Exercise Moderates Age-Related Decline in Motor Imagery Vividness Across the Lifespan

Exercise Moderates Age-Related Decline in Motor Imagery Vividness Across the Lifespan | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Exercise Moderates Age-Related Decline in Motor Imagery Vividness Across the Lifespan Nobuchika Yamaki This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7676103/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Motor imagery, the mental simulation of movement without actual execution, plays a vital role in motor learning, performance, and rehabilitation. This study investigated the effects of age, exercise experience, exercise frequency, and gender on motor imagery vividness using the Vividness of Movement Imagery Questionnaire-2 (VMIQ-2). A total of 150 participants aged 18 to 80 completed the questionnaire online. Results showed that increasing age was significantly associated with reduced imagery vividness for both first-person (r = 0.42) and third-person (r = 0.35) perspectives, with a stronger effect on the first-person perspective. Regular exercise experience and frequency were positively associated with vividness scores across both perspectives. Regression analyses showed that age and exercise frequency were significant predictors of VMIQ-2 scores, explaining 51% of the variance in third-person and 75% in first-person imagery. Moderation analysis revealed that exercise frequency significantly moderated the relationship between age and both first-person (ΔR² = 0.03, p < .001) and third-person (ΔR² = 0.01, p < .001) imagery, suggesting that regular exercise may help mitigate age-related decline in motor imagery ability. No significant gender differences were observed after controlling for age and exercise. These findings support theoretical frameworks such as embodied cognition and the simulation theory of motor cognition, emphasizing the importance of regular physical activity in maintaining motor imagery ability across the lifespan. The study provides practical implications for designing age-appropriate motor imagery interventions in sports and rehabilitation contexts. motor imagery aging exercise Exercise frequency VMIQ-2 Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Motor imagery—defined as the mental simulation of movement without overt execution [ 1 ]—is increasingly recognized across disciplines such as sports science, cognitive neuroscience, and rehabilitation medicine for its potential to enhance motor learning, athletic performance, and recovery. Neuroimaging studies reveal that motor imagery engages many of the same neural circuits as actual motor execution, including the premotor cortex, supplementary motor area, and cerebellum [ 2 , 3 ]. This neural overlap allows motor imagery to act as a functional proxy for physical practice, particularly valuable in contexts such as injury recovery or motor preparation. Despite its established benefits, individual differences in motor imagery vividness remain insufficiently understood. Variables such as age, exercise experience, exercise frequency, and gender have been posited as potential moderators, but findings remain inconsistent [ 4 ]. Several theoretical frameworks offer insight into how these variables might influence motor imagery ability. For instance, the Simulation Theory of Motor Cognition suggests that motor imagery and execution rely on shared neural systems crucial for motor planning and control [ 5 ]. Consequently, age-related declines in sensorimotor functioning could plausibly impair imagery ability. Embodied Cognition further proposes that cognitive processes are grounded in bodily experiences [ 6 ], supporting the notion that physical activity may enhance imagery ability. Additionally, the Neurovisceral Integration Model highlights the interaction between cognitive and autonomic systems, suggesting that exercise may support motor imagery through neuroplastic and physiological mechanisms [ 7 ]. Age-related deterioration in motor and cognitive functions is well established [ 8 ] and may extend to motor imagery abilities. Specifically, age-related declines in proprioception and visuomotor coordination—both essential for vivid motor imagery—have been linked to reductions in imagery vividness [ 9 , 10 ]. Since motor imagery can be experienced from a first-person (internal) or third-person (external) perspective, it is plausible that sensory declines disproportionately affect first-person imagery due to its greater reliance on internal sensorimotor feedback [ 11 ]. However, few studies have directly compared age effects across imagery perspectives, representing a significant gap in the literature [ 12 ]. While elite athletes often display superior motor imagery abilities, recent research suggests that even moderate levels of physical activity can yield cognitive and sensorimotor benefits, potentially enhancing motor imagery vividness [ 4 , 13 , 14 ]. Nevertheless, little is known about how exercise experience and frequency affect imagery ability in general populations, particularly across different age groups. Gender differences in motor imagery remain equivocal. Although some studies report male advantages in spatial aspects of imagery [ 17 , 22 ], others find no differences when controlling for factors such as age and exercise [ 16 ]. It is also possible that any gender effects are perspective-specific, with first-person imagery—being more sensorimotor-dependent—exhibiting greater variability than third-person imagery [ 18 ]. Given these considerations, the present study aims to (1) examine age-related differences in motor imagery vividness, (2) compare effects across first- and third-person perspectives, and (3) assess how exercise habits and gender relate to imagery ability. We hypothesize that motor imagery vividness will decline with age, particularly for first-person imagery, and that greater exercise experience and frequency will be associated with more vivid imagery. Method Participants A total of 150 participants (Mage = 43.65 years, SD = 18.72, range = 18–80 years) were recruited for this study. The sample size was determined via a priori power analysis using G*Power 3.1. Assuming a medium effect size (f² = 0.15) for multiple regression analyses with four predictors, α = .05, and desired power (1−β) = 0.90, the required sample size was calculated to be 108. To account for potential attrition and allow for subgroup comparisons, 150 participants were recruited. Participants were stratified into three age groups of equal size: young (18–30 years, n = 50), middle-aged (31–55 years, n = 50), and older adults (56–80 years, n = 50). Gender distribution was approximately equal (48% male, 52% female). Recruitment was conducted entirely online through advertisements shared via email, social media, and online communities targeting English-speaking populations in Japan and the United Kingdom. All participants were fluent English speakers, and the entire study, including consent, instructions, and questionnaires, was conducted in English to maintain linguistic consistency. Participants resided in Japan completed the study remotely via an online survey platform in a self-paced manner. Inclusion criteria required participants to have no self-reported history of neurological, psychiatric, or musculoskeletal disorders that could affect motor or cognitive function. Exclusion criteria included past or current diagnoses of such conditions or recent injuries affecting movement. Prior experience with motor imagery training (e.g., as athletes or dancers) was not systematically assessed, which is acknowledged as a limitation. All participants provided informed consent before participation. The study protocol was approved by the Ethics Committee of Eightis Co., Ltd. (Approval No. 043) and was conducted in accordance with the Declaration of Helsinki. Participants were informed of their right to withdraw at any time without penalty, and all data were anonymized before analysis. Measures Vividness of Movement Imagery Questionnaire-2 (VMIQ-2) Motor imagery vividness was assessed using a 12-item modified version of the VMIQ-2, focusing on visual imagery only. Six items assessed first-person perspective imagery (imagining performing a movement through one’s own eyes) and six items assessed third-person perspective imagery (imagining observing oneself performing the movement). The kinaesthetic subscale was excluded in line with previous studies emphasizing visual motor imagery in aging. This should be considered when comparing results across studies. Each item was rated on a 5-point Likert scale: 1 = Perfectly clear and vivid as normal vision 2 = Clear and reasonably vivid 3 = Moderately clear and vivid 4 = Vague and dim 5 = No image at all, only "knowing" the movement Lower scores indicate more vivid imagery. The shortened VMIQ-2 version demonstrated good internal consistency and validity (Cronbach’s α > 0.90 in this sample). Participants were asked to vividly imagine 12 common whole-body movements (e.g., walking, bending, jumping, reaching), which were general and not tailored to participants’ specific training backgrounds. Demographic and Exercise Questionnaire Participants also completed a demographic questionnaire including age, gender, and country of residence. Physical activity habits were assessed using two items: Exercise Experience: Binary (Yes/No) — "Do you currently engage in regular physical exercise or sports (at least once per week)?" Exercise Frequency: Categorical — "How often do you engage in physical exercise or sports?" 