Intervention 2 — Feedback from Cecilia (What are the other strengths of dyslexic people?)

After talking to Cecilia, she told me that looking for the strengths of dyslexic people is crucial if we are to change parents’ perceptions. This allows parents to understand that encouragement and the right guidance can lead to a better life for their children and that academic achievement is not the only criterion by which a person is judged.

This week, I have read a lot of papers and gained some knowledge:

Nearly forty years ago, Norman Geschwind noted an increasing number of studies suggesting that those with DD have superior talents in certain non-verbal skills that relate to art, architecture, engineering, and athletics. He was the first to highlight a likely evolutionary basis for the differences observed and, further, he suggested that when a relatively broad swath of a population exhibits a seemingly adverse condition, it is worth asking whether there might be some countervailing advantage at play (Geschwind, 1982). Decades on, researchers continue to ask similar questions, including Eide and Eide (2019), who noted: “[T]he question we need to be asking is not what’s wrong with the dyslexic brain, but what is dyslexic cognition for, what are these brains really built to do?.”

——————————————————————————————————————-

Until now, literature on the negative aspects of DD has dominated the ﬁeld. Stein highlighted that the relatively high incidence of impaired development of the magnocellular system in individuals with DD “would not be so common unless there were compensating advantages for dyslexia” (Stein, 2001, 13). Like Stein, Nicolson and Fawcett have noted (Nicolson, 2014) that cognitive and neurophysiological theories regarding automatization may also help to explain some of the enhanced abilities observed in individuals with DD. They have suggested, for example, that the delay in automatization presents a trade-oﬀ in that conscious access to information is retained, making it easier to modify and integrate information and, in turn, to facilitate innovation (Nicolson, 2014).

PROPOSED AREAS OF ENHANCED ABILITY ASSOCIATED WITH DEVELOPMENTAL DYSLEXIA:

Areas of enhanced ability that are consistently reported as being typical of people with DD include seeing the big picture, both literally and ﬁguratively (e.g., von Károlyi, 2001; Schneps et al., 2012; Schneps, 2014), which involves a greater ability to reason in multiple dimensions (e.g., West, 1997; Eide and Eide, 2011). Eide and Eide (2011) have highlighted additional strengths related to seeing the bigger picture, such as the ability to detect and reason about complex systems and to see connections between diﬀerent perspectives and ﬁelds of knowledge, including the identiﬁcation of patterns and analogies. They also observed that individuals with DD appear to have a heightened ability to simulate and make predictions about the future or about the unwitnessed past (Eide and Eide, 2011).
Individuals with DD have been proposed to exhibit greater ability in various areas of creativity. This has inspired several studies that have reported evidence for enhanced creative ability in a number of realms ranging from freeform drawing and other artistic objects (Cohn and Neumann, 1977) to literary creativity (Rack, 1981). Studies of creative ability also show evidence of a heightened ability to connect and carry out unusual combinations of ideas (Cancer et al.,2016), as well as a heightened ability in tasks requiring novelty, insight, and more innovative styles of thinking (Everatt et al., 1999).

Practitioners have long observed that there appear to be high proportions of people with DD in professions and courses of study that rely on these abilities such as art and design, engineering, and entrepreneurship (see e.g., Geschwind, 1982; Martino and Winner, 1995; West, 1997; Newman and Sternberg, 2012).
In the realm of entrepreneurship, there has also been a growing interest in the apparently large numbers of entrepreneurs with DD (Alexander-Passe et al.,2021). A study of entrepreneurs in the United States found that 35% were dyslexic, with 22% being highly or extremely dyslexic (Logan, 2009).
In students enrolled in higher education, the incidence of DD is particularly high in creative subjects like arts and engineering. Wolﬀ and Lundberg (2002) studied students enrolled at the University of Gothenburg, Sweden. They found that the prevalence of DD was signiﬁcantly higher in students studying ﬁne arts and photography compared with students studying economics and commercial law. At Central St Martins, University of the Arts London, United Kingdom, 75% of foundation year students had some form of DD (Steﬀert, 1996), and at the Royal College of Art, United Kingdom, 29% of students self-identiﬁed as having DD (RCA, 2015). In a study covering several United Kingdom universities across four degree disciplines (engineering, law, medicine, and dentistry), Lemon and Shah (2014) reported that self- identiﬁed DD in engineering was 28% compared with 5% in law. These self-reported ﬁgures are particularly high given that most people with DD do not get diagnosed (Aston et al., 2019). In these studies, it is tacitly assumed that admission to the degree programs ensured a high level of subject- speciﬁc talent, and the conclusion is therefore that higher education students with demonstrable skills in the arts and engineering are more likely to be dyslexic than students in non- creative subjects.

