Regional gray matter volume of dopaminergic system associate with creativity: Evidence from voxel-based morphometry

NeuroImage 51 (2010) 578–585

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NeuroImage j o u r n a l h o m e p a g e : w w w. e l s e v i e r. c o m / l o c a t e / y n i m g

Regional gray matter volume of dopaminergic system associate with creativity: Evidence from voxel-based morphometry Hikaru Takeuchi a,⁎, Yasuyuki Taki a, Yuko Sassa a, Hiroshi Hashizume a, Atsushi Sekiguchi b, Ai Fukushima b, Ryuta Kawashima a,b,c a b c

Division of Developmental Cognitive Neuroscience, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan Department of Functional Brain Imaging, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan Smart Ageing International Research Center, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan

a r t i c l e

i n f o

Article history: Received 2 November 2009 Revised 20 February 2010 Accepted 26 February 2010 Available online 10 March 2010

a b s t r a c t Creativity has been essential to the development of human civilization and plays a crucial role in cultural life. However, despite a number of functional imaging studies on creativity, the relationship between regional gray matter morphology and creativity has never been investigated in subcortical regions. We used voxelbased morphometry (VBM) to identify the gray matter correlates of individual creativity as measured by the divergent thinking test. We found positive correlations between regional gray matter volume and individual creativity in several regions such as the right dorsolateral prefrontal cortex, bilateral striata and in an anatomical cluster which included areas such as the substantia nigra, tegmental ventral area and periaqueductal gray. These findings suggest that individual creativity, as measured by the divergent thinking test, is mainly related to the regional gray matter of brain regions known to be associated with the dopaminergic system, congruent with the idea that dopaminergic physiological mechanisms are associated with individual creativity. © 2010 Elsevier Inc. All rights reserved.

Introduction Creativity is commonly agreed to involve bringing something into being that is original and also valuable (Ochse, 1990). Creativity has been essential to the development of human civilization and plays a crucial role in cultural life. Divergent thinking has been proposed to be a key aspect of creativity (Guilford, 1967). Divergent thinking pertains primarily to information retrieval and the call for a number of varied responses to a certain item (Guilford, 1967). A meta-analysis (Kim, 2008) demonstrated that divergent-thinking scores have a significantly stronger relationship with creative achievement than do scores on intelligence tests, supporting the validity of divergent thinking as predictive of creative ability. Previous psychological, neuropsychological and functional imaging studies have indicated that the dopaminergic system, including the frontal lobe, contributes to creativity. For example, a number of studies (cf. Kline & Cooper, 1986; O'Reilly et al., 2001; Eysenck and Furnham, 1993; Gianotti et al., 2001; Merten and Fischer, 1999; Poreh et al., 1993) reported a positive relationship between creativity

⁎ Corresponding author. Division of Developmental Cognitive Neuroscience, IDAC, Tohoku University, 4-1, Seiryo-cho, Aoba-ku, Sendai 980-8575, Japan. Fax: + 81 22 717 7988. E-mail address: [email protected] (H. Takeuchi). 1053-8119/$ – see front matter © 2010 Elsevier Inc. All rights reserved. doi:10.1016/j.neuroimage.2010.02.078

and schizotypy, which is associated with dopamine-related genes (Ettinger et al., 2006) and overactivity of subcortical dopaminergic systems (Kirrane and Siever, 2000). Furthermore, dopamine antagonists, generally used as antipsychotics, suppress creativity (Flaherty, 2005). While dopamine decreases latent inhibition, which is a behavioral index of the ability to habituate to sensations (Ellenbroek et al, 1996; Swerdlow et al, 2003), low latent inhibition is characteristic of both individuals with schizotypy (Swerdlow et al., 2003) and creative individuals with high intelligence (Carson et al, 2003). Functional imaging studies have shown the creative thinking process is associated with increased activity of the prefrontal cortex (PFC) (Folley & Park, 2005, Geake & Hansen, 2005) which is a part of dopaminergic system (Carlson, 2001). Furthermore, schizotypes increasingly recruit the right PFC during a divergent thinking test (Folley & Park, 2005). These reports are consistent with the perspectives of integrative reviews of creativity studies based on other research methods as well that suggest the dopaminergic system, including the PFC, are associated with creativity (Flaherty, 2005; Heilman et al., 2003). These associations could be mediated by procreativity cognitive mechanisms such as goal-directed thoughts, novelty seeking and problem solving, which are ascribed to the dopaminergic system or the PFC specifically (Flaherty, 2005, Dietrich, 2004; Duch, 2007). Two recent studies have investigated the cortical thickness correlates of creativity and neurochemical correlates of creativity (Jung et al., 2009a, 2009b). Utilizing cortical thickness

