Creativity as Flexible Cognitive Control - Psychology Today

Psychology of Aesthetics, Creativity, and the Arts 2010, Vol. 4, No. 3, 136 –143

© 2010 American Psychological Association 1931-3896/10/$12.00 DOI: 10.1037/a0017379

Creativity as Flexible Cognitive Control Darya L. Zabelina and Michael D. Robinson North Dakota State University Creative individuals have been described in terms suggestive of greater automatic processing (e.g., defocused attention, looser associations) and greater controlled processing (e.g., greater abilities to focus while working on a creative task). Both views cannot be correct from a static ability-related perspective. On the other hand, both views could be correct if creative individuals are better able to modulate the functioning of their cognitive control system in a context-sensitive manner. The present study (N ⫽ 50) assessed individual differences in creativity in terms of original responses on the Torrance Test of Creative Thinking (Torrance, 1974) and also in terms of creative behavior on the Creative Achievement Questionnaire (Carson, Peterson, & Higgins, 2005). The same participants performed a color–word Stroop task. Creative individuals were neither more nor less capable of overriding cognitive conflicts on incongruent (relative to congruent) Stroop trials. On the other hand, creative individuals displayed more flexible cognitive control, as defined by greater cognitive control modulation from trial to trial. Implications for theories of creativity and its underlying processing basis are discussed. Keywords: creativity, cognition, Stroop, automaticity, control

is more creative would utilize the cognitive control circuits of the brain to transcend mundane overlearned associations (Miller & Cohen, 2001). On the basis of such theories and sources of data, should lower or higher levels of cognitive control facilitate creative thinking and behavior? We contend that there appears to be no easy answer to this question. On the one hand, lower levels of cognitive control may facilitate the sorts of associative processes long viewed as important to creative thinking. On the other hand, individuals prone to automatic processing are likely to perseverate in their thinking, resulting in lower levels of creativity. In the present study, we sought to inform such discrepant views of creativity by attempting to link individual differences in Stroop costs—a classic measure of cognitive control ability (MacLeod, 1991)—to creative performance. Of more importance, we assessed individual differences in the flexibility of cognitive control, which we hypothesized would be of greater predictive value in differentiating creative versus noncreative individuals.

Although both automatic and controlled processes seem to characterize creative thinking in some uncertain combination, theories of creativity tend to emphasize one or the other somewhat exclusively. Psychodynamic theories of creativity tout the value of reliance on more primitive, primary-process thinking as a source of creative insight and production (e.g., Kris, 1952). Gardner (1982) has similarly suggested that creative thinking is childlike in nature and presumably spontaneous and automatic for this reason. A particular sort of theory of this type emphasizes the importance of unfocused or defocused attention in facilitating creative performance (Eysenck, 1995; Kasof, 1997). Defocused attention would necessarily be associated with low levels of cognitive control according to contemporary theories of executive attention (Posner & Rothbart, 2007; Rueda, Posner, & Rothbart, 2005). Such automaticity views of creativity can be contrasted with other theories emphasizing the importance of controlled processes. Especially high levels of creativity seem to require some degree of focused mental efforts (e.g., Groborz & Ne˛cka, 2003). Indeed, it seems quite unlikely that any creative idea would result in creative behaviors to the extent that there was no persistence in pursuing it (Feist, 1999). In neurobiological terms, it is quite apparent that the cognitive control capabilities of the human being, relative to other animal species, permit far less reliance on rigid stimulus–response associations and far greater capacities for creative thinking (Fuster, 1995; Stuss & Knight, 2002). By extension, human cognition that

The Potential Importance of Flexible Control Block and Block’s (2006) 30-year research program makes a lucid distinction between individual differences in control versus its flexible use. Their ego control construct differentiates individuals on the basis of whether they characteristically—that is, somewhat invariantly— express affect and impulse (undercontrol) versus inhibit such tendencies (overcontrol). Neither end of the continuum would be especially conducive to creativity, but for different reasons. Undercontrolled individuals would be spontaneous but lack the discipline for sustained creative efforts. On the other hand, overcontrolled individuals would be persistent but lack spontaneity (for findings supporting this trade-off, see Zabelina, Robinson, & Anicha, 2007). Block and Block (2006) contrasted ego control with ego resiliency. Resilient individuals are conceptualized as moderate in ego

Darya L. Zabelina and Michael D. Robinson, Department of Psychology, North Dakota State University. Darya L. Zabelina acknowledges support from a National Science Foundation Graduate Research Fellowship. Correspondence concerning this article should be addressed to Darya L. Zabelina, Department of Psychology, North Dakota State University, Department 2765, P.O. Box 6050, Fargo, ND 58108-6050. E-mail: darya .zabelina@ndsu 136

CREATIVITY AS FLEXIBLE COGNITIVE CONTROL

control rather than characteristically low or high along this dimension. The reason for this is that such individuals are seen to adjust their control of affect and impulse to best suit the present context. If the context favors spontaneity (e.g., while on vacation), such individuals are thought to relax ego control. On the other hand, if the context favors a greater degree of vigilance for inappropriate responses (e.g., while on a job interview), such individuals are thought to up-regulate their levels of ego control. Ego-resilient individuals, then, are viewed as flexible in the use of ego control resources. Ego resiliency has not typically been assessed in cognitive terms, and measures of creative originality and/or creative performance have rarely been administered in this research program (Block & Block, 2006). Nonetheless, Letzring, Block, and Funder (2005) report that ego-resilient individuals are viewed by acquaintances and clinicians as playful, imaginative, and possessing a wide range of interests. Such correlates of ego resiliency suggest that higher levels of flexible cognitive control may facilitate higher levels of creative originality and behavior. In the present study, we sought to assess flexibility in control in more objective cognitive terms and hypothesized that higher levels of cognitive control flexibility would be associated with higher levels of creativity. By contrast, following Block and Block (2006) and the aforementioned considerations, we hypothesized that context-invariant levels of cognitive control would be inconsequential in predicting individual differences in creativity.

