Background
Fatigue is associated with impairments in both physical and cognitive functioning and interference in performing daily tasks [
1‐
3]. It refers to normal, everyday experiences that are observed after sustained physical activity or mental exertion [
1,
4,
5]. Specific to physical functioning, neuromuscular fatigue can be defined as a reduced ability to generate a desired muscle force [
2,
6]. On the other hand, cognitive fatigue occurs due to prolonged periods of performing mentally demanding task that induces a state of subjective fatigue, feelings of “tiredness and lack of energy”, and performance decrements [
2,
7]. Recent studies have elucidated the negative impact of cognitive fatigue on neuromuscular function, which includes changes in strength, muscle activity, and joint steadiness [
7‐
12]. Concomitant to these biomechanical outcomes, cognitive fatigue has shown to limit activation of the prefrontal cortex (PFC) during muscle fatigue development in healthy young adults [
12,
13]. Aging has shown to further exacerbate the impact of concurrent cognitive demand on biomechanical indicators of neuromuscular control in older adults during non-fatiguing tasks [
14]. Because the normal aging process influences both physical and cognitive fatigue processes, it is likely that the nature and extent to which cognitive fatigue affects neuromuscular fatigue development in older adults differs that from younger adults; however there are no published biomechanical or neuroimaging data.
One of the vital functions related to functional independence and activities of daily living (ADL) in the geriatric population is the ability to grasp and hold objects [
15]. This ability requires a complex series of inputs from various body systems including the central nervous system (CNS) as well as the musculoskeletal system [
8,
16]. With advancing age, there are normal structural and functional changes that occur in the brain and within the musculoskeletal system, which may impact grasping functions. Older adults exhibit general decrements in grasping/holding due to age-related reduction in grip strength [
16]. However, aging is associated with an increase in type I muscle fibers that has shown to increase fatigue resistance in older adults [
17,
18]. Age-related changes at the CNS, particularly the brain, include reduced cerebral blood flow, loss of cortical excitability, reduction in cortical plasticity, and loss of grey matter [
8,
19]. Subsequently, functional brain imaging studies have shown age-related increased compensatory activation at the PFC, ipsilateral cortical motor and sensorimotor areas to maintain motor performance [
19,
20]. Conversely, reduced brain activity or inefficient cortical connectivity is observed in these brain regions, particularly the PFC, in older adults during fatiguing exercises (i.e. when motor task performance is not maintained) suggesting that PFC may be a limiting factor for impaired neuromuscular performance [
21,
22]. Cognitive fatigue, like physical fatigue, has shown to adversely impact numerous cognitive functions including attention, working memory and executive control, and this is particularly evident in older adults [
5,
23]. Working memory function (i.e., the ability to process and store information) is largely regulated by the PFC and is typically one of the first functions to deteriorate with age [
24‐
27]. In older adults, working memory function is a crucial cognitive function that along with reasoning, language, and learning abilities, enables performance of ADLs [
24]. At higher working memory loads, additional cognitive resources are required in order to compensate for the age-related declines in working memory function, specifically with reduction in activation of dorsomedial PFC [
27].
Given that the PFC plays a major role in regulating both cognitive and neuromuscular abilities, and that the normal aging process impacts PFC functioning, it is likely that age-related changes in PFC activity may moderate neuromuscular function when individuals are both cognitively and physically fatigued. The purpose of this study was to examine the impact cognitive fatigue on neuromuscular fatigue and associated PFC activity in older adults. It was hypothesized that cognitive fatigue will influence neuromuscular fatigue development and this relationship will be associated with altered PFC patterns.
Discussion
The present study investigated the impact of cognitive fatigue on neuromuscular fatigue development and associated PFC activation patterns during submaximal fatiguing handgrip exercises in older females. The results indicated that while cognitive fatigue did not affect traditional indicators of neuromuscular fatigue, i.e., endurance time and strength loss, it was associated with greater decrements in ∆HbO2 levels in the PFC during neuromuscular fatigue development after the 60-min cognitive fatigue condition when compared to the control condition.
Neuromuscular capacity, measured as a function of endurance time, has shown to be negatively affected by cognitive stress
prior to [
7] and
during physical fatigue exercises [
9] in younger adults. In the current study, prior cognitively fatigued state did not affect endurance time in older females. Methodological differences may explain the varied outcomes in the aforementioned studies when compared to the present study. For example, Marcora et al. [
7] investigated the effects whole body fatigue using a cycling fatigue protocol after completing a 90-min continuous performance task that required sustained attention, working memory, response inhibition, and error monitoring, while the current study focused on localized muscle fatigue of the lower arm after a 60-min exposure to two working memory tasks. Moreover, previous studies [
7,
45] that have investigated the impact of cognitive fatigue on muscle capacity have focused on postural (shoulder) and lower extremity (quadriceps) muscles rather than smaller muscle groups employed during handgrip exercises. Thus it is likely that the impact of cognitive fatigue on neuromuscular capacity is task- and muscle-dependent, as previously reported by Mehta et al. [
46,
48]. A recent study demonstrated that high levels of concurrent cognitive demand increases force fluctuations of the lower arm in older adults [
49]. It was suggested that the increase in fluctuations in the older adults may have been amplified due to age-related changes in the motorneuron pool via excitation or decreased inhibition when increased cognitive demand is present. Interestingly, the same research group demonstarted similar time to task failure during submaximal ankle dorsiflexion fatiguing exercises in the absence and presence of concurrent cognitive demands in older adults [
50], which is similar to what was observed here.
