 154) = 27.341; p < 0.0001; d = 0.7), and between the intermediate group ‘‘B’’ and group ‘‘C’’ (F(1, 151) = 18.237; p < 0.0001; d = 0.56). There was no significant difference between group ‘‘A’’ and group ‘‘B’’ (F(1, 145) = 0.580; p = 0.475; d = 0.11). Thus, age group ‘‘C’’ was slower in the real execution performance compared to the other two age groups (Table 2). 4.3. MC For the first task, MI time was shorter than real execution performance time (ME) in 41 subjects, and vice versa in 25 subjects. 10 subjects did not misestimate themselves and showed an identical time for MC. Concerning time difference (MC) between MI and ME, the ANOVA indicated no significant difference for the factor gender (F(1, 210) = 0.614; p > 0.05)). However, significant differences were observed for the factors age (F(2, 210) = 5.113; p = 0.002)), and task type (F(2, 210) = 9.823; p < 0.0001)) in the absence of a significant interaction. Further analyses indicated a significant difference between task types 1 and 3 (first hand and first hand again) (F(1, 156) = 15.278; p < 0.0001; d = 0.63), a significant difference between task type 1 and 2 (first hand and second hand) (F(1, 156) = 5.302; p = 0.023; d = 0.37), and a marginally significant difference between task type
2 and 3 (second hand and first hand again) (F(1, 156) = 3.733; p = 0.055; d = 0.31). This pattern shows that the MC performance improves when performed with the other hand, and improves even more with repetition of the same hand. In addition there was a significant difference between age group ‘‘A’’ and age group ‘‘C’’ (F(1, 154) = 9.228; p = 0.003; d = 0.22), and a significant difference between group ‘‘B’’ and group ‘‘C’’ (F(1, 151) = 9.311; p = 0.002; d = 0.31). No significant difference (F(1, 145) = 0.055; p > 0.05; d = 0.11) was observed between groups ‘‘A’’ and ‘‘B’’. Thus, the oldest age group ‘‘C’’ showed the worst MC performance. 5. Discussion The main results of this study are that, (1) the group with the oldest subjects was slower in real execution performance than the other two groups, (2) the group with the oldest subjects had a less precise MC ability than the other two groups and (3) based on the whole group of subjects, task performance with the ‘‘second’’ hand (task type 2) was associated with an improvement of MC but not with an improved execution performance and (4) in task type 3, repeated use with the same hand (used hand) showed improvement in ME. The age-dependent decline in the ME performance with the BBT indicates a partial loss of dexterity with increasing age. This is in agreement with other publications (Marneweck, Loftus, & Hammond, 2011; Mathiowetz et al., 1985). The reasons for this impaired execution remain speculative. A slowing of processing in motor areas of the brain as well as a subclinical dysfunction of joints, tendons and muscles might be responsible for our finding. Functional imaging studies have shown repeatedly that older adults compared with young adults had more widespread movement-associated brain activations involving motor and nonmotor areas. These changes were interpreted as a compensatory effect required by older adults to perform the motor task at the same level (e.g., Heuninckx, Wenderoth, Debaere, Peeters, & Swinnen, 2005). These age-related differences can also be found in MI tasks
Table 2 BBT results: age groups. Age groups
ME
Group B (35–54 years)
MC
Ratio
1.4 1.2
Group A (18–34 years) [TD$INLE]
Group C (55–83 years) Group A: (n = 25); Group B: (n = 24); Group C: (n = 27). ME: real performance time measured in seconds. MC: time difference between ME and MI, time measured in seconds. Ratio: ME minus MI, divided by ME. *p < 0.05.
1.4 1.2 2.4 1.8
[TD$INLE]
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(Zapparoli et al., 2013). The findings underscore the necessity to match for the factor ‘‘age’’ when comparing patients and healthy subjects in their ME. Our group of elderly subjects also showed a less precise MC in the test. Since we had eliminated the influence of longer execution times, the MC results cannot be attributed to a longer performance time per se, but rather indicate that old persons have both, a loss of dexterity and an impairment of MC ability when tested with the BBT. An age-related decline of MI has also been shown in other studies (e.g., Skoura, Papaxanthis, Vinter, & Pozzo, 2005). Saimpont, Pozzo, and Papaxanthis (2009) used the Hand Rotation Task to demonstrate an impaired ability of elderly subjects to implicitly simulate movements of the upper limbs. In another study (Personnier, Kubicki, Laroche, & Papaxanthis, 2010) it was shown that the temporal feature of imagined precision on gait was declined in the older age group. Similar findings were reported by Schott (2012). In that study, impaired MC was found for a walking test. Subjects aged 70 years or older were affected whereas no significant impairment of MC was observed in subjects aged 60–69 years. A correlation with the intactness of working memory was reported. In a study by Malouin, Richards, and Durand (2010) an impaired visual MI ability was associated with a decline in visuospatial and kinesthetic working memory. Saimpont, Malouin, Tousignant, and Jackson (2013) concluded that age-related MI ability declines depend on task difficulty. In summary, the existing literature suggests that different types of MI are affected with increasing age. This suggests a more generalized decline of MI abilities and not the loss of one particular function. The level of cognitive and, in particular, memory function may play an important role. In our study, we did not specifically address this issue. In future studies working memory abilities should be considered. Interestingly, MC was already improved when performing the BBT-MC task with the other hand without preceding ME. This suggests that subjects had some benefit from the preceding task execution even if it was not the same hand. It indicates that MC abilities are independent of whether the same or the other hand has been the subject of imagery. We therefore hypothesize that MC knowledge is stored in a brain area that is accessible by both hemispheres. A recent analysis of effective connectivity between different brain