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analysis (Fischl & Dale, 2000), the former revealed associations between cortical thickness and creativity in the PFC together with in other regions and the latter revealed associations between concentrations of N-acetyl-asparate and creativity in the regions in the PFC. But despite the large amount of literatures on creativity described above (for review, see also Flaherty, 2005; Heilman et al., 2003), no previous study has observed the relationship between regional gray matter volume (rGMV) and individual creativity in subcortical regions. Despite sensitivity of the cortical thickness analysis (Hutton et al., 2009), the major disadvantage of cortical thickness analysis which was used in the previous anatomical study of creativity (Jung et al., 2009a) is that the focus of the analysis is entirely on the cortex; changes in subcortical structures will not be picked up. It is important to investigate anatomical correlates of creativity in subcortical regions, considering there are several structures of dopaminergic system in subcortical regions. Potential correlates of rGMV include the number and size of neurons and glias, the level of synaptic bulk, neurites (May & Gaser, 2006; Draganski et al., 2004). Furthermore, rGMV is known to be the basis of individual intellectual abilities (Haier et al., 2004). Thus structural imaging of rGMV provides information about the origin of individual creativity. The purpose of this study is to investigate the association between rGMV including that of the subcortical regions and individual creativity. For this purpose we used psychological creativity tests for divergent thinking and voxel based morphometry (VBM) (Good et al., 2002). VBM and cortical thickness analysis both measure brain morphometry, but VBM can examine subcortical areas not really assessed with CT. Given the previous neuroscientific studies on creativity that have indicated the association between the dopaminergic system including the PFC and creativity, we reasoned that rGMV in the dopaminergic system, such as the PFC, striatum and midbrain architectures, is associated with creativity measured by the divergent thinking test. Methods Subjects Fifty-five healthy, right-handed individuals (42 men and 13 women) participated in this study as part of our ongoing project to investigate the associations between brain imaging and cognitive function, and their age-related change. All subjects who took part in this study also became the subjects of our intervention studies. Psychological measures for working memory, processing speed, attention, response inhibition, arithmetic, mental rotation, emotional intelligence, empathy, systemizing, executive function and emotional state, as well as MRI scans such as fMRI scans, diffusion tensor imaging, and arterial spin labeling, were performed together with the techniques described in this study. The mean age of subjects was 21.7 years old (standard deviation [SD], 1.44). All subjects were university students or postgraduate students. All subjects had normal vision and none had a history of neurological or psychiatric illness. Handedness was evaluated using the Edinburgh Handedness Inventory (Oldfield, 1971). Written informed consents for all the projects in which subjects participated was obtained. The procedures of all studies were approved by the Ethics Committee of Tohoku University. Creativity assessment The S-A creativity test (Society for Creative Mind, 1969) was used to assess creativity. J.P. Guilford made the draft plan and supervised the development of the test, after which the test was standardized for Japanese speakers (Society for Creative Mind, 1969). A more detailed discussion of the psychometric properties of this instrument and how it was developed is found in the technical manual of this test (Society for Creative Mind, 1969).The test is used to evaluate creat-

