Since life expectancy is increasing across the globe, it is important to identify factors that impact the quality of ageing. In addition to being largely viewed as a positive consequence of medical, social, and economic advancements over disease, global ageing also presents unique challenges and opportunities for our healthcare and social systems. World Health Organization (WHO) defines healthy ageing (HA) as developing and maintaining functional ability to enable well-being in old age. This definition of HA includes a state of complete physical, mental, and social well-being, not just the absence of diseases or infirmities.
Atallah et al.
[2] have found several potentially modifiable lifestyle factors that could influence the quality of ageing, such as smoking status, physical activity, and diet. Physical activity has been shown to affect brain plasticity, improving cognition and well-being
[3][4][5][6]. Experimental and clinical studies have reported that physical activity induces structural and functional changes in the brain, determining enormous biological and psychological benefits
[4][7][8]. Further, increasing physical activity and sport practice seems to prevent cognitive decline associated with ageing, to reduce the risk of developing dementia, and to prevent deterioration in executive function
[9][10][11]. Hence, maintaining an “enriched lifestyle” until middle age has a positive effect on cognitive function
[12]. Combined with many other experiences, physical activity provides a “reserve”-like advantage that maintains cognitive function in old age
[13].
2. Is Motor Imagery preserved in healthy elderly?
2.1. Motor Imagery Components
It is generally agreed that MI is a multidimensional construct. Thus, it is crucial to consider all of its different features when studying its age-related changes. To our knowledge, few studies have dealt with the investigation of different facets of MI and their changes during ageing. Moreover, most of these papers show conflicting results and heterogeneous methodologies. Later we will address the different methodology used in these studies, while in this section we will discuss the scientific evidence regarding the evolution of each MI component with age.
The term MI vividness is used to indicate the ability to generate vivid motor images and sensations in the mind
[17]. Scientific literature is divided on the evolution of MI vividness with age. This is largely due to the different aspects of this MI component that are taken into account by these studies. When assessing MI vividness, individuals can mentally simulate movements from a first-person perspective (i.e., as if one is the actor of the action) or from a third-person perspective (i.e., as if one is a spectator of the action). When individuals imagine a motor action in first-person perspective, they mostly experience kinaesthetic sensations, as if they were actually performing the action; in third-person perspective, MI visual representations are the most significant, as if the individual were watching themselves or others perform the action
[18]. While both modalities (kinaesthetic and visual) are investigated in studies on MI vividness, they are also not always differentiated from one another. Of all our selected studies, two reported that both young, middle-aged, and older adults showed good MI vividness skills. However, while in the young and middle-aged adults significantly higher visual than kinaesthetic abilities were found, this visual dominance was no longer observed in the older
[19][20]. The latter result was not replicated by the other two studies, where older adults’ MI vividness skills seemed to be preserved. In both studies, their performance was equivalent to that of the young in either kinaesthetic or visual mode
[17][21]. A final study showed that older adults (aged between 70 and 79) showed a general decline in MI vividness. Nevertheless, MI vividness skills were comparable between young participants and middle-aged or older (aged between 60 and 69), showing no differences between kinaesthetic and visual modalities. Interestingly, the decrease in physical activity, especially in the older adults, led to lowered kinaesthetic input, that compromised MI abilities
[22].
MI timing component refers to the duration of a movement during a mental simulation. According to the literature, the amount of time required to imagine a motor action is expected to be close to the one needed to execute it
[23]. Three of the studies that investigated age-related differences in MI timing, are in agreement in reporting a relative retention of this skill in healthy older
[17][19][22] Yet, other findings suggest that while in young adults the temporal congruence of MI (i.e., the difference between the movement execution and imagination time) is not affected by movements’ constraints, in older adults this skill is not always maintained when they imagine constrained movements. In a study by
[24], it was found that temporal congruence between imagined and executed movements sequence decreased with age. In this case, participants had to imagine and execute a series of fast and accurate arm movements between targets of decreasing sizes. This result was replicated in a similar study by
[25], where, however, it was also shown that visual cues could improve MI performance in older, even if the motor sequence was composed by constrained movements. It is interesting to note that, again, physical activity could represent a protective factor for the maintenance of MI timing skills in the older. Several studies have already proven that MI skills are better developed in individuals who regularly engage in physical activity
[14]. Evidence on active and sedentary older populations is needed to prove this beneficial role of physical activity in MI timing skills.