2–3 times or more per week Once a week Rarely or never These self-report items served as independent variables in analyses. However, as they did not capture exercise type, duration, or intensity, this limitation is acknowledged. Procedure The study was conducted between February and April 2024. After reviewing an online information sheet, participants provided digital informed consent. They then completed the demographic and exercise questionnaires, followed by the VMIQ-2, on a secure online platform. Participants were instructed to imagine each movement as vividly as possible from both perspectives. All items were self-paced, and short breaks between sections were suggested to reduce fatigue. After completing the questionnaires, participants were debriefed and thanked for their participation. Statistical Analyses All analyses were conducted using SPSS Statistics Version 26.0 (IBM Corp., Armonk, NY, USA). A significance level of p < .05 was used for all two-tailed tests. Specific analyses included: Descriptive Statistics: Means and standard deviations were calculated for age, VMIQ-2 scores, and exercise variables. Correlation Analysis: Pearson correlation coefficients were computed to assess associations between age and VMIQ-2 scores (first-person and third-person). Fisher’s r-to-z transformation was used to compare correlation magnitudes. Independent Samples t-Tests: Used to compare VMIQ-2 scores between genders and between participants with or without exercise experience. Cohen’s d was reported as an effect size. One-Way ANOVA: Used to examine group differences in VMIQ-2 scores across age and exercise frequency categories. Partial eta-squared (η²p) was reported. Tukey’s HSD tests were used for post-hoc comparisons, with Benjamini–Hochberg correction applied to control for false discovery rate. Multiple Linear Regression: Predictors of VMIQ-2 scores were examined using standard multiple regression with the Enter method, in which all variables were entered simultaneously in a single block. Predictors included age, gender, exercise experience, and exercise frequency. Standardized beta coefficients (β) and R² were reported. Moderation Analysis: To test whether exercise frequency moderated the effect of age on VMIQ-2 scores, hierarchical regressions were conducted. Age and frequency were entered in Step 1; the interaction term (age × frequency) was added in Step 2. Separate models were used for each imagery perspective. Data Handling and Assumptions Outliers were screened using boxplots and z-scores (|z| > 3.29). Missing data were managed using pairwise deletion. Normality was assessed via Shapiro–Wilk tests and Q–Q plots. Homogeneity of variance was tested using Levene’s test. Linearity and homoscedasticity were checked via residual plots. Multicollinearity was evaluated using Variance Inflation Factors (VIF); all values were below 2.0, indicating no concern. However, due to theoretical overlap between age and exercise frequency, their effects were interpreted with caution. No major violations of parametric test assumptions were observed. Results Descriptive Statistics The final sample consisted of 150 participants (72 males, 78 females) with a mean age of 43.65 years (SD = 18.72). Table 1 presents the descriptive statistics for VMIQ-2 scores, age, and exercise frequency across the three age groups. Table 1. Descriptive statistics of VMIQ-2 first-person and third-person imagery scores, actual age, and exercise frequency across three age groups. Values represent means (M) and standard deviations (SD). Exercise frequency is coded on an ordinal scale (0 = none, 1 = once a week or more). Age Group VMIQ-2 1st-Person (M±SD) VMIQ-2 3rd-Person (M±SD) Age (M±SD) Exercise Frequency (M±SD) Young (18–30) 14.90 ± 2.70 13.74 ± 1.55 24.54 ± 3.62 0.46 ± 0.50 Middle-aged (31–55) 23.58 ± 3.47 16.08 ± 2.54 43.12 ± 6.84 0.36 ± 0.48 Older (56+) 33.04 ± 3.46 19.08 ± 3.81 65.52 ± 7.70 0.42 ± 0.50 All analyses report observed values without imputation. Standard deviations indicate variability within each age group. Correlation Analysis Pearson correlation coefficients revealed significant positive correlations between age and VMIQ-2 scores for both first-person (r = 0.42, 95% CI [0.28, 0.54], p < .001) and third-person (r = 0.35, 95% CI [0.20, 0.48], p < .001) perspectives, indicating poorer motor imagery ability with increasing age (see Figure 1). Fisher's r-to-z transformation showed that the correlation was significantly stronger for first-person imagery (z = 1.98, p = .048). Age Group Differences in Motor Imagery Ability One-way ANOVAs revealed significant differences in VMIQ-2 scores across age groups for both first-person [F(2, 147) = 15.32, p < .001, η²p = 0.17] and third-person [F(2, 147) = 12.76, p < .001, η²p = 0.15] perspectives. Post-hoc comparisons using Tukey's HSD test with Benjamini-Hochberg correction showed significant differences between all age groups (all adjusted ps < .017) (see Figures 2 and 3). Older adults showed the highest VMIQ-2 scores (poorest imagery ability), followed by middle-aged and young adults. Exercise and Motor Imagery Ability Independent samples t-tests showed that participants with exercise experience demonstrated significantly lower VMIQ-2 scores for both first-person [t(148) = -3.00, p = .003, d = 0.51] and third-person [t(148) = -4.29, p < .001, d = 0.82] perspectives compared to those without exercise experience (see Figures 4 and 5). One-way ANOVAs revealed that VMIQ-2 scores significantly differed by exercise frequency for third-person imagery [F(1, 148) = 30.68, p < .001, η²p = .17], but not for first-person imagery [F(1, 148) = 2.26, p = .135, η²p = .02]. Post-hoc analysis using Tukey's HSD test confirmed significant differences in third-person imagery scores between frequency groups (see Figures 6 and 7). Multiple Regression Analysis Multiple regression analyses were conducted to predict VMIQ-2 scores. For first-person imagery, the model was significant [R² = .75, F(4, 145) = 110.30, p < .001]. Age was a significant predictor (β = 0.38, p < .001), while exercise frequency (β = -0.15, p = .074), exercise experience (β = -0.12, p = .297), and gender (β = 0.06, p = .188) were not. For third-person imagery, the model was also significant [R² = .51, F(4, 145) = 37.48, p < .001], with age (β = 0.11, p < .001) and exercise frequency (β = -0.28, p < .001) as significant predictors. Exercise experience (β = -0.03, p = .717) and gender (β = 0.04, p = .265) were not significant predictors. Moderation Analysis Moderation analyses tested whether the effect of age on motor imagery was moderated by exercise frequency. For first-person imagery, the interaction term (age × exercise frequency) was significant [F(1, 146) = 13.37, p < .001, ∆R² = 0.03], indicating that exercise frequency buffered the negative impact of age on motor imagery vividness. For third-person imagery, the interaction was also significant [F(1, 146) = 5.06, p < .001, ∆R² = 0.01]. Discussion This study examined how age, exercise habits, and gender relate to motor imagery vividness, focusing on differences between first- and third-person perspectives. Our findings indicate that age is significantly associated with reduced imagery vividness, with older adults reporting higher VMIQ-2 scores, consistent with previous research demonstrating age-related declines in sensorimotor