From a theoretical perspective, it is important to study the processes that play a role in predicting creativity under approach and avoidance motivation more thoroughly. For clarity, cognitive, affective, and volitional processes involved in creativity have been discussed separately in this paper. However, many of these processes are inherently interdependent. Threat appraisals, for example, are closely related to negative emotions (Lazarus, 1999), physiological stress responses (Seery, 2011), and reduced intrinsic motivation (Drach-Zahavy and Erez, 2002), whereas challenge appraisals are related to positive affect (Skinner and Brewer, 2002) and enhanced effort and motivation (Drach-Zahavy and Erez, 2002). Future research is needed to disentangle the roles of the various processes in shaping effects of approach and avoidance motivation on creativity, and to deepen our understanding regarding optimal levels of optimism. This will help to build theory, and to identify potential factors that impact these processes and can ameliorate the negative effects of avoidance motivation on creativity.

## **CONCLUSION**

Focusing on avoiding failure or negative outcomes can undermine creativity, due to cognitive (e.g., threat appraisals), affective (e.g., anxiety), and volitional processes (e.g., low intrinsic motivation). This can be problematic for people who are avoidance motivated by nature and in situations in which threats or potential losses are salient. Optimism positively impacts each of the problematic processes evoked by avoidance motivation, and should thus reduce the undermining effect on creativity. We further suggest that optimism may suppress the positive relation between approach motivation and creativity. More broadly, we propose that for effectively stimulating creative performance, it is important to address the core psychological processes underlying creativity and identify factors that influence these processes.

## **REFERENCES**

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

*Received: 28 November 2013; accepted: 11 February 2014; published online: 28 February 2014.*

*Citation: Icekson T, Roskes M and Moran S (2014) Effects of optimism on creativity under approach and avoidance motivation. Front. Hum. Neurosci. 8:105. doi: 10.3389/fnhum.2014.00105*

*This article was submitted to the journal Frontiers in Human Neuroscience.*

*Copyright © 2014 Icekson, Roskes and Moran. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

## The scientific study of inspiration in the creative process: challenges and opportunities

## **Victoria C. Oleynick , Todd M. Thrash\*, Michael C. LeFew , Emil G. Moldovan and Paul D. Kieffaber**

Department of Psychology, College of William and Mary, Williamsburg, VA, USA

#### **Edited by:**

Matthijs Baas, University of Amsterdam, Netherlands

#### **Reviewed by:**

Matthijs Baas, University of Amsterdam, Netherlands Marieke Roskes, Ben Gurion University of the Negev, Israel

#### **\*Correspondence:**

Todd M. Thrash, Department of Psychology, College of William and Mary, P.O. Box 8795, Williamsburg, VA 23187-8795, USA e-mail<EMAIL_ADDRESS>
Inspiration is a motivational state that compels individuals to bring ideas into fruition. Creators have long argued that inspiration is important to the creative process, but until recently, scientists have not investigated this claim. In this article, we review challenges to the study of creative inspiration, as well as solutions to these challenges afforded by theoretical and empirical work on inspiration over the past decade. First, we discuss the problem of definitional ambiguity, which has been addressed through an integrative process of construct conceptualization. Second, we discuss the challenge of how to operationalize inspiration. This challenge has been overcome by the development and validation of the Inspiration Scale (IS), which may be used to assess trait or state inspiration. Third, we address ambiguity regarding how inspiration differs from related concepts (creativity, insight, positive affect) by discussing discriminant validity. Next, we discuss the preconception that inspiration is less important than "perspiration" (effort), and we review empirical evidence that inspiration and effort both play important but different—roles in the creative process. Finally, with many challenges overcome, we argue that the foundation is now set for a new generation of research focused on neural underpinnings. We discuss potential challenges to and opportunities for the neuroscientific study of inspiration. A better understanding of the biological basis of inspiration will illuminate the process through which creative ideas "fire the soul," such that individuals are compelled to transform ideas into products and solutions that may benefit society.

**Keywords: inspiration, creativity, insight, effort, approach motivation**

#### **INTRODUCTION**

Describing his creative process, Mozart observed, "Those ideas that please me I retain in memory, and am accustomed, as I have been told, to hum them to myself. If I continue in this way," he writes, "it soon occurs to me how I may turn this or that morsel to account so as to make a good dish of it. . . All this fires my soul" (Harding, 1948). Mozart's depiction of inspiration possesses all of the core elements of the modern scientific inspiration construct—appreciation of new or better possibilities ("ideas that please me"), passive evocation ("it. . .occurs to me"), and motivation to bring the new possibilities into fruition (turning a morsel into a dish; "fires my soul"). Like Mozart, writers, artists, and other creators commonly emphasize the importance of inspiration in the creative process (Harding, 1948). Despite this, until recently, scientists have given little attention to inspiration.

Perhaps it is not surprising that inspiration has received little attention within the scientific community, given the numerous challenges that the inspiration concept has presented. Among these challenges have been (a) a lack of clarity about the meaning of inspiration; (b) difficulty of operationalization; (c) ambiguity about whether inspiration is distinct from related constructs; (d) preconceptions that inspiration is unimportant relative to "perspiration," and (e) a variety of barriers to neuroscientific investigation. The overarching goal of this article is to address each of these challenges and to point to opportunities for expanding upon the emerging scientific literature on inspiration. We address the first challenge, ambiguity of definition, in the next section.

#### **CONCEPTUALIZATION**

The term "inspiration" has been used in a variety disciplines (e.g., literary criticism, theology, psychology) and literatures within psychology (e.g., social comparison, humanism, creative process; for a review, see Thrash and Elliot, 2003). Often the term is not defined, is used interchangeably with other constructs, or is referenced only to be critiqued as mythical, unimportant, or unscientific. Further complicating matters, inspiration historically has been studied in a domain-specific manner, with little communication between researchers across domains. Recognizing the need for a unified, integrated definition of the inspiration construct, Thrash and Elliot (2003, 2004) undertook the task of developing a domain-general conceptualization that drew upon the core commonalities across diverse literatures. These efforts have yielded three complementary frameworks for conceptualizing inspiration that focus on different aspects of construct definition: core characteristics, component processes, and the transmission model. In this section, we review these domaingeneral conceptualizations and then show how they may be applied specifically to the case of inspiration to create.

#### **TRIPARTITE CONCEPTUALIZATION**

The *tripartite conceptualization* (Thrash and Elliot, 2003) specifies the three core characteristics of the state of inspiration: *evocation*, *transcendence*, and *approach motivation*. Evocation refers to the fact that inspiration is *evoked* rather than initiated volitionally by the individual. In other words, one does not feel directly responsible for becoming inspired; rather, a stimulus object, such as a person, an idea, or a work of art, evokes and sustains the inspiration episode. During an episode of inspiration, the individual gains awareness of new possibilities that *transcend* ordinary or mundane concerns. The new awareness is vivid and concrete, and it surpasses the ordinary constraints of willfully generated ideas. Once inspired, the individual experiences a compelling *approach motivation* to transmit, actualize, or express the new vision. This set of three characteristics is intended to be minimally sufficient to distinguish the state of inspiration from other states.

#### **COMPONENT PROCESSES**

Inspiration may be conceptualized not only in terms of the characteristics of the inspired state, but also in terms of the temporally and functionally distinct processes that compose an episode of inspiration. Thrash and Elliot (2004) argued that inspiration involves two distinct processes—a relatively passive process that they called being inspired *by*, and a relatively active process that they called being inspired *to*. The process of being inspired *by* involves appreciation of the perceived intrinsic value of a stimulus object, whereas the process of being inspired *to* involves motivation to actualize or extend the valued qualities to a new object. For example, one might be inspired by a breathtaking sunrise, or by the elegance of a new idea that arrives during an insight or "aha" moment. Thereafter one might be inspired to paint or undertake a new research project. The individual can, at any time, look to (or recall) the evoking stimulus for motivational sustenance. Thrash and Elliot (2004) further proposed that the process of being inspired *by* gives rise to the core characteristics of evocation and transcendence, whereas the process of being inspired *to* gives rise to the core characteristic of approach motivation.

These component processes are posited to be present across diverse manifestations of inspiration. Thrash and Elliot (2004) asked participants to produce narratives recalling either a time when they were inspired or a baseline experience (control condition). The inspiration narratives spanned topics such as becoming animated by a scientific or artistic insight, discovering one's calling, being influenced by a role model to succeed or live virtuously, and realizing that greatness is possible in response to an unexpected success. Despite superficial differences in narrative content, the inspiration narratives shared the underlying themes of having one's eyes opened during an encounter with a person, object, event, or idea (i.e., being inspired "by"), and wishing to express or actualize one's new vision (i.e., being inspired "to").

#### **TRANSMISSION MODEL**

From a less descriptive and more theoretical standpoint, inspiration may be conceptualized in terms of its purpose or function (Thrash and Elliot, 2004; Thrash et al., 2010b). Whereas simpler forms of approach motivation serve the function of movement toward and attainment of desired goal objects (e.g., food or affiliation), inspiration is posited to serve a unique approach function: it motivates the transmission or expression of the newly appreciated qualities of the evoking object (Thrash and Elliot, 2004; Thrash et al., 2010b). Inspiration thus serves the role of a mediator in a statistical sense. For instance, certain virtues that one observes in another person may lead to inspiration, which, in turn, leads the inspired individual to pursue these same virtues in a future self. Similarly, a creative seminal idea may inspire the individual, compelling him or her to bring the idea into fruition in the form of a creative invention, poem, or other tangible product.

#### **INSPIRATION TO CREATE**

The general inspiration construct as conceptualized above may be applied straightforwardly to the specific domain of creative activity. From the perspective of the tripartite conceptualization, the general characteristic of transcendence takes the form of *creativity—*the new or better possibilities are appreciated specifically for their creative potential. Regarding the component process conceptualization, the process of being inspired *by* is prompted by the emergence of creative ideas in consciousness, often during a moment of insight. Under optimal conditions (e.g., if the idea is actionable, and the person has the capacity for approach motivation), the process of being inspired *by* gives way to the process of being inspired *to*, which motivates action. Regarding the transmission model, creative inspiration often takes a specific form of transmission called *actualization* (Thrash et al., 2010b), in which one is inspired to bring a creative idea into fruition (i.e., the desirable features of the elicitor are transmitted from a seminal idea to a completed product).

We emphasize that, according to our conceptualization, inspiration is not posited to be the *source* of creative ideas. Instead, inspiration is a motivational *response* to creative ideas. Thus inspiration explains the transmission, not the origin, of creativity. This distinction is critical for at least three reasons. First, claiming that creativity comes from inspiration would not aid scientific understanding, much as attributing creativity to a "muse" would be an exercise in labeling a mysterious cause, not a scientific explanation. Second, scientists have already developed a variety of scientific constructs and theories to explain the origins of creative ideas, which include situational, dispositional, selfregulatory, cognitive, historical, and neurological processes (e.g., Koestler, 1964; Rothenberg, 1979; Martindale, 1990; Finke et al., 1992; Sternberg and Davidson, 1995; Amabile, 1996; Feist, 1998; Bowden and Jung-Beeman, 2003; Simonton, 2003; Baas et al., 2013). In contrast, scientists have given relatively little attention to the processes through which creative ideas are transformed into creative products. The inspiration construct helps fill this gap in the research literature. Finally, because this conceptualization of creative inspiration is derived from a general conceptualization, it is consistent with usage of the inspiration construct in other literatures. For instance, creative inspiration is a response to (not the cause of) creative ideas, much as interpersonal inspiration is a response to (not the cause of) virtuous qualities in others.

### **OPERATIONALIZATION**

Given the personal nature and elusiveness of the experience of inspiration, how can it possibly be measured in the laboratory? One might be tempted to throw up one's hands and turn instead to something that is more amenable to direct experimental control.

#### **THE VALUE OF SELF-REPORT**

We maintain that self-report is a straightforward and appropriate method for operationalizing inspiration, because the inspiration construct is inextricably intertwined with a distinctive phenomenological experience. Numerous creators have claimed—through conscious self-reports—that they experience inspiration and that this experience is critical to their creative process (Harding, 1948). Operationalizing inspiration through self-report allows researchers to put such claims to the test.