——————————————————————————————————————-

A New Framework: Cognitive Search

Approaches to explaining DD must account for both the difficulties and the enhanced abilities that are typical of people with DD. All the proposed strengths outlined above relate in some way to seeking out the unknown, often at the expense of exploiting known information. A useful framework for tying together these observations is cognitive search, which involves a trade-off between exploration–exploitation.

What Is Search?

Animals need to identify information and resources that have survival value. Since the availability of resources and information varies with time and location, the optimal search strategy will also vary. Moreover, uncertainty caused by environmental variability may obfuscate the optimal strategy. Any search thus involves navigating the trade-off between spending time and energy exploring new possibilities versus exploiting existing information.

Tipping the balance too far toward either exploration or exploitation puts the animal at risk of not obtaining the resources – or knowledge – needed to survive. Exploring endlessly without exploiting what has been found can be inefficient, whereas focusing too much on exploitation may be suboptimal or result in failure to adapt to change. This trade-off arises in many seemingly unrelated areas of endeavor, from evolution to the economy to artificial intelligence (Holland, 1992).

The simplest case is animals foraging for food. They could remain in a known area, where they exploit a local patch of resources; alternatively, they could search globally, exploring the unknown area beyond; or they could pursue any strategy in between. Animals can also search using their sensory systems. In the visual modality, an explorative search strategy could involve taking in a greater proportion of the visual scene to ascertain the visual gist, albeit more diffusely sampled. Another example could be moving the focus frequently between patches of information at the expense of analyzing specific visual points of interest in fine detail.

Search can also occur in more abstract spaces over information landscapes instead of physical ones, e.g., in searching for a new policy or solution to a problem. For problem solving, explorative search would lead to more original solutions rather than the exploitation of solutions that worked in the past. The more globally explored an information space, the greater the possibility of novel recombination or translation of knowledge between realms. Recombination has been argued to be one of the greatest drivers of innovation in the economy and in nature (Arthur, 2009; Page, 2011).

Appropriately balancing the trade-off between exploration and exploitation is essential to adaptive success in a complex, changing world (Cohen et al., 2007), and it is therefore thought to be one of the most significant selective forces operating in the evolution of cognition (Hills et al., 2010). Hence, search can be used as a unifying framework to understand many aspects of cognitive function and behavior across domains (Hills et al., 2015).

Given the nature of the difficulties and strengths proposed to exist in people with DD, we hypothesized that DD may reflect a cognitive specialization toward explorative search. In the next section, we examine whether cognitive and neurophysiological research shows evidence of enhanced explorative search relative to the general population, or any correspondingly diminished ability in local search and exploitation in people with DD.

Reframing Dyslexia-Associated Cognition From the Perspective of Search

As noted above, search is fundamental to how we understand behavior, from cognitive control over a range of domains to the evolution of cognition. We review existing data on individuals with DD covering a range of different cognitive domains and modalities. We examine evidence for cognitive differences from the perspective of cognitive search as characterized by the exploration–exploitation trade-off. We consider external search (i.e., perceiving and selectively attending to information in the external environment), then internal search (i.e., searching for information in memory or using information from memory to search for solutions to problems), and finally, neurophysiological characteristics. Note that different terms are used across disciplines to refer to an emphasis on exploration or exploitation

Supporting evidence varies greatly, depending on the area of cognition under study and its perceived relevance in understanding reading and writing difficulties. Nevertheless, regardless of the modality or specific terminology used, the recurring pattern that emerges supports the hypothesis that people with DD can be viewed as being specialized in explorative (global) search.

External Search

Just as organisms search their external environments by moving in physical space, they may also search for external information through attentional search (Hills and Dukas, 2012). An organism’s external world can be imagined as a multi-dimensional search space maintained using information available from all its senses (Hills and Dukas, 2012). Although much irrelevant information may be filtered out, it may still be impossible to process all information relevant to adaptation owing to limitations in sensory processing capacity and the brain’s limited rate of processing information. Given these constraints, a strategy for directing attention toward the most relevant cues in the information space at any particular time is necessary (Hills and Dukas, 2012). The most relevant information is that which confers a survival advantage (Dukas and Ellner, 1993). Hence, similarly to how search may take place in a physical space, in an information space, animals also need to navigate the exploration–exploitation trade-off. Below we consider information search in the visual and auditory modalities to examine how individuals with DD navigate this search’s trade-off in perceptual information spaces.