areas evoked by MI of unilateral hand movements has shown that the MI task not only activated areas in the contralateral but also in the ipsilateral hemisphere, mainly the supplementary motor area (SMA), the dorsal premotor cortex (PMd), the inferior parietal lobule (IPL) and the superior parietal lobule (SPL) (Gao, Duan, & Chen, 2011). SMA, PMd, IPL and SPL form a MI network that is activated in both hemispheres by unilateral MI. Information stored in this network is therefore accessible by each hemisphere. However, since the MI task employed by Gao et al. (2011) was not a MC task, our hypothesis is not proven yet. The MC skill transfer was independent of age, suggesting that this ability is less age-related than dexterity and MC per se. Our results are in accordance with a study in which a tapping sequence paradigm was used to train subjects either by motor performance or MI of the task (Amemiya, Ishizu, Ayabe, & Kojima, 2010). The authors reported that imagery was effective for both trained movement and intermanual transfer whereas execution was effective especially for the trained movement. Independent of age or gender, the real performance of the BBT task with the untrained hand did not result in an improved performance time, suggesting that there was no practice or knowledge transfer from one hand to the other. One could argue that the task was too simple or that subjects already were at ceiling with their performance. However, repetition of the task with the trained hand did result in a faster execution of the task. Thus, task
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performance could still be improved. A possible explanation of this finding is that an intermanual transfer of the motor skill requires a much higher number of repetitions. Schulze et al. (2002) have demonstrated in a study with healthy subjects that participated in a pegboard task for 120 min that such an intense motor training can transfer a motor function improvement from the trained hand to the untrained hand. In our study, the modified version of the BBT was easy to administer and took a maximum of 15 min including all task repetitions. None of the subjects reported any difficulties when performing the MC task. We suggest that the comparison between MI and real execution performance of the BBT provides relevant information about the individual dexterity and MI abilities. Thus, this test might be suitable for patients with neurological diseases participating in MI studies. Several studies have explored MI as a treatment in stroke patients. Two reviews concluded that MI might be helpful as an additional training to physical training (Barclay-Goddard, Stevenson, Poluha, & Thalman, 2011; De Vries & Mulder, 2007; Sharma et al., 2006; Zimmermann-Schlatter, Schuster, Puhan, Siekierka, & Steurer, 2008). However, a recent controlled trial with 121 stroke patients was unable to demonstrate a beneficial effect of MI (Ietswaart et al., 2011). Our own pilot study in which the BBT was used in stroke patients to test their MC abilities has not only demonstrated its feasibility in such a patient group. The BBT results also indicated that patients with severe sensory deficits were much more compromised in their MC ability than patients with pure motor stroke (Liepert et al., 2012). In future studies, it should be explored if this test is able to predict the effectiveness of MI training. Moreover, the intermanual transfer of MI abilities might offer an interesting treatment perspective in stroke patients. The hypothesis is that intense MI training with the unaffected hand could also improve MI skills for the affected side. Conflict of interest statement The authors declare that they have nothing to disclose. References Amemiya, K., Ishizu, T., Ayabe, T., & Kojima, S. (2010). Effects of motor imagery on intermanual transfer: A near-infrared spectroscopy and behavioural study. Brain Research, 1343, 93–103. Andree, M. E., & Maitra, K. K. (2002). Intermanual transfer of a new writing occupation in young adults without disability. Occupational Therapy International, 9(1), 41–56. Bakker, M., de Lange, F. P., Stevens, J. A., Toni, I., & Bloem, B. R. (2007). Motor imagery of gait: A quantitative approach. Experimental Brain Research, 179(3), 497–504. Barclay-Goddard, R. E., Stevenson, T. J., Poluha, W., & Thalman, L. (2011). Mental practice for treating upper extremity deficits in individuals with hemiparesis after stroke. Cochrane Database of Systematic Reviews, CD005950. Chen, H. M., Chen, C. C., Hsueh, I. P., Huang, S. L., & Hsieh, C. L. (2009). Test-retest reproducibility and smallest real difference of 5 hand function tests in patients with stroke. Neurorehabilitation and Neural Repair, 23(6), 435–440. Coelho, R. W., De Campos, W., Da Silva, S. G., Okazaki, F. H., & Keller, B. (2007). Imagery intervention in open and closed tennis motor skill performance. Perceptual and Motor Skills, 105(2), 458–468. Decety, J., & Gre`zes, J. (1999). Neural mechanisms subserving the perception of human actions. Trends in Cognitive Sciences, 3(5), 172–178. Decety, J., Jeannerod, M., & Prablanc, C. (1989). The timing of mentally represented action. Behavioural Brain Research, 34(1–2), 35–42. Desrosiers, J., Bravo, G., He´bert, R., Dutil, E., & Mercier, L. (1994). Validation of the Box and Block Test as a measure of dexterity of elderly people: Reliability, validity and norms studies. Archives of Physical Medicine and Rehabilitation, 75(7), 751–755. De Vries, S., & Mulder, T. (2007). Motor imagery and stroke rehabilitation: A critical discussion. Journal of Rehabilitation Medicine, 39(1), 5–13. Feltz, D. L., & Petlichkoff, L. (1983). Perceived competence among interscholastic sport participants and dropouts. Canadian Journal of Applied Sport Sciences, 8(4), 231–235. Gabbard, C., Cac¸ola, P., & Cordova, A. (2011). Is there an advanced aging effect on the ability to mentally represent action? Archives of Gerontology and Geriatrics, 53(2), 206–209. Gao, Q., Duan, X., & Chen, H. (2011). Evaluation of effective connectivity of motor areas during motor imagery and execution using conditional Granger causality. NeuroImage, 54(2), 1280–1288.
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