Development of metaphor identification and comprehension: chronological age, mental age, and gender

With respect to chronological age, the results of the current study indicate that the ability to identify and comprehend metaphors increase more between approximately eight and ten years than between seven and eight years, although it has to be noted that the involvement of such a breakpoint yielded only slightly higher explanation rates in the regression models (see Figures 1, 2, and 3). These results yield new knowledge about metaphorical language ability in a previously assumed crucial age span between seven and ten years (see, e.g., Gentner, Reference Gentner1988; Siltanen, Reference Siltanen1989; Winner et al., Reference Winner, Rosenstiel and Gardner1976). Individuals were located in middle childhood and at the transition from middle childhood to early adolescence (see, e.g., Berk, Reference Berk2014; Feldman, Reference Feldman2017; Steinberg, Reference Steinberg2016; see further the ‘Aims of the study’ section above), an age span in which a lot of biological, cognitive, social, and emotional changes take place (see, e.g., Steinberg et al., Reference Steinberg, Vandell and Bornstein2010). As previous studies indicate a change in metaphor processing techniques and properties that can be processed in this age span, our study indicates a possible shift approximately in the middle of this age span, at 8.2 years.

With respect to mental age, analyses showed that fourth-graders exhibited higher metaphor scores than second- and third-graders, whereas the lower grades did not differ statistically. Furthermore, between grades three and four the number of 2-point-answers (correct explanations of metaphoric pairs) apparently increased more than the number of 1-point-answers (less than fully adequate explanations), whereas the lower grades did not differ statistically regarding these scores. These results suggest that mental age in terms of ‘academic age’ (the school system in Austria enabled such a definition, see the ‘Aims of the study’ section above) can potentially be seen as an indicator of metaphor processing. Those children who reach an academic level at which they are prepared for entering a higher school stage (see footnote 1) showed the best metaphor processing performance.

In this study, no gender differences regarding metaphor processing were shown for children before and at the transition from middle childhood to early adolescence. Although Willinger and colleagues (Reference Willinger, Deckert, Schmoeger, Schaunig-Busch, Formann and Auff2017) argued that girls might compensate for the earlier superiority of boys (Lutzer, Reference Lutzer1991) by faster developing verbal abilities, in the current study no significant differences between girls and boys regarding verbal intelligence or linguistic abilities were shown.

The developmental changes suggested in the current study are supported by studies on brain development that show great structural and functional changes in this age span. In this context, it was shown that, at around age eight, children show the highest whole brain volume and grey matter volume (Brain Development Cooperative Group, 2012; Tanaka et al., Reference Tanaka, Matsui, Uematsu, Noguchi and Miyawaki2012) with a consequent great decrease (Brain Development Cooperative Group, 2012; Lebel & Beaulieu, Reference Lebel and Beaulieu2011), most likely due to synaptic pruning processes throughout middle childhood (e.g., Huttenlocher, Reference Huttenlocher, Dawson and Fischer1994). Furthermore, great changes can be seen in children between six and ten regarding neural fibers / white matter tracts (Uda et al., Reference Uda, Matsui, Tanaka, Uematsu, Miura, Kawana and Noguchi2015), whereas children at age eight show the greatest relative increase in whole brain white matter volume (Lebel & Beaulieu, Reference Lebel and Beaulieu2011). Between ages seven and ten, children show peaks in cortical thickness in the somatosensory cortex, the striate primary visual area, the primary motor cortex, and the parietal association areas (Shaw et al., Reference Shaw, Kabani, Lerch, Eckstrand, Lenroot, Gogtay and Giedd2008). These changes support theoretical considerations regarding metaphor processing that will be discussed below (e.g., Conceptual Metaphor Theory; Lakoff & Johnson, Reference Lakoff and Johnson1980/2003). As well as these structural changes, changes in functional connectivity also occur throughout middle childhood and early adolescence as neural activity shows shifts from local to more distributed networks (e.g., Fair et al., Reference Fair, Dosenbach, Church, Cohen, Brahmbhatt, Miezin and Schlaggar2007). Furthermore, such differences in brain structure and function were shown to depend on individual experiences (see, e.g., Steinberg, Reference Steinberg2010).