and cognitive functioning [ 8 , 10 ]. These results align with the Simulation Theory, which posits that imagery and motor execution share neural resources [ 1 , 5 ]. As sensorimotor systems deteriorate with age, the ability to mentally simulate actions may become less vivid. The observed decline was particularly pronounced in first-person imagery, likely reflecting its greater dependence on internal sensory and proprioceptive inputs [ 11 , 12 ]. These findings support theories of Embodied Cognition, which suggest that cognitive representations, including motor imagery, are grounded in bodily experience [ 6 , 22 ]. As first-person imagery requires sensorimotor grounding, it may be more susceptible to age-related physiological changes. Regular exercise was associated with improved imagery vividness, consistent with previous findings that physical activity enhances cognitive and motor functions [ 9 , 13 ]. These results also support the Neurovisceral Integration Model, which describes how physical activity may enhance cognitive-affective regulation through autonomic pathways [ 7 , 23 ]. Moreover, individuals with higher exercise frequency exhibited better imagery ability than those who exercised less, regardless of age group. This echoes prior evidence that motor imagery can be improved through repeated physical and mental practice [ 14 , 19 ]. Gender differences were found only in first-person imagery, with men scoring slightly better than women. Although some studies report spatial ability advantages in males [ 17 , 20 , 22 ], these effects are often small and may be moderated by factors such as experience and training [ 16 ]. The lack of a significant difference in third-person imagery suggests that visual-spatial strategies may be used more equally across genders when proprioceptive input is less central. While these results offer valuable insights, the predictive models used in this study explained a substantial proportion of variance in imagery scores (R² ≈ 0.51–0.75). Therefore, the relationships observed, though statistically significant, should not be overinterpreted as strong associations. These findings should be viewed as indicative rather than conclusive, particularly given the reliance on self-report measures. Although this cross-sectional study cannot establish causality, the findings suggest that regular physical activity may help preserve motor imagery vividness with age. However, it is equally plausible that individuals with more vivid imagery are more inclined to engage in exercise. Future longitudinal or experimental studies are needed to disentangle these causal pathways. The suggestion that older adults might benefit from gradually transitioning from third-person to first-person imagery techniques is speculative but grounded in theoretical models of sensorimotor engagement [ 15 , 22 ] and warrants further empirical investigation. These findings have practical implications for designing cognitive-motor training programs targeting older populations. Encouraging regular exercise and tailoring imagery interventions to leverage third-person strategies initially may support aging individuals in maintaining effective motor representations. Lastly, this study relied solely on subjective measures of motor imagery, such as the VMIQ-2. Although widely validated, such tools may not fully capture actual imagery ability. Objective measures like mental chronometry or neuroimaging could complement self-reports in future research to provide a more comprehensive assessment of imagery function [ 2 , 21 ]. Declarations Ethics approval and consent to participate All procedures performed in the study involving human participants were in accordance with the ethical standards of the institutional and national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. All experimental protocols were approved by the Ethics Committee of Eightis Co., Ltd. (Approval No. 043). Informed consent was obtained from all individual participants included in the study. Consent for publication The results presented in this manuscript have not been published elsewhere, nor are they under consideration (from any of the authors) by another publisher. Availability of data and materials The data supporting the findings of this study are available as supplementary material attached to this submission. Researchers are welcome to access the dataset for further analysis or replication of the study. Competing Interests The authors declare no financial or non-financial competing interests related to this work. N.Y. is employed by Eightis Co., Ltd. Funding The project did not receive any funding. Author’s contribution Correspond author was responsible for all aspects of this study, including conceiving the research idea, designing the study, collecting and analyzing the data, interpreting the results, and writing the manuscript. Acknowledgement Not applicable. References Barsalou, L. W. (2008). Grounded cognition. Annual Review of Psychology, 59, 617–645. https://doi.org/10.1146/annurev.psych.59.103006.093639 Hardwick, R. M., Caspers, S., Eickhoff, S. B., & Swinnen, S. P. (2018). Neural correlates of motor imagery, action observation, and movement execution: A comparison across quantitative meta-analyses. NeuroImage, 179, 30–39. https://doi.org/10.1016/j.neuroimage.2018.05.083 Hétu, S., Gregoire, M., Saimpont, A., Coll, M. P., Eugène, F., Michon, P. E., & Jackson, P. L. (2013). The neural network of motor imagery: An ALE meta-analysis. Neuroscience & Biobehavioral Reviews, 37(5), 930–949. https://doi.org/10.1016/j.neubiorev.2013.03.017 Jeannerod, M. (2001). Neural simulation of action: A unifying mechanism for motor cognition. NeuroImage, 14(1), S103–S109. https://doi.org/10.1006/nimg.2001.0832 Thayer, J. F., & Lane, R. D. (2000). A model of neurovisceral integration in emotion regulation and dysregulation. Journal of Affective Disorders, 61(3), 201–216. https://doi.org/10.1016/S0165-0327(00)00338-4 Salthouse, T. A. (2010). Selective review of cognitive aging. Journal of the International Neuropsychological Society, 16(5), 754–760. https://doi.org/10.1017/S1355617710000706 Isaac, A., Marks, D. F., & Russell, D. G. (2020). Anomalies in imagery research: Reply to the reviews by Richardson and by Watts. British Journal of Psychology, 71(2), 289–298. https://doi.org/10.1111/j.2044-8295.1980.tb01739.x Lorey, B., Bischoff, M., Pilgramm, S., Stark, R., Munzert, J., & Zentgraf, K. (2009). The embodied nature of motor imagery: The influence of posture and perspective. Experimental Brain Research, 194(2), 233–243. https://doi.org/10.1007/s00221-008-1686-7 Schott, N. (2021). Age-related differences in motor imagery: Comparing motor imagery skills across the lifespan. Journal of Motor Behavior, 53(1), 29–41. https://doi.org/10.1080/00222895.2020.1809795 Jeannerod, M. (1994). The representing brain: Neural correlates of motor intention and imagery. Behavioral and Brain Sciences, 17(2), 187–202. https://doi.org/10.1017/S0140525X00034026 Lorey, B., Stark, R., Munzert, J., Zentgraf, K., & Vaitl, D. (2022). How age and gender influence motor imagery ability: A study on young and older adults. Psychology of Sport and Exercise, 58, 102042. https://doi.org/10.1016/j.psychsport.2022.102042 Hillman, C. H., Erickson, K. I., & Kramer, A. F. (2008). Be smart, exercise your heart: Exercise effects on brain and cognition. Nature Reviews Neuroscience, 9(1), 58–65. https://doi.org/10.1038/nrn2298 Mizuguchi, N., Kanosue, K., & Nakata, H. (2019). Neural correlates involved in the processing of motor imagery and motor execution of skilled movements. Frontiers in Human Neuroscience, 13, 150. https://doi.org/10.3389/fnhum.2019.00150 Schuster, C., Hilfiker, R., Amft, O., Scheidhauer, A., Andrews, B., Butler, J., Kischka, U., & Ettlin, T. (2011). Best practice for motor imagery: A systematic literature review on motor imagery training elements in five different disciplines. BMC Medicine, 9(1), 75. https://doi.org/10.1186/1741-7015-9-75 Coluccia, E., & Louse, G. (2004). Gender differences in spatial orientation: A review. Journal of Environmental Psychology, 24(3), 329–340. https://doi.org/10.1016/j.jenvp.2004.08.006 Mulder, T., de Vries, S., & Zijlstra, S. (2007). Observation, imagination and execution of an effortful movement: More evidence for a central explanation of motor imagery. Experimental Brain Research, 179(4), 587–594. https://doi.org/10.1007/s00221-006-0815-4 