Visual Search

Visual information search refers to the analysis of visual information in order to identify visuospatial characteristics. The existence of visuospatial talents in individuals with DD has often been proposed (e.g., Geschwind, 1982; West, 1997; Eide and Eide, 2011). Gilger reviewed studies of dynamic and complex spatial processing in participants with and without DD, and he found that the empirical data for a general visuospatial advantage were inconsistent, with DD individuals performing a range of visuospatial tasks either as well as or worse than individuals without DD (Gilger et al., 2016). The exception was in the realm of holistic processing, in which individuals with DD consistently demonstrated enhanced abilities (Gilger et al., 2016).

This advantage was first demonstrated in studies using impossible figures, such as Escher’s famous Waterfall. These figures are locally congruent while globally impossible; to detect their impossibility, they must be scanned globally rather than locally (von Károlyi, 2001). Von Károlyi and colleagues found that participants with DD were able to detect impossible figures significantly faster than non-DD participants without a loss of accuracy (von Károlyi, 2001; von Károlyi et al., 2003). They proposed that these results suggest an enhanced ability in rapid and accurate holistic inspection whereby visual spatial information is processed globally rather than locally.

Similarly, individuals with DD have been shown to be faster at 3D mental rotation and manipulation than those without DD (Attree et al., 2009; Wang and Yang, 2011). These results suggest that individuals with DD have access to a unique way of processing visual information (Gilger et al., 2016), a proposal that is consistent with fMRI studies showing that individuals with DD use different functional networks during such tasks (Diehl et al., 2014). Gilger speculated that such a unique mode of information processing might also yield advantages in other tasks that require unique perspective-taking or an ability to see patterns in a distracting context of complex forms.

The notion that DD involves a visual component is long-standing. Research looking at more fundamental aspects of visual processing further supports the view that individuals with DD process information more globally as a trade-off for decreased local processing. Several studies have found that individuals with DD have deficits in focal attention (Facoetti et al., 2008; Ruffino et al., 2010) but better resolution for features in the periphery of the visual field (Geiger and Lettvin, 1987; Perry et al., 1989; Lorusso et al., 2004). This includes enhanced perception of low-spatial-frequency components, that is, features such as global shape, as opposed to high-spatial-frequency features such as sharp edges and fine details (Schneps et al., 2012). In contrast, it has been noted that non-DD individuals are more adept at identifying details located in the center of the visual field (Geiger and Lettvin, 1987; Perry et al., 1989; Lorusso et al., 2004).

As an alternative to the magnocellular deficit theory (Stein and Walsh, 1997; Stein, 2001, 2019), Schneps et al. (2012) posited the theory that there is instead a magnocellular shift toward the periphery in people with DD, according to which magnocellular density is reduced at the fovea and enhanced at the periphery. Schneps et al. (2007) proposed that people differ in the extent to which they can make use of information in the central versus peripheral fields, with these differences in turn affecting their tendencies for focused search versus broad comparisons. Taken together, these studies indicate that individuals with DD have lesser abilities in local visual search (exploitation) and enhanced abilities in global (explorative) visual search.

Auditory Search

Compared with visual search, less attention has been paid to DD-associated auditory differences from the perspective of search, but a study by Geiger et al. (2008) provided some insights. They investigated whether children with and without DD differ in their abilities on an auditory task. The task involved perceiving a set of stimulus words from a central location, first without interference, and then under two different masking conditions (white noise and a “cocktail party” speech mask) creating interference from the periphery.

For both groups, recognition performance was comparable in the central non-interference condition. However, in the cocktail party condition, the group with dyslexia performed significantly worse (Geiger et al., 2008, 3A). Their inferior performance seems to be associated with higher recognition intrusions from the speech masker (Geiger et al., 2008, 3B), indicating an inability to disregard the peripheral speech. This pattern mirrored findings for a companion task in the visual domain, leading Geiger et al. (2008) to suggest that individuals with DD have a wider spatial attention than those without DD in both auditory and visual modalities.