Although some claim that metaphor competence develops within a continuum, the current study, as well as other recent studies (e.g., Willinger et al., Reference Willinger, Deckert, Schmoeger, Schaunig-Busch, Formann and Auff2017), indicates that children and adolescents might show spurts in metaphorical language development. Regarding the development of metaphor processing, it was shown that (very) young children also understand some metaphors (e.g., Gibbs & Colston, Reference Gibbs and Colston2012; Pérez-Hernández & Duvignau, Reference Pérez-Hernández and Duvignau2016). Research indicates that, before effectively using explicit techniques like comparison and categorization that are commonly associated with metaphoric language (Gentner & Bowdle, Reference Gentner, Bowdle and Gibbs2008; Glucksberg, Reference Glucksberg2001), pragmatic conventions are constructed long before actual language in terms of metaphorical thought (e.g., Alessandroni, Reference Alessandroni2017). In the course of development, children start very early to overextend the meanings of words in order to label things or express (mostly) non-abstract concepts for which they lack literal terms (see, e.g., Clark, Reference Clark2003; Pérez-Hernández & Duvignau, Reference Pérez-Hernández and Duvignau2016; Pouscoulous, Reference Pouscoulous2011). Until approximately age four, children use metaphors in the form of overextended meanings of terms already acquired (Nerlich, Clarke, & Todd, Reference Nerlich, Clarke, Todd, Panther and Radden1999), whereas at some point they are able to deliberately extend meanings in order to intentionally overcome literal borders (e.g., Pouscoulous, Reference Pouscoulous2011). Eventually, this could be seen as a shift from metaphorical thought to metaphorical language (Alessandroni, Reference Alessandroni2017), paving the way [sic] for higher-order metaphoric processing.

Development of metaphor identification and comprehension: metaphor types

Although metaphor processing depends on a number of factors, such as aptness, conventionality, or context (see, e.g., Blasko & Connine, Reference Blasko and Connine1993; Goldstein, Arzouan, & Faust, Reference Goldstein, Arzouan and Faust2012), metaphor competence at a younger age strongly depends on the type of metaphor. The results of the current study showed that across grades two, three, and four attributional (configurational) metaphors were more easily identified and better understood than relational metaphors (conceptual and physiognomic). Fourth-graders showed the significantly highest identification and comprehension regarding all metaphor types, whereas slight differences were shown between second- and third-graders, depending on metaphor type (see the ‘Results’ section and Figure 4). Figure 4 also shows that for chronological age similar results can be expected. Nevertheless, it has to be noted that these results are results of exploratory analyses, due to the small number of items per metaphor type.

Figure 4. Development of metaphor processing between seven and ten years (discrete age groups, Panel a) and between grades two, three, and four (Panel b) with respect to each metaphor type. The y-axis shows the mean scores for each respective score. Mean scores are adjusted for number of items per metaphor type.

These results show that attributional metaphors which represent perceptual similarities based on physical properties are more easily identified and better understood than relational metaphors which represent either affective associations or cross-categorical similarities. The increased comprehension of metaphors that require building relational categories based on cross-categorical and affective grounds in this age span is consistent with previous studies (e.g., Cicone, Gardner, & Winner, Reference Cicone, Gardner and Winner1981; Siltanen, Reference Siltanen1989; Winner et al., Reference Winner, Rosenstiel and Gardner1976), whereas the increase regarding attributional metaphors somehow contradicts the results of Gentner (Reference Gentner1988), which stated that the attributionality of metaphors does not increase with age. These results are in line with previous studies that showed that young children best understand and produce metaphors that are based on physical similarities (e.g., Gentner, Reference Gentner1988; Siquerra & Gibbs, Reference Siquerra and Gibbs2007; Winner, Reference Winner1988/1997).