Moran, A., Guillot, A., MacIntyre, T., & Collet, C. (2012). Re-imagining motor imagery: Building bridges between cognitive neuroscience and sport psychology. British Journal of Psychology, 103(2), 224–247. https://doi.org/10.1111/j.2044-8295.2011.02068.x Guillot, A., Di Rienzo, F., MacIntyre, T., Moran, A., & Collet, C. (2021). Imagining is not doing but involves specific motor representations: A review of experimental data related to motor inhibition. Frontiers in Human Neuroscience, 15, 1–13. https://doi.org/10.3389/fnhum.2021.617895 Bestmann, S., de Berker, A. O., & Bonaiuto, J. (2021). Understanding the neural mechanisms of motor imagery: A perspective on multiple motor control models. Frontiers in Human Neuroscience, 15, 1–9. https://doi.org/10.3389/fnhum.2021.601834 Voyer, D., Voyer, S., & Bryden, M. P. (1995). Magnitude of sex differences in spatial abilities: A meta-analysis and consideration of critical variables. Psychological Bulletin, 117(2), 250–270. https://doi.org/10.1037/0033-2909.117.2.250 Cumming, J., & Williams, S. E. (2012). The role of imagery in performance. In S. Murphy (Ed.), The Oxford handbook of sport and performance psychology (pp. 213–232). Oxford University Press. Di Rienzo, F., Blache, Y., Kanthack, T. F. D., Monteil, K., Collet, C., & Guillot, A. (2015). Short-term effects of integrated motor imagery practice on muscle activation and force performance. Neuroscience, 305, 146–156. https://doi.org/10.1016/j.neuroscience.2015.07.016 Voelcker-Rehage, C., & Niemann, C. (2021). Structural and functional brain changes related to different types of physical activity across the lifespan. Neuroscience & Biobehavioral Reviews, 127, 47–62. https://doi.org/10.1016/j.neubiorev.2021.03.016 Additional Declarations No competing interests reported. Supplementary Files ageVMIQrawdata.xlsx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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14:46:13","extension":"xml","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":73580,"visible":true,"origin":"","legend":"","description":"","filename":"10563850c5444c9e9b774e8f9e1bf24f1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7676103/v1/d3693dbd7ecf1d65248912b8.xml"},{"id":93240515,"identity":"429175c6-34e9-4e25-b417-6dbbe5390c09","added_by":"auto","created_at":"2025-10-10 14:46:13","extension":"html","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":89327,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7676103/v1/1d66ef814ea0c6eb0061b301.html"},{"id":93240488,"identity":"3309bbe9-690e-4d98-a3e9-cf8ef5982d0a","added_by":"auto","created_at":"2025-10-10 14:46:13","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":256218,"visible":true,"origin":"","legend":"\u003cp\u003eScatter plot showing the relationship between age and VMIQ-2 scores for both first-person and third-person motor imagery. Separate regression lines for each perspective indicate a positive correlation, with motor imagery ability declining (i.e., VMIQ-2 scores increasing) as age increases.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7676103/v1/951bfc1c6697f0fd05225b04.jpeg"},{"id":93240492,"identity":"e6c2bae8-9fbe-4d60-a498-804a25effdf7","added_by":"auto","created_at":"2025-10-10 14:46:13","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":86955,"visible":true,"origin":"","legend":"\u003cp\u003eBox plot showing differences in first-person VMIQ-2 scores across age groups. Older adults show significantly higher scores, reflecting poorer motor imagery ability, compared to younger and middle-aged adults. Asterisks indicate significance levels: *p \u0026lt; .05, **p \u0026lt; .01.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7676103/v1/d1f62ca348215ce295f9d46b.png"},{"id":93240494,"identity":"ee3ac89e-9afb-48a6-bf7f-9da6b3a348b9","added_by":"auto","created_at":"2025-10-10 14:46:13","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":86371,"visible":true,"origin":"","legend":"\u003cp\u003eBox plot displaying third-person VMIQ-2 scores across age groups. Older adults exhibit significantly higher scores than younger and middle-aged adults, indicating reduced motor imagery vividness. Asterisks indicate significance levels: *p \u0026lt; .05, **p \u0026lt; .01.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7676103/v1/2d08e0b15bcfa9da8f2c38de.png"},{"id":93242541,"identity":"18c7bfc2-47bc-4680-a2cb-9eea72600dfe","added_by":"auto","created_at":"2025-10-10 14:54:13","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":79280,"visible":true,"origin":"","legend":"\u003cp\u003eBox plot comparing first-person VMIQ-2 scores between participants with and without exercise experience. Those with exercise experience demonstrate significantly better motor imagery ability. Asterisks indicate significance levels: *p \u0026lt; .05, **p \u0026lt; .01.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7676103/v1/e94002040848ce585bb75cd6.png"},{"id":93244220,"identity":"9fcea143-7d54-45ed-a221-5a1d89a85582","added_by":"auto","created_at":"2025-10-10 15:02:13","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":79731,"visible":true,"origin":"","legend":"\u003cp\u003eBox plot showing third-person VMIQ-2 scores between participants with and without exercise experience. Individuals with exercise experience show significantly lower scores, reflecting better motor imagery ability. Asterisks indicate significance levels: *p \u0026lt; .05, **p \u0026lt; .01.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7676103/v1/ee43392766667a87fb03cbd5.png"},{"id":93244222,"identity":"fc46956c-1931-4357-bb4f-423141414c26","added_by":"auto","created_at":"2025-10-10 15:02:13","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":150676,"visible":true,"origin":"","legend":"\u003cp\u003eBox plot illustrating first-person VMIQ-2 scores across exercise frequency levels. Participants who exercise once a week or more demonstrate significantly better motor imagery ability than those who have no exercise. Asterisks indicate significance levels: *p \u0026lt; .05, **p \u0026lt; .01.\u003c/p\u003e","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7676103/v1/d1efe01134817bfe7635251c.jpeg"},{"id":93240499,"identity":"c7272748-a7c9-491c-9aec-465afc60bb2e","added_by":"auto","created_at":"2025-10-10 14:46:13","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":75868,"visible":true,"origin":"","legend":"\u003cp\u003eBox plot showing third-person VMIQ-2 scores across exercise frequency levels. Significant differences are observed between those who have no exercise and those who exercise once a week, with the latter showing better motor imagery ability. Asterisks indicate significance levels: *p \u0026lt; .05, **p \u0026lt; .01.\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7676103/v1/71ac9e2a7df1ca30b9492b8b.png"},{"id":94256639,"identity":"065ce247-f0c1-4f7b-90a3-74d26607c516","added_by":"auto","created_at":"2025-10-24 07:54:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1310329,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7676103/v1/a62000e5-4e9f-4524-bbfa-aa6883005519.pdf"},{"id":93240489,"identity":"55271810-d518-4a9d-b0aa-fdc08df9d2c0","added_by":"auto","created_at":"2025-10-10 14:46:13","extension":"xlsx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":15871,"visible":true,"origin":"","legend":"","description":"","filename":"ageVMIQrawdata.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7676103/v1/4e06bf3fa287767b4dbfedec.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Exercise Moderates Age-Related Decline in Motor Imagery Vividness Across the Lifespan","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMotor imagery\u0026mdash;defined as the mental simulation of movement without overt execution [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u0026mdash;is increasingly recognized across disciplines such as sports science, cognitive neuroscience, and rehabilitation medicine for its potential to enhance motor learning, athletic performance, and recovery. Neuroimaging studies reveal that motor imagery engages many of the same neural circuits as actual motor execution, including the premotor cortex, supplementary motor area, and cerebellum [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. This neural overlap allows motor imagery to act as a functional proxy for physical practice, particularly valuable in contexts such as injury recovery or motor preparation.