Internal Cognitive Search

Humans also engage in internal cognitive search for information stored in memory, retrieving or internally manipulating such information to search for solutions. This section discusses different areas of memory and memory paradigms and how they relate to cognitive search. Evidence reviewed from a range of studies lends further support to the hypothesis that individuals with DD demonstrate a bias toward explorative internal search.

Procedural Memory

Procedural memory is a long-term memory system involved in implicit learning and use of knowledge; that is, memory that is not available to conscious awareness (Squire, 2004). Procedural memory supports learning and the execution of motor and cognitive skills, particularly those involved in sequences, and it engages a wide network of specific frontal, basal-ganglia, parietal, and cerebellar structures (Ullman, 2004). Learning to read, write, or play the piano are all examples of skills that are dependent upon procedural memory; once learned, the skills can be processed automatically and rapidly (Lum et al., 2013). Individuals with DD have been shown to be less efficient at procedural learning than non-DD individuals (Lum et al., 2013). It has been proposed that many of the difficulties observed in DD individuals may be explained by a failure to automatize skills because of an impaired procedural memory system and the underlying deficits thought to exist in the cortico-cerebellar circuit (Nicolson and Fawcett, 1990, 2007; Nicolson et al., 2001).

Automaticity allows tasks to be executed more quickly and efficiently. However, from the perspective of cognitive search, once a skill becomes automatic, one is essentially exploiting the same information again and again. Conversely, if an individual has difficulty acquiring automaticity, they retain declarative (conscious) awareness of the process. Therefore, they can still explore new, potentially better strategies, and integrate knowledge with other declarative information as it becomes available (Nicolson, 2014). This way of processing information may be slower and more effortful, but the trade-off is that it facilitates explorative search.

Fuzzy-Trace Theory

The exploration–exploitation trade-off in cognitive search also aligns with the trade-off present in the fuzzy-trace theory (FTT) of memory encoding and retrieval. FTT posits that information is represented in two parallel, independent memory traces called verbatim and gist (Reyna, 2005). Whereas verbatim traces encode literal information that supports precise analysis, such as the order of letters in a word or the digits in a number, gist traces are fuzzy but meaning-based representations such as context or category. While verbatim processing does not consist of meaningful interpretation, gist is characterized as insightful intuition (Brust-Renck et al., 2021).

This distinction between verbatim and gist trace memories resembles the contrast between local and global cognitive search. Local search is thought to involve the identification of between-item similarity, whereas in global search items are activated when they are related by context or category (Todd et al., 2012). People with DD have been shown to use synonyms more often when they fail to recall the exact form of a sentence compared with those without DD (Miles et al., 2006). This result attests to intact semantic representations in DD, and Obidziński and Nieznański (2017) have suggested therefore that individuals with DD may have enhanced gist memory. They used multinomial models to measure verbatim and gist memory processes and found that individuals with DD have poorer verbatim trace memory than participants without DD. However, they also reported higher probability of gist trace retrieval when semantically similar stimuli were presented to individuals with DD compared with controls. These results are relevant in the context of global search, as explained above, where items are activated in relation to the overall category. Thus, deficits in the cognitive process that facilitates differentiation between orthographically similar items may be accompanied by an enhanced ability to recognize semantic similarity.

Divergent Thinking

Several studies have shown that individuals with DD have enhanced abilities in various aspects of divergent thinking (Cockcroft and Hartgill, 2004; Akhavan Tafti et al., 2009; Bigozzi et al., 2016; Kapoula et al., 2016; Lam and Tong, 2021). Divergent thinking includes the ability to generate many solutions or ideas to solve a problem (fluency), flexibility in switching between categories, and the ability to elaborate and develop an idea. It also includes originality, i.e., the capacity to produce novel and unusual ideas (Furley and Memmert, 2015), which is a central feature of creativity (Runco and Acar, 2012). In contrast, convergent thinking “typically leads to conventional and “correct” ideas and solutions rather than original options” (Runco and Acar, 2012, 66). Regarding search, the cognitive control of explorative behavior is likely to require a divergent decision-making style, in contrast to exploitation which relies on a more convergent style (Hommel, 2012). The relationship between external search and divergent thinking was investigated by Martín-Brufau and Berná (2021), who found that high explorative external search ability corresponded to greater divergent-thinking ability; a relationship which they argued reflects shared mechanisms.