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ivity through divergent thinking (Society for Creative Mind, 1969) and it involves three types of tasks. Each task is preceded by two minutes of practice involving two questions with a five-minute time limit. All the participants answer the same questions. The first task requires subjects to generate unique ways of using typical objects (e.g. ‘Other than reading, how can we use newspapers? An example answer is ‘We can use them to wrap things.’) The second task requires subjects to imagine desirable functions in ordinary objects. (e.g. ‘What are the characteristics of a good TV? Write down as many characteristics as possible.’ An example answer is ‘A TV that can receive broadcasts from all over the world.’) The third task requires subjects to imagine the consequences of 'unimaginable things’ happening. (e.g. ‘What would happen if all the mice in the world disappeared?’ An example answer is ‘The world would become more hygienic.’) Each task requires subjects to generate as many answers as possible. The S-A creativity test has two versions: Version A and Version C. Each version has the same three types of tasks (thus no actual superiority exists between the two versions), but involves different questions. In this study Version A was used. The S-A creativity test provides a total creativity score, which was used in this study, and it scores the following dimensions of the creative process: (a) Fluency. Fluency is measured by the number of relevant responses to the questions and is related to the ability to produce and consider many alternatives. Fluency scoring is measured by the total number of questions answered after excluding inappropriate answers or answers that are difficult to understand. (b) Flexibility. Flexibility is the ability to produce responses from a wide perspective. Flexibility scoring is measured by the sum of the (total) number of category types that answers are assigned based on a criteria table or an almost equivalent judgment. (c) Originality. Originality is the ability to produce ideas that differ from others’. Originality scoring is based on the sum of the idea categories that are weighted based on a criteria table or an almost equivalent judgment. (d) Elaboration. Elaboration is the ability to produce ideas in detail (Society for Creative Mind, 1969). Elaboration scoring is measured by the sum of the answers that are weighted based on a criteria table or an almost equivalent judgment. These four dimensions correspond to the same concepts in the Torrance tests of creative thinking (TTCT; Torrance, 1966). Total creativity score is the sum of the score of originality and that of elaboration in the A version of the S-A creativity test. Scoring of the tests was performed at the Tokyo Shinri Corporation. The tests were evaluated by a single scorer of the Tokyo Shinri Corporation who was blind to the study design. Sample answers to the questionnaire, and the manner in which they were scored are presented in the Appendix. The analysis in this study was limited to that of total creativity score and did not include the scores of each dimension, because the scores of each dimension highly correlate with total creativity score (each correlation efficient N 0.79). Consistent with these, a previous study (Chávez-Eakle et al., 2007) that investigated the association between regional cerebral blood flow (rCBF) and each dimension of creativity revealed that creativity dimensions have important overlaps with their rCBF correlations. Thus, we believe only using total creativity score serves the purpose of this study. The split half reliability estimate used for testing the internal consistency of the total score of S-A creativity test was 0.80 according to the manual of this test (Society for Creative Mind, 1969). Total score of S-A creativity test has been shown to be highly correlated with various other external measures such as academic performance, various personality factors, job performance and problem solving abilities in daily life suggesting its ability to predict performance in everyday situations (Society for Creative Mind, 1969; Shimonaka & Nakazato, 2007). Furthermore, scores of the S-A creativity test, have been shown to be significantly correlated with frequency of visual hypnagogic experiences which in turn correlated with the vividness of mental imagery and neuroticism (Watanabe, 1998). Nevertheless, the associations between creative achievement and scores of this test