Thrash and Elliot (2003) developed a trait measure of inspiration called the Inspiration Scale (IS). Although the term "trait" has a variety of connotations, trait inspiration refers to nothing other than individual differences in the tendency to experience the state of inspiration. Because inspiration is a construct that is meaningful in individuals' lives but underappreciated by psychologists, the measure was designed to be straightforward and face valid. Items include statements such as, "Something I encounter or experience inspires me" and "I am inspired to do something." The IS has two internally consistent 4-item subscales: inspiration frequency and intensity. Both subscales are internally consistent, with Cronbach's αs equal to or greater than 0.90. The two subscales have been demonstrated to be highly correlated (*r* = 0.60 to 0.80), and therefore scores may be summed to form an internally consistent 8-item index of overall inspiration. The IS demonstrates measurement invariance across time (2 months) and across populations (patent holders, university alumni), indicating that the underlying latent constructs have comparable meaning at different points in time and in different populations. Two-month test-retest reliabilities for both subscales are high, *r* = 0.77. In short, the IS has excellent psychometric properties. Notably, the intensity subscale has been adapted for use as a state measure (e.g., Thrash and Elliot, 2004; Thrash et al., 2010a).

Some may worry that self-reported inspiration cannot be trusted, that it is not objective, or that it does not provide a full explanation. We respond to each of these potential limitations. First, inspiration, as assessed with the IS, tends to be unrelated or weakly related to social desirability, and its predictive validity is robust when social desirability is controlled1 (Thrash and Elliot, 2003; Thrash et al., 2010a). Second, although the IS provides a subjective indicator of inspiration, scores on this measure have been linked to a variety of external criteria and objective outcomes, as reviewed in the following section. Moreover, consciousness plays a critical role in the simulation of future action in humans (Baumeister and Masicampo, 2010) and may be necessary for inspired action. Accordingly, conscious self-report is intrinsically appropriate to the construct. Finally, we recognize that self-report measures may leave some researchers with a hunger for lower-level explanations, such as those involving physiological or neurological processes, but we see this as an opportunity rather than a problem—the inspiration construct may see an exciting second generation of research regarding neural underpinnings. In this case, self-reported inspiration provides a "bootstrap" that may guide researchers to underlying process. Although it is true that the self-report method is limited in some ways, it offers a well-validated starting point for neuroscientific investigations. Moreover, not investigating inspiration on the grounds that it is measured by self-report would lead researchers to overlook a critical predictor of creative output, the biological underpinnings of which would remain undiscovered.

#### **THE PLACE OF INSPIRATION IN CREATIVITY RESEARCH PARADIGMS**

The field of creativity assessment is active and dynamic, and thus a review of the literature is well beyond the scope of this article (for a review, see Plucker and Makel, 2010). We note, however, that the dominant research paradigms used in the study of creativity have unwittingly precluded attention to inspiration. Creativity is most often assessed using tests of creative ideation (e.g., Alternate Uses) or creative insight (e.g., Remote Associates Test). While such tests are very practical in laboratory contexts and allow researchers to focus on the processes underlying the emergence of creative ideas, they do not allow participants to transform creative ideas into creative products. Failure to accommodate the idea actualization process—that is, creation *per se—*renders inspiration speciously immaterial to the creative process. If the function of inspiration within the context of creativity is the actualization of creative ideas into creative products, useful paradigms must allow for idea actualization. Product-based assessments, such as the Consensual Assessment Technique (CAT; Amabile, 1982) and analysis of patent data, are the gold standard if one wishes to investigate the unique contribution of inspiration to the creative process.2 In fact, relevance to inspiration aside, assessment of creative products is considered by some to be the most appropriate and valid operationalization of creativity (Baer et al., 2004; Baer and McKool, 2009).

#### **DISCRIMINANT VALIDITY**

Ambiguity about whether inspiration is distinct from other constructs has been another impediment to research activity. If one presumes that inspiration is the same thing as, for example, creativity or insight, then one has no reason to study it. In this section, we clarify the distinctions between inspiration and several other constructs (creativity, insight, and positive affect).

1 In these instances, social desirability was assessed using either the Marlowe-Crowne Social Desirability Scale (Crowne and Marlowe, 1960) or the Paulhus Deception Scales (Paulhus, 1998).

2We note that the Consensual Assessment Technique has also been used to assess the creativity of ideas (e.g., Faure, 2004). Here, we refer specifically to the use of this technique in assessing the creativity of products.

#### **INSPIRATION AND CREATIVITY**

While there is considerable variability in the definition and usage of the term creativity within psychology (Silvia and Kaufman, 2010), there is some degree of consensus that creativity implies two qualities: novelty and usefulness (e.g., Feist, 1998; Plucker et al., 2004). We find it useful to explicitly conceptualize creativity as an *appraisal* of novelty and usefulness that may be applied to any of a variety of objects, particularly ideas and resulting products. Depending on the aims of the research, this appraisal may be made by the creator herself, by gatekeepers within a field, by an audience, or through various other operationalizations available to the researcher. We note that researchers often appear to have either ideas or products in mind as the ultimate objects of creativity appraisals, even when the term "creative" precedes other nouns (e.g., creative activity (Simonton, 2000), creative insights (Csikszentmihalyi and Sawyer, 1995), creative personalities (Feist, 2010), creative states (Jamison, 1989), or creative processes (Kris, 1952)).

Although the terms inspiration and creativity have occasionally been used synonymously (e.g., Schuler, 1994; Chamorro-Premuzic, 2006), our conceptualizations of inspiration and creativity involve a clear delineation. Creativity is an appraisal of novelty and usefulness that may apply (to various degrees) to content at any point in the creative process, from a seminal idea to the completed product. Inspiration, in contrast, is a motivational state. We posit that inspiration is often elicited when a creator appraises his or her idea as creative, and it is posited to motivate actualization of the idea in the form of a product that is likewise appraised (by its creator and perhaps others) as creative. We discuss empirical support for these proposals below.

#### **INSPIRATION AND INSIGHT**

Conflation of inspiration with insight is common in everyday language.3 An individual might exclaim, "I had an inspiration," where "inspiration" refers to the idea itself, not to the motivational response. In the scientific context, the term insight has been used to describe the process by which a problem solver suddenly moves from a state of not knowing how to solve a problem to a state of knowing how to solve it (Mayer, 1992). Within the creativity context, insight has also been conceptualized as the cognitive content that enters consciousness suddenly; the "aha!" moment (Csikszentmihalyi and Sawyer, 1995). Regardless of its exact usage, insight can be differentiated from inspiration in terms of its theoretical function. Whereas insight research is an attempt to explain the cognitive mechanisms, such as restructuring (Ohlsson, 1984), by which ideas enter awareness, inspiration research is an attempt to explain the motivational response that often (but not always) follows creative insight (see Thrash et al., 2010b).

If inspiration always followed from insight, then perhaps the inspiration construct would be superfluous. However, inspiration does not always follow. Thrash et al. (2010b) found that creative ideation tends to lead to inspiration but that this effect is moderated by individuals' approach temperament (i.e., sensitivity to reward; Elliot and Thrash, 2010). Individuals with a strong approach temperament tend to get inspired to create in response to creative insight, whereas individuals with a weak approach temperament report feeling a lack of inspiration in spite of their insight. Inspiration thus has important implications for the behavioral transmission of a creative insight into a creative product.

Recent work on the phenomenology of insight offers hints about how insight may lead to inspiration. Abrupt changes in processing fluency during insight have been found to endow an individual with elevated levels of positive affect (PA) and perceived truth regarding his or her solution (Topolinski and Reber, 2010). Given that PA is involved in both the insight "aha" experience and inspiration, it may facilitate a fluid transition from insight to inspiration. Moreover, perceiving one's solution as true, a consequence of insight, may bolster inspired motivation. As we have noted, however, insight can occur without inspiration. Dispositional factors of the individual (e.g., low approach temperament) and situational factors (e.g., contexts in which opportunities for transmission are not available) can impede inspiration. Likewise, inspiration can occur outside of the problem-solving context and without a discrete and sudden insight.

### **INSPIRATION AND POSITIVE AFFECT**

Activated PA, a high-arousal form of pleasant affect, is the strongest known correlate of inspiration (Thrash and Elliot, 2003). Indeed, the term "inspired" appears on the PANAS measure of activated PA (Watson et al., 1988). Because activated PA is often present during states of approach motivation (Watson et al., 1999), it particularly resembles the inspired *to* component process.

Although inspiration and activated PA overlap to some degree empirically and conceptually, considerable evidence supports their discriminant validity. First, inspiration and activated PA are factorially distinct (Thrash and Elliot, 2003). Second, consistent with the tripartite conceptualization of inspiration, experiences of inspiration involve greater levels of transcendence and lower levels of volitional control and ascriptions of personal responsibility (indicative of "evocation") compared to experiences of activated PA (Thrash and Elliot, 2004). Third, inspiration and activated PA have different proximal and distal antecedents (Thrash and Elliot, 2004). Activated PA is triggered proximally by reward salience (environmental cues and perceptions that something desired is attainable) and distally by approach temperament. In contrast, inspiration is triggered proximally by experiences of insight and distally by openness to experience. Finally, inspiration and activated PA have different distributions across days of the week; on Fridays, for instance, activated PA is at its peak while inspiration is at its trough (Thrash, 2007).

### **INSPIRATION, PERSPIRATION, AND CREATIVITY**

Perhaps the most pernicious obstacle to research on inspiration has been the longstanding belief that it is perspiration, and not inspiration, that is critical for creative output. Thomas Edison,

3The language of the items and response options of the Inspiration Scale (IS) eliminate this problem by clearly using the term "inspiration" to mean a state, not a cognition or idea.

regarding his work, once remarked that, "what it boils down to is one per cent inspiration and ninety-nine per cent perspiration" (Edison, 1903). This comment has sometimes been offered in support of the idea that effort is important to creativity and that inspiration, by comparison, is unimportant (e.g., Martindale, 1989, 2001; Sawyer, 2006). Furthering this line of reasoning, Fehrman and Petherick (1980) offered an account of why inspiration nonetheless endures as a folk explanation of creativity: when individuals are exposed to creative works, they misattribute creators' effort to inspiration, unaware how much effort was required to produce the work. It appears that reasoning such as this has precluded attention to a legitimate role of inspiration in the creative process.

Empirical data related to inspiration, perspiration, and creativity are now available for consideration. A number of studies indicates that inspiration is a robust predictor of creativity. At the between-person (i.e., trait) level, inspiration and creative selfconcept are positively correlated, and inspiration predicts longitudinal increases in creative self-concept (Thrash and Elliot, 2003). Trait inspiration also predicts objective indicators of creative output. In a sample of U.S. patent holders, inspiration frequency was found to predict the number of patents held (Thrash and Elliot, 2003). Inspiration also predicts creativity at the withinperson level, such that inspiration and self-reported creativity fluctuate together across days (Thrash and Elliot, 2003).

In three studies of different types of writing (poetry, science, and fiction), self-reported state inspiration during the writing process uniquely predicted creativity of the final product, as assessed by expert judges using the CAT (Thrash et al., 2010b). These findings held when a variety of covariates (e.g., openness to experience, effort, activated PA, awe) were controlled. Finally, inspiration has been shown to mediate between the creativity of seminal ideas and the creativity of final products in a manner consistent with the posited transmission function4 of inspiration (Thrash et al., 2010b). Covariates of inspiration (effort, activated PA, awe) failed to mediate transmission, indicating that the transmission function is unique to inspiration.

Having established a relation between inspiration and creativity, we now consider the role of "perspiration" in the creative process. Notably, Thrash et al. (2010b) documented a positive relation, rather than a negative relation, between inspiration and effort, indicating that these constructs are not mutually exclusive as the Edison quote may imply. The assumption that the presence of effort indicates low levels of inspiration is further challenged by a positive relation between inspiration and the work-mastery component of need for achievement (Thrash and Elliot, 2003). Both of these findings were documented at two statistically independent levels of analysis (between-persons, within-persons).

Certainly effort is important to the creative process, but its role is different than that of inspiration. Whereas writers' inspiration predicts the creativity of the product, writers' effort predicts the technical merit of the product (Thrash et al., 2010b). Thus inspiration and effort are unique predictors of different aspects of product quality. Moreover, screen capture data indicate that inspiration is involved in the automatic/generative aspects of the writing process (e.g., inspired writers produce more words and retain more of their original typing), whereas effort is related to controlled self-regulation (e.g., writers who exert effort delete more words and pause more to think; Thrash et al., 2010b). In short, inspiration and "perspiration" are not mutually exclusive, and they contribute in qualitatively different ways to the creative process and product.

