Introduction

Physiological aging is characterized by a gradual and multifaceted decline in cognitive functioning, even in the absence of neurodegenerative pathology. The degree and pattern of these cognitive changes vary widely among individuals, influenced by a complex interplay of genetic, biological, environmental, and lifestyle factors [1–3]. Processing speed tends to slow with age, resulting in longer reaction times and reduced efficiency in information processing [4]. As individuals age, the working memory capacity generally diminishes, leading to a reduced ability to control information [5]. This decline can negatively influence various cognitive functions, particularly those involved in engaging in complex reasoning tasks [6]. Executive functions, covering a set of cognitive control processes such as planning, cognitive flexibility, and inhibitory control, are particularly vulnerable to the aging process [7]. Deficits in inhibitory control, understood as the capacity to suppress prepotent, habitual, or contextually irrelevant responses in favor of resolute behavior, have been consistently observed in healthy aging populations [8]. This decline in inhibitory function not only compromises task performance in situations requiring selective attention and conflict resolution but also contributes to difficulties in everyday activities that demand focused cognitive control. As a result, older adults may be more easily distracted, have more difficulty ignoring irrelevant information, and take longer to resolve cognitive conflict, all of which contribute to age-related cognitive decline [9]. Given the centrality of inhibitory control in everyday functioning, it is crucial to employ robust experimental paradigms that can isolate and quantify these control mechanisms.

A well-established paradigm for assessing inhibitory control is the Stroop Color and Word Test, which is based on the Stroop effect first described in 1935 [10]. The Stroop test consists of three main conditions: the Word Reading Condition, where participants read color words printed in black; the Color Naming Condition, where they name the colors of patches; and the Interference Condition, where they name the ink color of incongruent color words [11]. Each of these conditions engages different cognitive mechanisms. The Word Reading Condition primarily assesses automatic processing, as reading single words, particularly in the Stroop paradigm, tends to require limited allocation of attentional resources compared to other tasks. This process remains largely unaffected by age, and performance in this condition tends to remain stable in older adults. The Color Naming Condition requires greater attentional engagement and controlled processing compared to the Word Reading Condition. Participants must name the color of non-word stimuli, which engages selective attention and processing speed—abilities known to decline gradually with age [12]. In contrast to reading, which is highly automatized, color naming relies on controlled attention and label selection, which increases cognitive effort and response latency. Slower responses in this condition among older adults may reflect general cognitive slowing and reduced efficiency in attentional resource allocation.

The Interference Condition places the highest demand on executive functioning, as it requires the participant to inhibit the automatic tendency to read a word to correctly name the ink color in which the word is printed. Older adults tend to exhibit greater difficulty and longer response times (RTs) in this condition, highlighting impairments in the ability to manage cognitive conflict and inhibit irrelevant information—a key feature of healthy cognitive aging [13]. This differential pattern of performance across conditions underscores the utility of the Stroop task not only in isolating components of cognitive control but also in highlighting how these components are selectively affected by the aging process [14].

For its investigation, advances in functional neuroimaging techniques have significantly improved our ability to non-invasively investigate age-related changes in brain function [15, 16]. Among these methods, electroencephalography (EEG) stands out as a particularly sensitive and temporally precise tool for detecting alterations in neural dynamics associated with aging [17, 18]. Several studies have documented systematic age-related changes in EEG rhythmic activity across frequency bands [19–21]. For instance, aging is associated with a general slowing of EEG rhythms, including a gradual reduction in alpha band power and peak frequency, which correlate closely with cognitive decline [22]. Furthermore, age-related increases in slower bands, alterations in coherence patterns, and decreased alpha reactivity during cognitive tasks have been consistently reported [23, 24]. EEG’s high temporal resolution allows for the analysis of rapid neural processes that underlie cognitive functions such as attention, working memory, and inhibitory control [25]. In particular, EEG is compatible with capturing dynamic brain states during task execution, offering real-time insights into how cognitive control processes are modulated across the lifespan [26]. Its portability, cost-effectiveness, and ability to be applied in both laboratory and clinical contexts further underscore its value [27]. These EEG markers provide non-invasive neurophysiological correlates of the variability in cognitive performance observed across the lifespan, making EEG an ideal tool to explore executive function decline, including inhibitory control [28, 29].