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have not been demonstrated in peer reviewed journals, unlike the Torrance Tests of Creative Thinking (TTCT) (for the associations between creative achievement and TTCT, see Kim, 2008; Plucker, 1999). However, the nature of the S-A creativity test is similar to that of the TTCT in that it consists of three problems, which are similar to three problems in the TTCT (Torrance, 1966). In these problems the subjects are asked to (1) improve a product (list ways to change a certain product so that it will have more desirable characteristics), (2) find interesting and unusual uses for a certain object and (3) list all the consequences should an improbable situation occur (Torrance, 1966). Assessment of psychometric measures of general intelligence Raven's Advanced Progressive Matrix (Raven, 1998), which is one of the purest psychometric measures of general intelligence (Raven, 1998) and which is often shown to be the most correlated with general intelligence and thus the best general intelligence measures (Raven et al., 1998) was used to assess intelligence. This test was used in our study to adjust for the effect of individual psychometric measures of intelligence on brain structures. This adjustment was performed since creativity is known to be associated with psychometric measures of intelligence among subjects of low to average intelligence (Barron & Harrington, 1981, [thus we did not necessarily expect to find a significant correlation in our sample of highly educated subjects]). It was also performed because we had to exclude the possibility that any significant correlation between rGMV and creativity was caused by the indirect association between rGMV and general intelligence, which is a higher level cognitive function than creativity. Raven's Advanced Progressive Matrix (Raven, 1998) contains 36 nonverbal items requiring fluid reasoning ability. Each item consists of a 3 × 3 matrix with a missing piece to be completed by selecting the best of 8 alternatives. The score of this test (number of correct answers in 30 min) was used as an index of individual psychometric measure of intelligence. Image acquisition All MRI data acquisition was conducted with a 3-T Philips Intera Achieva scanner. Using a MRPAGE sequence, high-resolution T1weighted structural images (240 × 240 matrix, TR = 6.5 ms, TE = 3 ms, FOV = 24 cm, 162 slices, 1.0 mm slice thickness) were collected. Preprocessing of structural data Data preprocessing of the morphological data was performed with VBM2 software (Gaser, 2006), an extension of SPM2, and default parameter settings were used (Gaser, 2006). In order to reduce the scanner-specific bias, we created a customized GM anatomical template from the pre-intervention data of all participants in this study. To facilitate optimal segmentation, we estimated normalization parameters with the protocol utilized by Good et al. 2001. In addition, we performed a correction for volume changes (modulation) by modulating each voxel with Jacobian determinants derived from spatial normalization, allowing us to also test for regional differences in the absolute amount of GM (Ashburner and Friston, 2000). Subsequently, all images were smoothed by convolving them with an isotropic Gaussian Kernel of 6 mm full-width at half maximum across the entire brain. A relatively lower smoothing parameter was used to preserve possible anatomical correlates of creativity which include fine structures such as those in the brainstem. A Gaussian Kernel of 6 mm fullwidth at half maximum has been validated since a previous study (Salmond et al., 2002) reported, that in VBM analyses, smoothing with a 4-mm FWHM kernel is large enough for the validity of the statistical tests. The resulting maps representing the rGMV were then forwarded to a group analysis.

Statistical analysis The group analysis of the morphological data was performed with VBM5 software (Gaser, 2007), an extension of SPM5. In the group analysis, we included only voxels that showed GM value N0.05 to avoid the possibility of partial volume effects around the borders between GM and WM as well as those between GM and CSF. At the group level analysis, we tested for the relationship between individual creativity measured by the divergent thinking test and rGMV. In the whole brain analysis, we used a multiple linear regression analysis to look for areas where the rGMV showed a significant relationship to individual creativity measured by the divergent thinking test (total creativity score in the S-A creativity test). The analysis was performed with sex, age and score of Raven's advanced progressive matrices as additional covariates. The level of statistical significance was set at P b 0.05, and corrected at the non-stationary cluster level (Hayasaka et al., 2004) with an underlying voxel level of P b 0.005. Non-stationary cluster-size tests can be applied to data known to be non-stationary (in another words, not uniformly smooth), such as VBM data (Hayasaka et al., 2004). In this non-stationary cluster-size test of random field theory, a lower cluster determining threshold resulted in a more conservative test (Hayasaka et al., 2004). Statistical analysis limited to males Given that sex differences have been reported in VBM studies of intelligence (see Haier et al., 2005), it is important to analyze the data separately for males and females in addition to using sex as a covariate, which ignores any actual sex differences. In our study, only males had a sufficient sample size, but it was worth knowing whether removing the females would change or void regional findings. In the whole brain analysis, using only data from males, we used a multiple linear regression analysis to look for areas where the rGMV showed a significant relationship to individual creativity measured by the divergent thinking test (total creativity score in the S-A creativity test). The analysis was performed with age and score of Raven's advanced progressive matrices as additional covariates.