The question of whether the audience correctly infers the presence of inspiration remains. The misattribution hypothesis states that it is the creator's *effort* that predicts the creativity of the product but that the audience incorrectly attributes this creativity to *inspiration* in the creator. An alternative to this model is the possibility that the audience correctly infers inspiration (Bowra, 1977). Thrash et al. (2010b) tested these competing hypotheses. Readers were found to correctly attribute creativity to writers' inspiration; likewise, they correctly attributed technical merit to writers' effort. These results, in addition to providing the first empirical evidence that readers can make veridical inferences about writers' motivational states, indicate that folk notions of the importance of inspiration are borne out by empirical data.

The psychological science of inspiration, as well as its relation to creativity, is now well-established. Inspiration has been conceptualized through integration of usages in diverse literatures, operationalized using a well-validated measure, discriminated from related constructs, and linked to creativity in multiple populations, contexts, and levels of analysis. Prior work provides a solid foundation on which investigations into the neuroscience of inspiration can rest.

#### **INSPIRATION IN THE NEUROSCIENCE LABORATORY**

In most respects, the challenges associated with studying creative inspiration are similar regardless of whether one approaches the topic as a neuroscientist, a psychologist, etc. Therefore, the preceding general challenges and solutions are also relevant specifically in the neuroscience context. However, we reiterate the importance of attending carefully to construct definition, because the term "inspiration" has occasionally been used in the neuroscience literature to refer to constructs that are quite different than the inspiration construct that we have discussed. In their classic EEG studies of the creative process, for instance, Martindale and Hasenfus (1978) used the terms inspiration and elaboration to refer to the stages that precede and follow, respectively, creative insight (see Kris, 1952, for a precedent for such usage in psychoanalysis). Inspiration as we have defined it—i.e., as a conscious motivational state rather than as a stage—is more likely to occur during Martindale and Hasenfus's elaboration stage than during the inspiration stage. We now turn to challenges that are particularly relevant within a neuroscience context.

One obstacle in studying inspiration in the laboratory is the impossibility of direct manipulation through exposure to

4The authors empirically tested the *transmission model*, which specifies that inspiration mediates the relation between the creativity of the seminal idea and the creativity of the product. Two alternate theoretical models, the *epiphenomenon model* and the *self-perception model*, which suggest that creativity of the idea influences both inspiration and creativity of the product, or that creativity of the idea influences creativity of the product which in turn influences reports of inspiration, respectively, were also tested using structural equation modeling. The authors found support for the transmission model of inspiration over the epiphenomenon and self-perception models.

exogenous elicitors. If one seeks to elicit inspiration through use of some kind of "inspiring" stimulus, then the manipulated elicitor is the independent variable and inspiration is a dependent variable. Thus caution is needed regarding causal inference, despite use of the experimental method (Thrash et al., 2010a). Although inspiration cannot be directly manipulated through exposure to exogenous stimuli, a researcher may build a case for causality using manipulation of elicitors in combination with statistical controls and cross-lagged analyses, as demonstrated by Thrash et al. (2010a). We note that these problems are not unique to the study of inspiration. Emotions, insight, and many other constructs elude strict experimental control; at best, they may be "elicited" rather than "manipulated".

A related challenge is that it may be difficult to capture authentic or intense experiences of inspiration in a laboratory setting, given that inspiration is elusive for certain individuals or under certain circumstances. One solution may be to, in effect, lower the threshold for what constitutes an episode of inspiration. Thrash and Elliot (2004), for instance, studied "daily inspiration" using experience sampling methods, and we suggest that such tolerance for less intense manifestations of inspiration can be extended to a laboratory study. Much as creativity is not the same thing as genius (Bruner, 1962), inspiration is a matter of degree, and moderate levels might be achievable even in some invasive neuroscience paradigms.

A third challenge is the need for repeatable trials and timelocking. Brain imaging techniques (e.g., fMRI, EEG, MEG) require designs in which the mental event under consideration may be (a) temporally isolated so that the recorded data and the mental event can be time-locked to an eliciting stimulus and (b) elicited repeatedly during a recording session in order to improve the signal-to-noise ratio (Dickter and Kieffaber, 2013). One possible method to address these requirements is to use participant self-report (indicating the onset of inspiration) as the time-locking event. Suppose, for example, participants invent captions for each of a series of photographs (a highly-repeatable activity) and report on levels of inspiration at the moment of getting an idea for each caption. Bowden and Jung-Beeman (2007) used a method similar to this in order to identify processes that distinguish solutions involving the experience of insight from those that do not. We caution, however, that inspiration generally is more prolonged in time than is insight (particularly when considerable activity is needed to actualize an idea), and therefore methods that capture subsequent variability in inspiration across time—not just the level of inspiration at the moment of insight will be particularly valuable.

One such method for capturing variability in inspiration across time, while simultaneously reducing the burden of eliciting inspiration repeatedly, is to record electrical brain activity using a non-invasive technique (such as EEG) during the creative process. For instance, if researchers record screen capture data during the writing process as in Thrash et al. (2010b), they can subsequently play back the recording to participants and collect continuous measures of recalled inspiration during the creative process (e.g., using a dial or slider input device). These ebbs and flows of inspiration can then be linked to variability in neural processes.

The difficulties associated with eliciting inspiration in order to study it at the within-person level may also be addressed by simply focusing on the individuals who are likely to be inspired (i.e., those who are high in trait inspiration). Elicitation may be circumvented altogether by examining structural brain differences between groups known to be high versus low in trait inspiration. One may separate groups into "more inspired" and "less inspired" using the IS. Additionally, as individuals higher in trait inspiration tend to exhibit greater levels of openness and extraversion, one might expect, for example, reduced latent inhibition and increased activity in the ventral tegmental area dopamine projections (Ashby et al., 1999; Depue and Collins, 1999; Peterson et al., 2002) for these individuals. Thus, inspiration's nomological network can serve as an informative starting point for between-person neurological analyses.

Next, we consider the question of where to look in the nervous system. While at present there is no neuroscience of the inspiration construct *per se*, literatures on related constructs can offer us some hints.

Insight relates to inspiration within the tripartite conceptualization in terms of both evocation and transcendence, and within the component processes model as the initial event that often leads one to become inspired *by*. During "Aha!" moments, one *transcends* a mental set and experiences a conceptual expansion (Abraham et al., 2012), and the experience feels automatic and unexpected; it feels *evoked* (Bowden et al., 2005). Therefore, certain neural components involved in insight experiences may be present at the onset of an inspiration episode. However, given that the literature on the neural correlates of insight is complex and that neural processes are under debate (Dietrich and Kanso, 2010), we caution against relying too heavily upon any one finding in guiding work on inspiration.

As inspiration involves not only transcendence and evocation, but also approach motivation, we may also look to the neuroscience literature on states of approach motivation (Elliot, 2008). There exists a burgeoning literature on approach motivation and appetitive affect, with attention to underlying neuronal circuitry (e.g., Bradley et al., 2001; Aron et al., 2005; Junghöfer et al., 2010), subcortical reward systems (e.g., Rosenkranz and Grace, 2002; Wise, 2004; Alcaro et al., 2007), neurotransmitters (e.g., Bassareo et al., 2002; Hoebel et al., 2008), and neurohormones (e.g., Frye and Lacey, 2001; Frye and Seliga, 2003; Frye, 2007). Findings in this area may offer suggestions for the neural underpinnings of the inspired *to* process.

Although the neurological findings regarding certain aspects of the inspiration construct can offer clues, the neural components of these pieces alone are unlikely to tell the full story. After all, we have already argued above that inspiration is not the same thing as insight or activated PA, nor is it the sum of these parts. For instance, an individual could be in an appetitive motivational state at the same time that he or she gets a creative insight, but he or she would not be inspired if the appetitive state reflects anticipation of eating, rather than of bringing the idea into fruition. The evoking object, in this case, the insight, does not meaningfully relate to the motivational object. The critical question for neuroscience is how processes related to generation of creative ideas recruit appetitive motivational processes, such that individuals respond to creative ideas not with indifference, but rather with a feeling of being compelled to act. How exactly does the prospect of turning a morsel into a dish fire the soul, as Mozart put it (in the opening quotation)?

In the initial stages of research on the neurological basis of inspiration, it may be useful to begin with a focus on overall inspiration instead of particular aspects or component processes. Inspiration as a unified concept can be measured quite efficiently using the 4-item intensity subscale of the IS (Thrash and Elliot, 2004). If necessary, inspiration could be assessed with a single item from the IS. Such items are surprisingly effective at capturing the full inspiration construct as we have defined it (Thrash et al., 2010b).

#### **CONCLUSION**

Writers, artists, and other creators have long argued that inspiration is a key motivator of creativity. Over the past decade, scientists have tested and found strong support for these claims. Scientific progress has required overcoming a number of challenges, including definitional ambiguity, difficulties of operationalization, ambiguities about discriminant validity, and skepticism about the importance of inspiration relative to perspiration. By developing an integrative conceptualization, operationalizing inspiration with the IS, establishing discriminant validity, and addressing skepticism with empirical evidence, these challenges have been largely overcome. Although additional challenges face the neuroscientist who wishes to study inspiration, similar challenges have already been overcome in relation to insight and other constructs. We believe that the stage has been set for a rigorous neuroscience of inspiration.

Brain-level explanations of an inspiration episode can then be integrated with explanations at other levels of analysis to produce a richer and more holistic understanding of inspiration. This deeper understanding will aid in determining how and why individuals sometimes feel (or do not feel) compelled to act on their creative ideas. Inspiration has the power to effect change not just for individuals, but also for societies. Technological advancements, cures for diseases, and solutions to environmental problems first emerge as promising ideas. It is difficult to overstate the importance of figuring out why, how, and for whom creative ideas to societal problems fire the soul and inspire the idea actualization process.

#### **ACKNOWLEDGMENTS**

This material is based on work supported by the National Science Foundation under Grant Number SBE-0830366, Science of Science and Innovation Policy.

#### **REFERENCES**

Amabile, T. M. (1996). *Creativity in Context.* Boulder, CO: Westview Press.

Amabile, T. M. (1982). Social psychology of creativity: a consensual assessment technique. *J. Pers. Soc. Psychol.* 43, 97–1013.

Finke, R. A., Ward, T. B., and Smith, S. M. (1992). *Creative Cognition: Theory, Research and Applications.* Cambridge, MA: MIT press.

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

*Received: 08 April 2014; accepted: 30 May 2014; published online: 25 June 2014*. *Citation: Oleynick VC, Thrash TM, LeFew MC, Moldovan EG and Kieffaber PD (2014) The scientific study of inspiration in the creative process: challenges and opportunities. Front. Hum. Neurosci. 8:436. doi: 10.3389/fnhum.2014.00436 This article was submitted to the journal Frontiers in Human Neuroscience*.

*Copyright © 2014 Oleynick, Thrash, LeFew, Moldovan and Kieffaber. This is an openaccess article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms*.

## The interplay between spontaneous and controlled processing in creative cognition

## **Leh Woon Mok \***

Department of Psychology, College of Healthcare Sciences, James Cook University, Townsville, QLD, Australia

#### **Edited by:**

Matthijs Baas, University of Amsterdam, Netherlands

**Reviewed by:** Hidenao Fukuyama, Kyoto

University, Japan Sietske Kleibeuker, Leiden University, Netherlands

#### **\*Correspondence:**

Leh Woon Mok, Department of Psychology, College of Healthcare Sciences, James Cook University, 1 James Cook Drive, Townsville, QLD 4811, Australia e-mail<EMAIL_ADDRESS>
Neural studies of creativity have yielded relatively little consistent results. For example, in functional neuroanatomical studies, the prefrontal cortex (PFC) has often been implicated as a critical neural substrate. However, results in electrophysiological (EEG) studies have been inconsistent as to the role of the PFC. EEG results have more often implicated widespread alpha synchronization, particularly in posterior regions, in creative cognition. Recent fMRI evidence has indicated that the PFC may be activated as a part of and together with other components of a deliberate control brain network. Controlled processing is neurologically dissociated from, but may co-occur with, spontaneous cognition mediated by a subset of the default-mode network (e.g., the angular gyrus [BA 39] in the posterior parietal cortex, which has been increasingly implicated in creative cognition). When the demand for controlled processing is substantially increased, default-mode processing may be suppressed. There is now preliminary evidence to suggest an association between alpha synchronization and default-mode processing. Creative cognition likely emerges from an optimal balance between spontaneous processing and controlled processing.