The primary objective of the present study is to extend previous findings on age-related cognitive decline by examining how inhibitory control and interference resolution—assessed through performance on the Stroop task—vary across the adult lifespan [30, 31]. Specifically, the study aims to confirm prior evidence indicating that executive functions, including inhibitory control, are particularly susceptible to age-related deterioration and to investigate their neural correlates at rest, which remain largely underexplored [32]. To this end, Stroop performance metrics were analyzed in relation to participants’ chronological age and subsequently correlated with neurophysiological markers derived from EEG spectral analysis. Special focus was directed toward alpha frequency bands (alpha 1 and alpha 2), which have been increasingly associated with cognitive control processes such as selective attention, inhibitory regulation, and the management of goal-directed actions. While previous research has often examined task-evoked EEG responses during cognitive tasks, a novel aspect of the present study is the correlation of Stroop performance with resting-state alpha activity. This approach allows us to investigate baseline neural network states underlying inhibitory control and to explore their predictive value for behavioral performance. Another innovative feature is that such an approach may also be extended to more ecologically valid or real-world contexts, offering the possibility to capture neural markers of inhibitory control beyond the constraints of laboratory-based paradigms. By exploring the relationship between behavioral performance and oscillatory activity, this study aims to advance our understanding of the electrophysiological mechanisms highlighting cognitive variability and decline in healthy aging.

Materials and methods

Results

Correlation analysis

Pearson correlation analysis revealed significant positive associations between age and RTs recorded in each of the three Stroop conditions. Specifically, age was positively correlated with RT in the Word Reading Condition [p = 3.18 × 10^–4, r = 0.37, 95% CI: (0.1766, 0.5344)], the Color Naming Condition [p = 1.04 × 10^–7, r = 0.52, 95% CI: (0.3555, 0.6582)], and the Interference Condition [p = 3.95 × 10^–15, r = 0.71, 95% CI: (0.5885, 0.7980)]. Additionally, another significant correlation was observed between age and the mean RTs across the three conditions [p = 4.02 × 10^–14, r = 0.69, 95% CI: (0.5638, 0.7843)]. Furthermore, the Pearson correlation between age and the number of errors reached statistical significance in the Interference Condition [p = 4.73 × 10^–2, r = 0.20, 95% CI: (0.0026, 0.3974)]. Results concerning Pearson correlations between age and RTs are presented in Figure 1.

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Figure 1. Pearson correlations between age and response time (RT). Scatterplots for the three Stroop task conditions: (1) Word Reading, (2) Color Naming, and (3) Interference Condition, reveal positive linear associations, with older age linked to longer RT. The final plot shows the correlation between age and mean RT across conditions.

Topographical representation

To further explore the spatial characteristics of the neurophysiological correlates of aging, topographical analyses were conducted on EEG spectral data. Analyses were performed considering both the RTs recorded in each of the three Stroop task conditions (Word Reading, Color Naming, and Interference), as well as the mean RT across all conditions. Following FDR correction (p < 0.05) to control multiple comparisons, statistically significant negative correlations were observed between age and alpha 2 power in occipital regions. Topographical distributions are represented in Figure 2.

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Figure 2. Topographical distribution of the correlations between response times (RTs) and alpha band power spectral density (PSD). Scalp maps display statistically significant negative correlations (false discovery rate (FDR)-corrected, p < 0.05) between RTs and PSD in the alpha 2 band. Warmer colors indicate stronger associations, with notable effects localized in occipital regions, suggesting an age-related reduction in posterior alpha 2 activity. This pattern reflects potential declines in attentional and inhibitory processes mediated by posterior cortical networks. No significant correlation emerged in (1) the Word Reading Condition, whereas a weak occipital effect was observed in (2) the Color Naming Condition. The correlation became stronger in (3) the Interference Condition, and a comparable effect was also observed when RTs were averaged across all three conditions. No significant correlations were found for the alpha 1 band.

