Ménétré E and Laganaro M (2019) Attentional Reorientation and Inhibition Adjustment in a Verbal Stroop Task: A Lifespan Approach to Interference and Sequential Congruency Effect. Front. Psychol. 10:2028. doi: 10.3389/fpsyg.2019.02028 Several parameters influence the interference effect elicited in a Stroop task, especially contextual information. Contextual effects in the Stroop paradigms are known as the Gratton or Sequential congruency effect (SCE). This research aims at isolating two processes contributing to the SCE in a Stroop paradigm, namely attentional reorientation from the color to the word and vice-versa, as well as inhibition (engagement/disengagement from one trial to the next one). To this end, in Study 1 subprocesses of the SCE were isolated. Specifically, attentional reorientation and inhibition were segregated by submitting young adults to a discrete verbal Stroop task including neutral trials. In Study 2, the same procedure was applied to 124 participants aged from 10 to 80 years old to analyze how interference, SCE, and the aforementioned decomposition of attention and inhibition change across the lifespan. In both studies, the Gratton effect was only partially replicated, while both attentional reorientation and inhibition effects were observed, supporting the idea that these two processes contribute to SCE on top of conflict monitoring and of other processes highlighted in different theories (contingency learning, feature integration, and repetition expectancy). Finally, the classical age-related evolution was replicated in Study 2 on raw interference scores, but no age effect was observed when processing speed was taken into account, nor on the isolated attentional reorientation and inhibition processes, which is in line with the hypothesis of stability of the inhibition processes over age.

Keywords: attention, inhibition, interference, conflict adaptation, Stroop, sequential congruency effect, Gratton, verbal responses

## INTRODUCTION

At a first glance, the Stroop effect seems incredibly simple: incongruency between color word and color font interferes with color (font) naming. However, the Stroop task involves multiple cognitive processes whose effects can be disentangled. They include automatic word reading, color naming and inhibition, aiming at constraining the attentional focus on the relevant dimension. This definition of the task is relevant only when the current trial is taken into account. However, previous literature favors the hypothesis that the interference effect can vary depending on the

context of the previous trials as investigated by the conflict adaptation literature. In the framework of the sequential congruency effect (SCE), or conflict adaptation effect paradigms, specific effects of the subprocesses were isolated, namely the activation and deactivation of inhibition resources from the previous trial to the current as well as the reorientation of the attentional focus from the word to the color dimension and vice versa. This paper aims at investigating these two processes (inhibition and attentional reorientation) using a SCE paradigm including neutral trials (Study 1), and their evolution in relation with age using a lifespan approach in Study 2.

In the following, we will review the Stroop, the SCE effects and their evolution across the lifespan before proposing to isolate the aforementioned subprocesses of the SCE.

#### The Stroop Task and the Stroop Effect

One of the main approaches to investigate inhibition is by well-known situations of interference, such as those elicited by the Stroop task (Stroop, 1935). Traditionally, the task requires participants to vocalize the printed color from which orthographic color names are presented. The interference comes from the overlays of two inconsistent semantic pieces of information, namely the color word (reading) and the color font (naming). The initial task designed by Stroop (1935) required the participant to name consecutively all the trials from the same condition printed on a card and the experimenter measured the time spent to read the entire card. It is noteworthy to mention that the paradigm has been adapted over time as the development of informatics allowed for the task to become discrete and for reaction times to be measured for each trial and for conditions to be randomized across trials.

The cognitive mechanisms behind the Stroop effect are still largely debated, and several models tried to define the interactions between word reading and color naming dimensions. Among the first interpretations of this interference effect, the "horse-race model" (Dunbar and MacLeod, 1984) suggested that color naming and word reading processes are launched simultaneously, triggered by the stimulus onset and compete only when the two processes reach the production stage. This model represented the reference until the arising of interactionist models, and particularly the model by Cohen et al. (1990). It also gained in credit after its integration in a computational modeling of the Stroop effect (Botvinick et al., 2001, 2004). Botvinick and colleagues' model contributed to the understanding of the main processes involved in the Stroop effect, and it also confirmed the presumed localization of the Stroop effect from a neural point of view. This derived computational model based on Cohen, Dunbar, and MacClelland's model confirmed that the anterior cingulate cortex plays a key role in conflict detection and resolution, as suggested by ERP (Liotti et al., 2000; Hanslmayr et al., 2008; Szucs et al., 2009 ˝ ), fMRI (e.g., Peterson et al., 2002; Derrfuss et al., 2005), and PET studies (e.g., Bench et al., 1993; Carter et al., 1995).

Besides trying to explain the underpinning of the Stroop effect in cognitive or brain models, researchers also tried to test the conditions of the Stroop effect by designing innovative paradigms. This apparently simple task was then derived in a variety of ways (Macleod, 1991), among which the reverse Stroop task (in which the subject has to read the word and ignore the color font) (e.g., Stroop, 1935; Abramczyk et al., 1983; Dunbar and MacLeod, 1984), the semantic Stroop task (obtained by varying the semantic closeness of the distractor from the target) (Klien, 1964), or the auditory Stroop task (modulating the verbal information and the pitch) (e.g., Hamers and Lambert, 1972; Green and Barber, 1981). Authors also manipulated the response modality which is known to play a role in the magnitude of the interference effect (White, 1969; Keele, 1972; Macleod, 1991). At a single trial level, oral responses seem to increase the interference of the Stroop effect and have no or less impact on the facilitation effect, when compared to manual responses (Redding and Gerjets, 1977; Sharma and McKenna, 1998; Lamers and Roelofs, 2011).

As presented above, embracing all the processes involved in the Stroop task is very complex. Giving an understanding including as many aspects as possible of the task was achieved by focusing particularly on two parameters which are relevant in the discrete version of the Stroop task, namely the impact of the context in which the trial occurs and the lifespan evolution of task performance. Indeed, a trial can be influenced by the properties of the previous trial, modulating the interference and facilitation effects. This contextual effect relies on the general concept of SCE, or conflict adaptation effect (Gratton et al., 1992; Botvinick et al., 2001; Mayr et al., 2003; Egner, 2007) and can be analyzed by controlling the distribution of subsequent trial types in the experiment. Additionally, interference and conflict adaptation effects tend to evolve from childhood to adulthood and through aging. These modulations need to be clarified over the entire lifespan.

## The Sequential Congruency Effect

The SCE is a widely studied effect in cognitive psychology, offering an insight into new dimensions of well-known paradigms. It is usually defined as the facilitation effect to resolve a conflict, probably attributable to a pre-activation of the conflict monitoring mechanisms (Gratton et al., 1992; Botvinick et al., 2001, 2004; Egner, 2007; Schmidt, 2013; Duthoo et al., 2014b). This effect is not limited to the Stroop task but has been applied to other paradigms such as the Flanker (e.g., Mayr et al., 2003) and the Simon task (e.g., van Gaal et al., 2010). Contextual effects were investigated according to two different approaches. First, researchers varied the proportion of trials across conditions. This manipulation constrains the attentional system to be focused on the most recurrent dimension of a stimulus, creating a cost when trials of the less frequent condition are processed (Lowe and Mitterer, 1982). For instance, if congruent trials constitute the rarest condition, latencies for these trials will increase compared to incongruent ones, reducing the interference effect. The reverse effect is obtainable by designing a task with less incongruent than congruent trials.

Second, to observe the contextual effect of the previous trials, it is possible to consider the analysis of a specific trial's latencies depending on the condition of the previous one. This effect, also known as the Gratton effect, reflects the modulation of the attentional and executive system when evolving from a congruent

to an incongruent trial and from an incongruent trial to a congruent one (Gratton et al., 1992).

To understand the mechanisms behind this effect, a comprehension of the features on which attention is focused for each condition is needed. On congruent trials, the attention is attracted to the word dimension. This statement is debated (e.g., Besner et al., 1997), but supported by some evidence. All cognitive systems tend to choose the most efficient way to process information. It has been shown that reading color words was faster than naming color patches (Cattell, 1886; Brown, 1915; Stroop, 1935). It implies that the most efficient way to process a congruent trial (e.g., the word "blue" written in blue font) would be to focus on the word instead of the color. This statement was favored by empirical evidence. The combination of word reading and color naming even speeds up latencies of congruent trials. This facilitation effect was found when congruent trials were compared to neutral words displayed in different colors (as, for instance, the word "house" written in blue) (van Maanen et al., 2009). It implies that a color word in a Stroop item involves the retrieval of at least the semantic information via the reading processes; even though not all word reading processes are fully implemented in the Stroop task.

Regarding incongruent trials, the attentional control is avoiding focusing on the word dimension and is centered on the color. According to Gratton et al. (1992), switching from a congruent to an incongruent trial is then more effortful than processing two consecutive incongruent trials, because in the latter context the attentional focus is already constrained on the color dimension and the conflict monitoring mechanisms are already on (Botvinick et al., 2001, 2004). In this seminal paper, the same effect was reported on congruent trials, showing a facilitation for a second congruent trial compared to a congruent trial preceded by an incongruent one. The exact cognitive mechanisms behind the Gratton effect are still intensively debated. Originally, Gratton and colleagues suggested that participants strategically expected the following trial to be from the same condition as the current one, which involved a preparation to deal with the next trial (Gratton et al., 1992). A few years later the conflict monitoring hypothesis was proposed, suggesting that the brain is equipped with a specific conflict monitoring system, which activates the resources to face a conflict (Botvinick et al., 2001, 2004). In the case of a repetition of incongruent trials, the conflict monitoring system does not need to be activated, which explains the observed facilitation of two subsequent incongruent trials. The contextual effect is no longer explained by strategic pre-orientation of attentional resources on the relevant dimension but by an automatic process located in the anterior cingulate cortex. However, this interpretation has also been questioned and alternative explanations such as the feature integration theory and contingency learning have been proposed (Duthoo et al., 2014b). It has been claimed, for instance, that the contextual effect was the result of visual features facilitation due to the repetition of the same item (Mayr et al., 2003). The experiment motivating this conclusion was centered on the Flanker task. This task contains a limited number of items, implying that the exact same item would be repeated from the previous trial to the current one multiple times during the task. In a second paradigm the effect was no longer significant since the same condition was repeated but without repetition of the exact same stimulus. Nevertheless, some studies replicated the paradigm with variable stimuli in the same condition and found a SCE (Wühr and Ansorge, 2005; Notebaert et al., 2006; Egner, 2007). A more strict interpretation of the repetition problem, called "feature integration theory" speaks for a modulation of the contextual effect if even some elements are repeated while some others are not (Hommel et al., 2004). According to the authors, each stimulus' dimensions are binned together and stored in an "event file." If part of the encoded features are repeated but some associated others are not, this creates an interference (Hommel, 1998).

An other issue regarding the type of stimuli included in the task has also been debated. In a Stroop task designed to elicit a SCE, only congruent and incongruent trials are usually included. However, the set of items is more limited in the congruent condition since the number of combinations of color fonts and color words is more limited in the congruent condition (both dimensions must match) as compared to incongruent condition. Therefore, the words in the congruent condition are more often associated to the correct response (i.e., the irrelevant information) which make them become more informative of the response (Mordkoff, 2012; Schmidt, 2013; Duthoo et al., 2014b). This imbalance might also contribute to the SCE, however, it probably does not explain it in its entirety either. A study using a six-colors oral Stroop task, which controlled for this bias, still found a consistent SCE (Duthoo et al., 2014a). As described above, many studies tried to identify the factors and cognitive mechanisms underlying the SCE. To further clarify the underpinning processes of the SCE, some researchers introduced neutral trials in the Flanker task (Kunde, 2003), or the Simon task (Wühr and Ansorge, 2005; Aisenberg et al., 2014). To our knowledge, Lamers and Roelofs (2011) were the only ones to design an oral and manual response Stroop paradigm including neutral trials to investigate if the Gratton effect was driven either by the reaction to the conflict, the reorientation of the attention, or by a combined effect of the two. Their results suggested that, independently of the modality of the response (verbal or manual), attention reorientation seems to be the main generator of the observed facilitation effect in the repetition of incongruent trials relative to incongruent trials preceded by another condition.