Results Behavioral data Behavioral data revealed an average total S-A creativity test score of 37.42 (SD, 11.49, range 14-67) and an average Raven's advanced progressive matrices score of 28 (SD, 3.42, range 23-34). None of the psychological and epidemiological measures (Raven's advanced progressive matrices score, age or sex) correlated significantly with the total S-A creativity test score (P N 0.1). For complete data of the distribution of the total S-A creativity test score, see Fig. 1.

Fig 1. Distribution of the scores from the S-A creativity test in our sample.

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Correlation of regional gray matter volume and creativity in the analysis using data from both sexes After controlling for the age, sex, and score of Raven's advanced progressive matrices, multiple regression analysis revealed that creativity scores were significantly and positively correlated with rGMV in (1) the right DLPFC (Fig. 2AB), (2) bilateral striata (Fig. 2BC), (3) an anatomical cluster that includes the dorsal midbrain, the reticular formation, the periaqueductal gray (PAG), the ventral midbrain (substantia nigra and ventral tegmental area) (Fig. 2CD), and (4) regions in the precuneus. There were no significant negative correlations between rGMV and creativity scores. These results are shown in Table 1. Correlation of regional gray matter volume and creativity in the analysis using data from males Compared with the result of a regression analysis using data from both males and females, there were two minor changes in the significant results of our analysis. A significant result of the analysis using data of both sexes in the precuneus (x, y, x = 11, -42, 6, t = 4.15, p = 0.048 corrected for multiple comparisons at cluster size with an underlying voxel level of P b 0.005) became insignificant when the analysis was performed using only data from the male samples (x, y, x = 9, -42, 12, t = 4.30, p = 0.163 corrected for multiple comparisons at cluster size with an underlying voxel level of P b 0.005). But the subtle statistical change was not enough to change our discussion of this region. In addition to the changes in the significant results in the precuneous, a previously insignificant result from the first analysis

Fig 2. Regions of correlation between rGMV and creativity test scores (P b 0.05 corrected for multiple comparisons at the non-isotropic adjusted cluster level, with an underlying voxel level of P b 0.005 uncorrected). Regions of significant correlation are overlaid on a single subject T1 image of SPM5. (A) Axial view. Regions of significant correlation are shown in the right DLPFC. (B) Coronal view. Regions of significant correlations are shown in the bilateral striata together with a significant cluster in the right DLPFC (C) Coronal view. Regions of significant correlations are shown in the regions of the bilateral striata, together with a significant anatomical cluster in the midbrain. (D) Axial view. An anatomical cluster with significant correlations is shown in the regions in the midbrain, extending into the parahippocampal gyrus. The anterior part of the cluster includes the substantia nigra and ventral tegmental area. The posterior part of the cluster includes architectures such as the PAG and the reticular formation.

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Table 1 Brain regions with significant positive correlations between rGMV and S-A creativity test score. Area Midbrain Caudate Middle frontal gyrus Precuneus Precuneus Caudate

L R

R

x

y

z

T score

Corrected p value (cluster)

3 -17 42 11 -13 19

-29 -27 26 -41 -40 -22

-9 20 36 6 68 25

5.10 4.57 4.37 4.15 4.03 3.93

b0.001 0.018 0.005 0.048 0.039 0.026

No regions showed significant negative correlations between rGMV and S-A creativity test score.