Assessing Cognitive Control Abilities Versus Their Flexible Use Cognitive control is required in contexts in which automatically activated thoughts are prone to error (Carter, Braver, Barch, Botvinick, Noll, & Cohen, 1998; van Veen & Carter, 2006). The most widely validated measure for assessing cognitive control is the color–word Stroop task (MacLeod, 1991). Individuals are asked to categorize the font color of presented words regardless of the word in question. Because word reading is automatic (Neely, 1991), individuals tend to display robust Stroop interference costs when font color and word meaning are incongruent (e.g., the word “red” presented in a green font) relative to when they are congruent (e.g., the word “red” in a red font). Greater Stroop interference costs (i.e., incongruent condition minus congruent condition) have been observed among clinical populations, such as among children high in attention deficit/ hyperactivity disorder (Barkley, 1997) or those exhibiting clinically significant antisocial behavioral tendencies (Morgan & Lilienfeld, 2000). On the basis of such findings, especially impulsive individuals appear less capable of overriding cognitive conflicts in the Stroop task (MacLeod, 1991). On the other hand, cognitive control abilities as assessed by Stroop interference costs have rarely predicted functional or dysfunctional outcomes among normal adult populations in zero-order terms (e.g., Lansbergen, van Hell, & Kenemans, 2007; Robinson, Pearce, Engel, & Wonderlich, 2009). This is likely so because capacities for cognitive control are present among all normal adult individuals (Rueda et al., 2005). If so, the flexible recruitment of cognitive control is likely to be more important than its absolute capacity in understanding individual differences in outcome realms such as creativity (Robinson, Schmeichel, & Inzlicht, 2009).

137

The importance of flexible cognitive control has recently been emphasized by the cognitive neuroscience literature (e.g., van Veen & Carter, 2006). For the brain to function in an ideal manner, cognitive control resources should be recruited specifically in the context of cognitive conflicts or error-prone processing tendencies (Carter et al., 1998; Holroyd & Coles, 2002). By contrast, there is no reason to enact processing in a controlled manner when automatic processing tendencies appear to be working, as doing so is costly in multiple manners (Bargh & Chartrand, 1999; Lieberman, 2003), not the least of which may involve overly rigid, rule-bound thinking and behavior (Block & Block, 2006). Flexible cognitive control, as opposed to more static cognitive control abilities, can be assessed in terms of trial-to-trial variations in performance. In the context of the Stroop task, flexible cognitive control is indicated to the extent that Stroop interference costs for target trials are lower after previous trials that did (i.e., incongruent prime trials) versus did not (i.e., congruent prime trials) require cognitive control recruitment (Kerns, Cohen, MacDonald, Cho, Stenger, & Carter, 2004). In other words, flexible cognitive control is defined in terms of up- or down-regulating cognitive control depending on whether its use was needed on the previous trial. Gratton, Coles, and Donchin (1992) first established that individuals recruit cognitive control in such a dynamic trial-to-trial manner. Subsequent studies have replicated this dynamic pattern quite well (e.g., Liston, Matalon, Hare, Davidson, & Casey, 2006; Wuhr, 2005). Moreover, flexible cognitive control performance has been shown to be reliant on activation of regions of the brain responsible for cognitive control, such as the dorsolateral prefrontal cortex (Kerns, 2006; Kerns et al., 2004). Therefore, flexible cognitive control can be viewed in terms of recruiting the cognitive control resources of the brain in a context-specific manner deemed to be most functional in general terms (Miller & Cohen, 2001; van Veen & Carter, 2006).

Creativity as Flexible Cognitive Control The purported benefits of automatic processing include its generative capacity (Dixon, 1981), as automatic processes are massively parallel and highly associative (Lieberman, 2003). The purported benefits of controlled processing include greater freedom from overlearned stimulus–response routines and the ability to sustain processing in a goal-directed manner (Miller & Cohen, 2001). Creative individuals, we suggest, are those whose minds are more capable of switching rapidly between these two processing modes in a manner suited to the present processing context. If so, individuals scoring higher in creativity should also score higher in flexible cognitive control (see Vartanian, 2009, for a related perspective). We examined this idea in the context of two different measures of creativity, one involving original responses on a version of the Torrance Test of Creative Thinking (TTCT; Torrance, 1974) and the other involving a history of creative achievements as assessed by the Creative Achievement Questionnaire (CAQ; Carson, Peterson, & Higgins, 2005). The TTTC is a measure of creative potential—a latent trait underlying creative behavior. The CAQ, on the other hand, is a measure of actual creative achievement—socially useful and acceptable products— that is dependent on creative potential but quite a few other factors as well (Eysenck, 1995; Ivcevic, 2009).

ZABELINA AND ROBINSON

138 Method Participants and Procedures

Participants were 50 (26 female, 24 male) undergraduate student volunteers from North Dakota State University seeking extra credit for their psychology classes. They were primarily Caucasian in race (⬎90%), and their average age was 19.14 years. The study was somewhat generically described as one involving “drawing pictures,” both in relation to our Sona Systems participant registration system and in terms of the consent forms subsequently administered. This was deemed best to emphasize the most salient activity involved while avoiding mention that the study concerned individual differences in creativity. The laboratory consisted of a large central room for initial instructions and six private adjoining rooms for data collection. Thus, assessment sessions always involved fewer than 7 individuals. In their private cubicle rooms, participants first completed a version of the TTCT (Torrance, 1974) and then the CAQ (Carson et al., 2005); both are further described below. Finally, they completed a color–word Stroop test administered by personal computer. The activities were described as independent, and the order of measures was held constant to facilitate the individual difference comparisons of central interest to the study.