**Keywords: creativity, spontaneous cognition, angular gyrus, lateral posterior parietal cortex, default-mode network, deliberate control, prefrontal cortex, multiple-demand network**

The advent of neuroimaging methodologies in the last two decades has seen an increase in studies of creativity from a cognitive neuroscience perspective. However, there is hitherto relatively little evidence for a clear and consistent pattern of brain activity that is associated with creative information processing in general, or with a particular proposed stage of it (see e.g., Arden et al., 2010; Dietrich and Kanso, 2010; Kaufman et al., 2010; Sawyer, 2011). Recent cognitive neuroscience evidence has supported the role that a subset of the brain's default mode network (DMN) plays in spontaneous cognition (e.g., the angular gyrus, Brodmann Area [BA] 39, in the posterior parietal cortex; Mok, 2012). Default network activity may be suppressed when there is a substantial demand for controlled processing. However, spontaneous processing and controlled processing may co-occur. This article aims to highlight how these findings may be integrated with the existing creative cognition literature to offer a preliminary unifying perspective.

#### **INTEGRATION WITH EXISTING THEMES**

Neural studies of creativity have typically employed the standard, bipartite definition of creativity (Runco and Jaeger, 2012). Creativity is regarded as an ability that enables one to produce behavior or work that is *novel* and *useful*; useful creative behaviors and products would be appropriate and relevant to one's social context (e.g., Amabile, 1982; Sternberg and Lubart, 1999). The focus is to illuminate the neurocognitive operations that occur during the creative *process* (Kaufman et al., 2010). In experimental studies of creativity, tests of divergent thinking have been widely used. It has been reasoned that cognitive processes that give rise to creative ideas are more likely generative and divergent in nature, where the thinker searches in various directions, leading to numerous varied possibilities and possibly novel combinations. Commonly used tests of divergent thinking include variants of the Alternate Uses Test (AUT), which requires the respondent to selfgenerate as many alternative or unusual uses for common objects as possible such as a paper clip or a brick; and the Torrance Tests of Creative Thinking (TTCT; Torrance, 1974), which is a battery of standardized verbal and figural tests. Despite a relative lack of consistent results, functional neuroanatomical studies using functional magnetic resonance imaging (fMRI) or positron emission tomography (PET) have often implicated the prefrontal cortex (PFC) as a critical neuroanatomical substrate of divergent thinking (e.g., Folley and Park, 2005; Goel and Vartanian, 2005; see Dietrich and Kanso, 2010). The PFC has long been thought to play a critical role in top-down cognitive control (Miller and Cohen, 2001). It has, thus, been deemed essential for common cognitive functions such as working memory, attentional control, cognitive flexibility and cognitive evaluation, all of which are thought to be important to creative information processing (Dietrich, 2004). However, when brain electrical activity was measured using electroencephalography (EEG), the divergent thinking paradigm did not yield comparable results in frontal regions (see e.g., Dietrich and Kanso, 2010).

In another line of cognitive neuroscience research, it has been demonstrated that the PFC, especially the dorsolateral aspect, may be activated as a part of and together with other components of (what is now known as) the multiple-demand network1 (Duncan, 2006). This form of cognitive processing is more deliberately engaged, attention-demanding, controlled and goal-directed, and is neurologically dissociated from, but may be concurrently experienced with, more spontaneous cognition mediated by a subset of the brain's DMN (Mok, 2012). A default brain region that is particularly involved in spontaneous processing (e.g., spontaneous prospection) is the angular gyrus (BA 39) of the lateral posterior parietal cortex (LPPC), whether of events and experiences in the short-term (Mok, 2012) or the long-term (Andrews-Hana et al., 2010).

On a fundamental and individual level, real-life creative activities may be substantially facilitated by spontaneous cognition, mediated by a subset of the brain's DMN and operating in the background as our concentration on the outside world is relaxed. However, when one is more focused on meeting more explicit and deliberate response demands such as in a test or timed situation, the demand for controlled processing may substantially increase, leading to a suppression of default processing (Mok, 2012). The differentiation between two processing modes—spontaneous vs. deliberate—for creative cognition has also been addressed in Dietrich (2004). More recent evidence is converging to indicate that creative cognition emerges from everyday cognitive abilities (Sawyer, 2011). Productive creative cognition may likely be facilitated by a delicate balance between more spontaneous processing vs. more controlled processing, both of which may be experienced concurrently to the extent that default activity does not become suppressed due to a substantial demand for controlled processing (Mok, 2012). In the literature, terms such as daydreaming and mind-wandering (e.g., Dietrich, 2007; Sawyer, 2011) have been used to describe mental states conducive to creative cognition. Such states are known to be mediated by the brain's DMN. Default network activity increases when we are asleep or when we are undisturbed and left to ourselves to daydream and/or mindwander (Mason et al., 2007; Buckner et al., 2008). Default-mode processing reflects the brain's resting-state activity when our focus on the external environment is relaxed (Buckner et al., 2008). This corresponds to cognitive states described by disinhibition or relaxation of constraints (Dietrich, 2007; Kaufman et al., 2010) deemed to be facilitative of creativity.

Previously, in a PET study, BA 39 of the LPPC has been implicated in the performance of a verbal creativity task (Bechtereva et al., 2004). Participants generated a story using a difficult vs. an easy word list. The difficult list comprised remotely associated words, whereas the easy list comprised semantically-related words. Two other task conditions controlled for the syntactic vs. memory-related aspects of the task. When a task condition operationalized as requiring a greater degree of creativity to problem solve was contrasted against a task condition operationalized as requiring a lesser degree of creativity, at least a left BA 39 region within the LPPC (Cho, 2010) was implicated. A very recent fMRI study has also implicated the LPPC, including the angular gyrus, in creative cognition when participants generated alternate uses, as opposed to ordinary characteristics, for common objects (Kleibeuker et al., 2013). In a structural neuroanatomical MR study, a positive correlation has been found between cortical thickness in a right angular gyral region and self-reported real-life creative achievements (Jung et al., 2010).

The inconsistent pattern of results in neural studies of creativity has often been attributed to a lack of psychometrically sound assessment instruments and/or a definitional issue of the various concepts under investigation (e.g., Arden et al., 2010; Dietrich and Kanso, 2010). Below I outline two factors that may influence the observed results. A key aspect of the experimental tasks commonly used in neural studies of creativity such as those based on the AUT and the Torrance Tests is that they are administered in timed conditions, much like a test situation in which the participant may feel the stress of having their responses critically evaluated. Such external task demands may require more attention and control, leading to an increase in control network activity and a suppression of default network activity. Plucker and Makel (2010) have also raised concerns about a timed testing condition. Moreover, in an unpublished set of data, Mok and colleagues observed that the MR scanning environment such as the continuously loud scanner noise may lead to a decrease in size of experimental effects that are dependent on default network processing. To cope with the effect of environmental noise, there may be a greater demand for controlled processing, leading to a relative suppression of default network activity. These factors may contribute to why fMRI studies of creativity were in general rather consistent in implicating the PFC when timed tasks were used or when a study session felt like a test situation. Studies employing the EEG methodology with timed task administrations appeared to have yielded inconsistent results with regard to the role of frontal regions in creative cognition. The superior temporal resolution of the EEG methodology (1 ms, as opposed to 2 s for fMRI and 40 s for PET; Sawyer, 2011) may have afforded a greater potential to capture transient task-related activity such as default network activity, rather than possibly more persistent control network activity.

It is noteworthy that EEG studies have, in fact, been more consistent in showing that divergent thinking (measured by the AUT and/or the Torrance Tests) is associated with strong alpha activity and alpha synchronization, particularly in the parietal regions but also in the frontal and central regions (e.g., Fink et al., 2007, 2009a,b; Grabner et al., 2007). More recent studies employing simultaneous resting-state EEG/fMRI measurements have found a positive correlation between blood-oxygen-level dependent (BOLD) signals in components of the brain's DMN, including the LPPC, and global alpha power (Mantini et al., 2007) and global alpha synchronization (Jann et al., 2009), respectively. Global measures of alpha activity were based on all electrode sites (frontal, central, temporal and posterior channels). Mantini et al. (2007) additionally found global alpha power

1Components of the multiple-demand network include the presupplementary motor area, the inferior frontal sulcus and the lateral PFC around it [BA 9], the anterior insula and the intraparietal sulcus (Duncan, 2006). The multiple-demand network has been found to be activated in a wide range of cognitive activity, from working memory storage/manipulation, executive control to response selection (Woolgar et al., 2011).

to correlate negatively with an intrinsic connectivity network more involved in dorsal attention, which included the PFC. This line of research appears to provide preliminary support for an association between global alpha synchronization and a state of mind corresponding to the brain in default mode. In default mode, active processing in control, and related sensory and motor brain regions is depressed. This harks back to the traditional interpretation of alpha synchronization as reflective of "cortical idling" (Pfurtscheller et al., 1996). A modern interpretation of alpha synchronization may be that it is related to the brain's default-mode processing.

Caution should be exercised in interpreting event-related alpha synchronization (ERS) as reflective of an inhibitory or topdown control process (cf. Klimesch et al., 2007). For example, alpha ERS observed over a short memory delay (1800 ms) in a working memory scanning task (a modified Sternberg task) has been interpreted as evidence against cortical idling but reflective of inhibition of brain areas not being used in processing (Schack and Klimesch, 2002). On close scrutiny, delay-period memory processing in this task might have been more spontaneously experienced than deliberately engaged, for the possibility that the probe stimulus, presented after the delay, would be contained in the (memory) set of simple stimuli presented before the delay. Delay-period memory processing of an (easy to discern) identity match stimulus may be facilitated, at default processing levels, concurrently by an LPPC region (for a prospective perspective) and a hippocampal region (for a retrospective perspective; Mok et al., 2009; Mok, 2012). When the memory set size was increased, delay-period ERS over posterior regions was stronger (Jensen et al., 2002; Schack and Klimesch, 2002). Upon presentation of the probe, event-related alpha desynchronization was observed (Klimesch et al., 2007). Participants likely engaged deliberately in controlled processing as they responded to the probe.

Alpha activity has also been taken as reflective of active inhibition of external sensory information during mental imagery (e.g., Cooper et al., 2003). More recent fMRI results, however, have supported the core, modality-independent role of the DMN in mental imagery (e.g., Mok et al., 2009; Daselaar et al., 2010). Another paradox was the simultaneous synchronization and desynchronization of different alpha responses in a recognition memory task (Klimesch et al., 2000). While transient evoked alpha synchronization may be observed at parieto-occipital sites, widespread induced alpha desynchronization may be observed at most recording sites. More spontaneously experienced cognitive processing in the LPPC, a DMN region, may co-occur with more controlled processing (Mok, 2012). The EEG signature of this cooccurrence warrants further investigation, as does a more systematic evaluation of the functional significance of alpha activity in general for spontaneous cognition mediated by a subset of the DMN.

### **A PRELIMINARY UNIFYING PERSPECTIVE AND SOME DEFINITIONAL ISSUES**

As reviewed, the LPPC of the DMN is particularly involved in spontaneous cognition and it has increasingly been implicated in creative processing. Spontaneous processing in the LPPC is particularly of a prospective, or rather future-oriented, perspective. In the delay task used in Mok (2012), participants experienced spontaneous delay-period prospection of a cue-unique response outcome, mediated by the angular gyrus in the LPPC; there appeared to be individual differences in which hemisphere might be more involved. In accounting for semantic priming in cognitive psychology, the presentation of the prime stimulus that precedes the target stimulus has also been thought to initiate a prospective memory process, leading to spontaneous semantic spreading activation (Neely and Keefe, 1989). Divergent thought processes that underlie creative cognition, elicited by the initial stimulus of concern, may be quite similar in nature to spontaneous semantic spreading activation. Such thought processes allow one to access remote associates, which are important for the generation of novel possibilities and new associations (Kaufman et al., 2010). Functional neuroimaging studies have supported the role of the angular gyrus in a wide range of semantic tasks (e.g., Seghier et al., 2010). The subregion within the human angular gyrus most involved in spontaneous prospective memory processing at default activity level appears to be the posterior subdivision (PGp; Mok, 2012; Seghier, 2013).