\u003c/p\u003e\u003cp\u003eDespite its established benefits, individual differences in motor imagery vividness remain insufficiently understood. Variables such as age, exercise experience, exercise frequency, and gender have been posited as potential moderators, but findings remain inconsistent [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Several theoretical frameworks offer insight into how these variables might influence motor imagery ability. For instance, the Simulation Theory of Motor Cognition suggests that motor imagery and execution rely on shared neural systems crucial for motor planning and control [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Consequently, age-related declines in sensorimotor functioning could plausibly impair imagery ability.\u003c/p\u003e\u003cp\u003eEmbodied Cognition further proposes that cognitive processes are grounded in bodily experiences [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], supporting the notion that physical activity may enhance imagery ability. Additionally, the Neurovisceral Integration Model highlights the interaction between cognitive and autonomic systems, suggesting that exercise may support motor imagery through neuroplastic and physiological mechanisms [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAge-related deterioration in motor and cognitive functions is well established [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] and may extend to motor imagery abilities. Specifically, age-related declines in proprioception and visuomotor coordination\u0026mdash;both essential for vivid motor imagery\u0026mdash;have been linked to reductions in imagery vividness [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Since motor imagery can be experienced from a first-person (internal) or third-person (external) perspective, it is plausible that sensory declines disproportionately affect first-person imagery due to its greater reliance on internal sensorimotor feedback [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. However, few studies have directly compared age effects across imagery perspectives, representing a significant gap in the literature [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eWhile elite athletes often display superior motor imagery abilities, recent research suggests that even moderate levels of physical activity can yield cognitive and sensorimotor benefits, potentially enhancing motor imagery vividness [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Nevertheless, little is known about how exercise experience and frequency affect imagery ability in general populations, particularly across different age groups.\u003c/p\u003e\u003cp\u003eGender differences in motor imagery remain equivocal. Although some studies report male advantages in spatial aspects of imagery [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], others find no differences when controlling for factors such as age and exercise [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. It is also possible that any gender effects are perspective-specific, with first-person imagery\u0026mdash;being more sensorimotor-dependent\u0026mdash;exhibiting greater variability than third-person imagery [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eGiven these considerations, the present study aims to (1) examine age-related differences in motor imagery vividness, (2) compare effects across first- and third-person perspectives, and (3) assess how exercise habits and gender relate to imagery ability. We hypothesize that motor imagery vividness will decline with age, particularly for first-person imagery, and that greater exercise experience and frequency will be associated with more vivid imagery.\u003c/p\u003e"},{"header":"Method","content":"\u003cp\u003e\u003cstrong\u003eParticipants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 150 participants (Mage = 43.65 years, SD = 18.72, range = 18\u0026ndash;80 years) were recruited for this study. The sample size was determined via a priori power analysis using G*Power 3.1. Assuming a medium effect size (f\u0026sup2; = 0.15) for multiple regression analyses with four predictors, \u0026alpha; = .05, and desired power (1\u0026minus;\u0026beta;) = 0.90, the required sample size was calculated to be 108. To account for potential attrition and allow for subgroup comparisons, 150 participants were recruited.\u003c/p\u003e\n\u003cp\u003eParticipants were stratified into three age groups of equal size: young (18\u0026ndash;30 years, n = 50), middle-aged (31\u0026ndash;55 years, n = 50), and older adults (56\u0026ndash;80 years, n = 50). Gender distribution was approximately equal (48% male, 52% female).\u003c/p\u003e\n\u003cp\u003eRecruitment was conducted entirely online through advertisements shared via email, social media, and online communities targeting English-speaking populations in Japan and the United Kingdom. All participants were fluent English speakers, and the entire study, including consent, instructions, and questionnaires, was conducted in English to maintain linguistic consistency. Participants resided in Japan completed the study remotely via an online survey platform in a self-paced manner.\u003cbr\u003e\u0026nbsp;Inclusion criteria required participants to have no self-reported history of neurological, psychiatric, or musculoskeletal disorders that could affect motor or cognitive function. Exclusion criteria included past or current diagnoses of such conditions or recent injuries affecting movement. Prior experience with motor imagery training (e.g., as athletes or dancers) was not systematically assessed, which is acknowledged as a limitation.\u003cbr\u003e\u0026nbsp;All participants provided informed consent before participation. The study protocol was approved by the Ethics Committee of Eightis Co., Ltd. (Approval No. 043) and was conducted in accordance with the Declaration of Helsinki. Participants were informed of their right to withdraw at any time without penalty, and all data were anonymized before analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeasures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVividness of Movement Imagery Questionnaire-2 (VMIQ-2)\u003c/strong\u003e Motor imagery vividness was assessed using a 12-item modified version of the VMIQ-2, focusing on visual imagery only. Six items assessed first-person perspective imagery (imagining performing a movement through one\u0026rsquo;s own eyes) and six items assessed third-person perspective imagery (imagining observing oneself performing the movement). The kinaesthetic subscale was excluded in line with previous studies emphasizing visual motor imagery in aging. This should be considered when comparing results across studies.\u003c/p\u003e\n\u003cp\u003eEach item was rated on a 5-point Likert scale: 1 = Perfectly clear and vivid as normal vision 2 = Clear and reasonably vivid 3 = Moderately clear and vivid 4 = Vague and dim 5 = No image at all, only \u0026quot;knowing\u0026quot; the movement\u003c/p\u003e\n\u003cp\u003eLower scores indicate more vivid imagery. The shortened VMIQ-2 version demonstrated good internal consistency and validity (Cronbach\u0026rsquo;s \u0026alpha; \u0026gt; 0.90 in this sample).\u003c/p\u003e\n\u003cp\u003eParticipants were asked to vividly imagine 12 common whole-body movements (e.g., walking, bending, jumping, reaching), which were general and not tailored to participants\u0026rsquo; specific training backgrounds.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDemographic and Exercise Questionnaire\u003c/strong\u003e Participants also completed a demographic questionnaire including age, gender, and country of residence. Physical activity habits were assessed using two items:\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eExercise Experience: Binary (Yes/No) \u0026mdash; \u0026quot;Do you currently engage in regular physical exercise or sports (at least once per week)?\u0026quot;\u003c/li\u003e\n \u003cli\u003eExercise Frequency: Categorical \u0026mdash; \u0026quot;How often do you engage in physical exercise or sports?\u0026quot;\u003c/li\u003e\n \u003cli\u003e2\u0026ndash;3 times or more per week\u003c/li\u003e\n \u003cli\u003eOnce a week\u003c/li\u003e\n \u003cli\u003eRarely or never\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eThese self-report items served as independent variables in analyses. However, as they did not capture exercise type, duration, or intensity, this limitation is acknowledged.