It should be noted that the conflict adaptation effect was named in different ways across the literature. It was first referred to as the Gratton effect, relatively to the seminal paper by Gratton et al. (1992), then conflict adaptation effect, and sometimes SCE. It is however not always clear whether these effects relate only to the comparison between a repetition of an incongruent trial as compared to an incongruent trial preceded by a congruent one, all the different combinations of previous and current trials, or the general contextual effects in which the current trials happen (i.e., the manipulation of the proportion of congruent and incongruent trials). In the studies presented here, since neutral trials will be added to the set of stimuli, some combinations of previous/current trials will not involve conflict, but a difference in the gradient of congruency. We will therefore use the term sequential congruency effect to describe

all the different combinations of previous and current trials, and Gratton effect on incongruent current trials to name specifically the facilitation due to the repetition of incongruent trials. The facilitation due to the repetition of two congruent trials compared to a congruent trial preceded by an incongruent one will be referred to as the Gratton effect on congruent trials.

To sum up, the SCE results in a complexification of the more basic interference paradigm which takes into account the previous trial's condition. Nevertheless, the effect proved its volatility since it has not been consistently replicated. Moreover, SCE and Stroop effects have been extensively investigated providing an in depth understanding of interference. Nevertheless, interference is not a static phenomenon. It is rather a dynamic process evolving throughout the human development (Comalli et al., 1962; Macleod, 1991; Li et al., 2009). However, virtually all the studies presented above recruited only young adults. A lifespan insight into the Stroop interference and SCE would therefore bring a better understanding of the ways humans process interference.

#### Lifespan Perspective of the Stroop Task

As many cognitive processes, the Stroop effect follows a U-shaped curve across the lifespan (Macleod, 1991). Interference is maximal during childhood, diminishes to become minimal during adulthood, and increases again with aging (Comalli et al., 1962). In children, the Stroop effect appears within the first year of reading acquisition, is maximal at this time of life, and decreases with age. The interference U-shaped distribution was not questioned until the last two decades, specifically regarding aging. Indeed, some studies reported a deficit in inhibition for the elderly (e.g., Andrés et al., 2008), while some others show a stabilization of inhibition performances (e.g., Sebastian et al., 2013) or even an improvement (e.g., Fernandez-Duque and Black, 2006). In particular, a recent meta-analysis (Rey-Mermet and Gade, 2018) concluded that when integrating processing speed by using derivate of mixed models analyses (state-trace analyses), the specific lifespan effect of inhibition disappeared.

There is clearly a need for additional investigations on the entire lifespan, focusing on either changes from childhood to adulthood or through aging (Craik and Bialystok, 2006). Regarding the SCE evolution across the lifespan, we are not aware of any study investigating how age impacts this effect all along the lifespan spectrum. There are, however, investigations on the transition from childhood to adulthood (Waxer and Morton, 2011; Kray et al., 2012; Larson et al., 2012; Ambrosi et al., 2016; Smulders et al., 2018) and on the transition from young to older adults (Puccioni and Vallesi, 2012; Aisenberg et al., 2014; Aschenbrenner and Balota, 2015; Xiang et al., 2016). These studies suggest that children show stronger interference effects and higher error rates relative to young adults, but when combining studies from the entire lifespan spectrum, the SCE seems globally stable across development, nonetheless showing stronger magnitudes at the extremities of the lifespan continuum. Studies using electrophysiological evoked potentials also failed to observe differences in the amplitude of the evoked potentials on the N450 component between children and young adults (Larson et al., 2012), suggesting that the processes underpinning the Gratton effect are identical in children and young adults. Another ERP study on different tasks (stimulus-response compatibility, Simon task and a hybrid choice-reaction/No-Go task) found differences in the magnitude of the Gratton effect between children and young adults (Smulders et al., 2018), which disappeared after correction of processing speed differences among the age-groups. Results on aging (Puccioni and Vallesi, 2012; Aisenberg et al., 2014; Aschenbrenner and Balota, 2015; Xiang et al., 2016), suggest that the Gratton effect is preserved. This paradigm helped clarify two main hypotheses regarding decrease in cognitive performances with aging (Puccioni and Vallesi, 2012). The first one stands for a general slowing explaining the exacerbated reaction times in the elderly (Salthouse and Badcock, 1991; Salthouse, 1996), while the second suggests that the elderly suffer from a frontal lobe degeneration, altering executive performances (West, 1996; West and Bell, 1997). Since the Gratton effect remained preserved with aging, the authors suggested that their results favored the general slowing hypothesis. This conclusion was corroborated by Aisenberg et al. (2014). By increasing the inter-stimulus interval, the authors reported normalized performances regarding the Stroop effect and SCE in aging. However, it is noteworthy to emphasize that some studies failed to replicate the Gratton effect either with young adults and elderly participants (Xiang et al., 2016). Since repetitions of the same dimension were avoided in the design of the task, the authors argued that the results favored the hypothesis of the feature integration theory. The results would then be attributable to the repetition of the same dimension's characteristic from the previous trial to the current one (Hommel, 1998; Mayr et al., 2003; Hommel et al., 2004).

To summarize, while the Stroop effect is among the strongest phenomena reported in cognitive psychology, the Gratton effect tends to be volatile, sometimes difficult to highlight and thereby rendering the interpretation of the involved cognitive processes difficult. It nevertheless emerges from the literature that the Gratton effect reflects, at least partly, the activity of the conflict monitoring mechanism (Botvinick et al., 2001, 2004; Duthoo et al., 2014b), pre-orienting the attentional focus on the relevant dimensions for the next trials. Regarding the lifespan evolution, the Stroop effect does not seem to be impacted by age, suggesting that processing speed is a much more relevant factor to explain age differences in inhibition. The SCE effect also tends to remain stable over the lifespan. Although both the SCE and lifespan approaches already represent valid methodologies to better understand the interference effect. To go further, we therefore suggest that new insights can be given through the inclusion of neutral trials to a SCE paradigm. In particular, we propose to dissociate the switching mechanisms from one dimension to another and the modulation of inhibition processes from one trial to the next over the entire lifespan, as detailed in the ensuing section.

## The Present Study: Beyond the Sequential Congruency Effect

As described above, the increased reaction times resulting in an interference effect in the Stroop task encompass the SCE.

In particular, the SCE can be further decomposed into the bidirectional reorientation of the attentional focus between the word or the color dimension and the engagement/disengagement of inhibition processes. To our knowledge, no study has tried to demonstrate this dissociation so far. However, some previous studies investigated the phenomenon of attentional capture by a salient stimulus close to the target followed by a reorientation of the attention from the distractor to the relevant target (Folk et al., 1992; Lamy et al., 2004; Serences et al., 2005; Chang et al., 2013). More precisely, a relatively close paradigm to the Stroop task was proposed in this domain (Serences et al., 2005; Chang et al., 2013). In these studies, the participants were asked to spot the red central letter among rows of letters displayed in different colors. The surrounding letters could be in red, in different colors, or in black. This paradigm allowed to isolate either the attentional capture effect alone or associated with the reorientation of the attention. Results suggest that attentional reorientation is a specific mechanism and the related brain regions activated involve mainly the temporo-parietal junction (although the involved brain network responsible for this reallocation of the attentional resources is still debated: Corbetta and Shulman, 2002; Geng and Vossel, 2013; Diquattro et al., 2014). Even though this task has some similarities with the Stroop task, it does not involve word processing. Moreover, in the SCE, the changes are made sequentially from the previous trial to the current one, while in the Serences et al. (2005) and Chang et al. (2013) studies, targets and distractors were presented simultaneously. To understand how the SCE was decomposed in subprocesses in the present study, **Figure 1A** represents the nine possible combinations of transitions from the previous trial

to the current one along with changes in the attentional focus and inhibition cost in a Stroop paradigm including neutral trials. In the present study, neutral trials were sequences of symbols presented in colored ink.

**Figure 1B** represents the expected results according to the division of the SCE into Gratton, inhibition and attentional reorientation effects. It is expected from the predictions of the Gratton effect, that when processing a repetition of incongruent (II)<sup>1</sup> trials, the second incongruent trial will show faster responses than an incongruent trial (I) preceded by a congruent trial (C), i.e., that (II < CI). A repetition of congruent trials (CC) should also be performed faster than a C trial preceded by an I (IC). Crucially, as shown in **Figure 1B**, an incongruent trial preceded by a neutral trial (NI) involves the engagement of inhibition load but no attentional reorientation. To isolate inhibition, an NI trial can be compared to an II trial, which involves the same processes, except for the engagement of the inhibition load. The same logic can be applied to the deactivation of the inhibition, by comparing IN trials to NN ones. To isolate the attentional reorientation processes, the cognitive cost caused by the switching from the color to the word dimension can be assessed by the comparison between NC and CC trials. The investigation of the opposite effect, namely the reorientation from the word to the color dimension, can be measured by comparing CN to NN trials. Finally, the Gratton effect implies a change in both dimensions simultaneously. It is nevertheless possible to identify other situations where both dimensions operate simultaneously. Between NC and IC, inhibition processes are deactivated while in both conditions the attention is reoriented from the color to the word dimension. In the NI – CI comparison, the attentional focus switches across dimensions and inhibition has to be activated. Therefore, the Gratton effect should be considered as the sum of the two subprocesses, since it involves a change in both dimensions.

Study 1 will focus on testing the theoretical framework described above regarding the decomposition of the SCE in attentional reorientation mechanisms and engagement or disengagement of the inhibition processes, then, Study 2 will analyze its evolution over the lifespan.

## STUDY 1

This study tests the SCE decomposition, inhibition, attentional reorientation effects and interactions between the two processes by adding neutral trials to the standard Stroop task on a group of young adults.

## Method

#### Participants

Twenty seven young adults (mean age = 24.4 years old, SD: 3; 17 women) were recruited for the purpose of this study. They were all native French-speakers, did not report any neurological, psychiatric, color vision or language impairment and received a financial compensation for their participation to the study. All of them gave a written informed consent and the local Ethics Committee approved the entire procedure (see **Appendix 1** for the gender and age distribution).

#### Materials

The stimuli were those of discrete standard Stroop tasks (from Fagot et al., 2008), namely four French color words ("bleu"; "jaune"; "rouge"; "vert", respectively: blue, yellow, red, and green) displayed in lower case, at the center of the screen in one of the four possible colors. The neutral stimuli were arrays of symbols ("++++"; "ˆˆˆˆ"; " "" "; "∗∗∗∗") presented in one of the four colors. The stimuli were either congruent (the color word matched the color in which the word was displayed), incongruent (the color word was displayed in a different color font) or neutral (a non-verbal symbol displayed in one of the different possible color fonts).

The total number of trials was 180, equally distributed among the three conditions (60 congruent, 60 incongruent, and 60 neutral). Stimuli order was pseudo-randomized by the Mix software (Van Casteren and Davis, 2006) to avoid the repetition of the same item, and allow a repetition of the same condition for a maximum of three consecutive trials. In addition, a color presented in the previous trial (target or distractor level) was not present in the following one, to prevent visual (and verbal) repetition, according to the "feature integration theory" (Hommel et al., 2004). As described in the Introduction section, the interference effect is maximized in SCE paradigms since word-color combinations are more numerous in the incongruent condition compared to the congruent one. This effect is known as the contingency learning effect (Mordkoff, 2012), and was controlled in the present study by adding neutral trials. In a Four colors Stroop task of 180 items, each color is therefore presented 15 times per Stroop condition.

#### Procedure

The subjects sat approximately 80 cm from a 17-inches screen (refreshment rate: 50 Hz). The experiment was performed on the E-prime software (E-Studio). Oral responses were recorded by a dynamic microphone, digitally amplified and the signal was redirected to a computer. Subjects had to produce only oral responses and reaction times were obtained by marking manually the onset of the production (the delay between stimulus presentation and vocal onset) during the pre-processing stage using the Check Vocal software (Protopapas, 2007).

