Introduction

Life presents itself as a bombardment of stimuli and experiences. One way to handle this massive quantity of stimulation is selection. It is well-known that humans are equipped with the ability to selectively attend to specific types of stimuli [1] or even to specific stimulus dimensions [2, 3]. A second way to handle massive stimulus input is automation, that is, the ability to process stimulus information very quickly, efficiently, outside awareness, and/or in the absence of an (explicit) processing goal [4].

Research on automatic stimulus processing has focused almost exclusively on the (semantic) analysis of a single stimulus. In the semantic priming literature, for example, literally hundreds of studies have been published concerning the automatic extraction of meaning from a single word (e.g., [5]). In the real world, however, a successful exchange between an organism and its environment typically involves a comparative integration of different sources of information. Even the simple act of buying a hamburger requires a comparison of different response options as a function of the stimulus environment and both short-term and long-term goals. It is therefore quite surprising that relatively little research has focused on the possibility that the analysis of the precise way in which two (or more) stimuli relate to each can occur under automaticity conditions (hereafter referred to as automatic relational stimulus processing). At least to some extent, this state of affairs seems to have resulted from the predominant view that automatic processes must be associative in nature whereas complex relational stimulus processing must be non-automatic in nature (e.g., [6]). There are, however, no a priori theoretical reasons to map the quality of a given process (i.e., a comparison between two stimuli vs. the analysis of a single stimulus) onto the automaticity conditions under which this process can operate [7, 8]. In other words, it is a matter of empirical research to describe what kind of processes can take place under different automaticity conditions. As soon as one adopts this approach, it becomes clear that, in principle, processes operating under automaticity conditions might be much more complex than previously assumed. In fact, several reports of automatic relational stimulus processing have already appeared in the literature, although the reported effects were not always described as such.

As a first example, consider the findings reported by Heider and colleagues [9]. In a series of four sequential priming studies, they used line drawings of large and small objects as target stimuli (e.g., a truck vs. a spoon) and asked participants to judge the size of these objects relative to either a small reference object (i.e., a football) or a large reference object (i.e., a car). Crucially, the prime set included line drawings of objects that were larger than the small reference object but smaller than the large reference object (i.e., a bike). Results showed that the impact of these ‘intermediate’ primes on target responding was dependent upon the magnitude of the reference object. When the reference object was small, the intermediate prime stimuli facilitated responses towards targets larger than the reference object relative to responses towards targets smaller than the reference object. In contrast, if the reference object was large, the same set of intermediate prime stimuli facilitated responses towards targets smaller than the reference object relative to responses towards targets larger than the reference object. Importantly, the primes were completely irrelevant for the target task. Accordingly, whereas the requirement to engage in a relational target task was probably an important prerequisite for the occurrence of the relational priming effect, the findings obtained by Heider and colleagues [9] demonstrated that the relational meaning of stimuli can be processed even in the absence of the explicit requirement to do so (i.e., goal-dependent unintentionality, see [4]; for related findings, see [10–16]).

The relational priming studies by Heider and colleagues [9] are somewhat limited, however, in the sense that the same two reference objects were used throughout the entire experimental session. As a result, the representation of the reference objects must have been highly activated in working memory, which may be an important prerequisite for automatic relational stimulus processing to take place. Research suggests, however, that this is probably not the case. Perhaps the best example comes from studies using an experimental task design that we will refer to as the Relational Stroop Task (hereafter referred to as RST). As an example, consider the findings reported by Paivio [17]. In Experiment 2, Paivio [17] presented participants with pairs of pictures (48 pairs in total) or printed names (also 48 pairs in total) of objects and animals differing in real-life size. Crucially, the physical size of the individual stimuli (i.e., the image size or font size) was manipulated such that the physical size relation and the conceptual size relation were either congruent (e.g., ‘lamp–ZEBRA’) or incongruent (e.g., ‘LAMP–zebra’). When asked to judge whether the conceptually larger member of each pair was presented on the left or the right, participants were clearly faster to respond on congruent pairs than on incongruent pairs, at least for the picture pairs (i.e., no effects were obtained with the word pairs). That is, similar to a classic Stroop task, performance was better when the relevant stimulus dimension (i.e., the conceptual size relation) and the irrelevant stimulus dimension (i.e., the physical size relation) pointed to the same response as compared to different responses (see [18], p. 237–238).