The PFC activated as a part of a control network is wellpoised to facilitate the evaluation and judgment of the social appropriateness of a novel idea, and the implementation of goaldirected plans (Dietrich, 2004). These processes will likely tap into contextual knowledge/memory whether social, cultural or historical. Depending on the content being processed, additional circuitries may be activated, e.g., sensory-perceptual cortices and related neural regions (for sensory-perceptual content such as visual and/or auditory content), emotional and associated limbic regions (for affective content), motivational systems (for appetitive or aversive content), and motor-related regions (for motor content). If additional neurocognitive analysis is involved, other relevant neural circuitries may be activated. Affective and/or motivational processes may modulate the balance between the deliberate and spontaneous processing modes and the efficacy of semantic associative processes (e.g., Shemyakina and Dan'ko, 2004), influencing the quality of ideational complexity vs. the effectiveness of judgment and implementation processes.

Runco (2010) introduced the notion of *optimization* and argued that it allows simplicity and parsimony in conceptualizing and defining creativity. Productive creative cognition likely emerges from an optimal balance between deliberate and spontaneous cognition. Runco (2010) further suggested that there is a single capacity, rather than two where one is for originality of thought and the other is for judiciousness, that underlies creative processing. On a neurocognitive level, in the service of everyday activities, this single capacity would correspond to the capacity to achieve, on a moment to moment basis, optimal balance between control network activity and default network activity, and optimal coordination between these respective networks and other brain regions involved in content processing. Evaluative and judgmental processes would be optimized to the extent of one's understanding of the social, cultural and historical context. Morality and empathy, and how the social brain interacts with other components of the DMN (Mars et al., 2012) can potentially influence evaluative and judgmental processes and bear on eventual implementation of creative endeavors. The moment-to-moment optimization of spontaneous vs. controlled processing, whether the moment serves idea generation, verification or implementation (cf. Wallas, 1926), may be modulated by individual differences such as personality and intelligence. An empirical question is whether it would be more viable to define optimization relative to a selfnorm or a population norm.

Novel ideas are rare, or rather deviant from the norm (Runco, 2004). Thought processes such as divergence and free association that give rise to deviant ideas are productively creative only to the extent that they are optimal but not excessive (Runco, 2004). The concept of deviance can be applied to accommodate documented links between creativity and deviant neurocognitive processes that underlie certain mental disorders (Kaufman et al., 2010), altered states of consciousness such as those induced by drugs, meditation, or long-duration exercise (Dietrich, 2007), and the "dark-side" of creativity such as the creation of weapons of mass destruction. Creativity studies with a developmental perspective (cf. Kleibeuker et al., 2013) should consider the developmental trajectory of the DMN vs. the control network and their respective connectivity with other brain regions; and the transition from relatively non-symbolic, language-free, and possibly innate abilities existing in infancy to symbolic or language-dependent abilities that may be modifiable and can benefit from training.

#### **IMPLICATIONS FOR FUTURE RESEARCH AND PRACTICE**

To better measure default network activity, study sessions that feel like a test (e.g., with timed administrations) should be reconsidered. Study designs could bias participants toward different levels of creativity within-subject, carefully matching/controlling for as many of the other aspects of the experimental task as is possible. A concurrent-task design could allow for a better estimate of the relative levels of default network activity vs. control network activity. The potential influence of the MR scanning environment on default network suppression should also be systematically studied.

In the mainstream school system, the assessment of learning remains critical. A curricular emphasis on an end-product to be delivered by a certain deadline and its assessment as an outcome of learning may create a learning environment (akin to a test situation) that regularly heightens the brain's control activity and suppresses default activity. Class activities should not engender persistent suppression of default processing on the individual level. Instead, with appropriate structuring and scheduling, more opportunities could be provided for developing minds and brains to spontaneously experience default-mode processing. Learning environments could be designed to enhance and/or maintain relevant default network activity despite existing external task demands. An appropriate use of prime stimuli to initiate optimal spontaneous semantic spreading activation could be a good starting point.

#### **ACKNOWLEDGMENTS**

A preliminary version of this paper has been presented as a part of the symposium on "Creativity in psychological sciences: a cross-disciplinary dialogue" at the 25th Annual Convention of the Association for Psychological Science, Washington, D.C., USA, in May 2013.

#### **REFERENCES**

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

#### *Received: 27 January 2014; accepted: 09 August 2014; published online: 28 August 2014*.

*Citation: Mok LW (2014) The interplay between spontaneous and controlled processing in creative cognition. Front. Hum. Neurosci. 8:663. doi: 10.3389/fnhum.2014.00663 This article was submitted to the journal Frontiers in Human Neuroscience*.

*Copyright © 2014 Mok. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms*.

## Creative thinking as orchestrated by semantic processing vs. cognitive control brain networks

## **Anna Abraham\***

Department of Community Medicine and Behavioral Sciences, Faculty of Medicine, Kuwait University, Jabriya, Kuwait

#### **Edited by:**

Matthijs Baas, University of Amsterdam, Netherlands

#### **Reviewed by:**

Nathalie Boot, University of Amsterdam, Netherlands Andreas Fink, University of Graz, Austria

#### **\*Correspondence:**

Anna Abraham, Department of Community Medicine and Behavioral Sciences, Faculty of Medicine, Kuwait University, P. O. Box 24923, Safat 13110, Jabriya, Kuwait e-mail<EMAIL_ADDRESS>
Creativity is primarily investigated within the neuroscientific perspective as a unitary construct. While such an approach is beneficial when trying to infer the general picture regarding creativity and brain function, it is insufficient if the objective is to uncover the information processing brain mechanisms by which creativity occurs. As creative thinking emerges through the dynamic interplay between several cognitive processes, assessing the neural correlates of these operations would enable the development and characterization of an information processing framework from which to better understand this complex ability. This article focuses on two aspects of creative cognition that are central to generating original ideas. "Conceptual expansion" refers to the ability to widen one's conceptual structures to include unusual or novel associations, while "overcoming knowledge constraints" refers to our ability to override the constraining influence imposed by salient or pertinent knowledge when trying to be creative. Neuroimaging and neuropsychological evidence is presented to illustrate how semantic processing and cognitive control networks in the brain differentially modulate these critical facets of creative cognition.

**Keywords: creative cognition, divergent thinking, semantic cognition, cognitive control, inhibitory control, frontostriatal network, fronto-parietal network**

The interest in uncovering the brain mechanisms underlying creative thinking, or the ability to generate original yet relevant responses in a given context (Stein, 1953), has a lengthy scientific history that dates back at least to the 1940s (Reitman, 1947; Ashby and Bassett, 1949). The most influential issues that have guided investigations on creativity and brain function include enhanced creative ability following brain damage (Miller and Miller, 2013), the dominance of right over left hemisphere function in creative thinking (Mihov et al., 2010), and the brain basis of exceptional ability among experts in creative domains such as music, art and dance (Bengtsson et al., 2007). The general (although not necessarily unanimous) picture that emerges from the literature is that creative performance and/or ability is particularly associated with frontal lobe (FL) function (Dietrich and Kanso, 2010), higher right brain activity (Mihov et al., 2010), greater EEG alpha power which reflects high internal processing demands (Fink and Benedek, 2012), and that it can be inadvertently boosted as a consequence of specific types of brain damage (Seeley et al., 2008).

Such generalizations regarding creativity and brain function primarily arise from adopting a somewhat unitary approach in investigating creativity where it is assessed as an undifferentiated general construct, as opposed to process-differentiated one. This is customarily achieved by contrasting brain activity (neuroimaging or EEG studies) or behavioral performance (neuropsychological studies) during creative vs. non-creative tasks. Several researchers have critically addressed theoretical and methodological concerns that arise in the context of neuroscientific investigations of creative thinking, such as the inability to prompt creativity in a reliable or valid manner and the suboptimal nature of comparison tasks in creativity paradigms (Dietrich, 2007; Arden et al., 2010; Sawyer, 2011; Abraham, 2013). The advantage of a unitary approach is that it delivers the "big picture" regarding our creative brains. However, the unitary approach is too generalized, and hence insufficient, if the overarching aim is to uncover the neural and information processing mechanisms by which creativity occurs. As several cognitive operations work in unison when we are engaged in creative idea generation, adopting a "process" approach to creativity (Kozbelt et al., 2010) in investigating the brain correlates of these different operations would allow us to realize such an objective.

#### **COGNITIVE COMPONENTS OF CREATIVITY**

The Geneplore model of creativity (Ward et al., 1995; Finke et al., 1996; Ward et al., 1997), which sought to characterize the different mental operations that are involved during creative thinking, was driven by the process approach. Although diverse in nature, these operations were proposed to have two components in common. First, they involve the generation of potential ideas or "preinventive" structures (e.g., the analogical transfer of information from one domain to another). Second, this initial generation phase is followed by extensive exploration of these preinventive structures (e.g., search for conceptual limitations).

According to this model, the essential difference between creative and "non-creative" or normative cognition does not lie in the type of mental operations themselves, but in the contexts to which these information processing toolboxes are applied (Abraham, in press). The contexts or problem solving situations that prompt creative cognition (e.g., compose a haiku) are relatively more open-ended, ambiguous, non-linear, abstract and unpredictable compared to those that primarily necessitate normative cognition (e.g., devise a weekly exercise regime). Creative cognition can therefore be assessed by examining normative cognitive processes under explicitly generative conditions. In fact, a number of such mental operations have been described (**Figure 1**; Abraham and Windmann, 2007). These include the ability to broaden the framework of established conceptual structures (conceptual expansion), mental visualization during creative idea generation (creative imagery), the ability to surpass the constraining influence of recently activated knowledge (overcoming knowledge constraints), and the sudden occurrence of a solution during problem solving as a result of a fundamental perspective shift (insight). So, how do these operations work in combination with one another during creative idea generation?

Imagine the following scenario. You are asked to imagine new uses for a shoe, beyond the object's customary use of foot protection. Allow yourself a few minutes to carry out this task before reading further and make note of the uses you generate.

 As these familiar options are quickly exhausted, the task becomes increasingly cognitively demanding. While trying to come up with novel ideas, you probably generated mental images to explore a shoe's physical parameters in terms of weight, volume, dimensions, materials, type: stilettos vs. sneakers, and so on (creative imagery). During this process, it may have become apparent to you that a shoe can be used as a make-shift container (conceptual expansion) and that the brutally angled sole of a stiletto lends itself to different uses than the flat sole of a sneaker. While exploring potential uses for a shoe as a highly angled container in the case of a stiletto, you may inadvertently recollect uses that are closely related to those you have already generated, such as using the stiletto's heel to impale a spider, and you strive to inhibit this tendency to rehash known associations (overcoming knowledge constraints). Then, seemingly out of the blue, the different elements that are being explored suddenly come together in a novel manner while you undergo some form of an "aha-experience" (insight) as you become aware of this new use of, for instance, using a shoe as a hamster slide (**Figure 1**).1

The focus in the present opinion article will be limited to evaluating the similarities and differences in brain function that are associated with conceptual expansion and overcoming knowledge constraints as these operations have received little to no attention thus far within the literature, unlike the processes of insight (Kounios and Beeman, 2009; Dietrich and Kanso, 2010) and imagery (Farah, 1989; LeBoutillier and Marks, 2003; Bartolomeo, 2008).

## **CONCEPTUAL EXPANSION**

The ability to expand acquired conceptual structures to include novel elements is investigated in tasks that assess conceptual expansion (Ward, 1994). The original task involved having participants generate animals that lived on another planet that was very different from Earth. How far these alien creatures deviated from generic Earth animals in terms of the absence of typical features and the presence of atypical features was assessed. As this animal task cannot be optimally implemented in its original form for neuroimaging research, three alternative experimental paradigms were developed to assess conceptual expansion. These have now been implemented in fMRI (Abraham et al., 2012b; Kröger et al., 2012; Rutter et al., 2012b) and EEG settings (Rutter et al., 2012a; Kröger et al., 2013).

The paradigms were devised with the objective of uncovering the brain correlates of conceptual expansion. Brain regions that were commonly activated across all three paradigms would be considered to be reliably involved in creative conceptual expansion. Two approaches were adopted when developing these paradigms2 where one was devised to assess "active" conceptual expansion (Abraham et al., 2012b) while the other assessed "passive" conceptual expansion (Kröger et al., 2012; Rutter et al., 2012b). Participants shouldered the task of expanding the concepts themselves (generate novel uses for a newspaper) in the volitionally generated or active conceptual expansion paradigm. In contrast, during the involuntarily induced or passive conceptual expansion paradigms, participants were presented with object-use combinations (Shoe → Plant pot) or metaphors (The clouds danced over the city), to which they reported experiences of conceptual expansion. This occurred when they encountered an object-use combination or metaphor that was deemed by them to be both novel (previously unknown to them) and appropriate.

