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5 The Anatomy of Creativity






Chapter Five
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The Anatomy of Creativity

To ask a Japanese to think in English terms amounts to asking an Impressionistic landscape painter to adopt the methods of a land surveyor.
—Arthur Koestler

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Overview of the Creative Process

It is time to sum up what has been noted about innovation in East Asia and move to more technical areas that will provide the tools needed to explain these observations. In the previous chapters I documented the present dependency of Japan, China, and South Korea on Western ideas and showed that this dependency is most acute in basic science, where theory and abstraction play a paramount role. We glanced at some distinctions between concrete and abstract thinking, saw how these differences are exhibited in East Asian and Western innovation patterns, and buttressed these observations with data from social psychology and intellectual history. I also gave examples of how language and orthography interact with thought, described some parallels between linguistic and social development as a prelude to the case I shall make for linking creativity with orthographic types, and hinted about the dynamics of creativity.
The argument that we shall pursue hereafter has two parts. I will show that the Chinese character-based writing used in East Asia has inhibited creativity on several “macro” levels that derive from the writing system’s complexity and its poorly defined links with the sounds of spoken language. This task will occupy the last few chapters of the book. Our immediate goal will be to identify some basic psycholinguistic and neurolinguistic traits associated with writing, both alphabetic and character-based, that relate on a “micro” level to creative thinking. To achieve this goal, I must be more specific about the creative process, as both a personal and social event. I must also describe its cognitive aspects and, where possible, its neurological correlates to demonstrate how writing systems influence a people’s disposition to create.
Creativity studies, like other areas of psychology, have both popular and scientific dimensions. Originally a minor field of psychological research, creativity burst into the public eye in the mid-1960s with the publication of Arthur Koestler’s The Act of Creation (1964), the first rigorous attempt to explain creativity in a format accessible to laypersons. The release of this 750-page treatise was timed perfectly, capturing the anti-authoritarianism of the era and helping to shape it by the nature of the subject and the spirit in which it was delivered. Koestler, a lifelong critic of the behaviorist paradigm that dominated what would later be called cognitive science, set out to humiliate this school of thought and the mechanistic worldview it supported by focusing on human creativity, the one trait behaviorism was least equipped to handle.
Koestler’s blend of science and romanticism made the book pivotal in another sense by serving both as a springboard for the pop psychology that found “creativity” in trivial endeavors and for serious inquiry into the matter by empirical scientists seeking verifiable antecedents for such concepts as “bisociation” and “matrices of thought.” The former trend culminated in a number of alleged practical guides for increasing personal creativity through meditation, out-of-the-box thinking, and so on. This approach mostly ignores the findings of creativity science on the roles of preparation and verification. Unfortunately, it captured the public’s fancy like much of the left- and right-brain theorizing of the 1970s did, preempting widespread appreciation for genuine scientific research into the nature of creativity.
As we shall see, there is no shortcut to creativity. Nor is there much anyone can do to enhance creative ability beyond investing the time and effort to master a knowledge domain, caring enough to think about it, and, perhaps, situating oneself in an environment where new ideas are rewarded. The notion that creativity could be linked with self-actualization and psychological fulfillment for the many is belied by the observation that society’s most creative individuals are often oddballs plagued by frustration or obsessive types immersed wholly in their discipline—in modern terms, selfabsorbed personalities with limited social skills. Successful societies tolerate these individuals (and the structures that support them) at great expense to short-term efficiency and at some risk to their own survival. To romanticize this process is to misunderstand it.
On the positive side, careful research has produced many solid (if quieter) studies on creativity over the past three decades. Our focus throughout this chapter will be on the findings of this latter group of specialists, who are interested in describing creativity as it happens, not in prescribing steps for its magical attainment. Significant progress has been made in this area by scholars from several disciplines, including psychology, neuroscience, information science, and sociology. Despite their different approaches— and without minimizing the disagreement on certain issues—there does seem to be a consensus on what constitutes the main parameters of creativity. Enough is understood now about creativity to allow us to examine its links with other psychological and sociological phenomena, including language and writing.
Contrary to what one would expect, specialists have found that human creativity depends on manipulating knowledge that already exists. The same maxim that one cannot create something from nothing in the physical universe also applies in the notional realm. Although creative insights seem to occur “out of the blue,” most of what is needed to produce the insight is already there, in the prepared mind, in one form or another. The key to creativity lies in juggling these existing forms to produce new (and useful) configurations.
That creativity proceeds from known patterns has long been appreciated. Philosopher Brand Blanshard sixty years ago defined invention as the problem of “how an end, already partially realized in the mind, gets the material to extend or complete itself.” Invention begins with “a collision between a system or order already present in the mind and some fragment that ought to be included in this and yet remains outside it” (1939:129-30). Churchland’s definition of scientific creativity as “the capacity to see or interpret a problematic phenomenon as an unexpected or unusual instance of a prototypical pattern already in one’s conceptual repertoire” (1995:278) likewise recognizes the role of existing knowledge in the creative process.1 I emphasize the importance of prior knowledge as an antidote to the popular notion of creativity as cost-free and spontaneous. While creativity often involves breaking through mental “barriers” (reorganizing knowledge networks), there is no creativity without a network of structures to build on.
These structures, technically speaking, are mental models of natural phenomena, realized as recurrent patterns of neuronal activation. They range from general patterns of wide applicability (highly abstract configurations distilled from multiple inputs) to specific rules for particular circumstances. To deal effectively with one’s habitat, people learn to perceive environmental features and events as instances of stereotypes, that is, generalized representations of phenomena probably based on relational attributes. Synaptic firing patterns invoked in the brain in response to recurring external stimuli becoming fixed (the relative weights of their neuronal configurations are strengthened), enabling individuals to recognize and respond appropriately to most situations they encounter.
The challenge—the opportunity for creativity—comes when perception of an event fails to elicit a useful match from one’s store of mental representations. As Holland et al. put it, “To represent environments fraught with novelty, mental models cannot rely exclusively on precompiled structures. Flexibility can come only through the use of combinations of existing knowledge structures” (1986:16). Deductive logic—applying fixed rules within an existing framework—cannot interpret a novel situation whose features lie outside that framework. New structures must be generated through induction, either by refining existing patterns or creating new ones.