Importantly, this RST effect occurred despite the fact that participants were to ignore the (task-irrelevant) physical size relation and therefore supports the idea that relational processing of physical size can take place automatically [4]. Moreover, given the use of a large number of stimulus pairs, the findings of Paivio [17] suggest that automatic relational stimulus processing can occur even for stimuli that are not actively stored in working memory. It may be noted, however, that Paivio [17] himself did not interpret his findings in terms or automatic relational stimulus processing. Instead, he seemed to endorse an explanation in terms of “internal analog representations that contain relative size information along with other attributes of the objects” (p. 646). It may also be noted that we readily replicated the RST effect in two unpublished studies, just like several other authors (e.g., [19–22]). As is the case for all data reported in this article, the raw data of these (unpublished) studies are available at https://figshare.com. They can be accessed directly via the following links: https://doi.org/10.6084/m9.figshare.5005940.v1 (for study 1, N = 21) and https://doi.org/10.6084/m9.figshare.5005985.v1 (for RST study 2, N = 34).

Interestingly, a special variant of the RST was used by Klauer and Musch [23]. They presented participants with pairs of words and manipulated both the evaluative meaning of these words (i.e., positive vs. negative) and an orthogonal, non-evaluative stimulus dimension (i.e., location, color, letter case, or grammatical category, in Experiments 5, 6, 7, and 8 respectively). Results showed that participants were faster to indicate that two words were similar in terms of a non-evaluative stimulus dimension (e.g., letter case) when these words were also similar in terms of their evaluative meaning (e.g., ‘love—pretty’ or ‘HATE—UGLY’) as compared to when these words had a different evaluative meaning (e.g., ‘love—ugly’ or ‘HATE—PRETTY’). Likewise, participants were faster to indicate that two words were dissimilar in terms of a non-evaluative stimulus dimension when these words were also dissimilar in terms of their evaluative meaning (e.g., ‘love—UGLY’ or ‘HATE—pretty’) as compared to when these words had the same evaluative meaning (e.g., ‘LOVE—pretty’ or ‘hate—UGLY’). In other words, task performance was best when task-irrelevant and the task-relevant relational stimulus information promoted the same response (for reviews of related findings, see [24, 25]). In structural terms, this setup is identical to the RST used by Paivio [17], except for the fact that nature of the relational information under study was different (i.e., a simple similarity relation vs. a more complex size relation, [18]). Similar findings in the perceptual domain were reported, amongst others, by Proctor and colleagues [26].

As explained above, the findings obtained with the RST are important because they suggest that automatic relational stimulus processing can occur even if the stimuli that enter the comparison process are not stored in working memory. Still, the usefulness of the RST as a tool to study automatic relational stimulus processing is limited. By definition, the RST requires dimensional overlap [27] between a task-relevant and a task-irrelevant (relational) stimulus dimension. Crucially, it is also a requirement that one of these relational dimensions can be manipulated via perceptual stimulus properties. As a result, the use of the RST is limited to the measurement of automatic relational stimulus processing in the domain of concrete, physical relations. For example, the ability to process conceptual size relations under automaticity conditions can be readily examined by asking participants to respond on the basis of the physical size relation between stimuli (and vice versa) [17]. It is unclear, however, how one could adjust the RST to capture automatic appraisals of abstract relations. It would be very difficult (if not impossible), for example, to construct an RST that allows for the measurement of the automatic appraisal of causal relations. In fact, even the simple automatic appraisal that one food option (e.g., a fresh salad) is healthier than another food option (e.g., a greasy hamburger) would be difficult to capture using the RST. Of course, one might note that the RST variant in which participants respond on the basis of the similarity/dissimilarity of stimuli [23] is quite flexible because it can be used to capture automatic similarity/dissimilarity appraisals across of a wide range of relational domains. However, by definition, this version of the RST does not allow one to probe the automatic appraisal of relational information more complex than simple similarity relations.