Explanations for the better understanding of such primary metaphors can be found within the Conceptual Metaphor Theory of Lakoff and Johnson (Reference Lakoff and Johnson1980/2003). They argue that metaphorical meanings originate in sensory and sensorimotor experiences like connecting early experiences of visually seeing things and understanding things because they can be seen (e.g., Gibbs & Colston, Reference Gibbs and Colston2012; Lakoff & Johnson, Reference Lakoff and Johnson1980/2003), and therefore can be expressed in different modalities (e.g., images, gestures, sounds; see, e.g., Alessandroni, Reference Alessandroni2017; Lakoff & Johnson, Reference Lakoff and Johnson1980/2003). As children repeatedly interact with the environment, they increasingly learn to distinguish between domains and to separate domains, especially regarding the sensory and sensorimotor domains (e.g., Gibbs & Colston, Reference Gibbs and Colston2012; Lakoff & Johnson, Reference Lakoff and Johnson1980/2003). Therefore, such metaphors increasingly allow accessing abstract areas of knowledge by connecting them to more and more concrete, physical domains, making them real tools of understanding (e.g., Alessandroni, Reference Alessandroni2017; Lakoff & Johnson, Reference Lakoff and Johnson1980/2003). In this context, it was shown that some primary metaphors are learned before others, like ‘emotional intimacy is proximity’ (e.g., Gibbs & Colston, Reference Gibbs and Colston2012; Lakoff & Johnson, Reference Lakoff and Johnson1980/2003).

These theoretical considerations can be linked to the results of the current study through the Theory of Metaphor Circuity of Lakoff (Reference Lakoff2014) and Narayanan (Reference Narayanan1997). They propose that real-life interactions with the environment lead to the building of embodied metaphor mapping circuits by neural learning. In this way, subsequent metaphorical inferences originate from neural simulation of situations which are understood, whereby complex forms (e.g., linguistic forms) are linked to these metaphorical mappings. Connecting this theory to the results of the current study, it can be hypothesized that such higher-order simulations would be associated with the number of real-life experiences that are collected with chronological age, and greater cognitive abilities with a higher mental age, as well as increased neural capacities given by the structural and functional changes in the brain. The results regarding the indicated spurt around age 8.2 and regarding attributional metaphors which represent perceptual similarities can especially be seen in the light of imaging studies which show that children between seven and nine show peak cortical thickness in regions associated with visual and somatosensory perception as well as motor processes (Shaw et al., Reference Shaw, Kabani, Lerch, Eckstrand, Lenroot, Gogtay and Giedd2008). Around age nine to ten, children show peak cortical thickness in parietal association cortices (Shaw et al., Reference Shaw, Kabani, Lerch, Eckstrand, Lenroot, Gogtay and Giedd2008) which are involved in the integration of sensory and somatosensory inputs (e.g., Purves et al., Reference Purves, Augustine and Fitzpatrick2001).

Development of metaphor identification and comprehension: the role of verbal intelligence and linguistic competence

The results of the current study showed that verbal intelligence significantly predicted metaphor identification and comprehension in the age span nine to ten, but not in seven- to eight-year-olds. These results show that, with respect to metaphor processing, verbal intelligence gains in importance with increasing age. Furthermore, this supports the notion that metaphor can be seen as a central feature of higher cognition and abstract thought (Coulson & Lai, Reference Coulson and Lai2015). Metaphor identification and comprehension showed the highest associations with verbal intelligence score vocabulary, arithmetic, and similarities.

Subtest vocabulary measures semantic knowledge, verbal comprehension, and verbal expression, as well as concept formation and verbal conceptualization; furthermore, it can be seen as an indicator of general language development (Strauss, Sherman, & Spreen, Reference Strauss, Sherman and Spreen2006; Tewes et al., Reference Tewes, Rossmann and Schallberger1999). It requires the examinee to provide definitions for words (Strauss et al., Reference Strauss, Sherman and Spreen2006; Tewes et al., Reference Tewes, Rossmann and Schallberger1999). This result is in line with previous studies showing an association between vocabulary and metaphor comprehension (e.g., Kasirer & Mashal, Reference Kasirer and Mashal2014). Knowledge of words can be seen as a fundamental tool of language in general and consequently also of metaphor processing. It can be hypothesized that a greater knowledge of words and a better understanding of the objects and concepts a word stands for facilitates the task of overcoming literal boundaries. In this way, it provides a tool and/or resources for the analysis of multiple properties. Linking vocabulary to Lakoff and Narayanan's theory of metaphor circuitry (Lakoff, Reference Lakoff2014), it can be further argued that the objects and concepts a word stands for form the basic elements in linking linguistic forms to metaphorical mappings.