 The stimuli were then displayed on a black background for 1500 ms, followed by a variable interstimulus black screen lasting from 1000 to 1200 ms. The timing was identical for all age groups. Participants were systematically asked to name the color in which the stimuli were displayed as fast and as accurately as possible, independently of the written sequence. Before the beginning of the task, the participants were trained on 32 trials including all possible stimuli combinations, to make sure they understood the task and to avoid a novelty effect on the first trials.

<sup>1</sup>Hereafter, transitions are indicated as the first letter of the previous trial next to the first letter of the current trial. For example, a congruent item preceding an incongruent one will be mentioned as a CI trial.

#### Data Analysis

For data cleaning purposes, a trial was considered as incorrect if the subject produced the wrong color name (even if the response was corrected), or if the subject did not give any answer. Incorrect responses and latencies exceeding two standard deviations from the individual mean reaction times were excluded from the latency analysis. For the congruent, incongruent and neutral conditions, the percentage of rejected trials were respectively 3.83, 17.07, and 3.02%. See **Appendix 5** for the percentage of excluded trials among SCE conditions. In addition, the first trial of each subject has not been analyzed as a SCE trial since there was no previous trial.

Analyses were performed using the R software (R Core Team, 2019). Data wrangling was mainly performed using the dplyr (Wickham et al., 2019) and tidyr (Wickham and Henry, 2019) packages, while statistical analyses were computed with the base package, lmerTest (Kuznetsova et al., 2017) and Lme4 (Bates et al., 2017) using the mixed models lmer function. Errors were analyzed by generalized mixed models using the glmer function.

Since contrasts were explored by turning over the intercept variable of the model to target all relevant comparisons, the resultant multi-testing bias was corrected using the Bonferroni method (Bonferroni, 1936). Therefore, the significance threshold was divided by the number of necessary models.

#### Results

In the Stroop task, overall production latencies were the fastest for neutral trials, and latencies were faster on congruent trials than on incongruent trials. **Table 1** displays the mean reaction times for the current condition and for the previous trial condition. When considering the previous trial's condition, an incongruent previous trial causes larger interference on the processing of the next trial than any other condition, while the congruent condition seems to be facilitatory for the next trial. Regarding accuracy, the best performance was observed in the congruent condition, while the incongruent condition generated the highest error rate. A previous incongruent trial tends to lead to higher error rates on the current trial, while a congruent previous trial minimizes the chances to commit errors as compared to the other two conditions. SCE latencies and error rates are presented in **Figure 2**.

Results of the Stroop and SCE were included in a linear mixed model. Model selection was performed by loading the random part of the model with all relevant variables as random slopes and intercepts, and reducing this random part until the model

TABLE 1 | Mean reaction times and accuracy rate per condition, separately for the current and the previous trial.

converged. Then, the most complex random structure able to converge was adopted (regarding model selection, see Zuur et al., 2009). More precisely, in a first model, all fixed factors were added as a random slope (Barr et al., 2013; Matuschek et al., 2017). Since the model did not converge, interactions between factors was removed at first and then the less relevant factors were removed hierarchically from the model. After several attempts, only the current trial was supported as random slope. Regarding random intercepts, the participants (Subject) and Items variables were retained. Regarding fixed factors, the model included the previous and current condition, the stimuli presentation order as well as the interaction between the previous and current condition to account for an eventual learning or fatigue effect occurring during the task (complete model detailed in **Table 2A**).

The general model showed a main effect of the current condition, the previous condition, a main effect of stimuli presentation order, as well as a significant interaction between the previous and the current condition.

The Stroop effect (latencies on incongruent trials compared to congruent ones) was replicated. Moreover, latencies on incongruent trials were also significantly slower than on neutral ones. Finally, the congruent and neutral conditions did not differ significantly. The decomposition of the previous trials main effect showed that all contrasts are significant, which confirms that compared to both neutral and congruent conditions, an incongruent previous trial interferes with the processing of the following one (see **Table 2B** for detailed results).

Regarding the post hoc decomposition of the SCE conditions, six models (two per current trial condition) were necessary to estimate the results. The original data was divided in three data frames, one for each current trial condition, and one model was run for each data frame including the previous trial condition (presented in **Table 3**). Since there are three previous possible conditions, two models per condition were necessary. As shown in **Figure 3**, there is only a partial effect of the SCE, since the Gratton effect on incongruent trials was not replicated (II trials are not performed faster in comparison to CI trials). This result is in opposition to the Gratton effect on congruent trials (facilitation for CC trials compared to IC trials), which was strongly significant. Regarding the division of the SCE, concerning the attentional reorientation, both effects returned significant. Although, regarding the inhibition activation and deactivation, only the contrasts corresponding to deactivation (NN vs. IN) reached significance. As shown in **Figure 3**, neither of the comparisons implicating an effect of both attention and inhibition simultaneously reached significance.

Errors were analyzed using generalized linear mixed models according to a binomial distribution. The results (see **Table 4**) show a significant difference between the congruent and incongruent conditions with increased error rates in the latter, as well as between the incongruent and neutral condition, but no difference between the congruent and neutral conditions was seen.

#### Discussion Study 1

This first study aimed at establishing whether the SCE embedded other processes which can be isolated by adding neutral trials to

In first line the lmer R function generating the model and (B) post hoc results (after Bonferroni correction, <sup>∗</sup> the significance threshold equals 0.025) of the current and previous trials condition.

a Stroop task. As highlighted in the Introduction section, two processes can be isolated: an attentional reorientation mechanism from the color to the word dimension and vice versa and the engagement/disengagement of the inhibition load. Results of Study 1 partially sustain the involvement of these processes. First, the Gratton effect on incongruent trials was not replicated, even though the same effect on congruent trials, i.e., a facilitation of CC trials relative to IC trials, was observed. As already described in

To obtain these values, six models were mandatory, implying that, according to Bonferroni correction method, <sup>∗</sup> the significance threshold is reduced to 0.008.

the Introduction, the Gratton effect on incongruent trials is very volatile and several studies failed to replicate it (Mayr et al., 2003; Lamers and Roelofs, 2011; Kreutzfeldt et al., 2016; Xiang et al., 2016). From a cognitive point of view, the effect relies on a reduction of the interference effect by a preparedness from the attentional and executive systems to face a conflict. However, if the conflict is too strong for the current trial, the facilitation effect is reduced or suppressed. The cost of the incongruent trials may explain the absence of a Gratton effect in the present study. However, the absence of the Gratton effect may also be related to a limited number of trials (N = 180) or subjects (N = 27), or to the presence of the neutral trials themselves. It has actually been reported that increasing the stimulus set size might increase the interference effect (Gholson and Hohle, 1968; Fraisse, 1969; Macleod, 1991), but this factor is also known to reduce the SCE (Kray et al., 2012). In the present experiment, by adding neutral trials, the number of stimuli increased, reducing the possibility to anticipate the next trial's condition (Gratton et al., 1992; Schmidt and De Houwer, 2011). Moreover, since the design of the study was done to control for the bias described in the "features integration theory" (Hommel et al., 2004), there was no repetition (on both dimensions, i.e., the color font or the color word) from the previous trial to the current one. When this effect is controlled for, a strong reduction of the SCE is observed, therefore also contributing to the absence of effect in this study. Moreover, by introducing neutral trials, the classically observed contingency learning effect was controlled for. As described in the Introduction, this effect reflects the non-conscious association between the color word and the color font as in a Stroop task including the same number of congruent and incongruent trials, the color word is significantly more often associated with the correct response. However, in the present paradigm, the effect has been counterbalanced since neutral trials were added.

It has been suggested in the literature that the Gratton effect is due exclusively to the preparedness to the conflict resolution (Botvinick et al., 1999, 2001, 2004). However, when adding neutral trials, some of the comparisons do not contain conflictual trials, and facilitation effects were also highlighted. This suggests that conflict adaptation as triggered by a preactivation of

TABLE 4 | Results of the generalized linear mixed models estimating differences between conditions regarding the accuracy.

Two models were necessary to perform all the comparisons, according to the Bonferroni correction, <sup>∗</sup> the significance threshold equals 0.025.

the conflict monitoring hypothesis, is a component of the SCE but it is not the only mechanism involved. Attentional reorientation and specific manipulation of the inhibition load (activation/deactivation) seems to be one of them. Here, with the isolation of further processes, a significant increase of RTs was observed for the conditions including an attentional reorientation from the color dimension to the word dimension and from the word dimension to the color one. Since only congruent and neutral trials entered this comparison, these results tend to validate that the mechanism of attentional reorientation also causes an increase of RTs independently of incongruence. Finally, the activation of the inhibition resources from the previous trial to the current one was not significant (NI as compared to II), whereas deactivation increased the latencies (IN as compared to NN). To understand this effect, we need to emphasize that the SCE involving incongruent current trials relies on a diminution of the interference. This partial effect could reflect the fact that a threshold is reached after which the SCE is not strong enough to minimize the interference.

Before any further interpretation of the results, we will investigate in Study 2 whether the same results are observed with a larger sample and how these effects evolve over the lifespan.

## STUDY 2

The paradigm was virtually identical to Study 1, but involving a larger sample of participants covering six age groups from school-age children to 80 year-old adults. As discussed in the Introduction, the interference effect is known to remain stable over the lifespan, except if processing speed is controlled for. We will therefore divide the classical interference index (I-C) by the neutral trials' latencies to control for processing speed. As processing speed is neutralized in the SCE analyses (since only one dimension is manipulated independently of the other involved processes), the results of the SCE should remain globally stable with aging. This trend should also be generalizable to the other age groups (school-aged children), even though the underlying cognitive processes are probably different. Although inhibition seems to remain stable across the lifespan, the literature does not provide hints about the lifespan evolution of other executive processes such as the reorientation of the attentional focus to one specific dimension. However, under the assumption that the absence of lifespan effects is generalizable to other executive mechanisms, a lifespan evolution of attentional reorientation should not be observed either.

## Method

#### Participants

Hundred and twenty four participants, including the first 20 participants from Study 1 [aged 10–80 years-old, mean age: 39.8 years (SD = 24)] were recruited from six age groups (10–13, 16–18, 20–30, 40–50, 60–70, 70–80). All participants were native French-speakers, without self-reported neurological, language, color perception, or psychiatric impairment and received a financial compensation for their participation to the study. All participants signed a written consent and the entire procedure was approved by the local Ethics Committee.

#### Materials and Procedure

Materials and procedure were identical to Study 1 (see **Appendix 1** for gender and age distribution among the different age groups).

#### Data Analysis

Data preprocessing followed the same procedure as described in Study 1. Four participants with mean RTs more than 2 SD away from the mean of their age-group were excluded (one from the age-group 16–18, one from the age-group 40– 50, and two from the age-group 60–70). Regarding extreme reaction times, congruent, incongruent and neutral conditions respectively showed a 4.36, 16.77, and 3.3% of rejected trials. For SCE conditions over the lifespan and specifically per age groups, see **Appendix 5**.

To analyze whether processing speed plays indeed a role over the lifespan, in addition to the standard interference index (estimated by subtracting the averaged congruent latencies from the incongruent ones:I–C), a second score was computed by dividing the standard interference score by the averaged neutral trials latencies for each subject. A one-way ANOVA assessed the evolution of each of these scores across the lifespan.

The SCE and the isolation of attentional reorientation and inhibition activation or deactivation was investigated by mixed models analyses, following the same principles as analyses performed in Study 1, except for adding the age groups as a fixed effect. Error analyses followed the same logic.

#### Results

#### Corrected and Uncorrected Interference Indexes Over the Lifespan

Regarding the evolution of the standard interference score (I - C) over the lifespan, the one-way ANOVA for uncorrected interference indexes revealed a significant main effect of age groups [F(5,111) = 4.07, p = 0.002]. According to the Tukey test and as shown in **Figure 4**, children aged 10–13 were significantly slower than young adults aged 20–30 [t(111) = 3.3, p = 0.02, SE = 18.29, β = 60.34], and than adults aged 40– 50 years [t(111) = 3.27, p = 0.02, SE = 18.53, β = 60.62]. Older adults (60–70 years old) showed larger interference than younger adults [relative to 20–30 years old: t(111) = −3.05, p = 0.03,

SE = 18.8, β = −57.4; and to 40–50: t(111) = −3.03, p = 0.03, SE = 19.03, β = −57.69].