One type of inductive change involves evaluating “the system’s rules as instruments for goal attainment, improving them where possible and favoring the better ones in application” (68). A goal-directed search is made of existing mental models that correspond approximately to the surface features of a problem (more accurately, to one’s analysis of those features). A solution is achieved when a match or near match is located. This lesser form of creativity corresponds to Brick’s (1997:8) “intrarepresentational” rule changes, which “do not depend on similarity judgments. They constitute a way to reorganize a given context.” In terms of the material presented in previous chapters, this process equates to the incremental improvements in technology that constitute the bulk of real-world innovation. While “creative” in a broad sense, they do not constitute “breakthroughs” as the term is usually understood.
Holland et al. concur that these “procedures for refining existing rules, though important, are inherently limited to rules already in place. If these rules are inadequate in important ways ... no amount of refinement will make up the deficit” (1986:78). There is, however, a second, more thoroughgoing type of inductive change used to “generate plausibly useful new rules that are capable of extracting and exploiting regularities in experience” (68). In this case, abstract patterns that have already been defined for other domains, or exist at a deeper, more general level, act as models for remapping or completing the elements of a problem by analogy.
This second form of induction is employed only after deliberate attempts have been made to understand problems in more or less familiar terms.2 It differs from the template matching that characterizes the first type of induction by requiring a fusion (or “bisociation”) of two separate configurations—an existing “source” pattern and one’s mental representation of the problem, called a “target” pattern. Combining the two patterns yields insight into problems that resisted solution in their original form. Brick calls this more radical process “interrepresentational,” which unlike the first variety “involves more than one representation. . . . What is transferred to the target is either structural traits or contents of the source, and the change pertains to the target” (1997:8). The process works not logically but analogically. It is responsible for the sort of breakthroughs that characterize scientific progress as it is stereotyped in the West.

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Stages of Creativity

Lay notions of a distinction between innovative and creative thinking correlate with these two hypothesized mental processes. Using an existing representation to understand a situation or solve a problem is not truly “creative” if the representation is normally invoked in that domain. Creativity in the deeper sense involves reaching outside the domain to identify a data set as an instance of a scheme that is usually applied to different kinds of data. A subset of this process occurs when a partial source analog is recovered that is similar enough to the target to attract the problem solver’s attention. The partial scheme is amalgamated with the target representation to produce a new structure more basic than either the target or the source.
The two inductive processes used in innovation versus creativity differ as much with respect to how the target data are handled as they do in the type of mapping strategies employed. In the lesser variety, target elements—perceived units and their relationships—are treated more or less as a given. By given I mean they are recognized as familiar elements in one’s repertoire of domain-specific components. These elements can be shifted about or replaced within the limits of what the overall conception requires. But a major remapping of the problem set (target) is precluded by the “chunkiness” of these elements, that is, by their status as indivisible units, and by what this chunkiness implies for their relationships with one another. This is a critical point that requires elaboration.
The matrices available to structure the elements of a problem depend, ultimately, on how one defines its elements. If the integrity of what are regarded as indivisible parts remains absolute, the potential for reordering is correspondingly limited, meaning that the matrices available for a problem’s representation are likely to be those already within the domain. Conversely, when the chunkiness of a representation is reduced by an analysis that penetrates its predefined units, the material becomes susceptible to representation by structures outside the domain. Analogies with hidden structures thus are facilitated by the randomness of the initial “workspace” (Hofstadter and FARG 1995:228).
Gick and Lockhart (1995) argue, in the same vein, that formulating a problem is as important as finding a source to complete it. In their words:
Two important processes exist. The first is the generation of a representation of the problem, or the problem solver’s understanding of problem elements and operations that can be used to solve the problem. The second is a search for a solution within the constraints of the representation. If the implementation of a solution succeeds, then the problem solving stops; if it fails, then the problem solver might go back and try to formulate a new representation for the problem that may be more effective, might keep searching within the same representation for a different solution to implement, or might get stuck and give up. (199)
Success in solving novel problems depends on the availability of source analogs, and also on one’s ability to couch a representation in terms general enough to facilitate deep matches but specific enough to preserve the problem’s essence. The importance of problem representation is captured anecdotally in phrases like “You have to ask the right questions to get the right answer.” Regressing to deeper (more abstract) sources on which to base an analogy—the other half of the road to insight—is expressed by the phrase “reculer pour mieux sauter” or “move one step back to jump two steps ahead.”
The creative process encompasses more than the two core aspects that I just described. Most specialists distinguish four independent phases of creativity, including preparation, incubation, inspiration, and verification (Abra 1988:16; see also Jaynes 1976:44; Poincare 1982:389; Martindale 1995:251). Csikszentmihalyi and Sawyer’s (1995:333) four-stage characterization substitutes “insight” for “inspiration” and “evaluation” for “verification” but is otherwise identical. As they describe it:
Although there are subtle variations in the definitions of these stages of creative insight among different researchers, we propose the following unifying framework: The first stage, preparation, which is stimulated by external pressures or by intrinsic motivation, involves focused conscious work, such as studying or analyzing data. These rational thought processes provide the raw material on which the subconscious can begin working.
A period of incubation ensues, followed by insight, and a lengthy period of evaluation. The authors note “Insight is part of an extended mental process. It is based on a previous period of conscious preparation, requires a period of incubation during which information is processed in parallel at a subconscious level, and is followed by a period of conscious evaluation and elaboration.” I shall discuss these stages in more detail in the next few sections.
Some researchers add a fifth stage—communication of results (Abra 1988:16)—in deference to the role of peer recognition. As we shall see later, there are intimate links between what appear to be individual creative acts and the culture within which these acts occur. Having one’s creation examined by peers not only satisfies the usefulness criterion that keeps the enterprise grounded in reality. The attitude of society toward the creativity of its members determines whether someone is disposed to create in the first place. Adding this fifth phase to the creative process closes the cycle of events by offering an explanation for creativity’s nebulous beginning (the disposition of individual thinkers to create) in terms of the process’s end result (degree of social acceptance).