using data from both sexes in the left insula (x, y, x = -31, 19, 10, t = 3.49, p = 0.791 corrected for multiple comparisons at cluster size with an underlying voxel level of P b 0.005) became significant when the analysis was performed using only data from males (x, y, x = -32, 19, 10, t = 4.42, p = 0.044 corrected for multiple comparisons at cluster size with an underlying voxel level of P b 0.005). But overall, even when the analysis was limited to males, most of the significant results remained significant, suggesting that removing the females did not change or void the regional findings. Discussion To our knowledge, this is the first study to investigate the association between individual creativity and rGMV in subcortical regions. Our findings showed that increased rGMV in an anatomical cluster including the substantia nigra, and the fronto-striatal regions which are involved with the dopaminergic system, is associated with creativity measured by the divergent thinking test. This is congruent with the ideas that creativity is associated with the dopaminergic system. Among regions whose rGM positively correlates with creativity, subcortical regions in the dopaminergic system (striata and brainstem regions), have not been identified as regions whose rGM positively correlates with general intelligence (Haier et al., 2004; Frangou et al., 2004; Gong et al., 2005, Wilke et al., 2003). Thus our results suggest that gray matter correlates of creativity are at least partly distinct from gray matter correlates of general intelligence or gray matter correlates working memory, which are closely associated with general intelligence (Conway et al., 2003), such as the lateral and medial prefrontal cortex and anterior cingulate cortex (ACC) (Haier et al., 2004; Frangou et al., 2004; Gong et al., 2005; Wilke et al., 2003; Shaw et al, 2006; Toga and Thompson, 2005; Narr et al., 2007; Hulshoff Pol et al., 2006; also for a recent review see Jung & Haier, 2007). Consistent with our expectations, a significant positive correlation between rGMV and creativity score was found in the DLPFC, and other regions in the dopaminergic systems such as the bilateral basal ganglia, and the anatomical cluster which includes the substantia nigra, and the tegmental ventral area. These regions overlapped three main dopaminergic systems in the brain; the nigrostriatal system, mesolimbic system and mesocortical system (Carlson, 2001). Neurons in the nigrostriatal system project to the striatum from the substantia nigra (Carlson, 2001) and this system plays a key role in motor control (Carlson, 2001). Involvement of this system with other higher order cognitive functions such as filtering of information flow to the frontal lobe has been implicated (McNab et al., 2007). Neurons in the mesolimbic system projects to the nucleus accumbens, hippocampus, and so on from the ventral tegmental area, and this system plays a key role in reward mechanism in the brain (Carlson, 2001). Finally, neurons in the mesocortical system projects to the prefrontal cortex from the tegmental ventral area, and are involved in problem solving, working memory and other higher order cognitive functions (Carlson, 2001). Each system and region is considered to contribute to creativity in its own way, as described below.