The brain regions that were found to be activated across all three paradigms were limited to the left hemisphere and included the anterior inferior frontal gyrus (IFG: BA 45/47), the temporal pole (TP: BA 38) and the lateral frontopolar cortex (FPC: BA 10). The IFG is central to semantic information processing in the brain (Bookheimer, 2002; Binder and Desai, 2011; Jefferies, 2013) with anterior aspects of this structure being involved in semantic selection and controlled semantic retrieval (Thompson-Schill, 2003; Badre and Wagner, 2007). The TP is also key structure of relevance in semantic cognition as it is widely held to underlie the domain-general or amodal repositories of conceptual knowledge of the brain (Lambon Ralph et al., 2009; Simmons and Martin, 2009). It is involved in the combination and integration of lexical representations to a context (Lau et al., 2008), as well as in the acquisition of new conceptual knowledge (Hoffman et al., 2014).

1This example is only presented for illustrative purposes to showcase differences between select cognitive operations during the creative act. As such, it not to be construed as a prototype that represents the manner in which the creative process typically unfolds. The list of selected operations is by no means exhaustive. Moreover, the occurrence, temporal order and interrelation between these operations would be expected to differ as a function of intraindividual, interindividual and contextual factors.

2The alternate uses task is widely employed in investigations of creativity where divergent thinking is assessed in terms of fluency or originality of the responses. Just as in studies of other facets of cognition, the same task can be implemented in different ways depending on the microlevel of study to allow for specific inferences to be made regarding creative function. Within the neurocognitive approach, the microlevel is centered on the brain correlates of the cognitive process. So the brain response when performing the alternate uses task is assessed relative to brain response when performing a closely matched control task that does not necessitate conceptual expansion, but nonetheless requires reasoning, fluency, semantic judgments, cognitive control, and so on.

The lateral FPC, in contrast, is held to mediate cognitive control at the most abstract level of information processing (Badre, 2008; Christoff et al., 2009) and plays a key role during relational reasoning (Christoff et al., 2001; Wendelken et al., 2008) as well as when combining information from two or more separate cognitive operations (Ramnani and Owen, 2004). Although the lateral FPC is not specifically limited to semantic aspects of information processing, both this brain region and the anterior IFG are sensitive to the degree of associative strength between concepts (Bunge et al., 2005; Green et al., 2010) with greater brain activity elicited by wider semantic distances.

To summarize, neuroimaging studies on conceptual expansion have revealed that brain structures (inferior frontal, temporopolar and frontopolar) that are collectively associated with the selection, controlled retrieval, combination and integration of semantic knowledge are preferentially more strongly engaged during creative conceptual expansion relative to other types of normative semantic information processing. Although nonverbal conceptual expansion has yet to be investigated in the same manner, the same brain network would be expected to be involved in conceptual expansion regardless of the stimulus type. This is because the use of verbal and non-verbal as well as semantic and non-semantic control tasks across the different paradigms revealed that the engagement of this network of brain regions during conceptual expansion cannot be merely attributed to verbal or semantic processing.

### **OVERCOMING KNOWLEDGE CONSTRAINTS**

The ability to override the hindering influence imposed by relevant but distracting information during creative idea generation (Smith et al., 1993) is referred to here as the process of overcoming knowledge constraints. In the original toy task that was devised to assess this operation, participants are asked to imagine and draw a novel toy that does not yet exist (previously/currently). But before they do so, they are shown examples of three novel toys that were generated by others. Unbeknownst to the participants, these novel toy examples were in actuality engineered by the experimenter to have three features in common. What is assessed after the participants generate their own responses is how many of these three elements are present in the participants' toy inventions. Higher scores reflect stronger incorporation of example elements, which in turn reflects a poorer ability to overcome knowledge constraints that were levied by a salient and distracting context.

Just as in the conceptual expansion task, the toy task cannot be optimally implemented in its original form for neuroimaging research. To date, no study has directly investigated the brain correlates of overcoming knowledge constraints during creative idea generation. Only two neuroimaging studies have an indirect bearing on this discussion where the opposite effect, of "cognitive stimulation" on creative problem solving upon being exposed to others' ideas, was assessed (Fink et al., 2010, 2012).

The behavioral findings indicated that prior exposure to common uses (generated by others) relative to no prior exposure, led to greater originality in self-generated uses. But this was not true with prior exposure to original uses. As Fink et al. (2012) did not assess the degree of similarity between self-generated vs. other-generated uses, it is not possible to speculate about how these two situations may have involved overcoming different types of knowledge constraints. When comparing the brain's response during idea generation following original-use-prior-exposure compared to no-prior-exposure or common-use-prior-exposure, heightened activity was found in the left posterior middle temporal gyrus (MTG). The posterior MTG is part of the brain's semantic system (Binder and Desai, 2011) and is held to underlie the "long-term storage of and access to information associated with lexical representations" which "serves as input to higher-order semantic processes" (Lau et al., 2008). If we were to presume that prior exposure to original ideas imposes more constraints on idea generation than no prior exposure to ideas, as has been suggested by behavioral research, one could postulate that posterior middle temporal regions are more actively recruited when having to overcome knowledge constraints.

Interestingly, neuropsychological evidence has demonstrated that damage to lateral parietal and temporal cortices (including the posterior MTG) is associated with poorer performance on the overcoming knowledge constraints toy task (Abraham et al., 2012a). Creative cognition was assessed in three neurological samples with lesions of the FL, basal ganglia (BG), or parietal-temporal lobe (PTL). The PTL group were significantly less adept at overcoming knowledge constraints, which is a pattern that fits with findings of semantic perseverative responses associated with this population, especially in the presence of semantic distractions (e.g., Corbett et al., 2011).

The BG and FL-POL (FL group with frontopolar/frontoorbital lesions) groups though were found to be better at overcoming knowledge constraints during creative idea generation compared to healthy control groups. This information processing advantage was very specific in that neither the BG group nor the FL-POL group displayed superior performance on any other aspect of creative cognition.

The BG together with the prefrontal cortex are part of the network in the brain that orchestrates executive function and cognitive control (Alexander et al., 1991; Robbins, 2007; Brocki et al., 2008). Within the prefrontal cortex, frontopolar regions underlie abstract cognitive control (Badre, 2008; Badre et al., 2009) while frontoorbital regions are associated with cognitive disinhibition (Cummings, 1993). BG lesions are accompanied by poor inhibitory control, marked inattention and increased distractibility (Fielding et al., 2006; Aron et al., 2007).

These factors would be advantageous in overcoming knowledge constraints as optimal performance on this task requires inhibiting salient information that is engineered such that increased effort must be expended to see past it. Having poor inhibitory control or being easily distractible would render one more capable of overcoming such constraints as one's attention is continually being involuntarily diverted away from any particular focus.

Further indirect support from this idea comes from a study on creative cognition in attention-deficit/hyperactivity disorder (ADHD) where adolescents with ADHD outperformed healthy matched control participants on the toy task (Abraham et al., 2006). Even within a sample of adults with chronic schizophrenia, a high degree of thought disorder symptoms (disorganization within the semantic content of thought) was associated with superior ability to overcome knowledge constraints on the toy task (Abraham et al., 2007). Indeed, both ADHD and schizophrenia are associated with dysfunctions of the fronto-striatal network in the brain (Robbins, 1990; Bradshaw and Sheppard, 2000; Robbins et al., 2012).

#### **CREATIVE COGNITION AND THE BRAIN**

The general picture that glimmers through when bringing together the findings from neuroscientific investigations of conceptual expansion and overcoming knowledge constraints during creative idea generation is that of a dynamic interplay between semantic processing and cognitive control networks in the brain.

Trying to conceive of an original idea necessarily involves broadening or expanding existing conceptual structures to include novel or previously unassociated features. When engaged in conceptual expansion, the brain's semantic processing network operates on overdrive, particularly the higher-order regions which mediate lexical selection, controlled retrieval, combination and integration processes. During this process of cogitation, when distracting but salient information threatens to throw a spanner in the works by hampering one's ability to generate truly original ideas, the cognitive control network of the brain storms into play to push these distractions out of one's mind. This can be done in one of two ways—by either inhibiting or ignoring this salient information.

Inhibiting or ignoring salient task-relevant information is in fact very difficult as our predictive brains are developed to be especially adept at efficient and effective goal-directed action (Bubic et al., 2010) and we are accustomed to operating in our daily lives within normative contexts where the distractions one may have to overcome can be unmistakably recognized and are not necessarily salient or relevant to the specific task at hand. Such distractions can therefore be (relatively speaking) easily ignored. During creative idea generation though, the distracting information can be exceedingly pertinent to the task at hand and cannot therefore go unheeded in the same manner. Under such conditions, imbalances within the fronto-striatal network seem to confer specific advantages in creative cognition, possibly owing to the manifestation of cognitive disinhibition and increased distractibility, which would allow for a greater ease in disregarding salient semantic distractors.

### **CONCLUSIONS**

The objective of this article was to outline the potential neurocognitive mechanisms that underlie two vital aspects of creative cognition—conceptual expansion and overcoming knowledge constraints—based on neuroscientific findings that adopted a process approach to investigate the same. What was highlighted was the role of the semantic processing and cognitive control networks in the brain during creative idea generation. These insights can help inform and guide future neuroscientific investigations on creativity as well as aid in the development of more detailed and targeted information processing models of creative neurocognition. Promising future directions for exploration include the impact of training-induced plasticity effects on different aspects of creative neurocognition as well as uncovering the association between information processing biases in creative cognition with reference to variability that is manifest in real world creativity.

#### **ACKNOWLEDGMENTS**

This work was supported by an academic mission grant from Kuwait University.

### **REFERENCES**

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

*Received: 01 December 2013; accepted: 08 February 2014; published online: 24 February 2014*.

*Citation: Abraham A (2014) Creative thinking as orchestrated by semantic processing vs. cognitive control brain networks. Front. Hum. Neurosci. 8:95. doi: 10.3389/fnhum.2014.00095*

*This article was submitted to the journal Frontiers in Human Neuroscience*.

*Copyright © 2014 Abraham. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms*.

## The time-course of EEG alpha power changes in creative ideation

## **Daniela Schwab, Mathias Benedek , Ilona Papousek , Elisabeth M. Weiss and Andreas Fink \***

Institute of Psychology, University of Graz, Graz, Austria

#### **Edited by:**

Bernard Arjan Nijstad, University of Groningen, Netherlands

#### **Reviewed by:**

Marzia De Lucia, Center for Biomedical Imaging (CIBM), Lausanne University Hoapital, Switzerland Nathalie Boot, University of Amsterdam, Netherlands

#### **\*Correspondence:**

Andreas Fink, Institute of Psychology, University of Graz, Universitaetsplatz 2/III, A-8010 Graz, Austria e-mail<EMAIL_ADDRESS>website: http://www.uni-graz.at/ biologicalpsychology/

Increases in EEG alpha power during creative ideation are among the most consistent findings in the neuroscientific study of creativity, but existing studies did not focus on time-related changes of EEG alpha activity patterns during the process of creative ideation so far. Since several cognitive processes are involved in the generation of creative ideas, different EEG correlates may result as a function of time. In this study we addressed this crucial point. Forty-five participants worked on the "Alternative Uses Task" while the EEG was recorded and changes in task-related power (relative to rest) in the upper-frequency band (10–12 Hz) for three isochronous time intervals of the idea generation period were determined. Alpha power changes during idea generation followed a characteristic time course: we found a general increase of alpha power at the beginning of idea generation that was followed by a decrease and finally by a re-increase of alpha prior to responding that was most pronounced at parietal and temporal sites of the right hemisphere. Additionally, the production of more original ideas was accompanied by increasing hemispheric asymmetry (more alpha in the right than left hemisphere) with increasing duration of the idea generation period. The observed time course of brain activity may reflect the progression of different but well-known stages in the idea generation process: that is the initial retrieval of common and old ideas followed by the actual generation of novel and more creative ideas by overcoming typical responses through processes of mental simulation and imagination.