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Breaking Down the Whole

Creativity is difficult because it conflicts with a human requirement to perceive phenomena in terms of existing categories. As Brick (1997:12-13) states, “The ability to categorize is of fundamental value for the simplest train of thought. If a subject cannot identify and reidentify the object he reasons about, then he cannot entertain any continuous, coherent thoughts.” Turner (1988:3) noted similarly that people categorize to avoid being swamped by the world’s complexity. These categories “cut our worlds into clusters [and] the fitness of our cognition will depend upon the fitness of these conceptual cuts.” Mental models in the form of concepts and relationships between concepts are built to interpret raw sensory data, so that the phenomena they are associated with become identifiable and predictable. Such categories persist to the extent that they model events “accurately,” in a way consistent with the needs of survival.
Creativity on the one hand relies on these models. For analogies to work, a large repertoire of source patterns or “prototypes” must be available in one’s mind to guide the reconfiguration of a problem’s data. We learn these prototypes, according to Churchland (1995:279), “solely within the domain of observable things ... in response to one’s ongoing sensory experience.” Concrete events are modeled on the basis of what we regard from past experience as stable units (collections of properties that can be manipulated as wholes) and plausible ways of linking these units. The modeling is a two-way street: sensory experience is ordered, and prior assumptions about order are validated or adjusted (alternative neural mappings are selected and strengthened).
Along with this “horizontal” formation of category structures, the mind also seeks to integrate commonalties from different category domains into what Koestler (1964:621) referred to as a “vertical abstractive hierarchy.” Just as sensory data “filtered” or categorized by perceptual mechanisms are used to shape categorical associations, so do these activated patterns serve as the data on which a more abstract set of assumptions is based. This “vertical progress in abstraction” (recognizing a particular pattern as an instance of a more general one) is the key to creative discovery.3 Although mastery of a categorical domain requires intelligence (recall and logic), it does not equate to competence in drawing inferences between levels, where a different set of skills (analysis and pattern recognition) are needed.
Turner (1988:4) also distinguishes categorical (Koestler’s horizontal) and analogical (vertical) connections, but views the distinction in more fluid terms. As he puts it: “Deeply entrenched analogical conventions we no longer find inventive. We regard them as straightforward category connections.”4 Like Koestler, Turner views category structures as “dynamic and subject to transformation under the pressure of analogy.” If categories structure the world as we know it, analogies “can inventively induce us to build new connections, and recast or tune others. A powerful analogy can re-structure, disturb, influence, and change our category structures, and successful analogical connections can ultimately become part of our category structures” (5).
Unfortunately for creativity, the same category structures on which analogy operates also serve as a brake on innovation. In Turner’s words, “category structures highlight certain connections between concepts, and mask possible alternative connections” (3). Ward et al. (1995:128) note similarly that “bringing to mind specific objects can inhibit creativity: the central properties of those objects set up roadblocks on the routes to innovation.” For the analogical mechanism to work, the target structure must be analyzed, that is, stripped of its concrete trappings, and reduced to a form to which abstract source patterns can relate.
There is unanimous agreement among creativity specialists, and cognitive scientists in general, on the need to disintegrate problems—dissolve the relationships between their units and what pass as “units” themselves—for analogical mapping to occur.5 We noted earlier Hofstadter et al.’s argument that analogy is facilitated by randomness in the problem space. This hypothesis, which accords with the commonsense view that smaller pieces can be reordered more easily than large chunks, was verified empirically by Hofstadter’s group through computer simulations. One aspect of these trials, which Hofstadter calls “an accurate description of the underpinnings of a typical paradigm shift in the human mind” (1995:257), involved “breaker codelets” that went into operation when snags were hit. Their “purpose is to arbitrarily break structures that they find in the work space, thus reducing the system’s attachment to a viewpoint already established as being problematic” (258). The analog of these codelets in human cognitive operations is the conscious exercise of analytical skills on a problem set.
Calvin, like Hofstadter, uses a competitive model to explain the evolution of “a more intelligent solution to a problem” (1996:104). In Calvin’s scheme, “The brain activity patterns associated with thinking a thought” get copied, occasionally with changes, and the variant patterns compete. The process is accelerated by
fragmentation and the isolation that follows: the Darwinian process operates more quickly on islands than on continents. For some fancy Darwinian processes requiring speed (and the timescale of thought and action certainly does), that might make fragmentation processes essential. (105-6)
The better one is able to isolate the core universal elements of a problem through fine-grained thinking, the better one’s chances are of finding these elements in existing “source” patterns. To Calvin, who views intelligence as the ability to discover “some new underlying order,” creativity is predicated on breaking a “pattern into meaningful parts and recombining” them (14—15).
Findlay and Lumsden (1988), on whose work we shall draw extensively here and in subsequent chapters, describe the cognitive processes leading to creativity as follows:
A a-node is an informational unit at higher levels of semantic organization, obtained from the distillation of information from subordinate nodes at lower levels of organization. . . . The creative process involves the production of a novel schema (a discovery) indexed by a new a-node. (22)
Findlay and Lumsden’s nodes essentially are concepts representing “pertinent information from personal experiences.” A schema is defined as “a network of nodes and links.” Concrete-bound nodes serve as the basis for high-level patterns (a-nodes). Creativity occurs when two or more of these a-nodes, constituting the target data and source pattern (s), have been activated and are represented in working memory. The authors add:
With regard to discovery, it is more likely that the production of new a-nodes is based on the establishment of connections among these primitive elements rather than among the a-nodes themselves, simply because the overwhelming advantage of vertical chunking as a means of cognitive economy implies that when a-nodes are activated, they have a more or less unitary representation in working memory. At least initially, conscious attention may be required to partition this representation into discrete elements of lower cognitive order, thereby creating the opportunity for new linkages. (22, my emphasis)
In contrast to the automatic and, for all intents, subconscious search for appropriate source patterns to map problem data, the up-front analysis needed to prepare data for reorganization (not to mention the subsequent labor to verify any new construct that emerges) entails a deliberate, conscious effort to isolate units, or the features of what are believed to be “units,” from their original context. There is nothing easy or natural about this analytical process. As Seifert et al. put it,
Obviously, if ultimate insight is to occur in resolving a difficult problematic situation, the problem first has to be taken seriously and confronted head-on. The would-be problem solver needs sufficient motivation to spend significant amounts
of time on an initial careful analysis of the problem situation, pushing ahead as far as possible with it, forming a coherent memory representation of the problem, and using all the available information in a solution attempt. (1995:110)
The need for preparatory analysis is especially great when the source and target domains share few surface characteristics, as is often the case in breakthrough science. Similarities between distant domains become evident only when the elements of the target representation have been abstracted to a level that coincides with potential source patterns. According to Vosniadou and Ortony (1989a:8), “Empirical work in analogical problem solving show that both adults and children have great difficulty retrieving a remote analog that can satisfy the target problems goals. . . . The problem often lies in the fact that neither children nor adults represent the problems at a level abstract (context-free) enough.”