Measures Abbreviated TTCT. The TTCT (Torrance, 1974) is arguably the gold standard performance-based test for assessing individual differences in creative originality (Kim, 2008). We used a shortened version of the TTCT, termed the ATTA, which displays favorable psychometric properties and predictive validity among adult populations (Goff & Torrance, 2002). The ATTA consists of three activities, one involving verbal responses and two involving figural responses (e.g., using incomplete figures to make pictures). Individuals were given 3 min for each activity, originality was scored according to the manual, and originality scores were averaged across activities (Goff & Torrance, 2002).1 The CAQ. Capacity for creative originality and its manifestation in creative performance can often be independent (Ivcevic, 2009). Thus, it was deemed important to assess individual differences in creative performance as well. We did so in terms of the CAQ (Carson et al., 2005). Individuals were asked to characterize their previous creative achievements in 10 artistic domains (architectural design, creative writing, culinary arts, dance, humor, inventions, music, scientific inquiry, theater and film, & visual arts). For each domain, participants could indicate that they had made 0 achievements (“I have no training or recognized talent in this area”) or had some training (e.g., scored as 1: “I have taken lessons in this area”), with 6 other ascending levels of creative performance (e.g., scored as 7: “My choreography has been recognized by a national publication”). To score creative achievement in a general manner, we averaged scores across the 10 different domains involved. Carson et al. reported extensive evidence for the reliability and validity of such total Creative Achievement scores. Stroop task. Cognitive control and its flexibility were assessed in terms of a basic color–word Stroop task (MacLeod, 1991), which was programmed with E-prime software. Individuals were asked to categorize the color of presented letter strings as

either green or red, using the “1” or “5” key, respectively, of a response box. To create conditions of color–word congruence and incongruence, we presented letter strings that involved either the word “green” or “red,” randomly selected by the computer program. There were 140 consecutive trials in the task. The background was black, ensuring high stimulus contrast. The response mappings (1 ⫽ green; 5 ⫽ red) were continuously displayed to reduce forgetting the mappings involved (Robinson, 2007a). Correct responses were followed by a 500-ms blank to prepare for the next trial. Error responses, which were infrequent (M ⫽ 3.01%), were penalized by a 1,000-ms visual error message. This procedure ensures a high degree of accuracy, thus rendering reaction times as the focus of interest (Sanders, 1998). Reaction times were positively skewed, and we therefore log-transformed them before the analyses reported later. In addition, particularly fast or slow responses can unduly influence response time means (Ratcliff, 1993). For this reason, we replaced 2.5-SD outlier log times with these 2.5-SD outlier scores (Robinson, 2007a). To assess individual differences in both cognitive control and flexible cognitive control, we coded trials in terms of whether they involved congruent or incongruent targets (i.e., on Trial n) and followed congruent or incongruent primes on the previous (i.e., n ⫺ 1) trial. Log and millisecond means were then averaged as a function of this 2 (prime congruence) ⫻ 2 (target congruence) within-participant design. Flexible cognitive control is defined in terms of a smaller (or perhaps even reversed) target congruency effect after incongruent primes and a larger target congruency effect after congruent primes (Gratton et al., 1992; Kerns et al., 2004).

Results Descriptive Results Descriptive results for the ATTA scores on originality in the present study (M ⫽ 5.54, SD ⫽ 3.38) were similar to norms reported by the test developers (Goff & Torrance, 2002). The same was true for scores (M ⫽ 12.65; SD ⫽ 10.77) from the CAQ measure of creative performance (Carson et al., 2005). The correlation between ATTA and CAQ scores was not significant, r ⫽ .14, p ⫽ .30. The nonsignificance of this relation is consistent with Runco’s (2008) suggestion that creative potential (as assessed by measures such as the ATTA) and creative behavior (as assessed by 1 Before scoring ATTA originality for the present study, Darya L. Zabelina first achieved a very high level of agreement with example responses from the ATTA manual. Sample protocols from a previous study (Zabelina & Robinson, 2010) were sent to the test developers, and again a very high level of agreement with the test developers was obtained (r ⫽ .93). Therefore, Zabelina scored creative originality, blind to the other individual difference measures assessed. Fluency scores (i.e., the number of pertinent responses generated) were also calculated for the ATTA. Fluency and originality were uncorrelated, p ⬍ .15, a result consistent with their general independence in previous investigations (e.g., Kim, 2008). Moreover, higher levels of fluency were not associated with cognitive control, whether defined in terms of Stroop interference costs or in terms of flexible cognitive control performance, Fs ⬍ 1. Thus, our results document a novel predictor of the originality of creative thinking independent of its fluency.