#### **Keywords: EEG, alpha power, creative ideation, divergent thinking, time-course**

Research on creativity—commonly defined as "the ability to produce work that is both novel and appropriate" (Sternberg and Lubart, 1996, p. 677)—has recently attracted great attention in psychology and particularly in the field of neuroscience. It is often dated back to Guilford's well-known presidential address at the American Psychological Association, where he highlighted the crucial importance of research on creativity which has been neglected for a comparatively long period of time (Guilford, 1950). Since then, creativity as a research topic has become more and more popular and has been addressed in various scientific disciplines by adopting a broad variety of different perspectives and methodological approaches (cf. Simonton, 2000; Runco, 2004).

The underlying neural basis of creative cognition is a major area of interest in creativity research. Based on the conceptualization of creative thought as the combination or interplay of different cognitive processes (e.g., Guilford, 1950), it is unlikely that there is just one "center of creativity" in the brain (cf. Dietrich, 2004). To come up with a creative idea, people need to be aware of a certain problem, to be able to analyze the situation and to redefine it. Then, possible alternatives or solutions resulting from cognitive processes such as flexible thinking have to be developed and are finally needed to be evaluated (cf. Guilford, 1950). Moreover, the generation of a novel idea is thought to involve the meaningful recombination of previously unrelated semantic concepts or frames of thought (Mednick, 1962; Koestler, 1964; Benedek et al., 2012). Thus, various cognitive processes such as attention, memory retrieval, working memory etc. could be considered as being crucially involved in the idea generation process. In this particular context it is hypothesized that the same combination of neural networks that is recruited in non-creative cognition (e.g., working memory) is implicated in creative cognition as well (e.g., Cabeza and Nyberg, 2000; Dietrich, 2004).

As a consequence of the broad variety of different approaches and methods that were used to investigate creativity, previous findings on neural correlates of creativity have been heterogeneous and often inconsistent (cf. Arden et al., 2010; Dietrich and Kanso, 2010). In reviewing relevant findings in this field, Dietrich and Kanso (2010) concluded that the results differ widely because of the diversity of possible assessments of creativity, including varying research foci (divergent thinking, artistic creativity, problem solving with insight) and neuroscientific methods (e.g., EEG, fMRI). Fink and Benedek (2012) suggested that comparing findings across different studies might be more reasonable by specifically looking at studies in which similar tasks and measurement methods were used. In doing so, Fink and Benedek (2012) reviewed EEG studies which specifically focused on the relationship between creative ideation (i.e., divergent thinking) and power in the alpha frequency band (8–12 Hz). Their review revealed robust evidence of EEG alpha power being particularly sensitive to various creativity-related demands: alpha power varies as a function of creativity-related task demands (the more creative a task the higher the level of alpha), as a function of originality (higher originality is accompanied by more alpha), and as a function of an individuals' creativity level (more alpha in higher creative individuals, see Fink and Benedek, 2012, 2013). Additionally, alpha power has also been observed to increase as a result of verbal creativity interventions (Fink et al., 2006, 2011). On the basis of these findings Fink and Benedek (2012) concluded that the observed alpha findings are among the most consistent findings in the neuroscientific study of creativity, and we might therefore assume that the study of alpha power changes is a valuable and powerful tool to study brain activity patterns during the process of creative idea generation. Traditionally, increases in EEG alpha power (hereinafter referred to as alpha synchronization) have been interpreted as sign of "cortical idling" (cf., Pfurtscheller et al., 1996). More recent studies suggested that alpha synchronization may indicate a state of high internal processing demands that are characterized by "the absence of bottom-up processing (Ray and Cole, 1985; Cooper et al., 2003) and thus can be classified a pure form of top-down activity" (von Stein and Sarnthein, 2000, p.311). This top-down process may have an attentional control function leading to inhibition of task-irrelevant stimuli (Klimesch et al., 2007). Therefore, alpha synchronization is probably associated with selective and active cognitive processing (Sauseng et al., 2005).

Alpha synchronization observed during creative ideation, which has consistently been observed over the prefrontal and temporo-parietal cortex (Fink and Benedek, 2012), may also reflect active cognitive processing and focused internal attention (Fink et al., 2009a; Benedek et al., 2011; Fink and Benedek, 2012; Jauk et al., 2013). Finding a creative solution requires effective memory retrieval and effective working memory processing for knowledge modulation (activation, inhibition and combination of knowledge; see e.g., Heilman et al., 2003; Dietrich, 2004). In addition, alpha synchronization at parietal sites of the right hemisphere seems to play an important role in creating ideas with high originality. In previous studies, stronger alpha synchronization at right parietal sites was found in higher creative individuals compared to less creative individuals (e.g., Martindale and Hines, 1975; Jaušovec, 2000; Razumnikova, 2007; Fink et al., 2009a,b).

Besides neuroscientific research on creativity, theoretical models were postulated to describe creative cognition and its possible stages or phases. The number of phases that are assumed as being implicated in the creative process vary (e.g., Wallas, 1926; Finke et al., 1992; Csikszentmihalyi, 1996). Exemplarily, in the "Geneplore" model two phases are hypothesized (Finke et al., 1992). According to this model, creative cognition is considered as the result of processing in circuits that consist of (reoccurring) generative and exploratory phases (Finke et al., 1992). The authors assume that idea generation starts with the construction of mental representations (generative phase) followed by interpretation and modification processes (exploratory phase). Other models propose four (preparation, incubation, illumination and verification; Wallas, 1926) or even five stages (preparation, incubation, insight, evaluation and elaboration; Csikszentmihalyi, 1996).

There were also attempts to examine the different strategies and cognitive processes involved in divergent thinking (i.e., creative idea generation) tasks. Gilhooly et al. (2007) performed a verbal protocol analysis of the alternate uses task (i.e., a common divergent thinking task that requires to generate creative new uses for common objects) and categorized the processes reported during the task. The study revealed that initial ideas were largely based on the retrieval of known uses from memory, whereas later ideas were based on more complex strategies such as focusing on specific object properties or using imagery (cf. Benedek et al., 2014a). As a result, ideas are generally observed to become more creative over time (e.g., Beaty and Silvia, 2012; Benedek and Neubauer, 2013). It was proposed that the generation of creative ideas involves executive processes such as prepotent response inhibition in order to overcome initial dominant responses and to provide top-down control of attention during strategic semantic search processes (Gilhooly et al., 2007; Beaty and Silvia, 2012; Benedek et al., 2012). This notion is further substantiated by studies reporting a close link of divergent thinking ability with higher-order cognitive ability (Nusbaum and Silvia, 2011; Beaty and Silvia, 2013; Jauk et al., 2013, 2014).

Until now, there is only very little evidence on the timecourse of creativity-related processes on the neurophysiological level. Studies which investigated neural correlates of insightful problem solving (i.e., problem solving accompanied by subjective experience of insight or the "AHA moment") reported an increase of alpha power at parietal and temporal sites of the right hemisphere shortly before solving tasks with insight (Jung-Beeman et al., 2004; Kounios et al., 2006; Sandkühler and Bhattacharya, 2008; Sheth et al., 2009). Time-related neural responses during the process of creative ideation (i.e., the generation of creative ideas) are yet unknown.

The aim of this study was therefore to investigate the timecourse of EEG alpha power during the process of creative ideation. Theoretical accounts assume the involvement of different phases or processes in creative idea generation (e.g., Wallas, 1926; Finke et al., 1992; Csikszentmihalyi, 1996), which is why we expect different patterns of EEG alpha power as a function of time. In order to address this question we reanalyzed a recent EEG study of our laboratory in which alpha power activity during idea generation was investigated (Fink et al., 2011). In that study participants were required to generate alternative uses to everyday objects (i.e., AU task) after being stimulated via affective and cognitive interventions, whereas during the control condition they performed the task without any intervention. As a measure of brain activity, only alpha power during the entire idea generation period was quantified. In the present study we focused on the time course of alpha power during different phases of idea generation. Therefore we determined alpha power estimates for three subsequent time intervals within the idea generation period of the AU task in order to get first insights whether or to which extent alpha power during creative ideation changes as a function of time. Based on recent evidence on the relationship between alpha power and creative ideation (Fink and Benedek, 2012), we expected time-related alterations of alpha power at prefrontal as well as over parietal and temporal sites (of the right hemisphere) as a possible indication of varying demands on memory retrieval and working memory processing during the process of idea generation. In addition, we also investigated whether ideas of varying originality show different time-related changes of EEG alpha power. Recent research revealed that alpha power at right parietal sites may be important in originality (Fink and Benedek, 2012), and given the manifold cognitive processes that are required to generate originality, we expected that the association between alpha power and originality may also vary as a function of time.

### **METHOD**

#### **PARTICIPANTS**

Forty-eight students participated in the study (cf. Fink et al., 2011). Three participants had to be excluded from data analyses due to technical problems during EEG recording. The final sample included 45 participants (22 women, 23 men) aged 18 to 32 years (*M* = 23.09, *SD* = 3.48). They were right-handed as assessed by a standardized handedness test (Steingrüber and Lienert, 1971; Papousek and Schulter, 1999). The participants indicated no history of medical, psychiatric or neurological disorders or treatment that could have interfered with any of the behavioral and neurophysiological measures. This study was approved by the local ethics committee of the University of Graz.

#### **TASK AND PROCEDURE**

Participants worked on the Alternative Uses (AU) task (cf. Wilson et al., 1953; Fink et al., 2007) while the EEG was measured. In the AU conventional everyday objects such as "shoes" or "toothpaste" were presented on the screen, and participants were instructed to come up with original and unconventional uses for these objects. Participants worked on three different experimental conditions, each of them consisting of 15 items. In two experimental conditions participants were stimulated via brief cognitive and affective intervention during idea generation (see Fink et al., 2011) while in the control condition no intervention was applied. The data presented in this paper are based on the 15 AU items of the control condition. At the beginning, two 2 min EEG sequences under resting conditions were recorded, the first with eyes closed, the second with eyes open. Before EEG recording, participants were carefully instructed how to perform the AU task.

The AU task started with the presentation of a fixation cross for the duration of 10 s (reference period, see **Figure 1**). Then the stimulus word (everyday object) appeared for 4 s on the screen. Subsequently, a white question mark appeared on the screen, indicating that participants had to think about useful and original ideas for the given stimulus for a time period of 10 s (idea generation period). Afterwards, the question mark changed its color into green signalizing the participants to articulate their idea within a time period of 4 s. For further analysis, the oral responses were recorded and transcribed (cf., Fink et al., 2007). At the end of each trial, participants were asked to evaluate their response either as "original" or "not original" via mouse click on the corresponding choice box on the screen. Then the next trial started. The presentation of the AU stimuli during EEG recording was fully randomized.

#### **ANALYSIS OF AU PERFORMANCE DATA**

Originality of creative idea generation in the AU task was assessed via self-rating and external ratings (Fink et al., 2007; Benedek et al., 2013). For the external ratings, nine experienced raters were instructed to judge the originality of each response of a participant on a five-point rating scale ranging from 1 ("highly original") to 5 ("not original at all"). Inter-rater agreement was satisfactory (*intra-class correlation coefficient* = 0.76). The ratings for each response were averaged over raters to obtain a measure of idea originality. For each participant, we then divided (via median-split) the total number of ideas into trials in which more vs. less original ideas (assessed via external ratings) were generated. This distinction was used as a within-subjects factor in further analysis. A paired samples *t*-test (*t*44 = 24.28; *p* < 0.001; *M*less original ideas = 3.54, *M*more original ideas = 2.66) revealed that the average score of more original ideas was significantly lower (denoting higher originality) than the average score of less original ideas.

#### **EEG DATA RECORDING AND ANALYSIS**

The EEG was measured with a BrainVision BrainAmp Research Amplifier (Brain Products) with Ag/AgCl electrodes and a stretchable electrode cap from the following 19 positions after the international 10–20 system (Jasper, 1958): FP1, FP2, F3, F7, F*Z*, F4, F8, T7, C3, C*Z*, C4, T8, P7, P3, P*Z*, P4, P8, O1, O2. The midline electrodes (F*Z*, C*Z*, P*Z*) were not included in the statistical analysis (given that we were also interested in potential hemispheric differences). The ground electrode was located at FP*Z*, the reference electrode was placed on the nose. To register eye movements, an electrooculogram (EOG) was recorded bipolarly between two electrodes diagonally placed above and below the inner and the outer canthus of the right eye. The EEG signals were filtered between 0.1 Hz and 100 Hz. An additional 50 Hz notch filter was applied. Electrode impedances were kept below 5 kΩ for the EEG and below 10 kΩ for the EOG. All signals were sampled at a frequency of 500 Hz.