Subtest arithmetic measures working memory, arithmetic problem solving, verbal comprehension, concentration, and attention (Strauss et al., Reference Strauss, Sherman and Spreen2006; Tewes et al., Reference Tewes, Rossmann and Schallberger1999), as it requires the examinee to mentally solve orally presented arithmetic problems within a time limit. This result is in line with previous studies showing associations between working memory and metaphor processing (e.g., Godbee & Porter, Reference Godbee and Porter2013).

Subtest similarities measures verbal analogical reasoning, verbal abstraction, concept formation, abstract thinking in terms of categories, verbal expression, and verbal comprehension, as it requires the examinee to describe how two words that represent common objects or concepts are similar (Strauss et al., Reference Strauss, Sherman and Spreen2006; Tewes, et al., Reference Tewes, Rossmann and Schallberger1999). Similar to the processing of metaphors (see, e.g., Gentner & Bowdle, Reference Gentner, Bowdle and Gibbs2008; Glucksberg, Reference Glucksberg2001, Glucksberg & Haught, Reference Glucksberg and Haught2006), properties of objects or concepts have to be analyzed so as to see what they have in common and/or to which categories/classes they belong. Furthermore, one has to decide which properties are of importance, and subsequently reject inadequate similarities that are for example too general. It can be hypothesized that the effective complementary use of comparison and categorization techniques regarding the processing of metaphors (see Career of Metaphor Theory; Gentner & Bowdle, Reference Gentner, Bowdle and Gibbs2008, or Quality of Metaphor Theory; Glucksberg & Haught, Reference Glucksberg and Haught2006) in the MTT can be seen as verbal intelligence performance, as a similar adaptive use of different processing techniques is very likely in subtest similarities. In this context, it has been shown that verbal analogical reasoning is predictive of metaphor comprehension in children with learning disabilities (Mashal & Kasirer, Reference Mashal and Kasirer2012).

Furthermore, although not significant in the regression analyses, linguistic competence subtest comprehension showed associations with metaphor processing similar to verbal intelligence subtests. Subtest comprehension measures verbal comprehension of sentences of varying grammatical complexity, which requires the examinee to re-enact heard sentences with toys (Grimm & Schoeler, Reference Grimm and Schoeler1990). This result is in line with previous studies regarding the role of linguistic competence (see, e.g., Johnson, Reference Johnson1991). At this point, it has to be noted that, for pragmatic reasons, two representative tests of linguistic competence were investigated. It cannot be ruled out that other subtests of the HELD would have yielded positive results in the analyses.

The role of the previously mentioned predictors is shown in an exemplary MTT item: ‘Fish – Winding River – Snake’. First, the properties of ‘fish’ (animal, lives in the water, some fish are predators, differs in body size and form, …), ‘winding river’ (elongated object in the nature in which water flows, home to many animals, winds through a landscape, …), and ‘snake’ (animal, lives on land or in water, predator, moves using winding movements of its long flexible body, …) have to be accessed from knowledge (vocabulary), and the concepts they stand for understood. These words have to be saved in working memory and, using verbal reasoning techniques, compared to see which properties they have in common, whereas inadequate properties like, e.g., ‘all objects can be found in nature’ (too general) have to be rejected. Successful processing of the metaphorical pair (‘Winding river’ and ‘Snake’) requires children to overcome literal boundaries and to give answers like “both the snake and the river wind through the landscape”, “both move through the country in winding movements”, “both meander through the landscape”, or the like.