Normative Results From the Stroop Task We used a repeated measures analysis of variance (ANOVA) to assess normative trends in Stroop performance. As expected, there was a main effect for target congruence, F(1, 49) ⫽ 20.73, p ⬍ .01, partial ␩2 ⫽ .29. Reaction times were faster for congruent (M ⫽ 506 ms) relative to incongruent (M ⫽ 530 ms) targets, a classic Stroop interference effect. There was also a main effect for prime congruence, F(1, 49) ⫽ 11.18, p ⬍ .01, partial ␩2 ⫽ .11. Incongruent primes led to slower target performance (M ⫽ 524 ms) than did congruent primes (M ⫽ 512 ms). Effects of this type are thought to reflect a greater degree of caution following cognitive conflicts or errors (Rabbitt, 1966; Robinson, 2007b). Of most importance, however, was a significant Prime Congruence ⫻ Target Congruence interaction, F(1, 49) ⫽ 83.92, p ⬍ .01, partial ␩2 ⫽ .62, indicating flexible cognitive control (Kerns, 2006). After congruent primes, there was a robust Stroop interference effect, as responses were slower for incongruent targets (M ⫽ 547 ms) than for congruent targets (M ⫽ 477 ms), F(1, 49) ⫽ 87.65, p ⬍ .01, partial ␩2 ⫽ .63. After incongruent primes, however, individuals were actually faster to respond when targets were incongruent (M ⫽ 512 ms) relative to congruent (M ⫽ 535 ms), F(1, 49) ⫽ 23.65, p ⬍ .01, partial ␩2 ⫽ .26. Thus, although the Stroop target effect was robust in terms of the target main effect, the more remarkable pattern was its elimination (and, in fact, reversal, as in Kerns, 2006) following incongruent primes. We hypothesized that this crossover pattern—indicating flexible cognitive control—would be particularly pronounced among creative relative to less creative individuals.

Relations Between ATTA Originality and Flexible Cognitive Control We conducted a general linear model (GLM) analysis to examine relations between ATTA originality and cognitive control performance in the Stroop task. GLM analyses combine features of ANOVA and regression and are capable of simultaneously modeling the influence of (a) within-participant variable designs of the present type and (b) between-participants variables (e.g., originality) without dichotomizing them (Robinson, 2007a). Dimensional variations in ATTA originality were z scored for this analysis (Aiken & West, 1991), and the within-participant factors of prime and target congruence were retained. Because normative results from the GLM—main effects for prime and target congruence as well as their interaction—were exactly as those reported earlier, here we report only results involving originality on the ATTA. In this GLM analysis, there was no main effect for originality on the ATTA Originality measure, F ⬍ 1. Thus, more creative individuals were neither faster nor slower in the task, regardless of prime and target congruence factors. The ATTA Originality ⫻ Target Congruence interaction was nonsignificant, F ⬍ 1. Thus, more creative individuals were neither higher nor lower in Stroop

interference costs, regardless of priming factors. The ATTA Originality ⫻ Prime Congruence interaction was also not significant, F ⬍ 1. Thus, the tendency to slow down after incongruent primes was equally manifest among those low versus high in creative originality. We hypothesized that creative individuals would exhibit more flexible cognitive control, a hypothesis initially supported by a three-way ATTA Originality ⫻ Prime Congruence ⫻ Target Congruence interaction, F(2, 98) ⫽ 4.21, p ⬍ .05, partial ␩2 ⫽ .08. To understand the nature of the three-way interaction, we estimated means for the Prime ⫻ Target interaction as a function of low (⫺1 SD) and high (1 SD) levels of originality on the ATTA, following Aiken and West (1991). Because there were no main effects or two-way interactions involving ATTA originality, and to simplify the presentation of the results in a manner best contacting the flexible cognitive control hypothesis, we computed difference scores to reflect the effects of prime congruence (congruent prime minus incongruent prime) for each target type separately considered. Such difference scores, as they vary by ATTA originality, are reported in Figure 1. As shown in Figure 1, both those low (⫺1 SD) and high (⫹1 SD) in ATTA originality displayed flexible cognitive control, but such effects were clearly more pronounced at high levels of ATTA originality. Follow-up analyses supported both points. A cognitive control flexibility score was calculated such that it reflected the prime ⫻ target interaction: ((incongruent/congruent log mean ⫹ congruent/incongruent log mean) ⫺ (congruent/congruent log mean ⫹ incongruent/incongruent log mean)). Simple slopes analyses (Aiken & West, 1991) were then performed, and they revealed that cognitive control flexibility was exhibited at both low (⫺1 SD, t[49] ⫽ 5.06, p ⬍ .01, ␤ ⫽ 0.30) and high (1 SD, t[49] ⫽ 7.93, p ⬍ .01, ␤ ⫽ 0.39) levels of ATTA originality. On the other hand, ATTA originality was a significant and positive predictor of such cognitive control flexibility scores, r(48) ⫽ .29, p ⬍ .05. Thus, the results support the hypothesis that higher levels of flexible cognitive control, but not cognitive control per se, predicts greater creative originality. We sought to conceptually replicate this result in terms of creative behaviors as assessed by the CAQ.

Priming Effects in Milliseconds

measures such as the CAQ) are dissociable. A history of creative behaviors, for example, would likely be influenced to a greater extent by developmental exposure to the arts and a history of formal training. Conceptual replication across the two different measures of creativity would thus be somewhat impressive, given their diverse nature and likely different developmental roots.

139

60 40 20 0

Congruent Targets

-20

Incongruent Targets

-40 -60 -80 -100 Low Originality

High Originality

Figure 1. Prime (congruent [solid bars] minus incongruent [open bars]) effects for congruent and incongruent target stimuli as a function of individual differences in originality on a shortened version of Torrance Test of Creative Thinking.