These problems can be sidestepped, however, by adopting a Simon-like response task [28]. In the classic Simon task, the compatibility of a required response and a task-irrelevant stimulus dimension varies over trials [18]. Craft and Simon [29], for example, asked participants to respond with a left or right key press based on the color of red and green stimuli presented on the left or the right of a screen. Results showed that participants were faster and more accurate to respond when the spatial position of the required response matched the location of the stimulus than when the spatial position of the required response and the stimulus were different. In sum, performance in a Simon-like response task is better when the required response is compatible with the task-irrelevant stimulus dimension as compared to when the required response is incompatible with the task-irrelevant stimulus dimension. In the past, this basic principle was already used successfully to study automatic evaluative stimulus processing [30] and (non-evaluative) semantic stimulus processing [31]. In the studies by De Houwer and Eelen [30], for example, participants were found to be faster in pronouncing positive and negative words based on a non-evaluative feature of (single) words (i.e., grammatical category) when the evaluative meaning of these words matched rather than mismatched the evaluative meaning of the (correct) response. Likewise, we suspected that the execution of a relational response on the basis of a task-relevant relation between two stimuli might be affected by a task-irrelevant relation between these stimuli, provided of course that there is dimensional overlap between the (relational) response set and the task-irrelevant relation under study.

The approach developed here was in part inspired by Moors and De Houwer [13] who used a Simon procedure to study the automatic appraisal of dominance and submissiveness. In their experiments, participants were presented with complex visual scenes showing the same two persons in different submissive/dominant relationships (e.g., an army officer shouting at a soldier). Each of the two persons acted as a dominant person on some trials and as a submissive person on other trials. Orthogonal to the manipulation of the nature of the interpersonal relationship, each person appeared equally often on the right and the left side of the visual scene and participants were asked to pronounce the words ‘dominant’ and ‘submissive’ based on the location of one target actor. Results showed that participants were faster to respond when the relational meaning of the responses matched the actual relational status of the target actor, despite the fact that relational stimulus information was in fact task-irrelevant. In principle, one can apply this logic to any type of relational information, although the authors themselves did not foresee this broad generalization. Therefore, the main aim of the present research was to demonstrate the generality of this relational Simon effect.

In Experiment 1, we presented participants with pairs of synonyms and antonyms and asked them to pronounce the words “synonym” and “antonym” depending on the match/mismatch in letter case. That is, in line with the general make-up of a Simon task, we manipulated the compatibility of two relational responses on the one hand and a task-irrelevant conceptual relation between two words on the other hand (i.e., the relational Simon task). Assuming that participants would process the (task-irrelevant) conceptual relation between the words automatically, we hypothesized that task performance would be better if the required relational response was compatible rather than incompatible with the conceptual relation. In Experiment 2, we replicated Experiment 1 using non-verbal responses. More specifically, we asked participants to judge a perceptual relation between two words on one subset of trials (i.e., same vs. different letter case) and to judge a conceptual relation between two words on the remaining trials (i.e., synonyms vs. antonyms). Crucially, both types of relatedness were manipulated orthogonally. Based on the assumption that participants would engage in an automatic appraisal of task-irrelevant relational information, we expected task performance to be better when the task-relevant and the task-irrelevant information promoted the same response as compared to a different response (i.e., the extrinsic relational Simon task). Finally, in Experiment 3, we sought to demonstrate that one could use the (extrinsic) relational Simon task to capture the automatic appraisal of complex comparative stimulus information.