Ward’s (1995) description of the need for abstract analysis at the early stage is uncompromising. It deserves to be quoted at length: “There are intuitive, empirical, and theoretical reasons for believing that people will be more innovative, as judged by deviations from characteristic category attributes, if they begin the task of imagining a new entity by considering a highly abstract categorization of what properties the entity ought to possess rather than if they begin retrieving and modifying a specific entity” (170). Modifying specific entities is precisely what is involved in run-of-the-mill innovation. Moving beyond these incremental changes requires thinkers to cast lower level representations in an abstract light. Ward explains why:
The heightened accessibility of an initially retrieved or presented example (or its component attributes) makes alternative examples or attributes less accessible or retrievable. By moving to a more abstract representation, one may be able to lessen the dominance of any one instance and better equate the accessibility of other items. One may then be able to retrieve an alternative item, perhaps a less typical one, or synthesize a novel item from the abstract principles. (172)
Radical restructuring demands that the thinker think on an abstract level. Abstract thought, in turn, requires separating elements from their concrete context through analysis. Popular belief notwithstanding, creativity turns out to depend at least as much on disintegrative and analytical skills as it does on integrative or synthetic talents.6 Analysis is needed both at the beginning and, as we shall see, the ending phases of creativity. It underlies the process to that extent.

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Advancing Backward

How fragmented must representations be for creativity to happen? We need to talk again about language, both to remind ourselves of this study’s focus and because of the role language has and does not have in the creative process, particularly in its middle or “unconscious” phase.
There is reason to believe that human consciousness is founded on language or on the symbolic manipulations that make up the heart of language. Jaynes argued in The Origin of Consciousness in the Breakdown of the Bicameral Mind that subjective consciousness “is built up with a vocabulary on a lexical field whose terms are all metaphors or analogs of behavior in the physical world” (1976:55). Jaynes viewed the bulk of language as based on metaphor and conscious mind as “a metaphor-generated model of the world . . . the invention of an analog world on the basis of language.” The “self” is also an artifact of conscious thought, inseparable from the metaphors we create. As he put it, “consciousness is an operation rather than a thing, a repository, or a function. It operates by way of analogy, by way of constructing an analog space with an analog T that can observe that space, and move metaphorically in it” (65-66).
The link between language and self-awareness has also been articulated by Illich and Sanders (1989), and by a number of other scholars who draw parallels between the externalizing of ideas through writing and the concept of a detachable self. We will discuss this line of thought in the following chapter in the context of alphabetic writing. Meanwhile, note the similarity between Jaynes’s view of consciousness as language-based and Deacon’s thoroughly modern notion of human consciousness as symbol-driven. Deacon argues, “No matter what else various theorists might claim about the nature of consciousness, most begin by recognizing that to be conscious of something is to experience a representation of it” (1997:448). From this follows the likelihood that changes in the form of representation—from iconic through indexical to symbolic—entail changes in the type of consciousness represented, the last type being peculiar to humans—the only “symbolic species.” Although we share primitive consciousness with lower animals, the specific consciousness humans experience is a function of symbol use and is, accordingly, linguistic in nature (449)?
Our ability to create and use symbols is supported by what Deacon terms a “nested hierarchy, where certain conditions in the lower levels of consciousness are prerequisite to the emergence of consciousness at each higher level” (449). They include, most basically, the brain’s ability to model iconic relationships (signs that signify by virtue of sharing a property with what they represent) and, one step higher, indexical relationships (signs whose specific character is causally dependent on the objects to which they refer). Just as indices are relationships among icons, so are symbols (conventional signs that depend on an interpretant for their meaning) relationships among indices (78). Symbols are formed by recognizing relationships between the objects to which a group of indices refer. Once a symbol is formed, however, the direction of dependency reverses (in Deacon’s terms: the “mnemonic strategy” shifts), and the objects themselves become identified indirectly in terms of their relationships within the higher scheme (87).
There are some interesting features in this semiotic-cognitive hierarchy that bear directly on creativity. Recall Findlay and Lumsden’s ot-nodes, described as “informational units at higher levels of semantic organization” obtained by distilling information from lower structural levels. Creativity, in their system, involves reconfiguring elements lower on the cognitive scale so that they are “indexed” by a new a-node (1988:22). It involves regressing from a higher cognitive state, where symbol manipulations prevail, to a relatively lower state, where information is represented ironically (by stimulus generalization) or indexically by what Deacon calls “spatial-temporal correlation or part-whole contiguity” (1997:79). Language and the symbols on which it is based have no role in this part of the creative process and actually impede it. This fact, well attested in the creativity literature, will be treated at length in Chapter 9.
Viewed within this cognitive assembly, Jaynes’s identification of language with metaphor and his distinction between thought and consciousness make perfect sense. If metaphor is the use of analogy on the symbolic level to extend—and in that sense create—language, what we regard as “genuine” creativity is the use of analogy on the indexical level to form new associations among the nonverbal tokens that refer to real world elements. Logic, which Jaynes describes as “the justification of conclusions we have reached by natural reasoning,” accounts for just a small part of our thinking (1976:41) and, unlike the preparation and validation stages of creativity, does not figure into the incubation and insight stages at all.8 As Jaynes put it, “Our minds work much faster than consciousness can keep up with. . . .