140 Relations Between CAQ Scores and Flexible Cognitive Control

We conducted a second GLM analysis in which we used individual differences in CAQ scores to predict cognitive control performance. CAQ scores did not predict faster speed in the Stroop task, F ⬍ 1, nor were the CAQ ⫻ Target Congruence or CAQ ⫻ Prime Valence interactions significant, Fs ⬍ 1. Of particular importance, such results suggest that creative individuals are neither more no less capable of overriding Stroop conflicts than are less creative individuals irrespective of the priming context. On the other hand, and consistent with the results reported earlier for ATTA originality, there was a significant three-way CAQ Score ⫻ Prime Congruence ⫻ Target Congruence interaction, F(2, 98) ⫽ 11.81, p ⬍ .01, partial ␩2 ⫽ .20. Estimated means for the three-way interaction were calculated as described earlier, and prime difference scores (congruent prime condition minus incongruent prime condition) for each target type are reported in Figure 2. Figure 2 again suggests that higher levels of cognitive control flexibility were observed among more creative individuals. Individual differences in cognitive control flexibility were then quantified in terms of the Prime Congruence ⫻ Target Congruence interaction, and analyses parallel to those reported above were performed. Significant cognitive control flexibility was exhibited at both low (⫺1 SD), t[49] ⫽ 4.51, p ⬍ .01, ␤ ⫽ 0.25) and high (1 SD, t[49] ⫽ 9.39, p ⬍ .01, ␤ ⫽ 0.44) levels of creative performance as assessed by the CAQ. On the other hand, CAQ scores were a robust predictor of higher levels of cognitive control flexibility, r(48) ⫽ .44, p ⬍ .01. The CAQ-based analyses thus replicated results involving ATTA originality scores in all respects.

Discussion

Priming Effects in Milliseconds

The present study was the first that we know of to directly examine whether creative individuals exhibit higher levels of cognitive control, lower levels of cognitive control, or neither. We examined this relationship in terms of individual differences in Stroop interference costs (MacLeod, 1991). Individual differences in creativity were not correlated with Stroop interference costs independent of the previous priming context. This was true both when creativity was defined in terms of a performance-based task

60 40 20 0

Congruent Targets Incongruent Targets

-20 -40 -60 -80 -100 Low Creative Achievement

High Creative Achievement

Figure 2. Prime (congruent [solid bars] minus incongruent [open bars]) effects for congruent and incongruent target stimuli as a function of individual differences in creative achievement on the Creative Achievement Questionnaire.

(i.e., the ATTA) and in terms of sustained and notable creative achievements in the past (i.e., the CAQ). Instead, and as hypothesized, creative individuals were better characterized in terms of their higher levels of flexible cognitive control. They, relative to less creative individuals, displayed greater modulation of the cognitive control system across trials. To be sure, similar tendencies were found in pattern (although not magnitude) at low levels of creativity as well, a result that is consistent with the idea that all human beings without brain damage may share an ability to modulate functioning of the cognitive control system (Miller & Cohen, 2001). Nonetheless, individuals low in creativity evidenced this normative pattern to a lesser extent. Thus, what the findings indicate is that highly creative individuals can be characterized in terms of unusually high levels of cognitive control flexibility.

Flexible Cognitive Control and Creativity Brainstorming, which facilitates creativity, involves letting go of self-censure in the service of novel decision-making solutions (Brown & Paulus, 2002). Intrinsic motivation, also linked to higher levels of creativity, can be similarly characterized (Collins & Amabile, 1999). The creativity theory of flow similarly contends that creative performance may be facilitated when self-censure drops out of awareness (Csikszentmihalyi, Abuhamdeh, & Nakamura, 2005). Finally, we (Zabelina & Robinson, 2010) have shown that a playful, childlike mindset among adults facilitates creative originality, presumably so because it encourages them to engage with the creativity task in a spontaneous, automatic manner (Gardner, 2004). Such theories and sources of data, we believe, capture something cognitively important to the creative process. When automatic processes are working, they should not be interrupted by the self-critical controlled mind (e.g., Dijksterhuis, Bargh, & Miedema, 2000). From this perspective, the creative individual is one who is likely to recognize the value of automatic processing tendencies that appear to be “working.” In turn, such individuals are likely to benefit from automatic processes linked to higher levels of creativity such as greater access to remote semantic associates (Ashby, Isen, & Turken, 1999; Baumann & Kuhl, 2002). It is for such reasons, we suggest, that creative individuals in the present study demonstrated larger Stroop costs after congruent Stroop trials. They, more so than low creative individuals, appeared to relax cognitive control when such resources are apparently not needed. On the other hand, it is quite apparent that higher levels of cognitive control, too, may be important to creative performance. The prefrontal cortex, responsible for cognitive control operations, facilitates flexible stimulus–response behaviors (Miller & Cohen, 2001). Indeed, damage to the prefrontal cortex results in stereotyped stimulus–response behaviors that are definitely not creative (Duncan, Burgess, & Emslie, 1995; Luria, 1966; Shallice, 2002). In personality-processing terms, cognitive control has been shown to facilitate novel solutions that bypass entrenched stimulus– response habits (e.g., Ackerman, Schneider, & Wickens, 1984). Finally, it appears that cognitive control, in the form of persistence and resistance from distraction, may be necessary for sustained creative performance (Feist, 1999).


The latter theories, we suggest, also capture something cognitively important to the creative process. When automatic processes are not working, they should be interrupted (Baddeley, 1996; Lieberman & Eisenberger, 2005) and overridden (Shallice, 2002) in service of novel information-processing solutions. The flexible use of cognitive control has been conceptualized in terms of greater awareness of problematic processing tendencies and the greater recruitment of cognitive control under such circumstances (Botvinick, Braver, Barch, Carter, & Cohen, 2001; Miller & Cohen, 2001). It is for such reasons, we suggest, that creative individuals in the present study demonstrated smaller Stroop costs after incongruent Stroop trials. In other words, they displayed higher levels of cognitive control particularly when the context suggested that the recruitment of cognitive control would be beneficial. Our link of higher levels of creativity to flexible cognitive control is novel. However, some precedents can be cited. Shirley Brice Heath, a recipient of a MacArthur “genius award,” provided a narrative account of her strategies for creative achievement in response to a focused interview (Shekerjian, 1990). In facilitating her creative potential, this eminent individual recommended minimal interventions when creative endeavors were progressing well and willful attempts to disrupt processing strategies that did not appear to be working. This narrative account appears quite consistent with our link of higher levels of creativity to the flexible and context-specific use of controlled processing strategies. Similarly, Kris (1952) viewed creativity in terms of regression in the service of the ego. From this perspective, regression (presumably linked to automatic processing tendencies) can be functional if guided and directed by an ego sensitive to conditions under which such regressive processes would be most functional. More recently, Vartanian (2009) reviewed an impressive body of evidence for the idea that creative individuals exhibit either greater or lesser attentional focus, depending on whether the task favors either greater or lesser attentional focus, respectively. The present results can be viewed as consistent with this cognitive flexibility theory, but in the context of a single task in which we were able to assess both general and context-specific tendencies toward cognitive control.