Discussion

Aging is commonly associated with a gradual decline in various cognitive functions, a process that can significantly influence daily functioning and overall quality of life [34]. Processing speed and inhibitory control are among the cognitive domains that may be particularly sensitive to, or affected by, age-related changes, given their role in efficient information processing and the regulation of goal-directed behavior [35]. For instance, the study by Ferguson et al. [36] (2021) showed that inhibitory control begins to decline from around 35 years of age, while working memory capacity starts to decline even earlier, from approximately 30 years of age, indicating that different cognitive functions may follow distinct trajectories of age-related decline. Understanding how these cognitive domains are influenced by aging is essential for interpreting performance differences across age groups and for developing interventions aimed at maintaining cognitive health. Exploring these processes can also help uncover the factors that support cognitive preservation and illuminate the mechanisms of successful cognitive aging. In this context, the concept of cognitive reserve has received increasing attention, referring to the brain’s capacity to manage age-related neural changes or pathology by utilizing more efficient neural networks and alternative cognitive strategies [37–39]. Building on this perspective, it becomes crucial to investigate how specific cognitive functions evolve with age.

This study aimed to investigate the trajectory of inhibitory control and interference resolution in physiological aging, using Stroop task performance as a behavioral marker of these cognitive functions. To this end, 91 healthy participants spanning a wide age range were recruited and administered all three conditions of the Stroop Color and Word Task—Word Reading, Color Naming, and Interference Condition—to assess how behavioral performance varies with age under different levels of cognitive demand. RTs and error rates were analyzed for each of the three conditions individually, as well as for the average performance across all conditions, and correlated with participants’ chronological age. Additionally, behavioral performance was also correlated with PSD derived from participants’ EEG recordings, with a particular focus on the alpha frequency band. Previous research has emphasized the importance of accounting for individual variability in alpha frequency when analyzing EEG data. This particular focus on the alpha band is also supported by other studies showing that individual variability in alpha activity is closely linked to cognitive performance. For instance, Klimesch et al. [40] (1993) reported that participants with higher task performance tended to exhibit increased alpha activity during cognitively demanding phases, such as memory retrieval, highlighting fundamental links between alpha oscillations and cognitive efficiency. This approach aimed to integrate neuropsychological and neurophysiological measures to explore age-related changes at both behavioral and neural levels.

From a behavioral perspective, results indicated a decline in performance with increasing age across all three Stroop conditions, as demonstrated by significant positive correlations between RTs and age. The same pattern was observed when considering the average RTs across the three conditions. It is important to underline that the effect observed with RTs became increasingly pronounced as task difficulty increased, highlighting a stronger age-related impact on more demanding cognitive processes. Additionally, a significant positive correlation between error rates and age was observed specifically in the Interference Condition. Complementing the behavioral data, neurophysiological analyses focused on the alpha frequency band-known to play a critical role in attentional regulation and executive control, revealed no significant correlations for the alpha 1 band, which is typically linked to basic sensory processing and general arousal. Conversely, statistically significant differences were observed in the alpha 2 band. In particular, resting-state alpha 2 PSD in occipital regions was negatively correlated with RTs in the Color Naming and Interference Condition, as well as with mean RT across all Stroop conditions. This finding is particularly interesting and aligns with the pattern observed in age-related correlations, showing that the strength of the association between occipital alpha 2 activity and RTs increases progressively with task difficulty. Specifically, the negative correlations identified in the Interference Condition mirror those obtained when considering mean RT across all three Stroop conditions. This pattern emphasizes the specific sensitivity of interference resolution processes to alpha 2 oscillations, potentially reflecting their role in facilitating attentional control and inhibitory functions when executive demands are intensified. From a theoretical perspective, alpha 2 rhythms have been linked to top-down regulatory mechanisms that support the suppression of irrelevant information and the flexible allocation of attentional resources, suggesting that their modulation at rest may index an individual’s baseline capacity for inhibitory control rather than representing a task-bound effect.