The picture of a scientist sitting down with his problems and using conscious induction and deduction is as mythical as a unicorn” (42-43).
Koestler’s verdict on the role of conscious, symbolic thought in creativity’s middle phase is identical: “not only verbal thinking but conscious thinking in general plays only a subordinate part in the brief, decisive phase of the creative act itself,” he stated. The “role of strictly rational and verbal processes in scientific discovery has been vastly overrated” (1981:13-14). Hesse concluded similarly that “standard forms of logic and linguistics” are irrelevant at this stage. She summarized the view of creativity scientists on this issue as follows:
It has long been obvious that the human problem solver does not generally think deductively or by exhaustive search of logical space. Propositional logic relies upon enumeration of premises, univocal symbolisation, and exclusively deductive connections, and these cannot be either a good simulation of human thought or an efficient use of computers. In real human thinking the meanings of concepts are constantly modified and extended by parallels, models, and metaphors, and the rational steps from premises to conclusion are generally non-demonstrative, being carried out by inductive, hypothetical, and analogical reasoning. (1988:318)
There is little to suggest that mental models are stored primarily as linguistic constructs. Indeed, much of linguistics is concerned with how deeper, preverbal thought is translated into a verbal format. Language, in its idealized written mode especially, is logical, serial, and symbolic. It is an affirmation of the conscious, focused self. What creativity needs in its insightful stage (as the metaphor suggests) is a categorically different mindset, one that is spatial and visual, not serial and verbal.9
Visual metaphors abound in scientific and popular accounts of creativity. We “dream up” a solution, use our “imagination,” “see” how a problem “comes together.” The primacy of visual over verbal thought in creativity’s decisive phase has long been recognized and is undisputed.10 Johnson, paraphrasing Kant, described “a level of imaginative activity at which we organize our representations into unified wholes.” It is not a concrete mental image as such, or “an abstract conceptual or propositional entity.” What appears is “an abstract structure of an image . . . the recurring structure or pattern of our imaginative process of forming an image.” These schemata “represent a level of cognitive activity where form and structure emerge in our understanding prior to propositionaljudgment” (1988:29, my emphasis).
This imagery finds its ultimate expression in dreams. Dreams are novel constructs built on prior experiences through free association. Although inadequate as a model of creativity (where the “free” association is guided), dreams mirror creativity’s incubation phase by being independent of what we view in conscious states as “the imperatives and continuity of the real world” (Mandler 1995:13). People sometimes do dream real solutions to vexing problems, but the experience is uncommon. When it does occur, it is only after a period of time has passed, which is also true of insights that emerge from wakeful (but preconscious) states. As Langley and Jones explain it,
There is no inherent reason why the retrieval cues must be external', they might also be internally generated during periods of free association, and this is exactly what dreams provide. But because the chains occurring in dreams are semirandom, they provide little more direction than chance external cues. Thus, dreambased illuminations may be delayed as long as those based on interactions with the environment. (1988:198)
The search for source analogues, while “unconscious” and languageindependent, is not completely random but depends crucially on feedback from the parts of the brain that are coding the target. The trick seems to be keeping the problem’s elements “in mind” while letting the rest of one’s thoughts stay loose enough for candidate sources to emerge. Blandshard (1939:164-65) called this connection between the one type of process and the other “the guidance of the immanent end of thought,” noting that “So far as the analogies are random and heterogeneous, thought is adrift on the tide of association.” Simonton (1995) and Martindale (1995) both explain the process in terms of location and level of neuronal activation. Here is Martindale’s account:
During the preparation stage of the creative process, attention must be focused. That is, a few nodes are highly activated and dominate consciousness. These nodes encode ideas thought to be relevant to the problem at hand. Of course, the creative solution lies in ideas thought to be irrelevant. During incubation, the nodes coding the problem remain primed or partially activated in the creative mind. In the uncreative person, the nodes coding the problem are deactivated. Rather than remaining in the back of the mind, the problem is forgotten. As the creator goes about his or her business, many nodes will be activated. If one of these happens to be related to the nodes coding the problem, the latter becomes fully activated and leaps into attention. (256)
Martindale calls this state in which many nodes are weakly activated “primary process thinking.” It corresponds to the preconscious, nonverbal thinking identified by other cognitive scientists as characteristic of the incubation phase. His term recognizes the evolutionary, structural, and operational primacy of nonsymbolic thinking, the opposite of “secondary process thinking” that is characterized by “a state of focused attention, where a few nodes are strongly activated,” as required for logical and other types of serial operations, including most language use (1995:259). Although Martindale does not say so, another way to describe these two distinct categories of thought are, respectively, “right track” and “left track” in recognition of the categorical split in thinking styles generally associated with the brain’s two hemispheres (Taylor 1988).

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Blosociation and the Bisected Brain

Summarizing what I have written up to this point, there appear to be three distinct cognitive requirements associated with creativity that bear on what I shall have to say later about the relationship between creativity and orthographic types. First, people need so-called “left track” analytical skills to isolate the elements of a problem from their concrete setting, and to express these elements abstractly enough to facilitate matches with stored models. Second, one needs to be able to visualize these segments of the problem out of their linguistic and symbolic contexts, as elements in an (evolutionary) lower part of the cognitive hierarchy where thinking is done by the “right track” processes of analogy and association. Third, people must be able to carry out the two processes in a complementary fashion, so that abstract target patterns elicit appropriate sources, near matches suggest better target representations, and proposed solutions are critically evaluated. In other words, data from the two processes must be exchanged.
There is strong evidence that these three cognitive requirements correlate with the brain’s hemispheric activities. Analytical and abstracting tasks invoked during creativity’s preparatory phase are characteristic of the logical operations carried out in the left hemisphere of most (but not all) people’s brains, hence the term “left track.”11 The spatial (multidimensional) thinking that supports the analogical associations needed during incubation is probably conducted in the right hemisphere. Insight, the sudden matching of the target representation with an abstract, nonverbal source pattern, depends on communication between the two halves. In the validation stage, the left hemisphere takes over again to scrutinize the right brain’s analogical proposals by logical analysis. Both hemispheres are involved separately and together in creativity.