The results regarding the increasing importance of verbal intelligence are in line with studies that argue that early metaphors become gradually more linguistically articulated (e.g., Melogno, Pinto, & Levi, Reference Melogno, Pinto and Levi2012). In this context, it was shown that, between ages three and five, children repeated metaphoric sentences similar to literal sentences, but had problems repeating anomalous sentences (Pearson, Reference Pearson1990), whereas five-year-olds showed some ability to verbally reason about metaphorical mappings (Ozcaliskan, Reference Ozcaliskan2005). Furthermore, Willinger and colleagues (Reference Willinger, Deckert, Schmoeger, Schaunig-Busch, Formann and Auff2017) proposed that metaphor competence in childhood and early adolescence could be influenced by increasing communicative experience (see, e.g., Hoff, Reference Hoff2006) in the course of increasingly complex relationships (see, e.g., Steinberg et al., Reference Steinberg, Vandell and Bornstein2010).

Development of metaphor preference: chronological age, mental age, and gender

With respect to chronological age, the results of the current study indicate that the preference for metaphors increases more when individuals have reached approximately age ten than between seven and ten. Similar to metaphor identification and comprehension, it has to be noted that the involvement of such a breakpoint yielded only slightly higher explanation rates in the regression models (see Figures 1, 2, and 3). These results indicate that individuals increasingly prefer metaphors when they are at the transition from middle childhood to early adolescence, approximately at age ten, which is in line with previous studies (Silberstein, Reference Silberstein1980; Silberstein, Gardner, Phelps, & Winner, Reference Silberstein, Gardner, Phelps and Winner1982).

With respect to mental age, analyses showed that fourth-graders exhibited higher metaphor preference than second- and third-graders, whereas the lower grades did not differ statistically. Similar to metaphor identification and comprehension, results indicate that those children who reach an academic level at which they are prepared for entering a higher school stage showed the highest preference for metaphors.

Besides the previously mentioned structural and functional changes in the brain, studies further indicate peaks in frontal lobe, parietal, and temporal lobe grey matter between approximately ten and eleven years (Lenroot & Giedd, Reference Lenroot and Giedd2006; Tanaka, Matsui, Uematsu, Noguchi, & Miyawaki, Reference Tanaka, Matsui, Uematsu, Noguchi and Miyawaki2012). Furthermore, besides great changes regarding white matter tracts between ages six and ten (Uda et al., Reference Uda, Matsui, Tanaka, Uematsu, Miura, Kawana and Noguchi2015), at approximately age ten, peak cortical thickness was shown regarding parietal association cortices and the frontal pole, as well as higher-order cortical areas like the dorsolateral prefrontal cortex and the cingulate cortex (Shaw et al., Reference Shaw, Kabani, Lerch, Eckstrand, Lenroot, Gogtay and Giedd2008).

Similar to the results regarding metaphor identification and comprehension, no gender differences regarding metaphor preference were shown.

Development of metaphor preference: metaphor types

The results of the current study showed that across grades two, three, and four attributional (configurational) metaphors were more preferred than relational metaphors (conceptual and physiognomic). Fourth-graders showed the significantly highest preference regarding all metaphor types, whereas slight differences were shown between second- and third-graders, depending on metaphor type (see ‘Results’ section and Figure 4). Figure 4 also shows that for chronological age similar results can be expected.

The result that attributional metaphors were more preferred than relational metaphors is in line with previous studies offering data on metaphor preference development (e.g., Willinger et al., Reference Willinger, Deckert, Schmoeger, Schaunig-Busch, Formann and Auff2017) and the development of metaphor type comprehension (please see above). In the early years, children seemingly (unconsciously) prefer metaphors in terms of overextended word meanings in order to label things or express (mostly) non-abstract concepts for which they still lack literal terms (see, e.g., Clark, Reference Clark2003; Perez-Hernandez & Duvignau, Reference Pérez-Hernández and Duvignau2016; Pouscoulous, Reference Pouscoulous2011). Later on, they become able to deliberately extend word meanings in order to intentionally overcome literal borders (e.g., Pouscoulous, Reference Pouscoulous2011). In the course of childhood and adolescence, professionals use metaphors in the education of children (Williams, Reference Williams1988) and in clinical treatments of children (e.g., Kallady, Reference Kallady2015), for example for explaining illnesses (Whaley, Reference Whaley1994), whereas parents use metaphors with their children so as to compare similarities, add interest, and positively evaluate them (Sell, Kreuz, & Coppenrath, Reference Sell, Kreuz and Coppenrath1997). Generally, metaphors are mainly used to clarify, add interest, be eloquent, compare similarities, and to provoke thought (Roberts & Kreuz, Reference Roberts and Kreuz1994).