With the corrected interference index((I–C)/N), the analysis showed a main effect of age groups [F(5,111) = 2.36, p = 0.04], but none of the post hoc comparisons reached significance after correction (see **Appendix 2** for detailed results).

#### Sequential Congruency Effects

Latencies and error rates of the SCE conditions are presented in **Figure 2** and **Appendix 3**. The results of the mixed model on latencies are presented in **Table 5**. The final model highlighted a significant main effect of the current trial condition, a significant main effect of the previous trial condition, and a significant main effect of stimuli presentation order. Previous and current trial conditions interact with age and, crucially, a significant interaction between the previous trial condition and the current condition is observed, without a triple interaction with age.

Since raw reaction times were expected to evolve following a U-shaped curve, a linear model could be biased relative to the quadratic shape of the curve. To further analyze this issue, two models were generated. The first one compared age groups from children to young adults, while the second one compared the young adults to older ones. Results were globally similar for both halves of the lifespan, except for stimuli presentation order, which was no longer significant in the second part of the lifespan, as well as the interaction between the current trial and the age groups which was significant only for the second half of the lifespan (results are presented in **Appendix 4**).

The post hoc decomposition of the model presented in **Table 5B** highlighted a significant difference between current congruent and incongruent conditions (the standard Stroop interference effect), as well as significantly slower reaction times for the incongruent condition compared to the neutral one. Congruent and incongruent conditions were not significantly different. Regarding the previous trials condition, all three conditions differ from each other, and a previous incongruent trial alters the processing of the next trial, independently of the next trial's condition.

Since the interaction between the previous and current conditions was significant as well, but not the triple interaction with age groups (see **Table 5A** above), contrasts were computed across all age-groups. As in Study 1, the original data frame was divided in three sets, each including only congruent, incongruent or neutral current trials conditions. A mixed model analysis was performed on each data frame with the previous trial's condition as a fixed effect, the previous trial's condition as random slopes, and subjects and item as random intercepts. Results are presented in **Table 6** and **Figure 5**.

Errors were analyzed using generalized linear mixed models. The model included as fixed effects the current and previous conditions, and the Subject and Item variables as random factors. Interactions between the previous, the current trial and with the age-groups was not included in the final model since it failed to converge. Results, as presented in **Table 7**, suggest that all conditions were significantly different from each other.

## Discussion Study 2

This second study aimed at assessing interference and SCE as well as the specific contribution of their subprocesses over the lifespan. The present study examined effects of a bidirectional attentional

#### TABLE 5 | (A) Main effects and interactions of the general model, and (B) contrasts on current and previous trial condition.

#### (A) Model: lmer(log(RT)∼ Previous.trial∗Current.trial∗Age.groups + Presentation.order + (1 + Current.trial| Subjects) + (1| Items), data = data, REML = FALSE)

<sup>∗</sup>The significance threshold was reduced to 0.008.

TABLE 6 | Summary table of the mixed models used to estimate the SCE conditions.

Seven models were necessary to estimate all the comparisons. After Bonferroni correction, <sup>∗</sup> the significance threshold was reduced to 0.008.

reorientation and engagement or disengagement of inhibition in a larger sample, as well as their evolution over the entire lifespan.

First, the standard Stroop interference index showed a main effect of age groups and significant differences, especially between the groups at the two extremities of the lifespan and those in the middle. However, the corrected version of the interference index ((I–C)/N) did not show any significant difference across age. This finding is in line with the literature claiming that there are no influences of aging on performance when the processing speed factor is controlled for (Aisenberg et al., 2014; Rey-Mermet and Gade, 2018; Smulders et al., 2018).

Second, the results on the SCE replicated those of Study 1 with a larger sample, showing again that the Gratton effect on incongruent trials is not robust (see Discussion of Study 1). Contrariwise, clear effect of attentional reorientation in both directions (from color to word or from word to color) appeared significant. On the larger group of Study 2, both activation and deactivation of inhibition slowed down production latencies, whereas only deactivation reached significance in Study 1. Notably, the inhibition activation effect goes in the opposite direction, suggesting that, inconsistent trials seem to be more effortful when preceded by an incongruent trial (II) than when preceded by a neutral trial (NI). This favors the interpretation mentioned in the discussion of Study 1, suggesting that the SCE was not powerful enough to reduce the interference effect. This effect in contradiction with the predictions (II slower than NI) might reflect an overload in terms of cognitive control, impacting nonetheless the previous trial but there seems to be a carry-over effect of the previous trial, impacting also the successive one. This finding is in line with the literature on other tasks suggesting that there is a reset of the attentional system (Kreutzfeldt et al., 2016), requiring time before being able to process a new item. This interpretation

is supported by the post hoc decomposition of the results showing that a previous incongruent trial increases significantly the latencies of the current one, independently of the current trial condition.

As described above, subprocesses were isolated from the SCE by adding neutral trials to a Stroop paradigm. These subprocesses are namely the disengagement of the inhibition resources and the reorientation of the attention, either from the word to the color dimension or the opposite direction. Both of the subprocesses returned significant with a larger sample. Moreover, the comparison involving both mechanisms: the transition from NC to an IC trial translating the cost due to an inhibition reduction while the attentional system is redirected to the word dimension is now significant. This new effect favors a role of the sample size in the results.

## GENERAL DISCUSSION

The present study aimed at investigating if different processes embedded in the Stroop interference effect and more precisely the SCE could be disentangled. In particular, we tried to isolate the effect of attentional reorientation from the color word to the color font dimension and the engagement/disengagement of the inhibition resources from one trial to the next. This was achieved by adding neutral trials to a SCE in a Stroop paradigm (non-verbal signs displayed in different colors) requiring oral responses. In a first study, this dissociation was tested on a group of young adults, while in Study 2, the isolation of attentional reorientation and inhibition processes was investigated on a larger sample, covering the entire lifespan.

## Standard Stroop Interference Effect

The standard interference effect was found in young adults as well as in the other age groups. The effect was larger in the youngest and oldest groups, following a U-shaped curve over the lifespan as previously reported (Comalli et al., 1962; Macleod, 1991; Li et al., 2009). Nevertheless, processing speed seems to be responsible for a large part of the observed difference among age groups. Indeed, when interference is corrected for processing speed (by dividing the interference index by the latencies of the neutral trials), age effects disappear. This latter observation is in line with recent results on aging (Rey-Mermet and Gade, 2018). To our knowledge, the effect of processing speed on differences in interference observed in the younger age groups have not been reported so far. Since interference is known to remain stable with aging when processing speed is controlled for, it was expected that the same effect would be observable for the group of children. The involved mechanisms are not necessarily identical for the two extremities of the lifespan, even though the behavioral results are similar. Interestingly, our results confirmed that for children as well, processing speed is the major dimension responsible for the evolution of the standard Stroop interference index. This finding implies that processing speed plays a key role in the evolution of the latencies over the lifespan.

## Sequential Congruency Effect

As reviewed in the Introduction, several theoretical accounts provide an understanding of the processes underlying the SCE. In Study 1 in a sample of young adults, there was a significant Gratton effect on congruent current condition whereas the same facilitation on incongruent trial did not reach significance. Among the possible interpretations of the lack of Gratton effect on Study 1 we evoked the sample size. However, this assumption has been disproved since the results remained globally identical in Study 2 on 124 participants. The quite low number of trials (180) could have been an explanation of the results, nonetheless, a study comparing a 384 trials task with a 192 trials one, reported virtually the same results, namely a consistent

TABLE 7 | Summary table of the generalized linear mixed model used to appreciate the differences between the three current items conditions regarding errors.

To estimate these post hoc, two models were necessary, implying that <sup>∗</sup> the significance threshold was divided by two and equals 0.025.

SCE in the Stroop task for young adults and elderly subjects (Aschenbrenner and Balota, 2017).

Regarding the involved mechanisms, the present study supports at least a mechanism of modulation of the inhibition load, which could favor the hypothesis of conflict monitoring. Moreover, the results strongly support attentional reorientation as a component of the effect. However, despite the fact that the design of this study controlled for biases such as the contingency learning effects (Mordkoff, 2012; Duthoo et al., 2014b), features integration theory (Mayr et al., 2003; Hommel et al., 2004), and repetition expectancy (by increasing the stimulus set size) (Gratton et al., 1992), no facilitation effect was found for a repetition of incongruent trials (II) as compared to CI. These effects might have diminished the Gratton effect on incongruent current trials, explaining the non-significant result. This interpretation is corroborated by the unexpected result that a repetition of incongruent trials (II) is more interfering than NI. Nevertheless, these alternative mechanisms cannot explain the entirety of the effect, as already suggested in the literature (Egner, 2007; Schmidt, 2013; Duthoo et al., 2014b). It is therefore possible that the Gratton effect could emerge with such a paradigm only when the right balance between interference effect and SCE is found. This can be achieved by reducing the interference effect, for example by adding an asynchrony of the stimulus onset between the color word and the color font presentation. It has been suggested that the Stroop interference effect could be reduced when presenting the color word distractor 400 ms before the color to name (Glaser and Glaser, 1982; Coderre et al., 2011) or when using a single centered colored letter (Besner et al., 1997; Augustinova et al., 2010). Regarding the Gratton effect on congruent trials, our results are in line with the literature and show that CC sequences are processed faster than IC sequences, which favors the hypothesis of a carry-over effect of the interference from a previous incongruent trial to the next one. In the same way age effects no longer appeared for speed corrected interference, age did not seem to interact with the SCE. This finding suggests that there is a potential stability of the effect over the entire lifespan. It seems therefore that control adjustment processes are functional already in school-age children and are preserved during aging. There is a discrepancy in the literature regarding the evolution of the SCE over the lifespan. Since no previous study investigated the entire lifespan, results will first be confronted to the results of studies investigating the changes during development and then to those on aging. From childhood to adulthood, the SCE is present and is consistently increased in children as compared to young adults. Regarding ERP data, results tend to show a stability of the N450 between children and adults (Larson et al., 2012). The present results seem to be in opposition with these arguments, as previous literature tends to favor the hypothesis that there is an evolution of overall performances. Results on older age groups are not as consistent. On the other hand, some results on the evolution of the SCE in aging suggest that the effect is increased, at least in a Stroop task with button press responses (Aschenbrenner and Balota, 2017), and in other attention and inhibition tasks (Smulders et al., 2018). Other studies tend to show a stability of performances across ages (Aisenberg et al., 2014; Larson et al., 2016). The present results also favor a stability of performances over the lifespan. However, as neutral trials were included in the present design, we cannot exclude that the SCE relies at least partly on the ability of the participant to predict the next trial's condition (Gratton et al., 1992; Mordkoff, 2012; Duthoo et al., 2014b). In which case results may evolve across the lifespan with a different design (with only congruent and incongruent trials). Nevertheless, such an explanation based on prediction cannot support the entirety of the SCE effects, since some contextual effects were reported on other SCE conditions.

Latencies show that elderly subjects only need more time, which may underlie the observed changes in raw performance (Aisenberg et al., 2014). This observation is in line with the general slowing hypothesis (Salthouse and Badcock, 1991; Salthouse, 1996), and is less compatible with the specific frontal lobe degeneration hypothesis leading to a reduction of executive functions, since all age groups seem to be homogeneous (West, 1996; West and Bell, 1997). However, since this conclusion relies on an absence of effect, further investigations should try to replicate these results.