Scholarly acceptance of distinct hemispheric roles in the creative process, while widespread today, was delayed by an early oversimplification that cast the notion in a bad light. Just as popular psychology had confused the middle phase of creativity with its whole, ignoring the analytical and sweaty parts of the operation, so did the original view of creativity as a “rightbrained” activity' err by omitting the critical left hemisphere contributions and the requirement that the two hemispheres operate in tandem. Creativity scientists working on the fringe of mainstream psychology were not eager to add another link to their misbegotten identification with the counterculture.12
I considered leaving the hemispheric discussion out of the present study for the same reason. Although it is unlikely this book will be linked to the counterculture, some of the points raised here about Asian orthography and technology' transfer will be seen by some as challenging or controversial. Since it is quite possible to argue my points about orthography’s influence on cognitive processes without referring to the physical seat of those processes, why add to the exposure? But the evidence tying hemispheric activities to creativity is so overwhelming that I concluded the association could not be ignored even in a summary presentation.
Let’s look first at the neurological evidence. Rauch’s 1977 study of braindamaged patients showed that people with portions of their left hemisphere removed re-presented the same problem over and over, unable to settle on an answer even when appropriate solutions had been achieved. Conversely, patients with right hemisphere lobotomies would persevere with the same hypothesis, failing to produce alternative solutions after the inadequacy of the original formulation became apparent. Later studies replicated these findings (Fiore and Schooler 1998:355). Generating analogical solutions to logical problems, often through nonverbal images, is associated with the incubation phase of creativity. The inability of people with right brain damage to perform this task suggests that the function is localized to the right hemisphere. By the same token, evaluating analogical solutions through logic defines creativity’s validation stage, and the failure of left-brain-impaired subjects at this task likewise points to a localized activity.
These hemispheric biases apply not only to phases of creativity. They are global in nature and manifest some well-known dichotomies. For example, Jaynes noted, on the basis of clinical tests of normal and commissuro-tomized patients and patients with left or right brain lesions, “that the right hemisphere is more involved in synthetic and spatial constructive tasks while the left hemisphere is more analytic and verbal.” The right brain “sees parts as having a meaning only within a context” that is, as wholes; the left “looks at parts themselves” (1976:119). Springer and Deutsch found that patients with right hemisphere damage do worse on “non-verbal tests involving the manipulation of geometrical figures, puzzle assembly, completion of missing parts of patterns and figures, and other tasks involving form, distance, and space relationships” (1998:16, my emphasis).
Although they were not designed to support creativity, these innate differences in hemispheric processing styles are what make creativity possible. Fiore and Schooler list four typical right hemisphere traits that are consistent with creativity’s incubation phase, including: “reliance on non-verbal processes, avoiding perseveration, access to nondominant interpretations, and perceptual restructuring” (1998:350). Schooler and Melcher, citing their own research and that of others, on the other hand found significant overlap between analytical problems and logical arguments—associated with creativity’s early and late stages—in terms of competition for left hemisphere processing space. Their use of the same cognitive resource derives from the fact that they are serial operations and depend on verbal memory “to maintain and manipulate information” (1995:125).
Language itself has long been known to be a left hemisphere activity, which coincides with our observations about symbolic activity and “secondary process thinking.” Its left lateralization goes beyond phonology to core linguistic structures, as evidenced by sign language’s dependence on the left hemisphere, not the right as one might expect from its spatial orientation. According to Calvin and Ojemann, “Deaf patients using sign language are just as impaired with left brain strokes as the rest of us, and their sign language is just as unimpaired by right brain strokes as ours is” (1994:65). The symbolic activity behind all forms of language—spoken, written, and signed—has its locus on the left, which has important implications for the mind’s ability to learn and apply analytical techniques, as we shall see.13
Recently a number of studies have argued for right hemisphere involvement in language (Beeman and Chiarello 1998). A closer look at these arguments confirms, however, that language, as understood by most linguists, is very much a left brain activity7. Although the right hemisphere is involved in language comprehension, it is concerned chiefly with the figurative meanings of words and relating words to context (146). As Deacon puts it, the right hemisphere is involved in the large-scale processing used to fit words and sentences into larger units such as “complex ideas, descriptions, narratives, and arguments” (1997:311-12).14 Its methods are holistic, as opposed to those of the left hemisphere, which focuses on manipulating language’s components. The identification of a part of language with the right hemisphere suggests, however, that what resides in the left is not language per se but the neurological connectivity that governs language’s analytical and logical features.
This observation is supported in part by the finding that neural activation is more constrained in the left hemisphere than in the right, giving the left hemisphere the ability to “modulate and restrict the scope of available meanings to those that are closely related to the current context” as required for the solution of logical problems (Chiarello 1998:145). The right hemisphere “maintains a broader range of related meanings, including those which may have been eliminated by more selective LH processes,” allowing it to participate in the analogical routines needed for creativity’s middle phase. With the ability to access distant (nondominant) interpretations “more concepts are likely to be accessed [by the right side] and more divergence from the current approach is likely to occur” (Fiore and Schooler 1998:360).
The physical basis for these hemispheric differences seems to be greater functional connectivity in the brain’s right half, as indicated by denser interneurons in the language areas and more dendritic branching, a higher ratio of white to gray matter, a greater diffusion of deficits caused by lesions, and more diffuse evoked potentials in the right (Beeman 1998:257). The two halves function differently because they are built differently.