EEG data were preprocessed by removing drifts and low pass filtering (50 Hz). The data were visually inspected for artifacts and artifactual epochs caused by muscle tension, eye blinks or eye movements were excluded from further analyses. Also, only trials with a valid answer were included in statistical analysis. In a next step, EEG signals were filtered by applying an FFT filter for the upper alpha frequency band (10 and 12 Hz). Power estimates were obtained by squaring filtered EEG signals, and then band power values (µV 2 ) were (horizontally) averaged for each single trial.

As in previous studies (e.g., Fink et al., 2009a, 2011), we quantified task-related power (TRP) changes in the upper alpha band during creative ideation. In computing TRP, 8 s time segments (out of 10 s) in the middle of the reference period (starting 1 s after the onset of the fixation cross) as well as the 8 s segment in the middle of the activation period (starting 1 s after the onset of the white question mark, cf. **Figure 1**) were

**FIGURE 1 | Overview of experimental task and measurement intervals**. Each AU trial started with a fixation cross for the duration of 10 s (reference period) before the stimulus word appeared for 4 s on the screen. During the presentation of the white question mark participants had to think about useful and original ideas for the stimulus for a time period of 10 s (activation period). Subsequently, the question mark changed its color into green and the participants had to articulate their most original idea within 4 s. Finally, participants were asked to evaluate their response either as "original" or "not original" via mouse click on the corresponding choice box on the screen (figure adapted from Fink et al., 2011).

used. The TRP for each electrode position (i) was computed according to the formula: TRP(logPow*i*) = log [Pow*i* activation] − log [Pow*i* reference] (Pfurtscheller, 1999). That means that the (logtransformed) power during the reference period (fixation cross) was subtracted from the (log-transformed) power during the activation period (creative ideation). Hence, increases in power from the reference to the activation period are reflected in positive values (i.e., referred to as alpha synchronization) whereas negative values indicate decreases in power (i.e., desynchronization). To investigate the time-course of TRP the 8-s idea generation intervals were splitted into three isochronous time intervals of 2.67 s each.

TRP values were analyzed using repeated measurement ANOVA in considering the factors ORIGINALITY (more vs. less original ideas), TIME (interval 1 [1–3.67 s], interval 2 [3.67– 6.33 s], interval 3 [6.33–9 s]), HEMISPHERE (left vs. right), and POSITION (eight positions in each hemisphere) as withinsubjects variables. *Post-hoc* pairwise comparisons were performed using Tukey's HSD. In case of violations of sphericity assumptions, the multivariate approach to the repeated measurements variables was used (Vasey and Thayer, 1987) and Bonferroni *post-hoc* tests (for ε < 0.70) were used.

### **RESULTS**

The ANOVA yielded significant main effects of TIME (*F*2,88 = 6.81, *p* < 0.00, η 2 *p* = 0.13), HEMISPHERE (*F*1,44 = 24.68, *p* < 0.00, η 2 *p* = 0.36) and POSITION (*F*7,38 = 2.90, *p* < 0.01, η 2 *p* = 0.11) as well as significant interaction effects of TIME ∗ HEMISPHERE (*F*2,88 = 17.70, *p* < 0.00, η 2 *p* = 0.29, TIME ∗ POSITION (*F*14,31 = 2.48, *p* < 0.02, η 2 *p* = 0.08), HEMI SPHERE ∗ POSITION (*F*7,38 = 4.95, *p* < 0.00, η 2 *p* = 0.13) and TIME ∗ HEMISPHERE ∗ POSITION (*F*14,31 = 2.63, *p* < 0.01, η 2 *p* = 0.07).

Alpha synchronization was stronger in the right than in the left hemisphere, a finding that was most pronounced at frontocentral and posterior cortical sites. Regarding the time-course of creative ideation, a characteristic trend of TRP was observed: as depicted in **Figure 2**, comparatively strong alpha synchronization occurred in the first time interval of idea generation.

Then, alpha power decreased (and mostly desynchronized) during the middle time segment of the idea generation period, especially over left frontal, temporal and parietal sites. In the last time interval, alpha synchronization increased again, particularly at right-hemispheric sites (see **Figure 2**). With respect to idea originality, two significant interaction effects emerged: ORIGINALITY ∗ HEMISPHERE (*F*1,44 = 4.35, *p* < 0.05, η 2 *p* = 0.09) and ORIGINALITY ∗ TIME ∗ HEMISPHERE (*F*2,88 = 3.10, *p* < 0.05, η 2 *p* = 0.07). The generally stronger increase in TRP in the right hemisphere was more pronounced for trials with more (vs. less) original ideas. The three-way interaction between originality, time and hemisphere is shown in **Figure 3**. During the first time interval both more and less original ideas were associated with comparatively strong alpha synchronization, similarly for both hemispheres. In the second time interval, more original ideas were associated with hemispheric asymmetry in alpha synchronization, with more TRP at right-than left-hemispheric sites. Interestingly, this asymmetry even increased at the third time interval of the idea generation period.

### **DISCUSSION**

The findings of this study suggest that the process of creative ideation is characterized by a distinctive pattern of task-related EEG alpha power changes as a function of time. Specifically, the findings revealed a rather strong increase of alpha power at the beginning of idea generation, followed by a decrease in the middle time interval and a final re-increase of alpha that was confined to the right hemisphere. The time-course of creative ideation was also accompanied by a clear-cut pattern of increasing hemispheric lateralization: at left-hemispheric sites, alpha TRP showed a steady decline over time, whereas in the right hemisphere alpha TRP rather seemed to follow a U-shaped function. Moreover, we found significant effects related to the originality of ideas: while at the beginning of idea generation virtually no differences between more vs. less original ideas were found, at later time intervals more original ideas were associated with increases in right-, relative to left-hemispheric alpha power.

The idea generation task was preceded by a period of stimulus presentation in which the given stimulus (i.e., AU item) was read and encoded. After that, the actual idea generation took place. The initial phase of creative idea generation is typically characterized by the retrieval of dominant responses from memory such as common uses for the presented objects (Gilhooly et al., 2007; Benedek et al., 2014a). Alpha band activity is thought to be related to the controlled access and retrieval from memory (Klimesch et al., 2007; Klimesch, 2012), and this process has not been associated with hemispheric lateralization of alpha power, or, if any, with a tendency for a left-over-right difference (Klimesch et al., 1999). It appears thus reasonable to assume that the initial pattern of bilateral alpha synchronization indicates the typical first phase during idea generation, namely the recall of common ideas from memory. After this initial process of creative idea generation, a general relative decrease of alpha power was observed and also a beginning hemispheric lateralization, as this decrease was less pronounced at right-hemispheric cortical sites. This lateralization then further increased in the last time-interval, driven by a reincrease of right-hemispheric TRP that was most pronounced at frontal and posterior cortical sites. Alpha synchronization over the right posterior cortex has been observed as being specific for creative thought (Fink et al., 2009a,b; Benedek et al., 2011; Jauk et al., 2012) and has been interpreted as a sign of focused internally-directed attention in order to facilitate imaginative processes during creative thought (Benedek et al., 2011; Fink and Benedek, 2012, 2013). In the context of our findings, the middle time-interval may represent a stage of the creative process during which basic retrieval from memory is increasingly receding (as indicated by reduced bilateral alpha synchronization), at the same time paving the way for more creative, imaginative thought processes. The latter would require directed and specific memory search in semantic networks, probably mediated by alpha desynchronization over left frontal, temporal and parietal sites, accompanied by a diffuse pattern of alpha synchronization over right-hemispheric regions. For example, Jensen et al. (2002) reported a strong alpha synchronization at posterior sites of the right-hemisphere especially at the end of working on a working memory task and stated "*that the tight temporal regulation of alpha provide strong evidence that the alpha generation system is directly or indirectly linked to the circuits responsible for working memory (p.877)"*.  These processes may be especially sensitive to interference from distracting irrelevant external stimulation and thus be accompanied by an even stronger right-hemispheric EEG alpha synchronization reflecting a process of task shielding (Jensen et al., 2002; Benedek et al., 2014b).

Most strikingly, the described pattern of results was more pronounced in higher original ideas compared to less original ideas (see **Figure 3**). A stronger alpha synchronization at righthemispheric sites for higher (vs. less) original individuals or ideas has been previously reported (e.g., Grabner et al., 2007; Fink et al., 2009a). Our study extends previously reported findings (Grabner et al., 2007; Fink et al., 2009a) since we included the aspect of time-course of idea generation. Regarding the earlier increase of alpha synchronization at right-hemispheric sites for higher original ideas, we assume that ideas of high quality require the same neural circuits and mechanisms than less original ideas, but probably in a more efficient manner, as indicated by an earlier and stronger increase in alpha synchronization of right-hemispheric sites compared to ideas of lower originality. For ideas of lower originality there is also an increase in alpha synchronization of right-hemispheric sites but only in the third time interval and the underlying idea generation process seems to be less advanced compared to ideas with higher idea originality. The resulting ideas might not be as elaborated as the more original ideas and are consequently rated as less original. This finding could thus be seen as additional support for the proposed interpretation of the EEG results.

As aforementioned, the present study is a re-analyses of a previous study of our laboratory (Fink et al., 2011). Therein, participants had to work on the AU task after being stimulated via affective and cognitive interventions and without any intervention. The analyses presented in this paper are based only on the trials of the control condition (i.e., without any intervention), and in this particular context we cannot completely rule out the possibility of spill-over effects (i.e., it may be possible that the interventions of the two other conditions may also have an unsystematic impact on the trials of the control condition). However, even though such kind of effects could possibly exist, it seems less likely that they were systematic since the trials were presented in a fully randomized order. Also, we cannot completely rule out the possibility that participants thought of more than one idea. However, behavioral analyses of idea fluency in this task showed that the average number of ideas within one minute is 4 (Benedek et al., 2013). As a consequence, a 10-s task should not elicit much more than 1 idea—particularly in view of the effect that participants were instructed to produce as original ideas as possible (i.e., instruction stressed quality, rather than fluency of ideas). We concede that people may still initially generate a dominant, typical response which is, however, rejected for the sake of finding creative ideas (Gilhooly et al., 2007). The brain activation related to such an initial response tendency was discussed to be associated with the earliest time epoch during idea generation. In addition, the analysis included the comparison of brain activity patterns associated with more vs. less original ideas which allowed for stronger and more powerful conclusions about the time-course of alpha activity during the process of creative idea generation.

To summarize, this study provides first insights into the timecourse of creative ideation from the neuroscience perspective. In investigating task-related alpha power changes during creative idea generation we were able to describe some of the manifold cognitive processes implicated in the process of creative idea generation at the level of brain. As the findings of this suggest, the observed time course of alpha activity may reflect the progression of different stages in the process of idea generation: the idea generation process showed an initial bilateral alpha synchronization followed by a relative decrease in alpha power and an increasing hemispheric lateralization driven by a re-increase of alpha power at right frontal and posterior cortical sites. This is an entirely novel finding and it is proposed that the distinctive patterns of task-related alpha activity as a function of time reflect the sequence of well-known stages of the creative idea generation process: that is the initial retrieval of common and old ideas, followed by the actual generation of novel and more creative ideas by overcoming typical responses through processes of mental simulation and imagination (Gilhooly et al., 2007; Fink et al., 2009a; Benedek et al., 2011, 2014b; Fink and Benedek, 2012, 2013; Jauk et al., 2012).

## **ACKNOWLEDGMENTS**

The authors wish to express their large gratitude to Ellen Hofer and Natascha Pichler for their valuable help in data collection.

### **REFERENCES**

during top-down processing in a working memory task. *Hum. Brain Mapp.* 26, 148–155. doi: 10.1002/hbm.20150

Steingrüber, H., and Lienert, G. (1971). *Hand-Dominanz-Test.* Göttingen: Hogrefe.

Wallas, G. (1926). *Art of Thought.* New York: Harcourt, Brace and Company.

Wilson, R. C., Guilford, J. P., and Christensen, P. R. (1953). The measurement of individual differences in originality. *Psychol. Bull.* 50, 362–370. doi: 10. 1037/h0060857

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

*Received: 07 February 2014; accepted: 27 April 2014; published online: 13 May 2014*. *Citation: Schwab D, Benedek M, Papousek I, Weiss EM and Fink A (2014) The timecourse of EEG alpha power changes in creative ideation. Front. Hum. Neurosci. 8:310. doi: 10.3389/fnhum.2014.00310*

*This article was submitted to the journal Frontiers in Human Neuroscience*.