#### SCE Versus Standard Interference Effect

Finally, the main aim of this study was to demonstrate that the SCE allows the isolation of other embedded processes, namely the reorientation of the attentional focus from the color to the word dimension or to the opposite direction and the engagement or disengagement of the inhibition load. The results of Study 1 and Study 2 support the implication of such mechanisms on top of the Gratton effect. However, the detailed subprocesses are clearly at play when the current trial is inconsistent, whereas they are not significant or effects are in the unexpected direction on the incongruent current trials. As suggested also by the results of Lamers and Roelofs (2011), the cost of processing incongruent trials is probably too high to allow sequential switching effects to emerge on incongruent current trials, but it clearly affects negatively the processing of the following trial whichever it is (see **Table 1**). This might be due to a carry-over effect of the interference from the previous trial, affecting the next one. To sum up, from the moment a Stroop trial is presented among other trials, the context in which it is presented will have an impact on the intensity of the interference effect. It has been widely described that conflict monitoring is a mechanism involved in

the preparedness to react to a potential conflict (Botvinick et al., 2001, 2004; Egner, 2007). The present results nevertheless suggest that attentional reorientation as well as specific adjustments of the inhibition load also play an important role in this effect.

Some limitations must be addressed in the current study. First, the number of trials (180) is not as high as in the majority of the studies. Although it has been suggested that this factor should not impact the results (Aschenbrenner and Balota, 2017), and additional studies seem necessary to understand how such effects are modulated by the number of trials. Second, by attempting to correct for a maximum of biases in the study such as the contingency learning effects (Mordkoff, 2012; Duthoo et al., 2014b) and the features integration theory (Mayr et al., 2003; Hommel et al., 2004), the number of SCE items are not perfectly balanced across all combinations of previous-current trials, which could have impacted the results. However, by adding neutral trials, the number of items increased as well, making the prediction of the next trial's condition much more difficult.

## CONCLUSION

The two studies showed that the SCE can be further decomposed into attentional reorientation mechanisms (from the word to the color dimension and from the color to the word dimension) and the engagement/disengagement of the inhibition load from one trial to the next. This was achieved by including neutral trials in a SCE design of a Stroop task. The results suggest that both decomposed processes are relevant to (young) adults as well as over the entire lifespan. The identified SCE subprocesses do not change across the different age groups, as well as the standard interference effect when processing speed is controlled for. The present findings also confirm that the Gratton effect is very volatile and might be influenced by the presence of neutral trials, or other task design related effects. Finally, the present studies highlighted the importance of taking into account the attentional reorientation as much

#### REFERENCES

as inhibition modulation mechanisms when dealing with interference effects.

#### DATA AVAILABILITY

The datasets generated for this study are available on request to the corresponding author.

#### ETHICS STATEMENT

Human Subject Research: The studies involving human participants were reviewed and approved by the Ethics Committee of the University of Geneva. Written informed consent to participate in this study was provided by the participants' legal guardian/next of kin.

#### AUTHOR CONTRIBUTIONS

Both authors contributed directly to the realization of the manuscript and approved it before submission. EM was involved in the data acquisition, analyses, interpretation, and manuscript writing and editing. ML supervised the work, and actively contributed to the manuscript edition and revision.

#### FUNDING

This research was funded by the Swiss National Science Foundation (SNSF), grant no. 100014\_165647.

## SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyg. 2019.02028/full#supplementary-material

Fraisse, P. (1969). Why is naming longer than reading? Acta Psychol. 30, 96–103.

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2019 Ménétré and Laganaro. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

## The Stroop Effect Occurs at Multiple Points Along a Cascade of Control: Evidence From Cognitive Neuroscience Approaches

#### Marie T. Banich\*

Institute of Cognitive Science, Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, United States

This article argues that the Stroop effect can be generated at a variety of stages from stimulus input to response selection. As such, there are multiple loci at which the Stroop effect occurs. Evidence for this viewpoint is provided by a review of neuroimaging studies that were specifically designed to isolate levels of interference in the Stroop task and the underlying neural systems that work to control the effects of interference at those levels. In particular, the evidence suggests that lateral prefrontal regions work to bias processing toward the task-relevant dimension of a Stroop stimulus (e.g., its color) and away from the task-irrelevant dimension (e.g., the meaning of the word). Medial prefrontal regions, in contrast, tend to be more involved in response-related and late-stage aspects of control. Importantly, it is argued that this control occurs in a cascade-like manner, such that the degree of control that is exerted at earlier stages influences the degree of control that needs to be exerted at later stages. As such, the degree of behavioral interference that is observed is the culmination of processing in specific brain regions as well as their interaction.

#### Edited by:

Benjamin Andrew Parris, Bournemouth University, United Kingdom

#### Reviewed by:

Emily Coderre, Johns Hopkins University, United States Kira Bailey, University of Missouri, United States

> \*Correspondence: Marie T. Banich<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Cognition, a section of the journal Frontiers in Psychology

Received: 16 May 2019 Accepted: 09 September 2019 Published: 09 October 2019

#### Citation:

Banich MT (2019) The Stroop Effect Occurs at Multiple Points Along a Cascade of Control: Evidence From Cognitive Neuroscience Approaches. Front. Psychol. 10:2164. doi: 10.3389/fpsyg.2019.02164 Keywords: Stroop, fMRI, dorsolateral prefrontal cortex, anterior cingulate, event-related potential

## INTRODUCTION

The premise of this article is that neuroimaging studies can provide unique insights into the locus of the Stroop effect. For purposes of this paper, we will define the Stroop effect as the inference that occurs between two dimensions of stimulus, one of which is task-relevant and one of which is taskirrelevant. Generally, when these two dimensions are incongruent (e.g., the word "red" printed in blue ink), more cognitive control is required than when the task-irrelevant information is congruent (e.g., the word "red" in red ink) or has no relationship to the task-relevant information (e.g., the word "sum" in red ink). In this paper, it will be argued that this interference can occur at a variety of levels. Furthermore, I will argue that neuroimaging studies can help identify the loci at which such interference occurs to a degree that may not always be possible in behavioral studies.

More specifically, behavioral studies have limitations in isolating the locus of the Stroop effect because it reflects the sum of processes yielding a final outcome of processing as reflected in reaction time or error rates. Since, as will be argued, the Stroop effect can be generated, and also influenced by control, at multiple levels along a cascade of control, cognitive neuroscience approaches can help to identify the multiple levels of interference and control. While careful experimental design

Yet, at the same time, simply examining which regions of the brain become active during performance of the Stroop task is not likely to yield critical information with regard to the potential loci of the Stroop effect. While there have been a number of metaanalyses to isolate brain regions consistently engaged during performance of Stroop-related paradigms with regard to both the more traditional Stroop tasks (e.g., Derrfuss et al., 2005) and variants (Feng et al., 2018), they do not necessarily provide insight into the locus of the Stroop effect. The reasons are that such meta-analyses aggregate findings across different variants of the Stroop task (discussed in more detail below) that may differ in the specific locus or loci that are most engaged by that variant (e.g., a vocal response vs. manual response Stroop task). Furthermore, such studies are often designed to examine cognitive control in general and not specifically designed to uncover the potential loci of the Stroop effect.

For that reason, in this paper, I review the findings of studies designed to isolate the different loci of the Stroop effect and their neural underpinnings, many of which are drawn from our laboratory's program of research that has melded specific behavioral paradigms with a cognitive neuroscience approach. From such work, we have proposed a model elucidating the brain systems that act with regard to the various loci of interference that can be engendered during the Stroop task (see **Figure 1**), as well as outlining a cascade of control between brain regions that influences the final behavioral interference effect that is observed.

As an overview, the cascade-of-control model suggests there are at least four important processes and brain loci that influence the Stroop effect. The first process, implemented by posterior regions of lateral prefrontal cortex, biases processing in posterior brain regions toward information that is most taskrelevant and/or away from information that is task-irrelevant. The second process, implemented by mid-dorsolateral regions, biases selection toward that information in working memory that is most relevant for the current task goal. The third process, implemented by caudal mid-cingulate regions, is involved in latestage selection, usually those that are response-related. Finally, rostral dorsal regions of the anterior cingulate cortex (ACC) evaluate the appropriateness of the response selected and send feedback to lateral prefrontal regions to make adjustments in control as needed.

Importantly, this model argues that the degree of Stroop interference observed and how it is controlled depend on how well earlier portions of the cascade, in this case mediated by lateral prefrontal regions, create an appropriate task set. To the degree that such control is not well enabled, medial brain regions, most notably portions of the ACC, must then exert control at later response-related stages of selection. Hence, the "locus" of the Stroop effect in any given experiment is influenced by the activity in and relationship between brain regions, as well as by the specific attributes of a given Stroop paradigm with regard to how much it taxes each of the four processes described above.

Before turning to the studies supporting this model, it should be noted that for purposes of this paper, the classic Stroop task as well as variants will be considered. Because what people describe as a "Stroop task" actually encompasses a family of tasks, we use a specific-naming convention to provide a bit more precision regarding the tasks being discussed. The phrase before the hyphen refers to the task-relevant dimension and the phrase after the hyphen refers to the task-irrelevant dimension. So, for example, the classic Stroop paradigm will be referred to as the color-word Stroop task, as the individual must identify the color in which an item is presented and ignore the meaning of the word.

## INTERFERENCE BETWEEN TWO PROCESSES THAT VARY IN THEIR AUTOMATICITY OR CONTROL DEMANDS

One level at which the Stroop effect occurs is through competition between two distinct processes, one that is more automatic and engaged by the task-irrelevant dimension and another that is less automatic, but which requires processing of the task-relevant dimension so as to meet task demands. In the classic color-word Stroop paradigm, word reading is more automatic than color identification. As such, it requires cognitive control to overcome the tendency to read the word and base a decision on that information to prioritize processing of ink color so as to guide responding.

This aspect of the Stroop task is well captured in computational models of the Stroop task, which includes a "prefrontal" unit that increases activation in units processing color so as to bias the competition toward that process, rather than word identification, in influencing response selection (Cohen et al., 1990). Behavioral evidence suggests that indeed it is the degree of engagement of the word reading process that influences the size of the Stroop effect (Monsell et al., 2001), with greater increases in the latency of color naming for words and pseudowords, which are more likely to engage word reading processes, than for consonant strings, "XXXXXs" or false fonts, which are less likely to engage word-reading processes.

Sometimes, word reading can be engendered not because of the "word-likeness" of letter strings, but because the meaning of the words enable attentional capture. This likely is the locus of interference observed in the emotional Stroop task, which is in essence a color-emotional word task by our nomenclature. In this task, there are various conditions. In one condition, the color of emotionally salient words, which can be either negative or positive in valence, such as "murder" or "joy," must be identified as compared to emotionally neutral words (e.g., "bench"). Here, word reading is engaged for emotionally salient words because they are thought to capture attention as compared to emotionally neutral words, making identification of the ink color difficult. In fact, the interference effect is reduced in this task vis a vis interference on the color-word task (e.g., Kaiser et al., 2015).

fpsyg-10-02164 October 4, 2019 Time: 18:35 # 2

Moreover, effects in the emotional Stroop task are sometimes hard to observe and may only occur in those individuals for whom the words have particular emotional significance (e.g., threat words for individuals who suffer from anxiety).

depends on how well control has been implemented at prior points in the cascade.

Conversely, manipulations that make the task-relevant dimension more salient can reduce the Stroop effect. In one study, Krebs et al. (2013) used a picture/scene-word Stroop task, in which individuals decided whether a picture represented an indoor or an outdoor scene on which was superimposed a taskirrelevant word ("outside" or "inside" in Dutch). Participants had previewed some of the picture scenes prior to the Stroop task while others were novel. Novel pictures, which are more likely to capture attention, were associated with reduced behavioral interference.

Although one must be careful in making reverse inferences from patterns of brain activation to cognitive processes (Poldrack, 2011), brain imaging studies can provide insights into the degree to which this competition between a more automatic and less automatic process engenders Stroop interference. In a study to examine this issue, Banich et al. (2000b) compared brain activation for two variants of the Stroop task, the standard colorword task and a color-object task, to reveal that automaticity of processing is critical for engaging cognitive control regions, more specifically the dorsolateral prefrontal cortex (DLPFC) and the inferior frontal gyrus (IFG). In the color-object task, individuals had to identify the color in which an object was displayed. On incongruent trials, objects were shown in an atypical color (e.g., a frog displayed in red, when frogs are typically green; a banana displayed in blue, when bananas are typically yellow). Brain activation was compared to neutral trials, in which the object displayed typically can occur in a variety of colors (e.g., a car displayed in red, when cars can be red, blue, gray, white, black, green, etc.).