This study’s results are supported by existing literature, which consistently reports that inhibitory control tends to decline with age. However, the extent and nature of this decline may vary depending on the specific inhibitory process being assessed and the task employed [41]. For instance, Kramer et al. [42] (1994) explored the relationship between aging and reductions in inhibitory efficiency. They assessed a range of inhibitory functions in both young and elderly adults using various tasks. The analysis of different task components revealed that, in many cases, elderly adults performed similarly to younger participants, offering limited support for age-related variations in inhibitory function. These findings underscore the importance of a subcomponent-based approach, suggesting that aging impacts some inhibitory processes more than others [43]. In line with these results, the study by Forte et al. [44] (2024) further supports the observations made in the present research. Specifically, Forte and his colleagues differentiated between congruent and incongruent stimuli within the Stroop task and examined how performance in these conditions correlated with age. Their sample encompassed a wide age range, including children. Consistent with the findings of our study, they reported significantly faster RTs for congruent compared to incongruent stimuli. Furthermore, when analyzing these conditions separately, a U-shaped distribution of RTs emerged. This pattern was primarily attributable to the inclusion of children, whose prolonged RTs reflect the ongoing maturation of cognitive processes. Similarly, Ferguson et al. [36] (2021) observed a comparable pattern, reporting that inhibitory control tends to decline with advancing age, particularly starting in middle age.

The neurophysiological results are also supported by previous literature. For instance, Klimesch et al. [45] (1999) highlighted that alpha 2 power follows a similar lifespan trajectory—increasing from childhood to adulthood and declining in older age—reflecting underlying cognitive changes. Consequently, the modulation of alpha 2 activity across the lifespan may underlie age-related differences in cognitive control and inhibitory processes, supporting the use of resting-state alpha 2 PSD as a sensitive biomarker of cognitive efficiency and neural integrity. Further evidence for the functional relevance of distinct alpha sub-bands comes from cognitive studies such as Fink et al. [46] (2005), which demonstrated that lower and upper alpha frequencies are differentially involved in cognitive processing. These findings support the idea that alpha sub-bands reflect distinct cognitive functions and are selectively modulated depending on task demands.

In conclusion, the present study offers a valuable contribution to the understanding of cognitive control mechanisms by providing neurophysiological support for well-established concepts in the literature. Unlike previous studies focusing on task-evoked EEG [47], the present work links individual differences in Stroop performance to resting-state alpha 2 activity, providing a novel perspective on baseline neural predictors of inhibitory control. This integrated behavior-EEG approach allows us to identify predictive markers that extend beyond traditional task-based measures [48]. Additionally, a key advantage of this study is the ability to observe the direction and sign of correlations from a topographical perspective, allowing precise localization of these effects at the scalp level. A limitation of this study is the limited ecological validity of the Stroop task, which may not fully capture the complexity of inhibitory demands in everyday life. Thus, the generalizability of our findings to real-world contexts should be viewed with caution. Nevertheless, the observed EEG markers hold promise for practical applications, including early screening of inhibitory deficits, monitoring cognitive decline, and guiding personalized cognitive training. Future studies should further explore the role of resting-state activity in predicting performance across various cognitive domains and populations, and consider combining EEG with other physiological or behavioral markers to develop more robust models of individual cognitive capacity. Longitudinal studies will be particularly valuable to track changes over time and to distinguish true age-related effects from cohort or individual variability, and could also focus on refining methodological approaches and more advanced statistical models. These efforts may have potential applications in designing and monitoring personalized cognitive rehabilitation programs, bridging the gap between laboratory findings and clinical practice.