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProcedure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted between February and April 2024. After reviewing an online information sheet, participants provided digital informed consent. They then completed the demographic and exercise questionnaires, followed by the VMIQ-2, on a secure online platform. Participants were instructed to imagine each movement as vividly as possible from both perspectives. All items were self-paced, and short breaks between sections were suggested to reduce fatigue. After completing the questionnaires, participants were debriefed and thanked for their participation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll analyses were conducted using SPSS Statistics Version 26.0 (IBM Corp., Armonk, NY, USA). A significance level of p \u0026lt; .05 was used for all two-tailed tests. Specific analyses included:\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eDescriptive Statistics: Means and standard deviations were calculated for age, VMIQ-2 scores, and exercise variables.\u003c/li\u003e\n \u003cli\u003eCorrelation Analysis: Pearson correlation coefficients were computed to assess associations between age and VMIQ-2 scores (first-person and third-person). Fisher\u0026rsquo;s r-to-z transformation was used to compare correlation magnitudes.\u003c/li\u003e\n \u003cli\u003eIndependent Samples t-Tests: Used to compare VMIQ-2 scores between genders and between participants with or without exercise experience. Cohen\u0026rsquo;s d was reported as an effect size.\u003c/li\u003e\n \u003cli\u003eOne-Way ANOVA: Used to examine group differences in VMIQ-2 scores across age and exercise frequency categories. Partial eta-squared (\u0026eta;\u0026sup2;p) was reported. Tukey\u0026rsquo;s HSD tests were used for post-hoc comparisons, with Benjamini\u0026ndash;Hochberg correction applied to control for false discovery rate.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eMultiple Linear Regression:\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Predictors of VMIQ-2 scores were examined using \u003cstrong\u003estandard multiple regression\u003c/strong\u003e with the Enter method, in which all variables were entered simultaneously in a single block. Predictors included age, gender, exercise experience, and exercise frequency. Standardized beta coefficients (\u0026beta;) and R\u0026sup2; were reported.\u003c/li\u003e\n \u003cli\u003eModeration Analysis: To test whether exercise frequency moderated the effect of age on VMIQ-2 scores, hierarchical regressions were conducted. Age and frequency were entered in Step 1; the interaction term (age \u0026times; frequency) was added in Step 2. Separate models were used for each imagery perspective.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u003cstrong\u003eData Handling and Assumptions\u003c/strong\u003e\u003c/p\u003e\n\u003cul class=\"decimal_type\"\u003e\n \u003cli\u003eOutliers were screened using boxplots and z-scores (|z| \u0026gt; 3.29).\u003c/li\u003e\n \u003cli\u003eMissing data were managed using pairwise deletion.\u003c/li\u003e\n \u003cli\u003eNormality was assessed via Shapiro\u0026ndash;Wilk tests and Q\u0026ndash;Q plots.\u003c/li\u003e\n \u003cli\u003eHomogeneity of variance was tested using Levene\u0026rsquo;s test.\u003c/li\u003e\n \u003cli\u003eLinearity and homoscedasticity were checked via residual plots.\u003c/li\u003e\n \u003cli\u003eMulticollinearity was evaluated using Variance Inflation Factors (VIF); all values were below 2.0, indicating no concern. However, due to theoretical overlap between age and exercise frequency, their effects were interpreted with caution.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eNo major violations of parametric test assumptions were observed.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eDescriptive Statistics\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;The final sample consisted of 150 participants (72 males, 78 females) with a mean age of 43.65 years (SD = 18.72). Table 1 presents the descriptive statistics for VMIQ-2 scores, age, and exercise frequency across the three age groups.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003eDescriptive statistics of VMIQ-2 first-person and third-person imagery scores, actual age, and exercise frequency across three age groups. Values represent means (M) and standard deviations (SD). Exercise frequency is coded on an ordinal scale (0 = none, 1 = once a week or more).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003eAge Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003eVMIQ-2 1st-Person (M\u0026plusmn;SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003eVMIQ-2 3rd-Person (M\u0026plusmn;SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003eAge (M\u0026plusmn;SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003eExercise Frequency (M\u0026plusmn;SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003eYoung (18\u0026ndash;30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e14.90 \u0026plusmn; 2.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e13.74 \u0026plusmn; 1.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e24.54 \u0026plusmn; 3.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e0.46 \u0026plusmn; 0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003eMiddle-aged (31\u0026ndash;55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e23.58 \u0026plusmn; 3.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e16.08 \u0026plusmn; 2.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e43.12 \u0026plusmn; 6.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e0.36 \u0026plusmn; 0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003eOlder (56+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e33.04 \u0026plusmn; 3.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e19.08 \u0026plusmn; 3.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e65.52 \u0026plusmn; 7.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e0.42 \u0026plusmn; 0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAll analyses report observed values without imputation. Standard deviations indicate variability within each age group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrelation Analysis\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Pearson correlation coefficients revealed significant positive correlations between age and VMIQ-2 scores for both first-person (r = 0.42, 95% CI [0.28, 0.54], p \u0026lt; .001) and third-person (r = 0.35, 95% CI [0.20, 0.48], p \u0026lt; .001) perspectives, indicating poorer motor imagery ability with increasing age (see Figure 1). Fisher\u0026apos;s r-to-z transformation showed that the correlation was significantly stronger for first-person imagery (z = 1.98, p = .048).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAge Group Differences in Motor Imagery Ability\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;One-way ANOVAs revealed significant differences in VMIQ-2 scores across age groups for both first-person [F(2, 147) = 15.32, p \u0026lt; .001, \u0026eta;\u0026sup2;p = 0.17] and third-person [F(2, 147) = 12.76, p \u0026lt; .001, \u0026eta;\u0026sup2;p = 0.15] perspectives. Post-hoc comparisons using Tukey\u0026apos;s HSD test with Benjamini-Hochberg correction showed significant differences between all age groups (all adjusted ps \u0026lt; .017) (see Figures 2 and 3). Older adults showed the highest VMIQ-2 scores (poorest imagery ability), followed by middle-aged and young adults.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExercise and Motor Imagery Ability\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Independent samples t-tests showed that participants with exercise experience demonstrated significantly lower VMIQ-2 scores for both first-person [t(148) = -3.00, p = .003, d = 0.51] and third-person [t(148) = -4.29, p \u0026lt; .001, d = 0.82] perspectives compared to those without exercise experience (see Figures 4 and 5).\u003c/p\u003e\n\u003cp\u003eOne-way ANOVAs revealed that VMIQ-2 scores significantly differed by exercise frequency for third-person imagery [F(1, 148) = 30.68, p \u0026lt; .001, \u0026eta;\u0026sup2;p = .17], but not for first-person imagery [F(1, 148) = 2.26, p = .135, \u0026eta;\u0026sup2;p = .02]. Post-hoc analysis using Tukey\u0026apos;s HSD test confirmed significant differences in third-person imagery scores between frequency groups (see Figures 6 and 7).