For both the color-word and color-object tasks, for a given condition, individuals were told to monitor one (but not the other) dimension of the stimuli, making it task-relevant. Their task was to indicate when an item with a given characteristic appeared. For example, for the color-object task, one condition required individuals to monitor for an item in a specific color (e.g., purple), making color task-relevant, while in the other

conditions, they monitored for a given "word" (a non-sense word), making the word task-relevant. Likewise, in the colorobject task, in one condition, individuals were once again told to monitor for the color purple, and in the other condition, to monitor for a non-sense shape (making shape task-relevant).

Importantly, while color identification is less automatic than word identification in the color-word task, color identification is more automatic than object identification in the color-object task. Hence, if automaticity of processing is indeed a locus of Stroop interference, the pattern of brain activation should be influenced more by the relative automaticity of processes, rather than the nature of the attribute being attended to (i.e., color). Importantly, distinct patterns of brain activation were observed for color monitoring depending on whether it was the less automatic process, as in the color-word task, in which case prefrontal mechanisms were engaged or the more automatic process, as in the color-object task, in which no prefrontal activity was observed. As such, this study provided evidence that relative competition between the automaticity of processes is one locus at which Stroop interference occurs, and that prefrontal regions are involved in control over such effects.

A subsequent study demonstrated that prefrontal mechanisms are engaged when a less automatic process must guide responding, regardless of the specific nature of that process (Banich et al., 2000a). In this study, activation for the contrast of incongruent vs. neutral trials in a color-word Stroop task was compared to that in a spatial-word Stroop task. In the colorword task, incongruent trials consisted of color words displayed in conflicting colors (e.g., "red" in blue ink) while neutral trials consisted of non-color-related words displayed in a particular ink color (e.g., "lot" in blue ink). In the spatial-word task, individuals pressed a button to identify whether a word appeared above, within, or below a box. On incongruent trials, the word's position conflicted with its meaning (e.g., the word "above" positioned below the box), while on neutral trials, a non-spatial-related word was displayed (e.g., the word "civil" positioned below the box). Overlapping regions of DLPFC were activated for these two tasks, indicating that the need to overcome the automaticity of word reading can be engendered regardless of the nature of the task-relevant attribute (color vs. spatial position).

Taken together, this experiment and the one discussed just above demonstrate that it is not the nature of information in a given stimulus dimension that drives Stroop interference, but rather the relative automaticity of the two processes. In the first study discussed, different patterns of activation were observed when color was the task-relevant dimension, depending on the nature of its automaticity vis a vis the task-irrelevant dimension. In the second study, similar patterns of activation were observed even when the task-relevant attribute differed because processing each of those dimensions was less automatic than word reading.

If indeed it is the automaticity of word reading vis a vis another process that engenders Stroop interference, then one should observe similar patterns of brain activation for the colorword and color-emotional word Stroop task. A direct comparison in the same participants showed that that DLPFC activity is observed for the incongruent condition of a color-word task as well as trials in a color-emotion word task containing either a positive and negative emotionally valenced word compared to a neutral non-emotional word (e.g., "integer") (Compton et al., 2003). These findings are consistent with the idea that the automaticity of word reading or attentional capture by the word so as to engage word reading must be overcome to enable successful color identification. This overlapping pattern of activation in the frontoparietal network (DLPFC and parietal regions) for the color-emotion word task as compared to the color-word task has been observed in additional non-clinical samples both with positively and negatively valenced words (Kaiser et al., 2015) as well as for positive and threat words (Mackiewicz Seghete et al., 2017).

The effects observed in the color-emotional word task suggest that to the degree that a word is salient, it will capture attention so as to enhance word processing. If so, this should be a general mechanism that can help to increase Stroop interference. This idea is supported by a study (Compton et al., 2003) in which the words were specifically varied in terms of their arousal ratings. More activation was observed in frontoparietal regions for negative words high in arousal as compared to those low in arousal, suggesting that it is the salience of the word that engenders a greater need for control. Demonstrating that this is a general effect not specific to emotion words per se, in another study, the frequency with which certain items appears was varied, such that a subset of words occurred less frequently (i.e., oddball trials). DLPFC activation was enhanced for these oddball trials as compared to more frequent trials (Milham et al., 2003a). Thus, any of a number of manipulations that make words more salient so as to increase the engagement of word processing seems to be one locus of the Stroop effect.

## INTERFERENCE BASED ON DIFFERENT LEVELS OF STIMULUS-RELATED REPRESENTATIONS

While standard computational models of the Stroop task suggest that it can be explained by competition between two distinct processes, neuroimaging data provide a more complicated picture. In particular, if that were simply the only locus of the Stroop effect, then the identity of the task-irrelevant information should not affect brain activation, as for all intents and purposes it is downregulated relative to the task-relevant dimension.

However, neuroimaging research provided a contrary result. Greater activity was observed in brain regions that process the task-irrelevant attribute for incongruent as compared to neutral trials (Banich et al., 2001), a finding at odds with a simple downregulation of task-irrelevant processing. More specifically, different regions of posterior cortex showed greater activity on the contrast of incongruent (e.g., "red" in blue ink) vs. neutral trials (e.g., "lot" in blue ink) for the color-word task as compared to the contrast of incongruent (e.g., a red frog, when frogs are typically green) vs. a neutral trial (e.g., a red car, when cars can be red among a variety of other colors) in the color-object task. As such, there must be an additional level of competition and/or selection.

In an attempt to understand the factors that drive this pattern of brain activation, Herd et al. (2006) modified the standard computational model of the Stroop task so that it was able to replicate the pattern of brain activation observed as well as the behavioral pattern of results. In the standard computational model, there is an input layer with two subsections – one for the receipt of color information and one for the receipt of word information. These are each linked to an output layer that governs responding. A prefrontal control node modulates processing so as to increase activation of information in the color portion of the input layer in comparison to the word portion of the input layer.

The revised model had three important modifications. First, it included a layer between input and output meant to represent processing of information in posterior cortex in color-specific and word-specific regions, respectively. Part of the goal of including this layer was to see if activation in these portions of the model could mimic the activation observed in posterior brain regions in the empirical neuroimaging studies. Second, it included an additional top-down node to bias toward the abstract concept of color as being critical for the task set. The rationale was that, outside of the Stroop task, individuals typically do not have an abstract representation of color that excludes color words. As such, a task set for "color" is likely to broadly activate information related to the semantic category of color, regardless of whether it is contained in the task-relevant or the task-irrelevant dimension of the Stroop stimulus. Third, also related to the semantics of color, the model was modified so that there were excitatory linkages between representations of color in the ink processing layer (e.g., green) with the related representation in the word processing layer (e.g., "green").

This model could replicate both the behavioral results of the Stroop task (i.e., longer RT for incongruent than neutral trials) and also patterns of brain activation with more activity in the color processing layer for incongruent than neutral trials. An additional virtue of creating such a model is that portions of it can be "lesioned" to determine what aspect of its architecture is critical to engendering its results. Suggesting that the alterations to the original computational model were critical, neither a model that had the top-down color biasing unit removed nor a model without reciprocal connections between related semantic features could replicate the observed empirical results. Hence, the outcome of this computational modeling suggests that it is the color-relatedness of a representation that serves as a locus of interference.

While the color-relatedness of items is important, studies suggest that the nature of representation to which the semantic category of color is linked can vary and yet still produce interference. Support for this assertion comes from comparison of activation for incongruent vs. neutral trials for three types of Stroop tasks: the standard color-word Stroop task, the colorobject Stroop task, and a color-object word Stroop task. As noted above, in the color-object task, an object with a typical color is displayed in an atypical color (e.g., a frog in red) on incongruent trials, while on neutral trials, an object is displayed in one of the many different colors in which it can appear (e.g., a car in red). In the color-object word task, the person simply views the word describing an object that has a typical color (e.g., "frog"), rather than seeing a pictorial depiction of the object. Distinct regions of cortex showed activation depending on the nature of the task-irrelevant attribute, suggesting that it was not just an amodal semantic representation of color that is the source of interference. For example, different regions of the ventral visual processing stream are activated on incongruent trials for the color-word task as compared to the color-object task, suggesting that interference may arise from more orthographically based as compared to visual form-related representations in the former task as compared to the latter. In addition, different portions of the IFG (BA 45 vs. BA 48) became active for the color-object as compared to the color-object word task despite the fact that the interference would arise from the same semantic characteristic (e.g., semantic memory with regard to frogs creates interference because they are typically green not red) (Banich et al., 2001). This finding also suggests that interference can arise at multiple stimulus-related levels.

Another way to examine stimulus-related representations of color is to compare patterns of activation when items have colorrelated information in both the task-relevant and task-irrelevant dimension as compared to when color-related information is restricted solely to the task-relevant dimension. One can examine this question by determining patterns of brain activation common across both incongruent and congruent trials that are greater than those observed on neutral trials. Investigations taking such an approach (Milham et al., 2002; Milham and Banich, 2005) show that there is not only increased activation in DLPFC, which presumably reflects a more general increased need for control to bias toward task-relevant information, but also increased activation in ventral lateral prefrontal cortex, portions of which are regions involved in semantic retrieval and selection (Badre and Wagner, 2007). Also suggesting interference at the semantic level, left temporal language areas show activation for the contrast of incongruent and congruent trials, which contain semantically related color information in both the ink color and the word, as compared to neutral trials, which in this case were words unrelated to color (e.g., "lot") (Milham and Banich, 2005).

In sum, the work reviewed in this section suggests that interference can potentially arise in the Stroop task at a number of stimulus-related dimensions, from visual form to orthography, as they relate to the task-relevant category, and also with regard to semantic representations of task-relevant information.

#### RESPONSE-RELATED ASPECTS OF INTERFERENCE

Another series of studies provided evidence that Stroop interference is also engendered at response-related levels. In the first study of this nature, brain activation was examined for two types of incongruent trials, response-eligible and responseineligible. In response-eligible trials, the competing word also names a potential response. An example would be the word "red" printed in blue ink when the potential responses are red, blue, and green. Response-ineligible trials on the other hand name competing colors, but those that are not a potential response, such as the word "purple" printed in blue ink, when the potential

responses are red, blue, and green. If a particular brain region is specifically engaged in dealing with response conflict, it should show greater activation to response-eligible than responseineligible trials. Importantly, in addition, this region should also show no more activation to response-ineligible trials, which have semantic conflict but no response conflict, than to neutral trials, which have neither semantic nor response conflict (e.g., the word "mile"). A region of mid-cingulate cortex showed such a pattern (Milham et al., 2001), which was confirmed in a subsequent study (Milham et al., 2003a).

Another way to examine response-related aspects of Stroop interference is to compare processing on different blocks of trials in which the stimulus-response mapping is one-to-one as compared to one-to-many. More specifically, on some blocks, each incongruent response-ineligible word was mapped to a different color (e.g., the word "purple" shown in blue, the word "violet" shown in green, etc.), whereas in other blocks, the same task-irrelevant word was presented but paired with a variety of colors (e.g., shown on some trials in blue, in other trials in green, etc.). Hence, stimulus-response mappings were more overlapping in the former condition than the latter. Each of these blocks also contained neutral words (e.g., the word "closet") with oneto-one as compared to one-to-many color mappings within the appropriate blocks. While DLPFC showed greater activity for incongruent vs. neutral trials, regardless of the nature of the response-mapping (1 to 1; 1 to 4), the ACC was sensitive to the response mapping, showing more activity when the colorresponse mappings were overlapping (one word to four colors) and hence harder to distinguish than when they were one-to-one (one word to one color) (Liu et al., 2006).