Creativity exploits these differences. Problems are analyzed by the left brain, whose sparse architecture facilitates focusing on parts. The right, meanwhile, with its enhanced connectivity seeks divergent analogues for left brain encodings. Its proposals are scrutinized by the left. On this matter— the cofunctioning of the two hemispheres—there is broad agreement. As Fiore and Schooler note, “most problems involve long and extensive logical reasoning, punctuated every now and then by an insight regarding an alternative way to proceed. Such hybrid problem solving processes highlight the close integration that insight and noninsight processes may often entail” (368). The right and the left work together to create solutions (I wish our political process worked this well). The organization is described eloquently by Bruce West and Jonas Salk in an essay where they wrote:
The mind may also be seen as a unit made up of two interactive distributed functions which may be referred to as intuition and reason. The brain, with its right and left hemispheres, may be seen as the binary structure for the functioning mind with its cofunctioning of intuition and reason. (1988:160)
We have accounted for the separate phases of creativity in hemispheric terms, but what of our earlier point about the need to coordinate these processes? Creativity depends not only on the capacity to formulate problems and evaluate solutions (left hemisphere) or on the ability to generate multiple hypotheses (right hemisphere). It also requires that these activities be linked. In an intriguing article, Bogan and Bogan argue that creativity depends in part on what they call “transcallosal interhemisphere exchange” used to enable the “integrated use of verbal and visuo-spatial thought” (1976:257-59). The authors point out “There is an inbuilt antagonism between analysis and intuition requiring subtle mediation to obtain a common ground.” This is done by the callosal fibers joining the two halves, which host both excitatory and inhibitory activity (260).
These fibers share the same global qualities of other neurons in their susceptibility to selection and strengthening through use, so that their ability to mediate data exchanges between the two hemispheres is enhanced and shaped by their exercise of cognitive demands. As we shall see later, alphabetic writing’s requirement for ongoing mediation between fractional and integrative thought processes plays the same role here in preparing the brain for creative thinking that the alphabet’s analytical demands play in acclimating the brain to fine-grained, abstract thought. In both cases the brain adapts to the tasks it is called on to execute. The end purpose of these demands—reading and writing or working through a creative process—is irrelevant. All that matters is that the processes are congruent.

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Living on the Edge

Creativity above all is a balancing act. One shuttles between a world shaped by rules and predictability and a different realm where freedom and randomness govern.15 Creativity demands that the complementary operations captured in such dichotomies as serial-parallel, logical-analogical, rational-
intuitive, verbal-visual, and fractional-holistic be optimized to support one another without jeopardizing the integrity of either operation. Coordination is as important to creativity as the separate operations are themselves.
Students of creativity have consistently pointed out the need to coordinate these two distinct types of processes. Blandshard spoke of creativity as the “result of two influences, on the one side the psychological and mechanical, which would drive it along the trail of association, and on the other the logical, whose attraction if sufficiently powerful, keeps it in the groove of necessity” (1939:127). Mitchell wrote of the need to explore “many plausible angles of possible interpretations while avoiding a search through a combinatorial explosion of implausible possibilities” (1993:22). More recently, McGraw (1997) described the need for “top down control with bottom up processing.” Too much freedom produces nothing useful or meaningful, while too much control takes out the “sparkle.”
The difficulty of achieving this balance is evidenced both by creativity’s scarcity and by the distribution of cognitive traits throughout populations. Our world is littered with intelligent left brain types skilled in the verbal arts or particular disciplines who pass through their lives without generating an original idea. The phenomenon has been described well by Thomas Kuhn (1962) and requires no elaboration here. On the other side are the inveterate visionaries and dreamers able to associate everything but unable to follow a single line of thought. What both lack is balance, or the ability to navigate what is commonly referred to as the “creative tension” set up by conflicting demands for freedom and order.
We learn to resolve this tension in the creative sphere when the environment provides us opportunities to grapple with analogous conflicts elsewhere. Language, which requires that we shift between unstructured thoughts and an ordered system, is one such venue. This is especially true for people whose written language approximates (but does not coincide exactly with) speech, where the interplay between formal writing and spontaneous speech acclimates users to the task of mediating opposing demands in exercising what is probably a unified process (Hannas 1997:245-47). Political society, of course, constitutes another venue where individuals reconcile the impulse to freedom with the need for order, to the extent that societies delegate that responsibility to individuals.
What then is needed for individual creativity? Amabile and Check list three elements: “ domain-relevant skills, including everything that the individual knows and can do in the target domain; creativity-relevant skills, including cognitive styles, personality styles, and work styles that are conducive to the generation of novel ideas, and intrinsic task motivation’ (1985:59). The authors consider the last item, motivation, “just as important as the role of intelligence, memory, and learning.” We shall see later how society plays an important role here by affecting one’s disposition to create. Their first two elements, however, relate directly to our argument about the need for both left and right track expertise (and the ability to mediate the two).
I emphasize that left track skills in this context refer almost entirely to analytical talent and domain mastery, not to intelligence per se. Specialists concur on the need for substantive expertise in a specific area. According to Gardner, “Individuals are not creative (or noncreative) in general; they are creative in particular domains of accomplishment, and require the achievement of expertise in these domains before they can execute significant creative work” (1994:145). Johnson-Laird expressed the same requirement in reverse, in terms of knowledge about what can not be done. He noted, “The exceptional thinker has mastered more constraints—to be used generatively as opposed to merely critically—and thus has a greater chance of making the required mapping” (1989:328). Churchland pointed out the need for people to be
sufficiently learned to have a large repertoire of powerful prototypes whose novel redeployments are worth exploring in the first place . . . and who are sufficiently critical to be able to distinguish between a merely strained metaphor on the one hand, and a genuinely systematic and enabling insight on the other. (1995:279)
The creative individual must be knowledgeable about the field in which he or she creates. This requirement supposes sufficient intelligence, as measured by IQ tests, to master a knowledge domain. That said, there is widespread agreement among creativity specialists that intelligence is a “necessary but insufficient” condition (Eysenck 1994:200). Past a certain point, IQ does not seem to matter. Findlay and Lumsden state:
The correlation between IQ and creative ability is relatively modest, up to about IQ 120, beyond which it appears to weaken even further. . . . Hence, despite the interest in IQ studies, their value for understanding creativity, discovery and innovation may ultimately prove quite limited. (1988:36)
Finke, Ward, and Smith report various studies, which found that “people with low IQs tend to be uncreative, whereas people with high IQs can be either creative or uncreative” (1996:28). The minimum IQ requirement relates to what I said earlier about domain mastery, whereas the irrelevance of a high IQ suggests that more than (left track) intelligence is involved. Martindale’s remarks on this subject are worth quoting:
The more intelligent one is, the more one can learn. There should, then, be a correlation between intelligence and creativity, and there is—but only up to an IQ around 120 or so, and then the correlation essentially vanishes. One finds extremely intelligent people who are not in the slightest bit creative and extremely creative people who are not wildly intelligent. (1995:253)
Left-track intelligence of the sort reflected in IQ tests is superfluous beyond what is needed to assimilate existing knowledge within a domain. One uses this knowledge to represent problems and evaluate solutions. Between these two phases of preparation and verification, associative (righttrack) skills are needed, the exercise of which has even less to do with IQ than the left track skills that precede and follow it. Herein lies the province of what James (1890:360) and Simonton called the “intuitive genius.” For highly creative people, Simonton noted, “Fewer connections are habitual or even properly symbolized.” Unlike the analytical genius, knowledge used by the intuitive genius is distributed more evenly. “Because mental elements are more richly interconnected, appreciably more ways exist of passing from one element to another” (1988a:402).
