As the proportion and absolute number of older people increase dramatically worldwide, aging has become a critical issue. When we age, the brain degenerates structurally and functionally. Prefrontal cortex (PFC), playing essential role in top-down modulation of cognitive function (Funahashi and Andreau, 2013), is frequently reported to have the most substantial age-related changes. PFC degeneration correlates with cognitive decline and increases risks of neurodegenerative diseases in older adults (Salat et al., 2001; Xu et al., 2019). Structural decay and functional hyperactivation in PFC were found to be associated with poor performance in executive function and memory in older adults (Heuninckx et al., 2005, 2008; Deary et al., 2006; Emery et al., 2008; Davis et al., 2009).

A growing number of studies presented the importance of autonomic nervous system (ANS) in aging and cognitive processing in addition to PFC. The neurovisceral integration model proposed by Thayer et al. (2009) and Thayer and Lane (2009), has brought forward the interplay between cognitive processes and ANS. The integral component of the internal regulation from brain to visceromotor, neuroendocrine, and behavioral responses is expressed as the central autonomic network (CAN). This entity supports goal-oriented behaviors and adaptability (Benarroch, 1993; Thayer et al., 2009). The output of CAN directly links to heart rate variability (HRV), and therefore HRV is considered as an indicator of CNS-ANS integration. In particular, HRV is sensitive to the neural flexibility in response to situational requirements. The aging ANS usually shows increased sympathetic activity and the relative decrease in parasympathetic activity, or vagal tone. In geriatric communities, ANS impacts cognition and potentially predicts memory loss independent from genetic risk factors (Shah et al., 2011; Saint Martin et al., 2013). Some studies suggested that ANS dysregulation may contribute to determining successful/unsuccessful aging, as well as cognitive-related disease, such as Alzheimer’s disease or other dementia (Daulatzai, 2012; Vasudev et al., 2012).

The association between HRV and cognitive function has been reported in several studies. Johnsen et al. (2003) revealed that the group with low HRV required longer reaction time in Stroop test than high HRV group. Hansen et al. (2003) also reported that high HRV group not only showed less reaction time but also higher correctness in executive function task than low HRV group. A systematic review summarized the influence of HRV on cognitive function, pointing out the possibility of HRV serving as an early biomarker for cognitive impairment (Forte et al., 2019). Previous studies also suggested that cognitive task-related HRV changed in parallel with PFC activity. Gianaros et al. (2004) found the decrease of task-induced heart period and vagal tone were associated with decreased regional cerebral blood flow in medial PFC. Nikolin et al. (2017) demonstrated increased task-induced and resting high frequency rhythm, an index for vagal tone, by applying transcranial direct current stimulation on dorsal lateral PFC as compared to sham group.

Mild cognitive impairment (MCI), a transitional stage between normal aging and dementia, is the onset and evolution of cognitive impairments beyond those expected based on the age and education of the individual (Petersen et al., 2014). As MCI progresses, decrease in cortical thickness were observed in widespread areas, including bilateral prefrontal areas, leading to worse cognitive performance compared to healthy controls (Ye et al., 2014). Some studies reported people with MCI showed higher task-induced cerebral activation than age-matched healthy controls, and such activation positively correlated with task performance (Sperling, 2007; Liang et al., 2011; Clément et al., 2013). Others observed decreased brain activity in people with MCI in parallel with cognitive decline, as the capacity of brain resources has been reached (Holtzer and Izzetoglu, 2020; Yeung and Chan, 2020). In addition, the autonomic dysfunction, particularly the parasympathetic division, is common in people with cognitive impairment. People with MCI were 5.6 times more likely to have autonomic dysfunction than the controls (Collins et al., 2012; da Silva et al., 2018).

Although cognitive degeneration is a natural process in aging, whether the subtle cognitive decline in MCI compared to healthy older adults (OA) would make differences in broader cognitive assessments, as well as the cognitive task-induced brain activation and autonomic response was unknown. Therefore, our study aimed to investigate the differences between young and OA with or without MCI in cognitive functions, task-induced PFC activation and HRV changes. We hypothesized that young adults (YA) would have greater performance in cognitive assessments, lower PFC activation and higher HRV compared to OA. And OA-MCI would have the poorest cognitive performance, highest PFC activation, and lowest HRV among three groups.

Ninety-three participants enrolled in the study. Among them, 31 participants in young adult group (YA), 44 in older adult group (OA), and 28 in older adults with MCI group (OA-MCI). Table 1 provides the basic information of the participants in three groups. Although the education level differed between young and older adults, the results remained unchanged after adjusting educational years with ANCOVA.

This study demonstrated the differences of global cognitive functions, executive functions, heart rate variability, and increase in prefrontal activity in YA, OA, and OA-MCI. Interestingly, we found that YA had best performance in the assessments of cognitive and executive functions, followed by OA, and OA-MCI had the poorest performance among three groups. However, PFC activity and HRV only showed differences between YA and OA. There were no significant differences detected between OA and OA-MCI.

In this study, we noted that EF and cognitive functions showed a decrease between different age groups (YA vs. OA), whereas there was an increase in the activation of PFC during SCWT-ic. The SCWT-ic measures the ability to inhibit cognitive interference in addition to attention, processing speed, cognitive flexibility, and working memory. These age-related findings during SCWT-ic in PFC may indicate the possible neural compensatory mechanisms (Yap et al., 2017; Udina et al., 2020), or compensation-related utilization of neural circuits hypothesis (CRUNCH) for relatively more challenging tasks (Reuter-Lorenz and Cappell, 2008). When the cognitive demand increases, more cortical resources are activated. High task complexity, such as SCWT-ic, may challenge the brain for compensation-related utilization in OA. However, despite the compensatory activation, the task performance in OA was still significantly lower as compared to YA. We further noted such compensation-related utilization was not significant during SCWT-c or CFT, which was in line with Yoon et al.’s (2019) study. In Yoon et al.’s (2019) study, they showed SCWT-ic was a more suggestive of neural compensatory mechanisms than CFT.