Experiment 1

Experiment 2

The relational Simon task as implemented in Experiment 1 has a practical limitation. By definition, a Simon task requires dimensional overlap between the response set and some task-irrelevant stimulus dimension. Accordingly, for the present research purposes (i.e., automatic relational stimulus processing), it is a requirement that the response set includes response options that are tied to the relational information under investigation. This requirement is easy to meet using verbal responses. In Experiment 1, for example, we simply asked participants to pronounce the words “synonym” and “antonym”, that is, two words that acquired a strong relational meaning because of the learning history of an individual. The use of verbal (relational) responses makes it difficult, however, to run large-scale or online studies because, typically, the presence of an experimenter is required to operate a voice key.

To resolve this issue, in Experiment 2, we adapted the experimental procedure used in Experiment 1 so that participants were required, on a subset of trials, to respond with a left or right keypress based on the conceptual relation between two words (i.e., synonyms vs. antonyms). On the remaining trials, participants used the same set of keys to judge a perceptual similarity relation (i.e., the match/mismatch in letter case). Crucially, we manipulated the conceptual and the perceptual relational dimension independently from each other. As a result, the (correct) response was either compatible or incompatible with the task-irrelevant relation on every trial. For two reasons, we anticipated that participants would be faster and/or more accurate to respond on compatible trials as compared to incompatible trials. First, each of the two responses might acquire an extrinsic relational meaning [38] that either matches or mismatches with the task-irrelevant relational dimension. According to this interpretation, the anticipated compatibility effect would result from (dimensional) overlap between the response set(s) and the irrelevant stimulus dimension(s) [27]. Alternatively, and perhaps more parsimoniously, one could also argue that it is simply easier to execute a response in a task-switch design if the relevant and the irrelevant task promote the same as compared to a different response (i.e., the so-called task-rule congruency effect, see [39]). According to this interpretation, the anticipated compatibility effect would result from overlap between two (otherwise unrelated) response sets (i.e., sometimes referred to as ‘RR compatibility’ [40]). We will return to this issue in the discussion section of Experiment 2.

Results

The raw data of this experiment are available at https://doi.org/10.6084/m9.figshare.5011655.v1. Mean response latencies were again computed after the exclusion of trials on which an incorrect response (12.20%) or a far-out value (2.46%) was registered. Far-out values were defined as values that deviated more than 2.5 standard deviations from the mean of an individual participant in a particular cell of the design [33]. The data of one participant were excluded from the analyses because his/her overall response latency (i.e., 2312 ms) exceeded our cutoff criterion of 2.5 standard deviations above the grand mean (M = 1472 ms, SD = 317 ms; threshold = 2265 ms). The data of two other participants were excluded because of excessive error rates (i.e., 40.23% and 33.59%) in comparison to the complete sample (M = 12.20%, SD = 7.81%; threshold = 31.74%). In sum, the analyses reported below are based on a final sample of 30 participants. None of the results below were contingent upon the exclusion of participants. Detailed descriptive statistics are provided in Table 1.

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Table 1. Mean response latencies (in ms) and mean error rates (in percentages) as a function of trial type and compatibility in Experiment 2 (SE in parentheses).

https://doi.org/10.1371/journal.pone.0186606.t001

The reaction time data were analyzed by means of a 2 (trial type: white trials vs. colored trials) × 2 (compatibility: compatible trials vs. incompatible trials) repeated measures ANOVA. The main effect of trial type was highly reliable: F(1, 29) = 205.69, p < .001, d = 2.62. Participants were much slower to respond on colored trials (M = 1768 ms, SE = 38.79 ms) as compared to white trials (M = 1206 ms, SE = 58.80 ms), suggesting that the synonym/antonym judgment task was much more difficult than the size judgment task. More importantly, the only other effect that reached significance was the main effect of compatibility, F(1, 29) = 4.23, p < .05, d = .38. As expected, participants were faster to respond on compatible trials (M = 1467 ms, SE = 47.16 ms) as compared to incompatible trials (M = 1506 ms, SE = 46.36 ms). There was no statistical evidence whatsoever that the compatibility effect was different for white trials and colored trials, F < 1.