Another way in which response-related interference in the Stroop task has been investigated is via an integrated Simon-Stroop task. In the Simon task, interference arises from stimulusresponse interference. In this task, interference is engendered when a right-sided (e.g., right hand) response is required to a left-sided stimulus (and vice versa) as compared to when the location of the item to be responded to and the effector making the response are on the same side of midline. In our integrated Simon-Stroop task, individuals viewed arrows that were located either to the right or left (Simon stimuli), or on different trials above or below (Stroop stimuli) a fixation point. Individuals were trained, for example, to press a right button for an upward arrow and a left button for a downward arrow. Simon interference, which is considered stimulus-response interference, was engendered by placing, for example, an upward arrow to the left of fixation, which then required a right button response to a left-sided stimulus. Stroop interference, which is considered engendered by conflict between two stimulus dimensions, occurred for example when an upward arrow was positioned below the fixation point.

While the contrast of incongruent vs. congruent trials yielded activation in DLPFC for both tasks, the Simon task trials generated activity in motor and response-related regions including the ACC and supplementary motor area (SMA), activity that was not observed in this spatial arrow– spatial position Stroop task. In contrast, the stimulus–stimulus interference of the Stroop task engendered activity in inferior parietal and inferior frontal regions that was not observed in the Simon contrast (Liu et al., 2004). Hence, this body of work suggests that another locus of Stroop interference is at responserelated aspects of processing. Consistent with this supposition, certain limitations of the classic computational model of the Stroop task by Cohen et al. (1990) with regard to fitting aspects of human performance can be overcome if the model includes a mechanism for performing final response selection (Stafford and Gurney, 2007).

## AN INTEGRATIVE MODEL: STROOP INTERFERENCE CAN OCCUR AT MULTIPLE POINTS ALONG A CASCADE-OF-CONTROL

The work described above suggests that Stroop interference can occur at multiple levels. How then can one integrate these findings to shed light on the locus of the Stroop effect? We have argued that, importantly, the degree to which control is exerted at one level of processing can then influence the degree to which interference is engendered or controlled at another.

A pair of early studies helped this idea to come into focus. As reviewed above, our work suggests a broad distinction between control engendered at the level of an abstract task set, mainly implemented by lateral prefrontal cortex, as compared to more response-related aspects of control, mainly implemented by medial prefrontal cortex. In examining differences in brain activation common to incongruent and congruent as compared to neutral trials (e.g., the word "lot") in the color-word task, there was a notable difference in patterns of activation for younger vs. older adults (Milham et al., 2002). In particular, younger adults exhibited more activation across frontal and parietal regions. Such findings are consistent with reported compromise with aging of prefrontal regions and processes involving executive function and cognitive control (Lockhart and DeCarli, 2014). In contrast, older individuals had more activation in portions of the ACC and SMA. This led us to consider the possibility that due to the lack of top-down control, older individuals were potentially utilizing more response-related mechanisms to deal with the interference.

The converse effect was observed in a study of practicerelated effects on the Stroop task. Since the Stroop effect can be maintained over tens of thousands of trials due to the automaticity of word reading, a Stroop task was used in which the interference effect could be reduced with practice. In this task, individuals were trained to assign a color-word label to a series of nonsense designs (e.g., nonsense design 1 was labeled "blue"). Then, later, they were shown either incongruent trials, in which a specific nonsense design was displayed in an incongruent color (e.g., nonsense design 1 labeled "blue" shown in yellow), or neutral trials, on which the nonsense designs were shown in white. To examine learning effects, the experiment was divided into thirds, examining activation for the first third, second third, and last third of trials. While lateral prefrontal activity stayed relatively static across the three portions of the task, that of

medial prefrontal activity declined, as did the behavioral Stroop effect, suggesting that individuals were gaining better control over interference. We interpreted this pattern as suggesting that less late-stage response-related interference was occurring, as reflected in reduced ACC activity, due to better top-down control by lateral prefrontal regions, which stayed engaged across all portions of the task (Milham et al., 2003b). Thus, ACC activity depends, in part, on the degree of interference control engendered by DLPFC.

Testing the idea that ACC activity depends in part on the degree of prior control exerted by DLPFC required using a method that afforded better temporal resolution than that provided by fMRI. The relationship between activity in DLPFC and ACC was examined by utilizing event-related potentials (ERPs) due to their superior temporal resolution, in conjunction with fMRI. Participants performed the Stroop task in the magnet and then again while electrophysiological recordings were made. fMRI results were used to enable source localization for ERP waveforms for the DLPFC and ACC. The relationship between ERPs generated by these sources was examined, in addition to how well they could predict, as tested via mediation models, interference on the Stroop task (indexed by the difference in performance between incongruent and congruent trials). The specific model examined whether the influence of DLPFC activity in the 300–440 ms time range on Stroop performance would be mediated, in part, by later ACC activity in the 520–680 ms time range. This pathway was significant. Moreover, the data showed that for individuals with larger DLPFC amplitude, indicative of higher levels of control, the degree of ACC activity was unrelated to behavioral interference. This finding is consistent with the idea that there is reduced need for late-stage selection when the task set is well specified so as to reduce interference from the task-irrelevant processing stream. In contrast, individuals with low DLPFC but high ACC amplitude exhibited a greater degree of interference as measured by the reaction time difference between incongruent and congruent trials, but no more errors than individuals with high DLPFC activity. In contrast, those individuals with both low DLPFC amplitude and low ACC amplitude committed more errors, suggesting that the reduced ability of the ACC to engage in late-stage selection led to compromised performance. An advantage of this approach was that alternative models could be tested. For example, one might argue that this model predicted the data because it posited that the effect of a component occurring earlier in time, that recorded from the DLPFC, was moderated by a component occurring later in time, that recorded from the ACC. Arguing against such an interpretation, a model positing a pathway from an earlier ACC component (in the 220–340 ms time range) via the DLPFC component (at 300–440 ms) did not predict performance. Nor did a model in which activity derived from source location of another brain region involved in cognitive control, RIFG, was substituted for DLPFC (Silton et al., 2010).

Integrating all these findings, we posited a cascade-of-control to control interference in the Stroop task (Banich, 2009). As discussed earlier (and as shown in **Figure 1**), this model argues that posterior portions of lateral prefrontal cortex are involved in setting a top-down attentional set (i.e., pay attention to ink color) for task-relevant information and act by modulating activity either in one or both of the posterior brain regions that process the task-relevant and task-irrelevant dimension of the Stroop stimulus. This idea is consistent with activation of IFG across distinct meta-analyses of Stroop tasks (Derrfuss et al., 2005). Such task setting can occur even prior to stimulus presentation in a proactive manner (see, for example, Braver, 2012). Once a stimulus appears, relevant information is identified and then mid-DLPFC regions are involved in selecting which of the relevant information should be actively maintained in working memory. Regions of mid-DLPFC have been implicated in buffering relevant information in working memory from interference from competing information (Burgess and Braver, 2010). This information is then sent along to more posterior and dorsal regions of ACC, which are then involved in responserelated and late-stage selection, which is required prior to emitting a response. Research with monkeys implicates the ACC as being particularly important for response selection (Isomura et al., 2003). Then, more rostral regions of ACC are involved in response evaluation, which can send a signal back to DLPFC (e.g., Jahn et al., 2014) as posited by the conflict monitoring theory (Botvinick et al., 2004; refer back to **Figure 1**). Consistent with this notion of a cascade are findings from ERP studies in which the onset of the two stimulus dimensions – taskrelevant and task-irrelevant – are varied in time. These studies reveal that ERP waveforms sensitive to stimulus incongruity vary depending on the stimulus onset asynchrony between these two dimensions, implicating a cascading process of interference effects (Appelbaum et al., 2009; Coderre et al., 2011).

## OTHER TYPES OF INTERACTIONS BETWEEN BRAIN REGIONS THAT MAY INFLUENCE THE LOCUS OF THE STROOP EFFECT

Conceptualizing Stroop interference as occurring via a cascade of control provides additional avenues to consider how the locus of Stroop interference might be considered. In this section, we consider some approaches in that regard. One issue not yet discussed is the mechanism via which top-down biasing by prefrontal regions for a task set influences processing of each of the task-relevant and the task-irrelevant dimension of a Stroop stimulus. One can ask whether interference occurs because the representation of task-relevant information is not adequately upregulated or because the representation of task-irrelevant information is not adequately downregulated. Because of the specificity of brain regions that process each of the two stimulus dimensions contained in Stroop stimuli, one can leverage brain imaging to examine this question.

A number of studies have examined whether, for example, in the standard color-word Stroop task, activity is increased in color processing regions or downregulated in word processing areas (e.g., Egner and Hirsch, 2005; Purmann and Pollmann, 2015). This question is generally approached via the utilization of localizer scans where individuals are shown a series of

words and then separately colors to identify, on an individual participant basis, those brain regions that are specifically involved in processing words and then those specifically involved in processing color. One can then examine the degree of activation of each of these regions on average for incongruent trials as compared to congruent trials. Work using such an approach suggests that both mechanisms (upregulation of task-relevant material, downregulation of task-irrelevant material) may occur (e.g., Polk et al., 2008; Coste et al., 2011).

Recently, we have expanded on such approaches to specifically examine how processing of task-relevant vs. task-irrelevant dimensions of a Stroop stimuli predict the degree of Stroop interference that is observed on a trial-by-trial basis (Banich et al., 2019). In our approach, participants performed a localizer task, which in conjunction with multi-voxel pattern analysis (Norman et al., 2006) was used to determine the pattern of brain activity over visual cortex that is specifically associated with processing the task-relevant dimension and then to also determine the pattern of activity associated with the task-irrelevant dimension.  On each trial, we determined how much activity over posterior cortex was similar to that typical for each dimension (using a classifier fit), that is, how much the pattern of activity looks like face activity and additionally how much the pattern looked like word activity. This approach provided a trialby-trial readout of how much each dimension was being attended and/or processed.

The important question for purposes of the present article was the degree to which processing of each of these dimensions could predict RT on a given trial and the degree to which such activity occurs as a result of activity in DLPFC modulating activity of posterior brain regions processing each of the task-relevant and task-irrelevant stimulus dimensions. The results yielded different patterns for incongruent as compared to congruent trials. On incongruent trials, greater DLPFC activity directly predicted longer RT, suggesting that when individuals were having difficulty on a given trial, they needed to engage more top-down mechanisms. In addition, more DLFPC activity was associated with less of a classifier fit for faces, suggesting that this brain region is downregulating processing of the task-irrelevant face. However, the degree of processing of the task-relevant face did not predict RT. Hence, interference, at least in the population of individuals in this study, late adolescents, seems to be predicted on incongruent trials by the degree to which DLPFC mechanisms must be engaged. On congruent trials, as on incongruent trials, more DLPFC activity was associated with a poor classifier fit (i.e., less activity) for faces. However, for these trials, more processing of the word was associated with longer RT, suggesting that when more attention needed to be directed to the word to extract the relevant information, RT was elongated.

While these results must be considered in the context that they were obtained in adolescents in whom cognitive control mechanisms are still developing (Andrews-Hanna et al., 2011), they nonetheless raise two important points. First, they provide another example of how brain imaging techniques can be leveraged to try to provide insights into the locus of the Stroop effect that would otherwise be difficult to obtain via behavioral methods alone. Secondly, they suggest that when one talks about the "locus of the Stroop" effect, considered in the context of a cascade, those effects can potentially vary for congruent and incongruent trials, and the interference observed may be a combination of these two effects.

Also suggesting that the locus of the Stroop effect may vary depending on task demands are findings examining the Stroop effect from a network perspective (Spielberg et al., 2015). Using a graph theory approach, higher demand for inhibitory control is associated with restructuring of the global network into a configuration that is more optimized for specialized processing (functional segregation), more efficient at communicating the output of such processing across the network (functional integration), and more resilient to potential interruption (resilience). In addition, there were regional changes with right inferior frontal sulcus and right anterior insula occupying more central positions as network hubs, and dorsal ACC becoming more tightly coupled with its regional subnetwork. This work also suggests that interference is generated via a cascade of activity among regions situated within a larger network and that such configurations can change with control demands on incongruent vs. congruent trials.