Older adults exhibited decrements in ∆HbO
2 levels in the PFC as a result of cognitive fatigue when compared to the control condition even though neuromuscular fatigue outcomes, i.e., endurance time and strength loss, were similar. In a previous (and similar) investigation in young adults [
13], we found that concurrent mental fatigue during neuromuscular fatiguing protocol (concurrent condition) was associated with greater PFC activation initially when compared to the same fatiguing exercise in the absence of mental fatigue (control). This trend was explained by an initial need for additional resources placed by the cognitive demand in order to maintain both cognitive and motor task performance [
13]. We also found a reversal trend at exhaustion; PFC activity during the concurrent condition was significantly lower than that observed in the control condition. This decrease was attributed, in parts, to compensatory activation in different brain regions given that endurance times remained comparable between the two conditions. The present study did not find the aforementioned PFC activation trends with older adults. First, PFC activity during the cognitive fatigue condition was lower than that during the control condition. Second, the reversal trend was not observed; cognitive fatigue-related decrements in ∆HbO
2 were consistent over time. However, ∆HbO
2 trends (Fig
4) suggest that the magnitude of the difference between control and cognitive fatigue-specific activation is both hemisphere- and time-dependent, whereas in our previous investigation in younger adults [
13] we only observed time-dependent PFC activation patterns. It is likely that aging may differentially impact bilateral PFC regulation when individuals are both cognitively and physically fatigued. In support of this, previous research has demonstrated that age-related reductions in PFC activation is observed during physically fatiguing exercises [
21,
22] as well as during tasks involving the working memory [
51]. Interestingly, neuromuscular performance remained unchanged between the control and cognitive fatigue conditions, indicating potential neural adaptations to compensate for the observed reduction in PFC activity. The
scaffolding theory of cognitive aging [
52‐
55] suggests that with aging there is a compensatory shift in neural recruitment to accommodate cognitive challenge [
54,
55]. While the present study focused solely on the activation of the PFC, other brain regions are involved in fatigue development, particularly in older adults [
8,
19,
56]. Previous research has demonstrated a shift in activation centers in the brain to maintain neuromuscular performance during a fatiguing protocol [
57]. It is likely that the presence of cognitive fatigue accelerated cortical redistribution in older adults to maintain neuromuscular performance. Because only the PFC was monitored in the present study, further investigation is warranted to provide support for the proposed hypothesis on shifting of brain activation centers when older adults are both physically and cognitively fatigued. The premotor and motor areas may be of interest due to their interconnection with the PFC during motor tasks under stress [
58]. Particularly with aging, the PFC decreases in size, which may alter connection to the premotor cortex and result in a decline in motor capabilities [
59].
In general, heart rate increased linearly during neuromuscular fatigue development, implying that all participants reached similar physiological fatigued states [
47]. This physiological increase over time was accompanied with an increased perception of discomfort. While heart rate and ratings of perceived exertions are highly correlated [
60], these outcomes were not found sensitive to the different cognitive fatigue conditions, which are a departure from findings reported by Marcora et al. (2009), who demonstrated that a prior cognitive fatigued state is associated with greater perception of effort and discomfort and decreased muscle endurance. It is likely that the exposure to the cognitively fatiguing task may have played a role in the discrepancies observed between the two studies. Heart rate variability, as measured by the LF/HF ratio (a measure of sympathovagal balance [
61,
62]), was also found to be similar across both cognitive fatigue conditions in the present study. An increase in LF/HF has shown to indicative of increased stress [
61,
63,
64]. Thus similar LF/HF ratios across both cognitive fatigue and control 60-min conditions indicate that the participants experienced similar levels of stress, if any, across both conditions.
There are some limitations in the present study that warrant discussion. First, the study examined the impact of cognitive fatigue on neuromuscular function and associated PFC activity in older females. This was done to avoid sex-specific differences in both cognitive and neuromuscular capacity. Pereira et al. [
49] reported that older females are more susceptible to the effects of neuromuscular fatigue; especially at high and low levels of cognitive demand during sustained upper arm exertions, when compared with males of the same age. Additionally, they reported that younger women exhibited greater fatigability, at higher levels of cognitive demand, compared to their male counterparts. These sex differences may have important implications for work-related tasks that require either high or low levels of cognitive workload, particularly with the aging workforce. Future research is warranted to extent the current investigation to include a larger sample of both males and females in both the younger and older population to examine age-specific differences. Second, the present study monitored the PFC regions due to equipment constraints. Existing neuroimaging investigations of fatigue development suggest a shift in activation centers in the brain to compensate for fatigue-related loss in neural efficiency, particularly with the normal aging process [
8,
19,
57]. Future research is needed to examine activation of motor function-related brain regions to understand age-related changes in functional brain activation patterns when individuals are physically and cognitively fatigued. Third, differentiating the effects of cognitive fatigue and stress and/or anxiety that may originate due to the cognitive fatigue protocol through the use of cortisol markers may provide a better understanding of how neuromuscular fatigue and associated PFC functioning is impacted by these non-biomechanical risk factors in older adults. Finally, a majority of the participants were overweight and obese (body mass index (BMI): 29.74 (4.9) kg/m
2). Because increased adiposity has been previously associated with impaired neuromuscular functioning and altered brain function [
36,
65,
66], it is likely that the BMI status of the study pool may have influenced the study outcomes. For example, in younger obese adults, altered handgrip force control has been associated with stunted PFC activity [
65], particularly under stress [
66]. However, there is no published evidence of the same in the geriatric population. Results from the present study need to be supplemented with data from non-obese and obese older males and females to examine how obesity influences the findings reported here.
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
All authors contributed to the study design. RM and AS designed the study. AS conducted the study. RM and AS conducted data analyses with various bioinstruments. AP and QZ assisted in the statistical analyses. AS drafted the initial manuscript. All authors contributed to the revision of the manuscript and have read and approved the final version.