The same set of tests was performed for the error data. In line with the reaction time data, the critical main effect of compatibility was highly reliable, F(1, 29) = 53.28, p < .001, d = 1.33. Participants responded more accurately on compatible trials (M = 7.16%, SE = 1.09%) as compared to incompatible trials (M = 13.91%, SE = 1.59%). The (theoretically less important) main effect of trial type failed to reach significance, F(1, 29) = 2.34, p = .14, d = .28. There was again no evidence for an interaction between the two factors, F < 1.

Experiment 3

The results of Experiments 1 and 2 suggest that one can use the (extrinsic) relational Simon task to capture (automatic) relational stimulus processing. Still, the generalizability of these findings is somewhat limited, for two reasons. First, in Experiment 2, participants switched between two relational tasks that were highly similar to each other. Judging whether two words are synonyms is, in a sense, a similarity judgment task, just like the letter-case comparison task. So, participants switched between a conceptual and a perceptual similarity judgment task, which may have been a prerequisite for the (extrinsic) relational Simon effect to occur. Second, even if a high degree of similarity between the two relational tasks was not a necessary precondition for the effect to occur, the relational information under study was relatively simple. Whereas existing tools already allow for a measurement of (automatic) similarity judgments (e.g., [23]), it is a unique strength of the (extrinsic) relational Simon task that it can be readily adjusted to allow for the measurement of complex rank-order judgments.

Accordingly, to demonstrate this versatility of the (extrinsic) relational Simon task, we conducted a final study in which participants switched between two unrelated relational tasks, one of which required rank-order judgments. In Experiment 3, we presented participants with pairs of digits either in the same color or in a different color. On one subset of trials (indicated by the presentation of two digits in white), participants indicated as quickly as possible whether the largest digit appeared on the left or the right side of the computer screen. On the remaining trials (indicated by the presentation of digits in red, green, blue or yellow), a simple color similarity judgment was required. We thus switched back to a traditional extrinsic Simon approach in the sense that an orthogonal manipulation of the two relational dimensions was restricted to one subset of (diagnostic) trials. Despite the fact that the two relational tasks were quite dissimilar, we expected participants to respond faster and more accurately on the color judgment trials if the (task-irrelevant) size relation between the digits promoted the same versus a different response.

Results

The raw data of this experiment are available at https://doi.org/10.6084/m9.figshare.5008973.v1. The data of one participant were excluded from the analyses because his/her overall mean response latency (i.e., 1083 ms) exceeded our cutoff criterion of 2.5 standard deviations above the grand mean (M = 729 ms, SD = 113 ms; threshold = 1011 ms). Likewise, the data of one participant were excluded because of an exceptionally high error rate (i.e., 32.81%) in comparison to the complete sample (M = 10.52% ms, SD = 7.72%; threshold = 29.81%). Analyses were restricted to the 192 (critical) color trials. Mean response latencies were computed after the exclusion of trials on which an incorrect response (9.24%) or a far-out value (2.33%) was registered. Far-out values were again defined as values that deviated more than 2.5 standard deviations from the mean of an individual participant in a particular cell of the design (see [33]). Detailed descriptive statistics are provided in Table 2.

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Table 2. Mean response latencies (in ms) and mean error rates (in percentages) as a function of response assignment and compatibility in Experiment 3 (SE in parentheses).

https://doi.org/10.1371/journal.pone.0186606.t002

The reaction time data were analyzed by means of a 2 (response assignment) × 2 (compatibility) repeated measures ANOVA. The only effect that reached significance was the main effect of compatibility (i.e., the extrinsic relational Simon effect), F(1, 21) = 20.17, p < .001, d = .96. As predicted, participants were faster to respond on compatible trials (M = 699 ms, SE = 18.18 ms) as compared to incompatible trials (M = 737 ms, SE = 19.72 ms). An analysis of the error data revealed the same pattern of effects. The main effect of compatibility was reliable, F(1, 21) = 9.98, p < .001, d = .65, and did not depend on the nature of the response assignment, F < 1. Participants made fewer errors on compatible trials (M = 5.35%, SE = 0.82%) as compared to incompatible trials (M = 13.14%, SE = 2.42%).