Limitations, Additional Considerations, and Future Research Directions A potential limitation of the present study is its racial and cultural homogeneity. At the same time, two points should be made in favor of the likely generality of our results. First, there is extensive evidence for the construct validity of one of our measures—ATTA Originality—across samples composed of different races, socioeconomic backgrounds, cultural backgrounds, and indeed primary spoken languages (Cramond, 1993; Torrance, 1977). Second, we assessed cognitive control tendencies that are tied to basic brain mechanisms that are unlikely to vary by race or cultural background (MacLeod, 1991; Miller & Cohen, 2001). Our sample was also relatively homogeneous with respect to age in that all tested individuals were of traditional college age. We suggest that there is value to such a sample in that it effectively controls for age-related influences in cognitive control (e.g., MacLeod, 1991). Even so, it is important to point out that our results emphasized flexible cognitive control rather than absolute

141

levels of cognitive control, and we are not aware of any systematic research on age differences in cognitive control flexibility. In any case, we were interested in the predictive value of cognitive control flexibility within an age group rather than differences across age groups. Although we view it likely that the present individual difference predictions would be found with younger and older individuals too, this possibility remains to be examined. We used the color–word Stroop task to assess cognitive control and cognitive control flexibility. This is arguably one of the best cognitive control measures, as it has a long history in cognitive psychology and has been validated in numerous ways (MacLeod, 1991). Of perhaps more importance, response conflict tasks such as the Stroop task must be used to examine the trial-to-trial variations in cognitive control that we sought to assess (Kerns, 2006). This said, there are certainly other measures of cognitive control that may be used in future studies of creative cognition. This includes task-switching measures (Rogers & Monsell, 1995), memory-updating measures (Miyake, Friedman, Emerson, Witzki, & Howerter, 2000), and noncomputerized tasks such as the Delis– Kaplan Executive Function System (Delis, Kaplan, & Kramer, 2001). Indeed, we are struck by the relative dearth of studies on relations between cognitive control processes and creative cognition. We did not assess individual differences in intelligence in our investigation. It may have been useful to do so to demonstrate discriminant validity. However, it should be mentioned that our focus was on creative originality and creative behavior, which merit more process-related analyses of the present type. In addition, relations between intelligence and creativity are potentially complex and have been debated over time (Batey & Furnham, 2006). Finally, we suggest that intelligence itself is a heterogeneous construct from a cognitive control perspective (Friedman, Miyake, Corley, DeFries, Hewitt, & Young, 2006). Thus, the value of the present investigation was its demonstration of a specific cognitive control function—namely, flexible cognitive control— that appears to underlie individual differences in both creative potential and behavior. Replication of the present findings seems warranted, particularly with respect to other measures of flexible cognitive control (Kerns, 2006). From a neurological perspective, electroencephalograph and functional magnetic resonance imaging studies of creativity have primarily examined the brain correlates of more versus less creative responses in normative terms (e.g., Nagornova, 2007). The present findings encourage the use of such technologies in relation to individual differences in creativity, much as individual differences in intelligence have been profitably modeled in brainprocessing terms (Duncan et al., 2000; Jensen, 2006). Individual differences in flexible cognitive control are likely to predict other functional outcomes aside from higher levels of creativity. Indeed, we suggested that flexible cognitive control may underlie individual differences in ego resiliency (Block & Block, 2006), although we know of no studies directly supporting this point. Studies of the present type are also needed in supporting the purported benefits of flexible cognitive control (van Veen & Carter, 2006). From a broader perspective, then, the present results are important precisely because they link individual differences in flexible cognitive control to their wider and more substantive individual difference correlates and consequences.