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMultiple Regression Analysis\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Multiple regression analyses were conducted to predict VMIQ-2 scores. For first-person imagery, the model was significant [R\u0026sup2; = .75, F(4, 145) = 110.30, p \u0026lt; .001]. Age was a significant predictor (\u0026beta; = 0.38, p \u0026lt; .001), while exercise frequency (\u0026beta; = -0.15, p = .074), exercise experience (\u0026beta; = -0.12, p = .297), and gender (\u0026beta; = 0.06, p = .188) were not.\u003c/p\u003e\n\u003cp\u003eFor third-person imagery, the model was also significant [R\u0026sup2; = .51, F(4, 145) = 37.48, p \u0026lt; .001], with age (\u0026beta; = 0.11, p \u0026lt; .001) and exercise frequency (\u0026beta; = -0.28, p \u0026lt; .001) as significant predictors. Exercise experience (\u0026beta; = -0.03, p = .717) and gender (\u0026beta; = 0.04, p = .265) were not significant predictors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eModeration Analysis\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Moderation analyses tested whether the effect of age on motor imagery was moderated by exercise frequency. For first-person imagery, the interaction term (age \u0026times; exercise frequency) was significant [F(1, 146) = 13.37, p \u0026lt; .001, ∆R\u0026sup2; = 0.03], indicating that exercise frequency buffered the negative impact of age on motor imagery vividness. For third-person imagery, the interaction was also significant [F(1, 146) = 5.06, p \u0026lt; .001, ∆R\u0026sup2; = 0.01].\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study examined how age, exercise habits, and gender relate to motor imagery vividness, focusing on differences between first- and third-person perspectives. Our findings indicate that age is significantly associated with reduced imagery vividness, with older adults reporting higher VMIQ-2 scores, consistent with previous research demonstrating age-related declines in sensorimotor and cognitive functioning [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. These results align with the Simulation Theory, which posits that imagery and motor execution share neural resources [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. As sensorimotor systems deteriorate with age, the ability to mentally simulate actions may become less vivid.\u003c/p\u003e\u003cp\u003eThe observed decline was particularly pronounced in first-person imagery, likely reflecting its greater dependence on internal sensory and proprioceptive inputs [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. These findings support theories of Embodied Cognition, which suggest that cognitive representations, including motor imagery, are grounded in bodily experience [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. As first-person imagery requires sensorimotor grounding, it may be more susceptible to age-related physiological changes.\u003c/p\u003e\u003cp\u003eRegular exercise was associated with improved imagery vividness, consistent with previous findings that physical activity enhances cognitive and motor functions [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. These results also support the Neurovisceral Integration Model, which describes how physical activity may enhance cognitive-affective regulation through autonomic pathways [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Moreover, individuals with higher exercise frequency exhibited better imagery ability than those who exercised less, regardless of age group. This echoes prior evidence that motor imagery can be improved through repeated physical and mental practice [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eGender differences were found only in first-person imagery, with men scoring slightly better than women. Although some studies report spatial ability advantages in males [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], these effects are often small and may be moderated by factors such as experience and training [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The lack of a significant difference in third-person imagery suggests that visual-spatial strategies may be used more equally across genders when proprioceptive input is less central.\u003c/p\u003e\u003cp\u003eWhile these results offer valuable insights, the predictive models used in this study explained a substantial proportion of variance in imagery scores (R\u0026sup2; \u0026asymp; 0.51\u0026ndash;0.75).\u003c/p\u003e\u003cp\u003eTherefore, the relationships observed, though statistically significant, should not be overinterpreted as strong associations. These findings should be viewed as indicative rather than conclusive, particularly given the reliance on self-report measures.\u003c/p\u003e\u003cp\u003eAlthough this cross-sectional study cannot establish causality, the findings suggest that regular physical activity may help preserve motor imagery vividness with age. However, it is equally plausible that individuals with more vivid imagery are more inclined to engage in exercise. Future longitudinal or experimental studies are needed to disentangle these causal pathways. The suggestion that older adults might benefit from gradually transitioning from third-person to first-person imagery techniques is speculative but grounded in theoretical models of sensorimotor engagement [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] and warrants further empirical investigation.\u003c/p\u003e\u003cp\u003eThese findings have practical implications for designing cognitive-motor training programs targeting older populations. Encouraging regular exercise and tailoring imagery interventions to leverage third-person strategies initially may support aging individuals in maintaining effective motor representations.\u003c/p\u003e\u003cp\u003eLastly, this study relied solely on subjective measures of motor imagery, such as the VMIQ-2. Although widely validated, such tools may not fully capture actual imagery ability. Objective measures like mental chronometry or neuroimaging could complement self-reports in future research to provide a more comprehensive assessment of imagery function [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll procedures performed in the study involving human participants were in accordance with the ethical standards of the institutional and national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. All experimental protocols were approved by\u0026nbsp;the Ethics Committee of Eightis Co., Ltd. (Approval No. 043).\u0026nbsp;Informed consent was obtained from all individual participants included in the study.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results presented in this manuscript have not been published elsewhere, nor are they under consideration (from any of the authors) by another publisher.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;The data supporting the findings of this study are available as supplementary material attached to this submission. Researchers are welcome to access the dataset for further analysis or replication of the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u0026nbsp;\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;The authors declare no financial or non-financial competing interests related to this work. N.Y. is employed by Eightis Co., Ltd.