MI controllability refers to the ability to manipulate a mental representation of the movement
[17]. Among our selected studies, only two assessed MI controllability. In both studies, a deterioration of this skill with the advancing of age was shown
[17][22].
Lastly, MI accuracy was assessed by three studies. While two of these reported poorer performance in older
[26][27], one reported no differences between young and older individuals
[28]. The heterogeneity of the results concerning this MI component serves three possible explanations: (1) the studies used tasks that were too different in terms of their difficulty; (2) the studies examined young populations against highly older populations (over 70); (3) the majority of the tasks used in these studies failed to consider the possible impact of other cognitive factors, like planning, problem-solving, or depth perception.
Most of our selected studies have highlighted that the maintenance of specific cognitive abilities is crucial for the preservation of MI abilities in old age. Among these skills, working memory seems crucial to MI vividness and timing
[17][19][22]; mental rotation processes and cognitive flexibility are associated with MI controllability
[28]; planning and problem-solving skills appear fundamental for MI accuracy
[27].
However, only one study by Schott
[22] has actually evaluated the mediating effect of working memory on MI components during ageing. Specifically, findings from this study suggest that ageing in itself is not a potentially impairing factor for MI, rather it is the decline in cognitive functions, like working memory and attention, together with changes in activation patterns of several brain regions that can result in a loss of vividness and timing of MI.
In conclusion, it must be stressed how most of the studies analysed so far failed to provide a sample that was adequately representative of the healthy older population. Some studies used samples with individuals who were too old, others with those who were too young. It is essential to increase the number of studies that consider the ‘young-old’ population (aged from 60 to 69 years old), as it seems that in that age range, some MI components are nearly always preserved.
2.2. Heterogeneity in Methodology
Self-report questionnaires and behavioural tasks have provided most of the evidence on MI in healthy ageing. Our research showed that in the last decade, nine studies have combined both of these methods to study MI in older populations.
When assessing vividness the Kinaesthetic and Visual Imagery Questionnaire (KVIQ) [
30] is the most used tool. Ths 10-item self-report questionnaire assesses individuals' ability to vividy imagine 10 basic movement.
As for MI controllability e accuracy, most of the studies used behavioral tasks to assess age-realted changes in MI. One of the most used paradigm was the Controllability of Motor Imagery (CMI)
[22]. This test evaluates the ability to supplement, transform, and reconstruct one’s internally visualized body schema in response to verbal instructions. In this study, two conditions were performed: a recognition test (controllability of body schema) and a regeneration test (ability to transform visual imagery). Participants had to perform 10 sets of trials with six consecutive instructions. In each trial, they were asked to imagine that they were moving their body parts according to the verbal instructions. On the regeneration test, the participants had to actually execute the final position immediately after the instructions were completed. On the recognition test, they were required to select among five pictures the one that fit the imagery they had.