General discussion

While research on automatic stimulus processing has focused almost exclusively on the (semantic) analysis of single stimuli, increasingly more studies suggest that the realm of automatic stimulus processing extends to complex relational information [9–11, 15–17, 19–23, 26, 46, 47]. The present studies add to this line of research by showing that the (extrinsic) relational Simon task can be used to capture automatic relational stimulus processing. In each of these experiments, we observed a clear-cut (extrinsic) relational Simon effect, that is, irrespective of the type of stimulus materials used, irrespective of the similarity between the relational information that was task-relevant and the relational information that was task-irrelevant, and irrespective the complexity of the task-irrelevant relational information. We can thus conclude that the (extrinsic) relational Simon effect is a robust phenomenon that, given its procedural flexibility and simplicity, has the potential of becoming a widely applicable instrument to study (automatic) relational stimulus processing.

Importantly, there are good reasons to argue that the (extrinsic) relational Simon effect is characterized by several automaticity features [4]. Remember that the (extrinsic) relational Simon effect can occur only if participants process two (orthogonal) sources of relational stimulus information at the same time. The short response latencies, especially in in Experiment 1 and Experiment 3, thus imply that automatic relational stimulus processing is fast and efficient [4]. Moreover, the observation that participants were influenced by relational information that was task-irrelevant suggests that automatic relational stimulus processing is (at least to some degree) difficult to control [41].

Some caution is in order, however, when evaluating the extent to which participants did or did not engage in intentional processing of the relational information that was task-irrelevant. Both in Experiment 2 and 3, participants switched between two relational tasks based on the color of the to-be-compared stimuli. As a result, participants did not know which task to perform until the critical stimuli appeared on the computer screen. It is thus a possibility that (at least some) participants processed both types of relational information in an intentional manner (on at least a number of trials) to deal with this situation. Although post-hoc analyses seemed to rule out this possibility, it could be worthwhile to conduct follow-up studies examine this issue more thoroughly. For example, one might present a task cue prior to the presentation of each trial so that participants can readily ignore relational information that is task-irrelevant [41]. As an alternative approach, one could also manipulate the relative frequency of the two relational tasks so that one relational task becomes the default and the other relational task becomes the exception [44, 48]. If the extrinsic relational Simon effect were to replicate under such conditions, this would be a very strong indication that the occurrence of this effect is not critically dependent on the conscious intention to process the relational information that is task-irrelevant.

It is important to emphasize, however, that the task-switch design used in Experiments 2 and 3 is just one way to study (automatic) relational stimulus processing. In Experiment 1, participants simply performed the same perceptual matching task throughout the entire experiment and conceptual information was always task-irrelevant. Nevertheless, a clear-cut relational Simon effect emerged. This finding is a clear-cut demonstration that relational processing of task-irrelevant stimulus information can indeed take place even in the absence of the (conscious) goal to do so. Research conducted by Proctor and Healy [49] also corroborates this conclusion. They presented participants with pairs of letters strings and asked them, in one condition, to classify these pairs as ‘same’ if the strings contained the same letters, regardless of whether the letters were in the same order (and as ‘different’ if different letters were used for the two strings). Results showed that participants were slower to respond to the rearranged (but otherwise identical) letter pairs as a function of the total number of positions that letters were displaced. Such a displacement effect indicates that participants were unable to ignore the order information (which is relational by definition), despite the fact that this order information was entirely task-irrelevant (for related findings, see [50, 51]).