Several studies have found that individuals with DD significantly out-perform their peers on various aspects of divergent thinking (e.g., Cockcroft and Hartgill, 2004; Akhavan Tafti et al., 2009; Bigozzi et al., 2016; Kapoula et al., 2016). It should be noted that such studies often focus on non-verbal tests of creativity to avoid literacy confounds (e.g., Cockcroft and Hartgill, 2004; Bigozzi et al., 2016). Indeed, when verbal, figural and non-verbal tests of creativity were used, Lam and Tong (2021) found that children with DD performed worse on verbal creativity, equally on figural creativity but they out-performed their peers on non-verbal creativity. A meta-analysis similarly found that groups with dyslexia showed a significant performance disadvantage in verbal versus figural creativity (Erbeli et al., 2021a).

Bigozzi et al. (2016) and Akhavan Tafti et al. (2009) found that in fluency and flexibility subtests, the performance of participants with DD was equivalent to their peers, whereas in other studies performance was significantly better (Cockcroft and Hartgill, 2004; Kapoula et al., 2016; Lam and Tong, 2021 (in non-verbal tasks)). Most studies found that individuals with DD significantly outperformed those without DD in tests of originality (Cockcroft and Hartgill, 2004; Akhavan Tafti et al., 2009; Bigozzi et al., 2016; Kapoula et al., 2016; Lam and Tong, 2021 (in non-verbal tasks)), although this result may not always be consistent (Majeed et al., 2021). Bigozzi et al. (2016), who differentiated between fluency and originality to avoid possible confounding factors, still found greater originality among those with DD. Such findings align with the results of another study which showed that students with DD performed significantly better on tasks that involved connecting unusual combinations of ideas supporting new possibilities and original solutions (Cancer et al., 2016). Two recent meta-analyses highlight that a consistent creative advantage is not always found in children and adolescents with dyslexia (Erbeli et al., 2021a; Majeed et al., 2021). However, Erbeli et al. (2021a) found that compared with adolescents, adults with dyslexia did show a creative advantage over non-dyslexic adults. Initial evidence also suggests that enhanced creativity in individuals with dyslexia may be more pronounced in females than males (Erbeli et al., 2021a). Majeed et al. (2021) also found that in the adult samples, individuals with dyslexia significantly out-performed those without dyslexia on creativity scores.

Episodic Memory

Differences in declarative memory have also been proposed to exist in individuals with DD. Declarative memory supports the encoding, storage, consolidation, and conscious recollection of factual knowledge (semantic memory) and personally experienced events (episodic memory) (Squire, 2004; Lum et al., 2013).

From an evolutionary perspective, the utility of memory is to guide and influence future actions. Semantic memory is concerned with knowledge that is not tied to its context of acquisition, such as facts (Tulving, 2002; Moscovitch et al., 2016) and which, we suggest, might be viewed as supporting more local search. By contrast, episodic memory encodes the context of past experience, including information specific to the time and space of acquisition (Tulving, 2002). A key adaptive function of episodic memory is to also allow individuals to flexibly retrieve and recombine these building blocks of previous experiences to envisage future events (Schacter and Addis, 2007; Schacter et al., 2017). Hence, episodic memory supports more explorative search through imagined simulations and future outcomes (Hills et al., 2015), referred to as episodic future thinking (Atance and O’Neill, 2001).

Episodic future thinking provides an internal search space, a simulation of future possibilities, through which one can search to explore and evaluate possibilities. It allows one to predict the likelihood of a future outcome even for possibilities that have not been experienced previously (Buckner and Carroll, 2007; van der Meer et al., 2012; Schacter et al., 2017). As such, it saves time and energy, avoiding the need to physically explore different possibilities and enabling an individual to anticipate and avoid problems. However, it also delays action, which could carry risks in itself (Hills et al., 2015). Time spent searching internally is also therefore subject to the trade-off between exploration and exploitation (Hills et al., 2015).

Eide and Eide (2011) proposed that individuals with DD have enhanced episodic memory and that they rely preferentially on episodic rather than semantic strategies for long-term memory. This proposal aligned with later research which found that, in the general population, individuals differed in how they remembered the past – some had richer episodic memory while others more readily retrieved the semantic features of events (Sheldon et al., 2017).