Mi timing was mostly studied through a combination of neuroimaging and behavioral paradigms. A large body of literature has documented that changes in cognitive function associated with normal ageing are accompanied by age-related changes in brain activity [33]. As for motor functions, neuroimaging studies have demonstrated that older individuals’ brain activation patterns differ when executing both simple and complex movements [34]. Motor Imagery-related neuroimaging studies are based on the assumption that motor imagery and motor execution depend on partially overlapping neural systems. Dorsal premotor cortex, supplementary motor area, ventral lateral premotor cortex, intraparietal sulcus cortex, and supramarginal gyrus all belong to this shared neural network [35]. It appears that most fMRI studies agree that executive control, sensory-motor, and visuospatial brain networks are hyperactive in healthy older, during MI tasks. Zapparoli et al. [35] have used fMRI in combination with a chronometric test to assess MI timing skills in both young and older participants. They found significant neurofunctional differences between young and older subjects during the MI task. Specifically, they found an hyperactivation of older participants’ brains, primarily in the occipito-temporo-parietal areas. Neyland et al. [45] used graph theory and network community structured analysis to find differences in MI-related brain connectivity between young and older individuals. Their findings showed that older individuals were characterized by a decreased connectivity in both default mode network (DMN) and sensorimotor network (SMN) during an MI task. DMN decreased connectivity was expected, since this network was originally identified as a collection of regions that show coordinated decreases in activity, during goal-directed and attention-demanding tasks. On the other hand, SMN decreased connectivity was in contrast with previous studies supporting the compensation hypothesis [40]. The dorsal attention network (DAN) showed an increased connectivity in elderlies, during MI task. Most researchers agree that the DAN facilitates visuospatial attention and short-term memory. There is also recent evidence that DAN plays a role in spatial orientation. However, these results should be interpreted with caution, since the sample of older people used was composed of over 70-year-olds. Finally, a study by Burianova et al. [47] used a combination of fMRI and magnetoencephalography (MEG) to assess MI skills in older individuals. The use of MEG allowed them to analyse GABAergic transmission. The results were not consistent with the compensatory hypothesis, showing instead that stronger connectivity to bilateral primary motor cortex in the older group was negatively correlated with their execution performance, but not their imagination one. Overall, an increase in GABA levels was detected. This was due to ageing and could significantly impact the effectiveness of neural communication within the motor system.
3. Conclusions
The present review is one of the most recent attempts to discuss insights concerning MI age-related changes. Even though MI-based training has therapeutic and rehabilitation potential, research on MI in the older has stalled despite technological and scientific innovations. We have found that heterogeneity in the experimental protocols, as well as the use of populations with unrepresentative age, is making it challenging to draw unambiguous conclusions about MI skills preservation. Self-report and behavioural task have shown that some MI components are preserved, while others are damaged. Evidence from neuroimaging studies revealed that, during MI tasks, older individual hyperactivate their sensorimotor and attentional networks. Some studies have argued that this represents a compensatory mechanism, others claim that this is a sign of cognitive decline. However, further studies are needed to establish whether MI could be used as a promotion factor to improve cognitive functioning and well-being in older people. Recently, most scientific study has been focused on pathological older populations, thus neglecting to promote well-being and healthy ageing to prevent physical and cognitive impairments typical of old age. Several evidence has now recognized physical activity as a crucial environmental factor in cognitive functioning boosting and psychological well-being promotion [4–6,48]. It has been proved that an active lifestyle, based on physical activity, could also counteract age-induced cognitive decline [9]. These experimental findings are in line with the clinical panorama, where the concept of “active ageing” is gaining more and more interest. It is known that, with age, the brain’s ability to adapt to the environment decreases gradually, leading to a decline in brain function and neuroplasticity. In a recent study, Rahmi et al. [49] demonstrated that physical activity impacts brain health and cognitive function, as well as cellular and structural changes in older individuals’ brains. Biological changes in the older include increased neurogenesis and synaptogenesis, dendritic remodelling, and synaptic plasticity. They also showed that acute exercise training improves older individuals’ cognitive performance and their quality of life [50]. Enhancing MI skills can replicate the positive effects of physical activity on healthy ageing, since motor imagery and motor execution depend on partially overlapping neural systems [40]. Further, as some evidence on young individuals has shown, physical activity also boosts MI skills [14]. In light of all the methodological issues highlighted in our review, we are still far from concluding that MI-based training is an actually effective option in promoting healthy ageing. However, a greater understanding of how elderlies’ MI work can help us improve movements and gestures that are generally weakened with age.