142 References

Ackerman, P. L., Schneider, W., & Wickens, C. D. (1984). Deciding the existence of a time-sharing ability: A combined methodological and theoretical approach. Human Factors, 26, 71– 82. Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. Thousand Oaks, CA: Sage. Ashby, F. G., Isen, A. M., & Turken, A. U. (1999). A neuropsychological theory of positive affect and its influence on cognition. Psychological Review, 106, 529 –550. Baddeley, A. (1996). Exploring the central executive. The Quarterly Journal of Experimental Psychology, 49A, 5–28. Bargh, J. A., & Chartrand, T. L. (1999). The unbearable automaticity of being. American Psychologist, 54, 462– 479. Barkley, R. A. (1997). Behavioral inhibition, sustained attention, and executive functions: Constructing a unifying theory of ADHD. Psychological Bulletin, 121, 65–94. Batey, M., & Furnham, A. (2006). Creativity, intelligence, and personality: A critical review of the scattered literature. Genetic, Social, and General Psychology Monographs, 132, 355– 429. Baumann, N., & Kuhl, J. (2002). Intuition, affect, and personality: Unconscious coherence judgments and self-regulation of negative affect. Journal of Personality and Social Psychology, 83, 1213–1223. Block, J., & Block, J. H. (2006). Venturing a 30-year longitudinal study. American Psychologist, 61, 315–327. Botvinick, M. M., Braver, T. S., Barch, D. M., Carter, C. S., & Cohen, J. D. (2001). Conflict monitoring and cognitive control. Psychological Review, 108, 624 – 652. Brown, V. R., & Paulus, P. B. (2002). Making group brainstorming more effective: Recommendations from an associative memory perspective. Current Directions in Psychological Science, 11, 208 –212. Carson, S. H., Peterson, J. B., & Higgins, D. M. (2005). Reliability, validity, and factor structure of the creative achievement questionnaire. Creativity Research Journal, 17, 37–50. Carter, C. S., Braver, T. S., Barch, D. M., Botvinick, M. M., Noll, D., & Cohen, J. D. (1998). Anterior cingulate cortex, error detection, and the online monitoring of performance. Science, 280, 747–749. Collins, M. A., & Amabile, T. M. (1999). Motivation and creativity. In: R. J. Sternberg (Ed.), Handbook of creativity (pp. 297–312). New York: Cambridge University Press. Cramond, B. (1993). The Torrance Tests of Creative Thinking: From design through establishment of predictive validity. In R. F. Subotnik & K. D. Arnold (Eds.), Beyond Terman: Contemporary longitudinal studies of giftedness and talent (pp. 229 –254). Norwood, NJ: Ablex. Csikszentmihalyi, M., Abuhamdeh, S., & Nakamura, J. (2005). Flow. In A. J. Elliot & C. S. Dweck (Eds.), Handbook of competence and motivation (pp. 598 – 608). New York: Guilford Press. Delis, D., Kaplan, E., & Kramer, J. (2001). Delis–Kaplan executive function scale. San Antonio, TX: The Psychological Corporation. Dijksterhuis, A., Bargh, J. A., & Miedema, J. (2000). Of men and mackerels: Attention, subjective experience, and automatic social behavior. In: H. Bless & J. P. Forgas (Eds.), The message within: The role of subjective experience in social cognition and behavior (pp. 37–51). New York: Psychology Press. Dixon, N. F. (1981). Preconscious processing. New York: Wiley. Duncan, J., Burgess, P., & Emslie, H. (1995). Fluid intelligence after frontal lobe lesions. Neuropsychologia, 33, 261–268. Duncan, J., Seitz, R. J., Kolodny, J., Bor, D., Herzog, H., Ahmed, A., . . . & Emslie, H. (2000). A neural basis for general intelligence. Science, 289, 457– 460. Eysenck, H. J. (1995). Genius: The natural history of creativity. Cambridge, England: Cambridge University Press. Feist, G. J. (1999). The influence of personality on artistic and scientific creativity. In R. J. Sternberg (Ed.), Handbook of creativity (pp. 273– 296). New York: Cambridge University Press.

Friedman, N. P., Miyake, A., Corley, R. P., DeFries, J. C., Hewitt, J. K., & Young, S. E. (2006). Not all executive functions are related to intelligence. Psychological Science, 17, 172–179. Fuster, J. M. (1995). Gradients of cortical plasticity. In: J. L. McGaugh, N. M. Weinberger, & G. Lynch (Eds.), Brain and memory: Modulation and mediation of neuroplasticity (pp. 250 –256). New York: Oxford University Press. Gardner, H. (1982). Giftedness: Speculations from a biological perspective. New Directions for Child Development, 17, 47– 60. Gardner, H. (2004). The unschooled mind: How children think and how schools should teach. New York: Basic Books. Goff, K., & Torrance, E. P. (2002). Abbreviated Torrance Test for Adults manual. Bensenvill, IL: Scholastic Testing Service. Gratton, G., Coles, M. G., & Donchin, E. (1992). Optimizing the use of information: Strategic control of activation of responses. Journal of Experimental Psychology, 121, 480 –506. Groborz, M., & Ne˛cka, E. (2003). Creativity and cognitive control: Explorations of generation and evaluation skills. Creativity Research Journal, 15, 183–197. Holroyd, C. B., & Coles, M. G. H. (2002). The neural basis of human error processing: Reinforcement learning, dopamine, and the error-related negativity. Psychological Review, 109, 679 –709. Ivcevic, Z. (2009). Creativity map: Toward the next generation of theories of creativity. Psychology of Aesthetics, Creativity, and the Arts, 3, 17–21. Jensen, A. R. (2006). Clocking the mind: Mental chronometer individual differences. Amsterdam, the Netherlands: Elsevier. Kasof, J. (1997). Creativity and breadth of attention. Creativity Research Journal, 4, 303–315. Kerns, J. G. (2006). Anterior cingulate and prefrontal cortex activity in an fMRI study of trial-to-trial adjustments on the Simon task. NeuroImage, 33, 399 – 405. Kerns, J. G., Cohen, J. D., MacDonald, A. W., III, Cho, R. Y., Stenger, V. A., & Carter, C. S. (2004). Anterior cingulate conflict monitoring and adjustments in control. Science, 303, 1023–1026. Kim, K. H. (2008). Commentary: The Torrance Tests of Creative Thinking already overcome many of the perceived weaknesses that Silvia et al.’s (2008) methods are intended to correct. Psychology of Aesthetics, Creativity, and the Arts, 2, 97–99. Kris, E. (1952). Psychoanalytic explorations in art. New York: International Universities Press. Lansbergen, M. M., van Hell, E., & Kenemans, J. L. (2007). Impulsivity and conflict in the Stroop task: An ERP study. Journal of Psychophysiology, 21, 33–50. Letzring, T. D., Block, J., & Funder, D. C. (2005). Ego-control and ego-resiliency: Generalization of self-report scales based on personality descriptions from acquaintances, clinicians, and the self. Journal of Research in Personality, 39, 395– 422. Lieberman, M. D. (2003). Reflexive and reflective judgment processes: A social cognitive neuroscience approach. In J. P. Forgas, K. D. Williams, & W. von Hippel (Eds.), Social judgments: Implicit and explicit processes (pp. 44 – 67). New York: Cambridge University Press. Lieberman, M. D., & Eisenberger, N. I. (2005). Conflict and habit: A social cognitive neuroscience approach to the self. In A. Tesser, J. V. Wood, & D. A. Stapel (Eds.), On building, defending and regulating the self: A psychological perspective (pp. 77–102). New York: Psychology Press. Liston, C., Matalon, S., Hare, T. A., Davidson, M. C., & Casey, B. J. (2006). Anterior cingulate and posterior parietal cortices are sensitive to dissociable forms of conflict in a task-switching paradigm. Neuron, 50, 643– 653. Luria, A. R. (1966). Higher cortical functions in man. New York: Basic Books. MacLeod, C. M. (1991). Half a century of research on the Stroop effect: An integrative review. Psychological Bulletin, 109, 163–203.