It must be noted, however, that both our studies and those reported by Proctor and Healy [49] are characterized by an important procedural limitation. Even though participants were not required to process the relational information that was task-irrelevant, the experimental task did require the participants to engage in relational stimulus processing. The question thus arises whether the activation of such a relational processing goal is a necessary precondition for the (extrinsic) relational Simon effect to occur (i.e., goal-dependent unintentionality, see [4]). To examine this possibility, instead of asking participants to pronounce the words ‘synonym’ and ‘antonym’ based a perceptual relation between two words (cf. Experiment 1), one may ask participants to use these relational responses based on a perceptual feature of just one of the two words. If the relational Simon effect would replicate under these conditions, this observation would provide a very strong argument in favor of the hypothesis that automatic relational stimulus processing is not critically dependent upon the activation of an explicit relational processing goal.

In this context, it is perhaps interesting to refer to a relatively old but ingenious sequential priming study reported by McKoon and Ratcliff [52]. In a lexical decision task, they presented participants with word pairs that were all highly associated. Crucially, each prime word was paired with two different target words to create different types of semantic relatedness. For example, in one subset of trials, synonym pairs (e.g., close–near) were contrasted with antonym pairs (e.g., close—far). Likewise, in another subset of trials, two members of the same category (e.g., car—truck) were contrasted with word pairs consisting of a category member and a category name (e.g., car—vehicle). Mckoon and Ratcliff [52] embedded these critical word pairs in a context of filler trials so that, for example, synonym/antonym pairs were tested either in a list of mostly synonym pairs or mostly antonym pairs. The results clearly showed that target responding was speeded when a pair was tested in a list of other pairs of the same relation as itself relative to a list of pairs of a different relation. For example, antonym pairs in an antonym list were associated with faster response times than did antonym pairs in a synonym list. This observation is important as it implies that participants picked up the broader relational context and applied it to the individual trials under automaticity conditions, even in the absence of an explicit relational target task. In fact, observations like those reported by McKoon and Ratcliff [52] can be taken as evidence that relational stimulus processing may very well be the rule rather than the exception (but see [53]).

This conclusion is also relevant for the field of so-called implicit measures. It is a well-known fact that the validity of self-report measures (e.g., questionnaires, interviews) can be quite low if respondents are unwilling and/or unable to self-diagnose and report the to-be-measured psychological construct [54–56]. To circumvent this problem, researchers have developed a wide range of assessment tools, often referred to as implicit measures, that allow one to capture psychological constructs under automaticity conditions [57]. Typical examples are the implicit association test [58], the evaluative priming paradigm [59, 60], the (extrinsic) affective Simon task [44], and the affect misattribution paradigm [61]. Crucially, each of these measures capitalizes on the idea that the presentation of a stimulus results in an automatic and unconditional retrieval of associated attributes from memory. In many cases, however, it is not only important to determine the extent to which two concepts (e.g., a target concept and a target attribute) are related in memory but also the precise way in which they are related [62–64]. In the context of depression, for example, it makes a huge difference to know whether an association between the self and the attribute ‘good’ reflects actual self-esteem (i.e., the belief that one is good) or ideal self-esteem (i.e., the desire to feel good about oneself, see [63–65]). To capture this type of complex relational information, (implicit) measures are needed that allow one to diagnose how individuals tend to relate different concepts. Two such measures were developed relatively recently, i.e., the implicit relational assessment procedure [66] and the relational responding task [67]. The present research adds to this literature by showing that one can also use a Simon-like procedure to capture automatic relational stimulus processing. For example, again using the same example of implicit self-esteem, one may present participants with two classes of self-descriptive adjectives. One class of adjectives, presented in a white front, consists of adjectives unrelated to self-esteem (e.g., male, female, Belgian). The other class of adjectives, presented in either a blue or a yellow front, consists of adjectives related to self-esteem (e.g., good, bad, competent). Participants can then be asked to judge whether the adjectives apply to them on the white trials and to judge the color of the adjectives on the remaining trials using the same response keys. Using such a setup, the extrinsic relational Simon effect would reflect actual self-esteem at the implicit level. The same logic can be applied to capture ideal self-esteem. Further research would be required though to ascertain whether such an approach would be sensitive and robust enough for actual use in applied settings.