Development of metaphor preference: the role of verbal intelligence and linguistic competence

The results of the current study showed that verbal intelligence significantly predicted metaphor preference in the age span nine to ten but not in seven- to eight-year-olds. These results indicate that, regarding metaphor processing, verbal intelligence gains in importance with increasing age. Metaphor preference showed the highest associations with verbal intelligence scores vocabulary, arithmetic, and comprehension, whereas verbal intelligence scores vocabulary and arithmetic were already associated with metaphor identification and comprehension.

Subtest comprehension measures knowledge about general principles, knowledge about social situations and practices, verbal reasoning and concept formation, verbal comprehension and expression, practical judgment, learning from experiences, social maturity, and common sense, as well as social judgment, and is dependent on cultural aspects (Strauss et al., Reference Strauss, Sherman and Spreen2006; Tewes et al., Reference Tewes, Rossmann and Schallberger1999). The examinee is required to answer questions based on his/her understanding of general principles and social situations (Tewes et al., Reference Tewes, Rossmann and Schallberger1999).

Given this result, it can be hypothesized that children who have a greater general understanding are more interested in and show greater stimulation by metaphoric contents. Their increased understanding could enable them to overcome literal boundaries more easily and to be more receptive to the stimulating aspects of metaphors. In this context, a fMRI study showed that, compared to literal control passages, metaphor processing was associated with increases in brain regions that are associated with emotional processing (Citron, Güsten, Michaelis, & Goldberg, Reference Citron, Güsten, Michaelis and Goldberg2016). Regarding the stimulating nature of metaphor, it was further shown that metaphor processing was associated with the need for cognition (Olkoniemi, Ranta, & Kaakinen, Reference Olkoniemi, Ranta and Kaakinen2016), as well as participation in cognitively stimulating activities (Lifshitz-Vahav, Shnitzer, & Mashal, Reference Lifshitz-Vahav, Shnitzer and Mashal2016). Furthermore, metaphors are used to create and reinforce social intimacy (Horton, Reference Horton2007, Reference Horton2013), and are more often used to describe emotional states than, for example, actions (Fainsilber & Ortony, Reference Fainsilber and Ortony1987). In this context, it was further shown that even five-year-olds recognize specific emotions that are expressed by metaphors (Waggoner & Palermo, Reference Waggoner and Palermo1989) and that parents use metaphors to positively evaluate their children (Sell et al., Reference Sell, Kreuz and Coppenrath1997).

This hypothesized stimulating effect of metaphors gets support from Relevance Theory (Sperber & Wilson, Reference Sperber, Wilson, Horn and Ward2004), which can be applied to metaphors. In this context, Gibbs and Tendahl (Reference Gibbs and Tendahl2006) evaluated the predictive value of Relevance Theory with respect to metaphor processing in terms of maximizing cognitive effect and minimizing cognitive effort. In the course of this theory, some claim that metaphor processing requires additional cognitive effort but yields more effects than literal speech. Linking this claim to the current study, it can be hypothesized that individuals with increased understanding tend to accept this additional cognitive effort because they are able to (unconsciously) grasp the stimulating aspects of a metaphor. Another claim is that metaphor processing is stopped at the first interpretation that satisfies the expectation of the relevance of a linguistic content. Regarding this link, it can be hypothesized that children with greater achieved understanding increasingly use these real-life experiences to form metaphor mappings (see statements above and Lakoff, Reference Lakoff2014) and therefore grasp the simulating nature of metaphors more pronouncedly than children who do not have so many experiences at their disposal.