The PFC activations did not differ significantly in any of the three tasks between OA and OA-MCI, but the task performances were worse especially the SCWT-ic and CFT in OA-MCI as compared with OA. Previously, we also noted no significant difference in PFC during usual walking and cognitive dual task walking between OA and OA-MCI (Weng et al., 2023). We thus speculate that the inability to activate more PFC for compensation may lead to poorer performance, both cognition and motor, in people with MCI as compared with healthy older adults.

The HRV, on the other hand, acts as the modulated consequence of the central-peripheral neural feedback. HRV could be seen as the responsiveness to the executive task demands (Thayer et al., 2009; Mathewson et al., 2010; Luque-Casado et al., 2016). In present study, HRV was observed from three aspects, RRI, RMSSD, and pNN50 during resting and task execution. Similar to PFC activations, RMSSD and pNN50 showed significant differences between two age groups (YA vs. OA) but not between OA and OA-MCI. Previous studies have presented performance-related reduction in RRI as the increased autonomic responsiveness in cognitive and EF task paradigm (Hansen et al., 2003; Mathewson et al., 2010). Faster heart rate usually reacts in parallel with lower baroreflex sensitivity. The greater autonomic reactivity including increased task-related heart rate and reduced vagal tone, was believed to potentially predict the EF performance. Age would weaken the autonomic control and EF performance (Mathewson et al., 2010), which was consistent with our findings.

The significant decrease in RMSSD in resting and during task in OA as compared to YA, further supports the age-related decrease in parasympathetic activity. Previous studies also showed the close relationships between decreased RMSSD and decreased executive function in older adults (de Vilhena Toledo and Junqueira, 2010; Eggenberger et al., 2020). Although the ECG recording for each task trial lasted for only one minute in present study, it was still possible to detect the differences between YA and OA. Potentially, RMSSD can be a HRV variable used in ultra-short recording period (Esco and Flatt, 2014; Laborde et al., 2017). The pNN50, another commonly used index for parasympathetic activity, also highly correlates with RMSSD (Umetani et al., 1998; Shaffer and Ginsberg, 2017). In our findings, OA had significantly lower pNN50 in all three tasks compared to YA, strengthening the results of attenuated HRV.

Recently, an increasing number of studies have addressed the associations between HRV and cognitive performances. In general, lower HRV was associated with poorer global cognition and performance in multiple cognitive domains, in which EF was the most investigated (Forte et al., 2019). Most studies measure resting HRV while some used reactive or task-induced HRV, however, with very different protocols. Nicolini et al. (2014) showed that older people with MCI exhibited small HRV changes to postural provocation compared to healthy older adults, even though there were no significant differences between two groups in resting. Marshall et al. (2018) showed that older people with frontotemporal dementia had degraded ability to identify facial emotion, alongside with attenuated cardiac reactivity. McDermott et al. (2019) showed that although older people with amnestic MCI had similar level of stress regulation as healthy older people, there was a positive correlation between pressure regulation index and HRV yet with no significant group effect. Lin et al. (2016) reported an association between lower mental fatigability and greater rebound in reactive HRV in people with MCI. Although the types of stimuli were not directly comparable to our study protocol, these previous studies suggested that older people with MCI were likely to have decreased cardiac reactivity in association with poorer performances, which was not consistent with our funding in the current study. Grässler et al. (2023) reported the significant decreases in RMSSD from resting to a Stroop task in people with MCI as compared with healthy control, indicating the vagal withdrawal in people with MCI. However, our results did not show the significant effects of cognitive impairment on autonomic control. It was worth noting that most studies that detected the difference between healthy and people with MCI acquired ECG recording in longer periods. Despite the fact that longer recording periods provides better validity in accuracy and predictive power, short and ultra-short periods provide greater possibility in clinical application whereas the usage of ultra-short term, as the proxies of long- and short-term, needs more research (Shaffer et al., 2020). As we explored the ultra-short time period during task execution, we did not find statistical significance impacted by mild cognitive impairment.

There are several limitations in this study. Due to the limited time period in ECG recordings, we were not able to process frequency-domain analysis. However, the indices chosen in this study still show significant findings between different age groups, which are in line with previous studies. We believe that short-term epochs as in our protocols were possible for detecting cognitive task-induced changes between younger and older adults, but unclear for MCI. The results in this study should be interpreted with care because it was a cross-sectional study and the associations of the outcomes did not indicate causality. Replication in larger cohorts with more evenly distributed gender and participants are needed.

Cognitive decline was seen in older adults, and even larger in people with MCI. Older people showed lower performances in general cognitive function and executive function, combined with compensatory increase of PFC activity, and reduced HRV. However, the PFC activity and HRV reaction was similar in healthy older adults and those with mild cognitive impairment.

The data that support the findings of this study are available from the corresponding author, upon reasonable request.

The studies involving humans were approved by the Institutional Review Board of National Yang Ming Chiao Tung University. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

P-HK: Conceptualization, Investigation, Methodology, Visualization, Writing – original draft, Writing – review & editing. Y-RY: Methodology, Writing – review & editing. N-CY: Formal analysis, Software, Writing – original draft. P-YL: Investigation, Project administration, Writing – original draft. C-FL: Resources, Software, Writing – review & editing. R-YW: Conceptualization, Funding acquisition, Supervision, Writing – review & editing.