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Increased rGMV in the right DLPFC may contribute to higher creativity through diverse higher order cognitive functions that are associated with this region, described below. Creativity is a complex cognitive function and it requires diverse cognitive abilities, such as working memory, sustained attention, cognitive flexibility, and fluency in the generation of ideas and the judgment of propriety, that are typically ascribed to the PFC (Dietrich, 2004; Baldo et al., 2001). For example, as for cognitive flexibility, the ability to break conventional or obvious patterns of thinking, and adapt to new and higher order rules, is at the heart of theories of creativity such as Guilford's (1967) concept of divergent thinking. Thus, increased right PFC functions, which are reflected in increased rGMV, may contribute to creativity through the diverse cognitive functions involved in this region. Furthermore, the involvement of diverse general cognitive processes within creative processes may underlie the common involvement of the right DLPFC in general intelligence (e.g., Haier et al., 2004, also for a review see Gray & Thompson, 2004) and creativity, seen in this study. The result of the significant positive correlation between rGMV in the right DLPFC and creativity score may also be comparable to previous studies that report the involvement of the right frontal lobe in creativity. These studies report that the right frontal lobe is involved in generating unusual or distant verbal associations, both of which apparently characterize creative thinking (Kiefer et al., 1998; Seger et al., 2000). Furthermore, Schizotypes, who have enhanced creative thinking ability, increasingly recruit the right PFC during a divergent thinking test (Folley & Park, 2005). Results of these studies are congruent with the idea that the right hemisphere is specialized for creativity (Bogen and Bogen, 1988; Hoppe, 1988). Nevertheless, this idea is a matter of debate (Flaherty, 2005). Some functional imaging studies on creativity report the involvement of the bilateral frontal lobe in creative thinking ability (e.g. Chávez-Eakle et al., 2007). Another study also showed enhanced creativity in musicians, which is measured by the verbal divergent thinking test (Gibson et al., 2009). Musicians also show greater bilateral frontal activity during divergent thinking than nonmusicians (Gibson et al., 2009). These studies may suggest that enhanced divergent thinking in musicians is supported by increased bilateral frontal lobe activity. In our study, too, there were non-significant results in a few clusters of the left DLPFC which showed a correlation between rGMV and creativity (uncorrected P b 0.005). However, the superiority of the right, compared with the left, DLPFC's influence on creativity was not clear in this study. We cannot state whether there was selective involvement of the right frontal lobe in creativity. Perhaps contributions to creativity come from the bilateral frontal lobes. Increased rGMV of the bilateral striata may be associated with higher creativity through an inferior irrelevant-information filtering system and comparable to an anatomical study of psychosis. One interesting characteristic of creative individuals is their inability to filter information that flows into their minds (inferior irrelevantinformation filtering system). This subject has been studied well with a dichotic listening paradigm (e.g. Rawlings, 1985; Dykes & McGhie, 1976). For example, Rawlings (1985) reported that when participants were told to shadow information in one ear in the dichotic listening task, but also to try to remember the information from the nonshadowed ear, creative individuals and subjects with schizophrenia and schizotypal disorder showed more intrusion errors on the shadowing task and a better memory for the secondary information. Previous neuroimaging studies revealed that the basal ganglia system (globus pallidum and less notably striatum) is the neural correlate of the irrelevant-information filtering system (McNab & Klingberg, 2007). A previous structural imaging study revealed that schizophrenic subjects show increased volume of the striatum (Siever & Davis, 2004), while an increased psychometric measure of intelligence is associated with decreased gray matter morphometry in the striatum. This contrasts with the positive correlation between

the PFC's gray matter morphometry and psychometric measures of intelligence (Frangou et al., 2004). Putting these together, increased rGMV in the striatum, which underlies the inferior irrelevant information filtering system and increased rGMV in the striatum, may be one of the common neural correlates of creativity and schizophrenia, both of which are characterized by an inferior irrelevant information filtering system. Perhaps, highly creative and cognitively intact subjects can find useful patterns among a disorienting barrage of seemingly irrelevant information and exert creativity. Our result regarding the significant positive correlation between rGMV in the cluster that included the mesencephalic dopaminergic system and creativity score is comparable to that of previous structural imaging studies that reported increased GMV in this region in relation with dopamine. A previous interventional study (SalgadoPineda et al., 2003) reported increased rGMV following levodopa administration, which is used for dopamine replacement therapy. Furthermore, other studies reported increased rGMV in this region in patients with Tourette's Syndrome, which is different from psychosis but is another disease whose symptoms are associated with excess function of the dopaminergic system; in this disease, the mesencephalic dopaminergic system is associated with the disease (Shapiro et al., 1989; Singer et al., 2002; Albin et al., 2003). These studies suggest that the morphology of the mesencephalic dopaminergic system is associated with dopamine function, and they further support the idea that creativity is associated with dopamine function, as described in the introduction. Furthermore, our results may indicate that the common involvement of increased rGMV in this region mediates the possible relationship between creativity and Tourette's syndrome (Sacks, 1992). Involvement of the anatomical cluster in the midbrain including the dorsal part of midbrain (PAG and reticular formation) with creativity is congruent with psychological studies that reported creativity is associated with trait anxiety, arousal, and psychiatric diseases like anxiety disorder and panic disorder. Reticular formation determines overall level of arousal and awareness (Carlson, 2001). On the other hand, creativity is associated with an individual baseline arousal level (Martindale, 1999). Thus, increased rGMV may affect the individual level of arousal, which in turn may affect creativity. The PAG is a major site for processing fear and anxiety (Behbehani, 1995), and rGMV of the PAG is increased in patients with panic disorder (Protopopescu et al., 2006). In addition, panic disorder together with anxiety disorder, is more often observed among creative individuals than normal subjects (e.g. Ludwig, 1994) and many people who are creative have high trait anxiety (Carlsson et al., 2000). Thus, increased rGMV of the PAG may mediate these associations between creativity and psychiatric diseases. Increased rGMV in the precuneus may be associated with higher creativity score as measured by the divergent thinking test through visual and mental imagery processes. Previous studies have shown the association between creativity and visual imagery (Finke, 1996). Also, rGMV in the precuneus has been implicated in visual and mental imagery (see review for Cavanna & Trimble, 2006). Thus, one simple interpretation of our results in the precuneus is that developed regional gray matter in this region underlies clear visual imagery, which helps the imagination in creative thinking. Increased rGMV in the insula may be associated with higher creativity scores as measured by the divergent thinking test through facilitation of linguistic output. In this study, only when the analysis was limited to males, rGMV in the left anterior insula positively correlated with creativity. However, whether this is a male specific association is not clear, considering a similar statistical tendency exists even when females are included in the study and considering the sample size of females in this study is limited to analyze sex specific relationship between rGMV and creativity. It has been pointed out that the anterior insula is involved with speech production (for a review, see Augustine, 1996) and non-fluent aphasia is associated