Studies of declarative memory in individuals with DD have yielded inconsistent results, possibly reflecting the use of verbal tests that tax cognitive abilities known to be weaker in people with dyslexia (Hedenius et al., 2013). To avoid such problems, Hedenius et al. (2013) tested object recognition after incidental encoding since incidental learning rather than intentional encoding, and recognition rather than free recall, are less reliant on working memory and executive function. Finding enhanced recognition scores in individuals with DD, they speculated that the advantage in declarative memory might be mediated by a compensatory seesaw interaction derived from a deficit in procedural memory. Attree et al. (2009) also employed an incidental-learning paradigm and studied spatial memory in DD using a realistic computer-generated virtual environment. Under these conditions, the group with DD also scored higher compared with a non-dyslexic control group.

The amount of detail revealed in episodic simulations (i.e., imagined events) has been shown to be strongly correlated with the level of detail retrieved from episodic memories (Addis et al., 2016). Moreover, studies using episodic specificity induction (ESI), whereby subjects are briefly trained to recollect more details from episodic memories, found an increase in the detail of subsequent episodic simulations (Madore et al., 2014). Conversely, studies indicate that limitations in an individual’s ability to recall details of past experiences correspond to limitations in the ability to generate detailed simulations of future possibilities (see Szpunar and Radvansky, 2016, 211).

Studies of amnesiac patients for example have found that deficits in episodic memory positively correlate with an impoverished ability to construct new imagined experiences (Hassabis and Maguire, 2007; Race et al., 2011). It is therefore predictable that, if individuals with DD have enhanced episodic memory, they should have correspondingly enhanced episodic future thinking abilities. Having the ability to create richer internal simulations may facilitate explorative search for successful solutions.

In terms of convergent versus divergent thinking abilities (described in the preceding section), ability in future simulation is expected to be related to the latter but not to the former (Addis et al., 2016). Addis et al. (2016) showed that greater divergent-thinking abilities are associated with greater capacity to imagine more detailed future episodes. In addition to increasing simulation detail, ESI has been shown to enhance divergent thinking (Madore et al., 2015).

This link between episodic memory, episodic simulation, and divergent thinking is further supported by a study in which amnesic patients with diminished episodic memory for past experiences had difficulty imagining the future as well as decreased abilities in divergent thinking (Duff et al., 2013). This finding is consistent with fMRI evidence (Benedek et al., 2014) showing that “divergent thinking recruits some of the same default network regions typically linked with future simulation” (Addis et al., 2016, 95). In addition to evidence for enhanced episodic memory, greater divergent thinking ability in adults with DD, therefore provides further supporting evidence for Eide and Eide’s (2011) proposal that people with DD have enhanced episodic memory, and in turn enhanced ability in explorative search through episodic future thinking.

Working Memory

Working memory (WM) refers to the ability to process information and store the intermediate products of that processing for a brief period before using it (Ghani and Gathercole, 2013). It is well established that individuals with DD typically have a low WM capacity with regard to the central executive and phonological loop (Ghani and Gathercole, 2013) as well as the visuospatial sketch pad (Lipowska et al., 2011).

The role of cognitive search strategies in memory has been investigated in studies of the relation between phonological WM capacity and how information is retrieved from long-term memory (Rosen and Engle, 1997). Local search is thought to involve looking for similarity between items, whereas in global search items are activated in relation to the context and overall category (Todd et al., 2012). Individuals with a high WM capacity have been shown to transition less frequently between local and global cues compared with individuals with a low WM capacity (Rosen and Engle, 1997; Hills and Pachur, 2012). This indicates that individuals with high WM capacities are better at exploiting local information when searching in long-term memory while individuals with a lower WM capacity, (such as individuals with DD), tend to move more readily from local patches of information to global exploration (Todd et al., 2012). These findings agree with observations of individuals with DD found to be particularly talented at seeing “relationships of likeness and “togetherness”; connections between perspectives and fields of knowledge; and big-picture or global connections that create heightened abilities in detecting gist, context, and relevance” (Eide and Eide, 2011).

Several studies have observed a negative correlation between WM capacity and divergent-thinking ability. For example, training WM using a mental calculation paradigm has been found to improve WM capacity but reduce performance in divergent-thinking tasks (Takeuchi et al., 2011). While none of the studies have looked at DD, some have considered ADHD, a diagnosis frequently given alongside dyslexia (Germanò et al., 2010). In studies of cognitive search, ADHD is considered a pathology related to goal-directed search, characterized by too much exploration (Hills, 2006; Todd et al., 2012). Individuals with ADHD have been shown to have a low WM capacity (Kofler et al., 2010; Rhodes et al., 2012; Fugate et al., 2013) and better performance in aspects of creative thought such as conceptual expansion and the ability to overcome knowledge or example constraints (Shaw, 1992; Abraham et al., 2006; White and Shah, 2016). They also score more highly on originality in divergent-thinking tasks (White and Shah, 2006, 2011).