CREATIVITY AS FLEXIBLE COGNITIVE CONTROL Miller, E. K., & Cohen, J. D. (2001). An integrative theory of prefrontal cortex function. Annual Review of Neuroscience, 24, 167–202. Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., & Howerter, A. (2000). The unity and diversity of executive functions and their contributions to complex “frontal lobe” tasks: A latent variable analysis. Cognitive Psychology, 41, 49 –100. Morgan, A. B., & Lilienfeld, S. O. (2000). A meta-analytic review of the relation between antisocial behavior and neuropsychological measures of executive function. Clinical Psychology Review, 20, 113–156. Nagornova, Z. V. (2007). Changes in the EEG power during tests for nonverbal (figurative) creativity. Human Physiology, 33, 277–284. Neely, J. H. (1991). Semantic priming effects in visual word recognition: A selective review of current findings and theories. In D. Besner, G. W. Humphreys, & N. J. Hillsdale (Eds.), Basic processes in reading: Visual word recognition (pp. 264 –336). London: Erlbaum. Posner, M. I., & Rothbart, M. K. (2007). Research on attention networks as a model for the integration of psychological science. Annual Review of Psychology, 58, 1–23. Rabbitt, P. M. (1966). Errors and error correction in choice-response tasks. Journal of Experimental Psychology, 71, 264 –272. Ratcliff, R. (1993). Methods for dealing with reaction time outliers. Psychological Bulletin, 114, 510 –532. Robinson, M. D. (2007a). Lives lived in milliseconds: Using cognitive methods in personality research. In R. W. Robins, R. C. Fraley, & R. F. Krueger (Eds.), Handbook of research methods in personality psychology (pp. 345–359). New York: Guilford Press. Robinson, M. D. (2007b). Gassing, braking, and self-regulating: Error self-regulation, well-being, and goal-related processes. Journal of Experimental Social Psychology, 43, 1–16. Robinson, M. D., Pearce, E. A., Engel, S. G., & Wonderlich, S. A. (2009). Cognitive control moderates relations between impulsivity and bulimic symptoms. Cognitive Therapy and Research, 33, 356 –367. Robinson, M. D., Schmeichel, B. J., & Inzlicht, M. (2009). How does the self control itself? Questions and considerations from a cognitive control perspective. Manuscript submitted for publication. Rogers, R. D., & Monsell, S. (1995). Costs of a predictable switch between simple cognitive tasks. Journal of Experimental Psychology, 124, 207– 231.

143

Rueda, M. R., Posner, M. I., & Rothbart, M. K. (2005). The development of executive attention: Contributions to the emergence of self-regulation. Developmental Neuropsychology, 28, 573–594. Runco, M. A. (2008). Commentary: Divergent thinking is not synonymous with creativity. Psychology of Aesthetics, Creativity, and the Arts, 2, 93–96. Sanders, A. F. (1998). Elements of human performance: Reaction processes and attention in human skill. Mahwah, NJ: Erlbaum. Shallice, T. (2002). Fractionation of the supervisory system. In D. T. Stuss & R. T. Knight (Eds.), Principles of frontal lobe function (pp. 261–277). New York: Oxford University Press. Shekerjian, D. (1990). Uncommon genius: How great ideas are born. New York: Viking. Stuss, D. T., & Knight, R. T. (2002). Principles of frontal lobe function. New York: Oxford University Press. Torrance, E. P. (1974). The Torrance Tests of Creative Thinking norms— Technical manual (research ed.) for figural tests, Forms A and B. Princeton, NJ: Personnel Press. Torrance, E. P. (1977). Discovery and nurturance of giftedness in the culturally different. Reston, VA: Council on Exceptional Children. van Veen, V., & Carter, C. S. (2006). Conflict and cognitive control in the brain. Current Directions in Psychological Science, 15, 237–240. Vartanian, O. (2009). Variable attention facilitates creative problem solving. Psychology of Aesthetics, Creativity, and the Arts, 3, 57–59. Wuhr, P. (2005). Evidence for gating of direct response activation in the Simon task. Psychonomic Bulletin and Review, 12, 282–288. Zabelina, D. L., & Robinson, M. D. (2010). Child’s play: Facilitating the originality of creative output by a priming manipulation. Psychology of Aesthetics, Creativity, and the Arts, 4, 57– 65. Zabelina, D. L., Robinson, M. D., & Anicha, C. L. (2007). The psychological tradeoffs of self-control: A multi-method investigation. Personality and Individual Differences, 43, 463– 473.

Received June 14, 2009 Revision received August 11, 2009 Accepted August 11, 2009 䡲

E-Mail Notification of Your Latest Issue Online! Would you like to know when the next issue of your favorite APA journal will be available online? This service is now available to you. Sign up at http://notify.apa.org/ and you will be notified by e-mail when issues of interest to you become available!