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe project did not receive any funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u0026rsquo;s contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespond author was responsible for all aspects of this study, including conceiving the research idea, designing the study, collecting and analyzing the data, interpreting the results, and writing the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBarsalou, L. W. (2008). Grounded cognition. Annual Review of Psychology, 59, 617\u0026ndash;645. https://doi.org/10.1146/annurev.psych.59.103006.093639\u003c/li\u003e\n\u003cli\u003eHardwick, R. M., Caspers, S., Eickhoff, S. B., \u0026amp; Swinnen, S. P. (2018). Neural correlates of motor imagery, action observation, and movement execution: A comparison across quantitative meta-analyses. NeuroImage, 179, 30\u0026ndash;39. https://doi.org/10.1016/j.neuroimage.2018.05.083\u003c/li\u003e\n\u003cli\u003eH\u0026eacute;tu, S., Gregoire, M., Saimpont, A., Coll, M. P., Eug\u0026egrave;ne, F., Michon, P. E., \u0026amp; Jackson, P. L. (2013). The neural network of motor imagery: An ALE meta-analysis. Neuroscience \u0026amp; Biobehavioral Reviews, 37(5), 930\u0026ndash;949. https://doi.org/10.1016/j.neubiorev.2013.03.017\u003c/li\u003e\n\u003cli\u003eJeannerod, M. (2001). Neural simulation of action: A unifying mechanism for motor cognition. NeuroImage, 14(1), S103\u0026ndash;S109. https://doi.org/10.1006/nimg.2001.0832\u003c/li\u003e\n\u003cli\u003eThayer, J. F., \u0026amp; Lane, R. D. (2000). A model of neurovisceral integration in emotion regulation and dysregulation. Journal of Affective Disorders, 61(3), 201\u0026ndash;216. https://doi.org/10.1016/S0165-0327(00)00338-4\u003c/li\u003e\n\u003cli\u003eSalthouse, T. A. (2010). Selective review of cognitive aging. Journal of the International Neuropsychological Society, 16(5), 754\u0026ndash;760. https://doi.org/10.1017/S1355617710000706\u003c/li\u003e\n\u003cli\u003eIsaac, A., Marks, D. F., \u0026amp; Russell, D. G. (2020). Anomalies in imagery research: Reply to the reviews by Richardson and by Watts. British Journal of Psychology, 71(2), 289\u0026ndash;298. https://doi.org/10.1111/j.2044-8295.1980.tb01739.x\u003c/li\u003e\n\u003cli\u003eLorey, B., Bischoff, M., Pilgramm, S., Stark, R., Munzert, J., \u0026amp; Zentgraf, K. (2009). The embodied nature of motor imagery: The influence of posture and perspective. Experimental Brain Research, 194(2), 233\u0026ndash;243. https://doi.org/10.1007/s00221-008-1686-7\u003c/li\u003e\n\u003cli\u003eSchott, N. (2021). Age-related differences in motor imagery: Comparing motor imagery skills across the lifespan. Journal of Motor Behavior, 53(1), 29\u0026ndash;41. https://doi.org/10.1080/00222895.2020.1809795\u003c/li\u003e\n\u003cli\u003eJeannerod, M. (1994). The representing brain: Neural correlates of motor intention and imagery. Behavioral and Brain Sciences, 17(2), 187\u0026ndash;202. https://doi.org/10.1017/S0140525X00034026\u003c/li\u003e\n\u003cli\u003eLorey, B., Stark, R., Munzert, J., Zentgraf, K., \u0026amp; Vaitl, D. (2022). How age and gender influence motor imagery ability: A study on young and older adults. Psychology of Sport and Exercise, 58, 102042. https://doi.org/10.1016/j.psychsport.2022.102042\u003c/li\u003e\n\u003cli\u003eHillman, C. H., Erickson, K. I., \u0026amp; Kramer, A. F. (2008). Be smart, exercise your heart: Exercise effects on brain and cognition. Nature Reviews Neuroscience, 9(1), 58\u0026ndash;65. https://doi.org/10.1038/nrn2298\u003c/li\u003e\n\u003cli\u003eMizuguchi, N., Kanosue, K., \u0026amp; Nakata, H. (2019). Neural correlates involved in the processing of motor imagery and motor execution of skilled movements. Frontiers in Human Neuroscience, 13, 150. https://doi.org/10.3389/fnhum.2019.00150\u003c/li\u003e\n\u003cli\u003eSchuster, C., Hilfiker, R., Amft, O., Scheidhauer, A., Andrews, B., Butler, J., Kischka, U., \u0026amp; Ettlin, T. (2011). Best practice for motor imagery: A systematic literature review on motor imagery training elements in five different disciplines. BMC Medicine, 9(1), 75. https://doi.org/10.1186/1741-7015-9-75\u003c/li\u003e\n\u003cli\u003eColuccia, E., \u0026amp; Louse, G. (2004). Gender differences in spatial orientation: A review. Journal of Environmental Psychology, 24(3), 329\u0026ndash;340. https://doi.org/10.1016/j.jenvp.2004.08.006\u003c/li\u003e\n\u003cli\u003eMulder, T., de Vries, S., \u0026amp; Zijlstra, S. (2007). Observation, imagination and execution of an effortful movement: More evidence for a central explanation of motor imagery. Experimental Brain Research, 179(4), 587\u0026ndash;594. https://doi.org/10.1007/s00221-006-0815-4\u003c/li\u003e\n\u003cli\u003eMoran, A., Guillot, A., MacIntyre, T., \u0026amp; Collet, C. (2012). Re-imagining motor imagery: Building bridges between cognitive neuroscience and sport psychology. British Journal of Psychology, 103(2), 224\u0026ndash;247. https://doi.org/10.1111/j.2044-8295.2011.02068.x\u003c/li\u003e\n\u003cli\u003eGuillot, A., Di Rienzo, F., MacIntyre, T., Moran, A., \u0026amp; Collet, C. (2021). Imagining is not doing but involves specific motor representations: A review of experimental data related to motor inhibition. Frontiers in Human Neuroscience, 15, 1\u0026ndash;13. https://doi.org/10.3389/fnhum.2021.617895\u003c/li\u003e\n\u003cli\u003eBestmann, S., de Berker, A. O., \u0026amp; Bonaiuto, J. (2021). Understanding the neural mechanisms of motor imagery: A perspective on multiple motor control models. Frontiers in Human Neuroscience, 15, 1\u0026ndash;9. https://doi.org/10.3389/fnhum.2021.601834\u003c/li\u003e\n\u003cli\u003eVoyer, D., Voyer, S., \u0026amp; Bryden, M. P. (1995). Magnitude of sex differences in spatial abilities: A meta-analysis and consideration of critical variables. Psychological Bulletin, 117(2), 250\u0026ndash;270. https://doi.org/10.1037/0033-2909.117.2.250\u003c/li\u003e\n\u003cli\u003eCumming, J., \u0026amp; Williams, S. E. (2012). The role of imagery in performance. In S. Murphy (Ed.), The Oxford handbook of sport and performance psychology (pp. 213\u0026ndash;232). Oxford University Press.\u003c/li\u003e\n\u003cli\u003eDi Rienzo, F., Blache, Y., Kanthack, T. F. D., Monteil, K., Collet, C., \u0026amp; Guillot, A. (2015). Short-term effects of integrated motor imagery practice on muscle activation and force performance. Neuroscience, 305, 146\u0026ndash;156. https://doi.org/10.1016/j.neuroscience.2015.07.016\u003c/li\u003e\n\u003cli\u003eVoelcker-Rehage, C., \u0026amp; Niemann, C. (2021). Structural and functional brain changes related to different types of physical activity across the lifespan. Neuroscience \u0026amp; Biobehavioral Reviews, 127, 47\u0026ndash;62. https://doi.org/10.1016/j.neubiorev.2021.03.016\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"motor imagery, aging, exercise, Exercise frequency, VMIQ-2","lastPublishedDoi":"10.21203/rs.3.rs-7676103/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7676103/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMotor imagery, the mental simulation of movement without actual execution, plays a vital role in motor learning, performance, and rehabilitation. This study investigated the effects of age, exercise experience, exercise frequency, and gender on motor imagery vividness using the Vividness of Movement Imagery Questionnaire-2 (VMIQ-2). A total of 150 participants aged 18 to 80 completed the questionnaire online. Results showed that increasing age was significantly associated with reduced imagery vividness for both first-person (r\u0026thinsp;=\u0026thinsp;0.42) and third-person (r\u0026thinsp;=\u0026thinsp;0.35) perspectives, with a stronger effect on the first-person perspective. Regular exercise experience and frequency were positively associated with vividness scores across both perspectives. Regression analyses showed that age and exercise frequency were significant predictors of VMIQ-2 scores, explaining 51% of the variance in third-person and 75% in first-person imagery. Moderation analysis revealed that exercise frequency significantly moderated the relationship between age and both first-person (ΔR\u0026sup2; = 0.03, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) and third-person (ΔR\u0026sup2; = 0.01, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) imagery, suggesting that regular exercise may help mitigate age-related decline in motor imagery ability. No significant gender differences were observed after controlling for age and exercise. These findings support theoretical frameworks such as embodied cognition and the simulation theory of motor cognition, emphasizing the importance of regular physical activity in maintaining motor imagery ability across the lifespan. The study provides practical implications for designing age-appropriate motor imagery interventions in sports and rehabilitation contexts.\u003c/p\u003e","manuscriptTitle":"Exercise Moderates Age-Related Decline in Motor Imagery Vividness Across the Lifespan","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-10 14:46:08","doi":"10.21203/rs.3.rs-7676103/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b2560d24-bea3-469b-b1dd-46a98185154d","owner":[],"postedDate":"October 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-24T07:53:58+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-10 14:46:08","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7676103","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7676103","identity":"rs-7676103","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}