Fugate et al. (2013) studied divergent-thinking ability in students with high fluid intelligence who were diagnosed with ADHD. They had speculated that low WM could reduce the ability to form novel combinations of information as it would reduce the ability to hold information in mind. Instead, they found that the lower the WM capacity, the higher the levels of divergent thinking (Fugate et al., 2013). Not all studies have found a negative correlation between WM and divergent-thinking ability, so other factors such as intelligence or processing speed may also play a role (Takeuchi et al., 2020).

In addition to the ability for divergent thinking, lower WM has also been associated with enhanced insight-based reasoning (DeCaro et al., 2016). Insight refers to the sudden reinterpretation of a stimulus, situation, or event to produce a non-obvious interpretation, seemingly disconnected from the stream of conscious thought, that finds a solution to a problem or the comprehension of a joke or metaphor (Kounios and Beeman, 2014). Insight-based reasoning contrasts with deliberate, analytic, incremental problem-solving, which is also associated with different patterns of brain activity (Kounios and Beeman, 2014). Given these characteristics, insight-based reasoning may be considered a more explorative process and analytical reasoning a more exploitative one.

Although there have been no formal studies of reasoning style in DD, insight-based reasoning has been proposed, based on clinical observations, as an area of enhanced ability (Eide and Eide, 2011). Support for this proposal came from later experimental work revealing that high WM capacity has a negative impact on the ability to perform the problem restructuring and solving processes necessary for insight (DeCaro et al., 2016). This is thought to be because insight problem solving relies on “associative processes that operate outside of close attentional control” (DeCaro et al., 2016).

Lower WM capacity is typically viewed as a shortcoming in people with DD compared with people without DD. However, available evidence on WM also suggests that those with DD might experience compensatory advantages in their capacities for divergent thinking and insight-based reasoning, that is, in cognitive domains manifestly related to explorative search.

Similarly, the pattern emerging from evidence related to internal cognitive search is that DD-associated cognition shows both a diminished ability to exploit and, generally, a correspondingly enhanced ability to explore.

Neurophysiological Differences

Minicolumn Circuitry

In addition to cognitive differences, there is also evidence for neurophysiological differences in individuals with DD that relate to the exploration-exploitation trade-off. One such difference regards minicolumn circuitry. Minicolumns are an elementary unit in the neocortex of all mammalian brains (Buxhoeveden and Casanova, 2002). They are essential in cortical information processing, with differences in connectivity within and between modular cortical circuits relating to differences in how information is processed (Casanova and Tillquist, 2008; Williams and Casanova, 2010). In a study by Williams and Casanova (2010), the minicolumn circuitry for individuals with DD was found to have stronger global connectivity at the cost of local connectivity relative to controls and individuals on the autism spectrum. Specifically, greater mini-columnar width and spacing and fewer minicolumns result in fewer local connections. The corresponding enlargement of the gyral window makes a larger number of commissural fibers possible, increasing in turn the volume of tracts such as the corpus callosum (Williams and Casanova, 2010). Thus, decreased local connectivity in the cortex benefits long-range connectivity.

Williams and Casanova found the inverse to be true of individuals on the autism spectrum, who were found to have stronger local connectivity. In this case, relative to controls and individuals with DD, individuals with autism have a greater number of minicolumns with reduced width and reduced spacing, enabling hyperconnectivity in short-range connections within these modules. Furthermore, an associated decrease in the size of the gyral window places constraints on the developing commissural white matter and contributes to a decrease in long-range connectivity between modular units.

Williams and Casanova proposed that these differences in minicolumn circuitry give rise to a spectrum of cognitive styles that range from those with a holistically oriented, gestalt processing bias (DD) to those with a detail-oriented or local processing bias (autism). In other words, owing to physical limitations in the brain, individuals with DD have a global processing bias resulting in enhanced abilities for exploring information, and vice-versa for individuals with autism. These results align with the pattern that individuals with DD have a global search bias.