If high IQ has little to do with creativity, extreme fluency in associative thinking by itself cannot lead to creativity either. The right track analogue of the high IQ type is the schizophrenic, who has lost touch with “reality,” that is, the logical relations between ideas. The creative thinker and the schizophrenic differ in their ability to weigh and balance. As Eysenck described it, for both creative and psychotic personalities the concept of relevance “is broadened, and ideas and associations become relevant that would not appear to be so for the ordinary person. Creative thinking is distinguished from schizophrenic thinking by a more critical assessment of the products of such thinking” (1994:231).
Abnormally good left track or right track skills are less important for creativity than the ability to mediate both types of functions, exercised in adequate measure. No one in his or her right (or left) mind would question the intellectual abilities of East Asians. If creativity and high intellect did correlate, there would be no grounds for the present thesis. On the other hand, neither Westerners nor Asians claim a monopoly on schizophrenia. Both sides of the world have their share of overly active right-brained personalities able to find associations where there are none.16 What matters for creativity is that these bicameral skills be integrated. It makes sense, accordingly, to view external factors that facilitate coordination between the two types of skills as part of what makes certain people and groups more creative than others.
Later I shall describe in detail the effects of writing as a facilitator (or inhibitor) of creativity-related skills. We will also look at the link between cultures steeped in particular orthographic traditions and their adaptation to creativity tasks. Finally, we will consider some derivative or associative properties of writing that relate indirectly to creative behavior.
Here I shall merely register the specialists’ view that social structures and norms have an important impact on individual creativity. Brick pointed out that “a society that promotes and encourages creativity and strives for novelty and unexpected solutions to problems will probably foster more people that behave in a way that we would call creative than a society that is indifferent or negative” (1997:6). Mandler noted, “Both the creative artist and scientist are part of a cultural tradition that values the novel construction and seeks out novelty. On the other hand, there are social and cultural conditions in which the novel is avoided and considered inappropriate (e.g., in authoritarian societies).” Societies that value harmony above all else will view creativity “as destructive of existing values and standards” (1995:21-22). Hennessey and Amabile concluded, “There is no doubt that salient factors of extrinsic constraint in the social environment can have a consistently negative impact on the intrinsic motivation and creativity of most people most of the time” (1988:34).
Social constraints that frustrate one’s motivation to create are also expressed by the absence of diversity. Dunbar, who studied the cultures, work processes, and creative results of different scientific laboratories, found that the one lab in his sample whose staff did not use analogical reasoning made no progress in understanding their research task. He further noted, “All the staff in this laboratory came from highly similar backgrounds and consequently drew from a similar knowledge base” (1995:384-85). Findlay and Lumsden noted in the same vein that background knowledge needed to generate analogies “depends not only on the individual’s capacity to learn and store information, but also on such macroscopic factors as the accessibility of diverse sociocultural environments” (1988:17). Homogeneous, politically centralized societies thwart creative impulses—and eventually the disposition of its members to create—by depriving individuals of opportunities to enrich their store of potential source analogs.
Simonton cited three more social factors related to creativity that will be seen as particularly relevant in the present context. One is the effect of conformist education. As Simonton put it, “the iconoclastic facet of creativity— the capacity to produce genuinely original chance configurations—quite obviously requires that the young creator not be excessively socialized into a single, narrow-minded way of associating ideas” (1988a:413). Another factor is privacy. Simonton offers the following technical explanation for its needs:
Social interaction may elicit a social-interference effect. . . . The mere presence of others tends to raise arousal, which in turn increases the likelihood that highly probable responses will be emitted at the expense of responses less probable. Because the chance-permutation process demands access to low-probability associations, such socially induced arousal would necessarily inhibit creativity. To the extent that the presence of others implies the possibility of evaluation, this interference effect would be heightened all the more. (404)
Finally, Simonton points to the need for societies to tread a narrow path between political pluralism (“creativity increases whenever a civilization is fragmented into a large number of sovereign nations”) and the violent events that sometimes accompany fragmentation. He writes, “Wars between states, for instance, tend to produce an ideological Zeitgeist that may not welcome innovation, and creativity is definitely unlikely to come forth after a political system crumbles into total anarchy, as registered by military revolts, dynastic conflicts, political assassinations, coups d’etat, and other exemplars of chaos among the power elite” (415).
As in the personal sphere, creativity demands that societies live on the edge between stasis (left hemisphere perseveration) and chaos (right hemisphere randomness).17 Stability is needed as a baseline for survival and for individuals to build up a store of domain-specific knowledge. On the other hand, society must be able to tolerate enough pot stirring, skepticism, and “creative dissent” to make innovation safe and respectable for a critical minority of individuals. The challenge is to keep the two requirements in balance—a goal that meshes fairly well with the Western ideals of federalism, minimal government, and linear progress. East Asian society historically has been less adept at achieving this balance, as evidenced in its view of “progress” as a cyclical movement from stability through chaos and back to stability. China in particular, with its highly centralized authoritarian governments, cannot seem to stay on the cutting edge, and is either falling off the one side or the other into rigidity or chaos.
The Western and Eastern traditions seem to offer, respectively, exactly what is needed to foster and to frustrate scientific creativity. Among the many factors that have influenced members of the two cultures to think and act in creative and noncreative ways, orthography perhaps stands out as the most important because it touches on processes that underlie a basic difference in the two culture’s cognitive styles. Its effects on creativity began with the origins of both civilizations.
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