### TASK-RELATED VARIABLES THAT MAY INFLUENCE THE LOCUS OF THE STROOP EFFECT

The implications of the results discussed just above, and the model proposed, are that the Stroop effect can occur at a number of different loci and may be influenced by the interaction between these loci as well (e.g., top-down biasing by DLPFC; responserelated, late-stage selection by ACC). As a result, it may indeed be that where the Stroop effect is observed is dictated essentially by where your paradigm puts it, even if only implicitly. Two examples are provided here.

First, one of the reasons we used manual responses in most of our fMRI studies was to avoid the potential for head motion that is associated with verbal responding. However, that design choice likely influenced what was observed. In paradigms with a verbal response, there is a much stronger and more automatized mapping between seeing the word (or color) red and verbally producing the word that is associated with it than, for example, training individuals that pressing a button with your index finger denotes "red." Although we have never formally performed such a comparison, based on prior studies showing differences in activation based on response modality (verbal, manual) during a spatial Stroop task (Barch et al., 2001), one might expect that the interference effects in a vocal color-word Stroop paradigm would more likely involve response-related processing relative to top-down biasing mechanisms, as compared to manual response versions in which there is likely to be less response-related interference. Said differently, pressing an index finger to denote the color red when the word says "blue" is likely to engender less response interference than saying "red" compared to the

well-ingrained tendency to say "blue" when seeing the word blue. This idea has been recently supported by a study in which the vocal and manual Stroop effects were compared. The vocal Stroop effect was about twice as large as the manual one. Moreover, ERP recordings indicated that while both the vocal and manual version produced an N400 (suggestive of semantic interference), only for the vocal version was there a responselocked component over left inferior frontal and parietal regions, suggesting additional interference at the level of word production (Zahedi et al., 2019) (however, it should be noted that an alternative suggestion is that different portions of the anterior cingulate are involved in response-related selection for manual vs. vocal tasks; e.g., Liotti et al., 2000; Swick and Turken, 2002).

As a second example, the locus of the Stroop effect may vary depending on the relative automaticity of two processes. One of the reasons that the classic color-word Stroop effect gives such a potent behavioral interference effect is that word reading of color words is so automatic, being some of the earliest learned words. In contrast, the behavioral interference effects for a spatial location–spatial word Stroop task are much less potent. Hence, there may be a greater need for top-down biasing by DLPFC in the former case than the latter.

### INDIVIDUAL DIFFERENCES THAT MAY INFLUENCE THE LOCUS OF THE STROOP EFFECT

The locus of the Stroop effect may also vary depending on the characteristics of an individual or his/her experience. For example, during the teen years, overcoming interference engendered by Stroop stimuli seem to rely to a greater degree on DLPFC in older adolescents, but on the ACC in younger ones (Andrews-Hanna et al., 2011). Young adults with ADHD appear to show reductions in both DLPFC and ACC activity relative to controls, suggesting disruptions in both top-down and latestage/response-related aspects of controlling Stroop interference (Banich et al., 2009). Individuals with depression exhibit less DLPFC activity, especially in the left hemisphere (Herrington et al., 2010), with this effect being modulated by level of anxiety (Engels et al., 2010). Moreover, individual differences in approach and avoidance can modulate the lateralization of involvement of the DLPFC in top-down control (Spielberg et al., 2011).

In other individuals, different brain regions other than the typical ones are engaged. For example, women with a history of childhood abuse compared to controls exhibit less fronto-parietal activation, but more activity in regions that are part of the ventral attention/surveillance system during both a standard color-word and color-emotional word Stroop task (Mackiewicz Seghete et al., 2017). In adolescents with severe substance and conduct problems, more activation is observed in medial temporal regions including hippocampal regions (Banich et al., 2007), suggesting potentially a more instance-based processing of Stroop stimuli.

Studies with twins can help to elucidate the potential causes of these effects. For example, in a small sample of monozygotic twins who were discordant for stressful life events, those higher in stressful life events recruited regions of ventrolateral and medial frontal cortex as well as limbic regions while performing an emotional word–emotional face Stroop task. The control cotwins showed only the more typical recruitment of frontoparietal regions thought to be important for executive control of attention and maintenance of task goals. Behavioral performance was not significantly different between twins within pairs, suggesting that the twin who had experienced greater stress recruited additional neural resources associated with affective processing and updating working memory to obtain the same level of behavioral performance (Godinez et al., 2016). A study utilizing a case-control discordant twin pair design revealed that co-twins of individuals with ADHD, like their affected ADHD twin, show reduced activity in the anterior cingulate and insula compared to the unrelated controls, suggesting familial influences. In contrast, portions of the frontoparietal network appear to be the location of effects specific to ADHD, with twins with childhood ADHD showing reduced superior frontal (Brodmann's Area – BA 6) and parietal region (BA 40) activity compared to both their control co-twins and unrelated control twins (Godinez et al., 2015).

Other work suggests that the nature of the cascade is affected by individual differences. For example, using a source-guided examination of ERP effects, Silton et al. (2011) found that for individuals with high levels of depression, increased LDLPFC activity was directly related to decreased Stroop interference and that ACC did not play an intervening role. Separately for individuals with high levels of anxious apprehension (i.e., worry), higher ACC activity was related to more Stroop interference. These results indicate that depression and anxious apprehension modulate temporally and functionally distinct aspects of the fronto-cingulate network involved in top-down attention control. Additionally, Spielberg et al. (2014) observed that during performance of a color-word Stroop task, increasing levels of anxious arousal were positively associated with coupling of the right DLPFC with orbitofrontal cortex (OFC). In addition, increasing levels of depression were positively associated with right DLPFC–OFC coupling and negatively associated with left DLPFC–OFC coupling. As such, it may be that additional regions to those outlined by our model are brought into the set of regions influencing Stroop interference as a function of individual differences. For example, our model focuses exclusively on cortical regions. Yet at least some research suggests that the ventral tegmental area (VTA)/substantia nigra (SN) and locus coeruleus (LC) also show alterations in activity on incongruent vs. congruent trials, and have differential connectivity to prefrontal regions (Köhler et al., 2016). Hence, individual differences in noradrenergic and/or dopaminergic function may influence the locus of the Stroop effect as well.

#### CONCLUSION

The main takeaway from the work reviewed in this article is that the locus of the Stroop effect can occur at multiple levels from the initiation and creation of a task set for the task goal (e.g., make a decision based on ink color) to late-stage response-related aspects of control. In general, our model suggests that lateral

prefrontal regions are more involved in selection and modulation of specific information processing streams (i.e., task-relevant vs. task-irrelevant) while cingulate regions are more involved in latestage response-related aspects of control. However, even within this general dichotomy, these mechanisms are likely invoked along a cascade, providing the opportunity for control and interference to occur at multiple time points. Additional evidence points to the important role that connectivity between brain regions plays in producing the Stroop effect. Furthermore, the locus of interference may be influenced by the nature of the paradigm (e.g., vocal vs. manual responding in a color-word Stroop task) and by characteristics of an individual.

As such, there is likely no single locus of the Stroop effect, which is both the advantage and the disadvantage of using this task to understand mechanisms of control. On the one hand, if a researcher desires an all-purpose task for examining cognitive control, or alterations to such control, without regard to its locus, the family of Stroop tasks is an excellent choice. One of the reasons we have used Stroop variants in our research is exactly because it is a "broad spectrum" task for detecting deviation in cognitive control. In addition, we chose it because the task instructions are easily understood and, as such, it can be administered across a wide range of ages and with neurologically normal and clinical populations. Moreover, it provides a robust behavioral effect. In addition, while its effect may be more robust at the group than at the individual level (Enkavi et al., 2019), we have found that an interference score [i.e., (Incongruent RT − Congruent RT)/Congruent RT] that accounts for individual differences in overall RT works well especially when combined with neuroimaging. Another aspect of the Stroop task that makes it so versatile is that there are a wide variety of variants that are available.

It is, however, exactly this variation across Stroop paradigms that can be a disadvantage of the task, as it can make comparison across different studies difficult. Researchers often discuss using the "Stroop task" when they use one of the many members of the family of Stroop task variants. Yet, each variant of the task likely generates the need for control at different loci, as our research has demonstrated. To help facilitate comparison across studies, we have tried to be more explicit in our task nomenclature by indicating both the task-relevant and

#### REFERENCES

task-irrelevant dimensions (e.g., the classic color-word Stroop task). If this nomenclature were adopted more broadly across the field, it might facilitate comparisons across studies. However, to truly facilitate comparison, it would also be important to indicate the nature of neutral trials. In some studies of the classic color-word Stroop task, the neutral trials are simply a series of colored "xxxxxxx"s. Such stimuli are not as likely to engage word reading mechanisms as, for example, the neutral non-color words that we have typically employed (refer back to discussion in section "Interference Between Two Processes That Vary in Their Automaticity or Control Demands"), which will also influence the locus of the Stroop effect (as will the specific contrast being examined, e.g., incongruent vs. neutral trials, incongruent vs. congruent trials).

In conclusion, the "Stroop task" can be used either more as a hammer to detect cognitive control across a variety of loci in a broad-based manner or more as a scalpel to investigate control at a very limited level if designed with specifically constrained stimuli and contrasts. Just as there is a family of Stroop tasks, there is also a family of loci at which the Stroop effect can occur. Moreover, the different loci may be generated across a series of distinct but interacting brain regions to produce the single behavioral effect that is observed.

## AUTHOR CONTRIBUTIONS

The author confirms being the sole contributor of this work and has approved it for publication.

## FUNDING

Portions of the research described in this article were supported by NIH grants P50 MH079485, R03 HD062600, R01 MH070037, R01 MH105501, and R01 MH61358. Preparation of this article was supported by R01 MH105501.

## ACKNOWLEDGMENTS

The author would like to thank all of her collaborators who helped in this line of research.

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revealed by case–control, discordant twin pair design. Psychiatr. Res. 233, 458–465. doi: 10.1016/j.pscychresns.2015.07.019

fpsyg-10-02164 October 4, 2019 Time: 18:35 # 11

**Conflict of Interest:** The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2019 Banich. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

## An fMRI Study of Response and Semantic Conflict in the Stroop Task

Benjamin A. Parris<sup>1</sup> \*, Michael G. Wadsley<sup>1</sup> , Nabil Hasshim<sup>2</sup> , Abdelmalek Benattayallah<sup>3</sup> , Maria Augustinova<sup>4</sup> and Ludovic Ferrand<sup>5</sup>

<sup>1</sup> Department of Psychology, Bournemouth University, Poole, United Kingdom, <sup>2</sup> School of Psychology, University College Dublin, Dublin, Ireland, <sup>3</sup> Exeter MR Research Centre, University of Exeter, Exeter, United Kingdom, <sup>4</sup> Normandie Université, UNIROUEN, CRFDP, Rouen, France, <sup>5</sup> Université Clermont Auvergne, CNRS LAPSCO, Clermont-Ferrand, France

An enduring question in selective attention research is whether we can successfully ignore an irrelevant stimulus and at what point in the stream of processing we are able to select the appropriate source of information. Using methods informed by recent research on the varieties of conflict in the Stroop task the present study provides evidence for specialized functions of regions of the frontoparietal network in processing response and semantic conflict during Stroop task performance. Specifically, we used trial types and orthogonal contrasts thought to better independently measure response and semantic conflict and we presented the trial types in pure blocks to maximize response conflict and therefore better distinguish between the conflict types. Our data indicate that the left inferior PFC plays an important role in the processing of both response and semantic (or stimulus) conflict, whilst regions of the left parietal cortex (BA40) play an accompanying role in response, but not semantic, conflict processing. Moreover, our study reports a role for the right mediodorsal thalamus in processing semantic, but not response, conflict. In none of our comparisons did we observe activity in the anterior cingulate cortex (ACC), a finding we ascribe to the use of blocked trial type presentation and one that has implications for theories of ACC function.

Keywords: task conflict, semantic conflict, response conflict, fMRI, selective attention, Stroop 2-1 mapping, Stroop

## INTRODUCTION