In this study, in accordance with Kogan and Chadrow (Reference Kogan and Chadrow1986), metaphor preference was defined as the identification of a metaphoric pair at the first attempt, followed by a correct or less than fully adequate explanation. Therefore, in this study, real preference for metaphorical contents was based on identifying as well as understanding the metaphor to a certain degree. It can be hypothesized that metaphor identification as well as comprehension itself can be seen as ‘academic’ performance that is based on logical deductive verbal reasoning and factual knowledge about words and the objects, entities, and principles they stand for. On the other hand, those who prefer metaphors can be seen as ‘connoisseurs’ who enjoy the metaphorical contents, based on understanding metaphors via inferential reasoning which itself is based on general knowledge and understanding. The authors of the current study address this topic in an upcoming publication (Deckert et al., unpublished observations).

At this point, it has to be noted that most of the explanations in this study are theoretical and raise new research questions for future studies. Future studies should investigate different aspects of metaphor processing and possible predictors using different neuroscientific imaging methods.

Prospect of a cognitive model of metaphor processing in middle childhood and early adolescence

Finally, we present a summary of cognitive predictors and theoretical considerations that build the basis of a cognitive model of metaphor processing in individuals from middle childhood to middle adulthood that is currently evaluated by our study group. In the following, we will focus on the age span investigated in a recent study (Willinger et al., Reference Willinger, Deckert, Schmoeger, Schaunig-Busch, Formann and Auff2017), as well as the current study, namely middle childhood to early adolescence.

In advance, a theoretical consideration that partially influences the model is that the authors of the current study hold the view that metaphors, at least when measured by the MTT, presumably pose to some degree some kind of ill-structure problems which involve a certain level of uncertainty (for example “WHICH of the three words have something in common?” and “WHAT do they have in common?” in the MTT vs. “WHAT do these words have in common?” in the similarities subtest used in this study). Furthermore, the following summary concerns linguistic articulated/verbal metaphors. Overlaps with the processing of visual metaphors are very likely but will not be discussed here.

First, the metaphorical words/utterances are received via verbal comprehension ability (see properties of the WISC-III subtests in the current study). Next, the properties of the objects, concepts, or principles these words/utterances stand for need to be accessed from semantic knowledge (subtest vocabulary, current study). A greater knowledge of words presumably provides a tool as well as resources for the analyses of multiple properties which are most likely fundamental components in metaphor processing (see, e.g., Lakoff, Reference Lakoff2014). Therefore, the individual is required to produce a temporary mental pool containing a number of properties regarding vehicle and topic which are mostly directly accessed from knowledge. Producing such a mental pool resembles processes of divergent thinking, a cognitive performance that has already been associated with ill-structured problems (Del Missier, Visentini, & Mäntylä, Reference Del Missier, Visentini and Mäntylä2015). Deductive/convergent thinking, on the other hand, in terms of the ability to identify and complement relational systems based on similarities (non-verbal analogical reasoning; see, e.g., Willinger et al., Reference Willinger, Deckert, Schmoeger, Schaunig-Busch, Formann and Auff2017), seemingly lays the basis for the next processing steps. Together with verbal reasoning (current study), these analogical reasoning abilities additionally allow the generation of further inferences based on these similarities (see, e.g., Gentner & Smith, Reference Gentner, Smith and Ramachandran2012). In this context, verbal reasoning (which can be seen as the language-related ability to identify and complement relational systems) seems to hold a special role in metaphor processing, together with verbal abstraction and concept formation (current study). These abilities presumably serve as ‘translation tools’ that allow for processing language contents (see vocabulary) by means of general (reasoning) and special metaphor processing techniques like comparison (Gentner & Bowdle, Reference Gentner, Bowdle and Gibbs2008) or categorization (Glucksberg, Reference Glucksberg2001). In the course of these deductive thinking procedures relevant similarities between topic and vehicle have to be identified whereas irrelevant similarities have to be rejected (see, e.g., Glucksberg, Reference Glucksberg2001), which requires decision-making ability (current study, see properties of WISC-III subtest similarities). Although the literature struggles to define exact decision criteria in metaphor processing (see Relevance Theory; Gibbs & Tendahl, Reference Gibbs and Tendahl2006), decision-making was shown to be predictive of solving ill-structured problems (Del Missier, Visentini, & Mäntylä, Reference Del Missier, Visentini and Mäntylä2015). Studies suggest that in order to process metaphors adequately it is presumably necessary to analyze words and phrases repeatedly by means of different and/or already used but modified mental operations (Willinger et al., Reference Willinger, Deckert, Schmoeger, Schaunig-Busch, Formann and Auff2017). Such procedures are possibly influenced by working memory capacity and inhibition ability, which potentially enable the maintenance of already generated interpretations in the mind for further processing and evaluation, and to successfully suppress irrelevant properties (see current study but also, e.g., Godbee & Porter, Reference Godbee and Porter2013; Kintsch, Reference Kintsch2000). These processes could be further influenced by mental capacity, which allows for the simultaneous activation of different task-relevant schemes that are not adequately activated by situational inputs (Johnson & Pascual-Leone, Reference Johnson and Pascual-Leone1989). Recent studies suggest that cognitive flexibility under time pressure, in the form of set-shifting (see Diamond, Reference Diamond2013) holds a special role in metaphor processing as it seemingly facilitates the adaption of processing strategies in a flexible and quick way as it allows for an efficient iterative processing and potentially facilitates to overcome literal boundaries (Willinger et al., Reference Willinger, Deckert, Schmoeger, Schaunig-Busch, Formann and Auff2017). Cognitive flexibility was also shown to predict performance in ill-structured decision problem solving (Vandermorris, Sheldon, Winocur, & Moscovitch, Reference Vandermorris, Sheldon, Winocur and Moscovitch2013). Furthermore, it was shown that information processing speed predicts metaphor processing as it most likely addresses the speed requirements of language processing (Willinger et al., Reference Willinger, Deckert, Schmoeger, Schaunig-Busch, Formann and Auff2017).

The authors of the current study assume that many of the previously mentioned abilities are also important for metaphor preference but refer to the results of the current study which suggest that instead of relying on semantic knowledge in the form of vocabulary and logical deductive verbal reasoning, those who prefer metaphoric contents possibly rather rely on inferential reasoning that is itself based on general knowledge.

It can be assumed that the development of metaphor processing is strongly influenced by brain development (see, e.g., Blakemore, Reference Blakemore2008; Brain Development Cooperative Group, 2012; Shaw et al., Reference Shaw, Kabani, Lerch, Eckstrand, Lenroot, Gogtay and Giedd2008; Steinberg, Reference Steinberg2010; Wendelken, O'Hare, Whitaker, Ferrer, & Bunge, Reference Wendelken, O'Hare, Whitaker, Ferrer and Bunge2011; Yin et al., Reference Yin, Liu, Zeljic, Wang, Lv, Fan and Wang2016) and presumably influenced by communication experience (see, e.g., Hoff, Reference Hoff2006; Steinberg, Reference Steinberg2016). This summary includes a number of cognitive abilities which theoretically underlie metaphor processing but there is no claim for completeness. The authors of the current study currently evaluate a cognitive model of metaphor processing by including these predictors within a single study design using a sample of individuals from middle childhood to middle adulthood (Deckert et al., unpublished observations).

Take-home message

• • Throughout life, metaphor can be seen as central feature of human communication, higher cognition, and abstract thought.

• • Chronological as well as mental age are positively associated with metaphor processing.

• • Middle childhood and the transition from middle childhood to early adolescence is seemingly a crucial age span for the development of higher-order metaphor processing.

• • Results indicate a possible spurt in metaphor comprehension at approximately 8.2 years.

• • In the investigated age span, metaphors that represent perceptual similarities based on physical properties are best identified, best understood, and most preferred.

• • These results are supported by studies on metaphor competence and brain development as well as by established theories.

• • Verbal intelligence is positively associated with metaphor processing, whereas this effect becomes stronger with increasing age.