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with hypometabolism centered on the left anterior insula (Nestor et al., 2003). Furthermore, a deficit in the region involved with speech production has been associated with decreased creativity through decreased linguistic output and consequent depression (Flaherty, 2005). Thus, one simple interpretation of our results in the left anterior insula is that developed regional gray matter in this region underlies facilitated linguistic output, which helps creative production. Although, our results are congruent with the neuroscientific background of creativity, our results are partly different from recent studies investigating the anatomical and neurochemical correlates of creativity (Jung et al., 2009a, 2009b). The former studies investigated associations between cortical thickness and revealed that cortical thickness in regions such as the right angular gyrus positively correlates with measures of creativity and cortical thickness. Other regions, such as the orbitofrontal gyrus, negatively correlate with measures of creativity. The latter investigation revealed associations between a measure of creativity and concentrations of N-acetylasparate in the medial prefrontal cortex. These regions do not overlap regions identified as gray matter correlates of creativity in this study. Discrepancy in the results may stem from a number of differences in method, including psychological measures of creativity, spatial normalization approaches, smoothing, and gray matter indices (gray matter volume vs. cortical thickness). Another possible cause of discrepancy is the lack of statistical power in these and our studies to detect all the gray matter correlates of creativity, and the false negative results in these studies as well as our study may explain the discrepancy. For example, in our study there was a statistical tendency of correlation between creativity and rGMV in the right angular gyrus (x,y,z = 55, -51, 34, t = 3.93, p = 0.012 uncorrected for multiple comparisons at the non-isotropic adjusted cluster level, with an underlying vowel level of P b 0.005 uncorrected). In this study, we revealed the relationship between brain structure and creativity, and discussed it mainly in terms of dopamine and psychopathology. But, we believe we only revealed parts of the complex associations between brain structure and creativity. Creativity is a set of complex cognitive functions as described above. The dopaminergic system itself is complex and there is an inverted U-shaped relationship between the amount of dopamine receptor stimulation and its effect on performance (Cools, 2008). Also creativity is associated with diverse psychopathological conditions, as was briefly introduced in this paper. Finally, the relationship between cognitive functions and brain structures, such as rGMV, is sometimes not expressed by a simple linear relationship, and also those relationships are affected by age (e.g. Shaw et al., 2006). Our approach was limited because of a few factors. We didn't measure dopamine-related-functions, and we used young healthy subjects with high-level educations; thus our interpretations have a certain limitation. Focusing on highly intellectual subjects was certainly warranted for the purpose of this study, given the correlation between intelligence and creativity among subjects with normal and inferior intelligence (Sternberg, 2005). We also had to exclude the effect of intelligence on rGMV. It may be productive to reveal the effect of dopamine function on brain structure or the details of other complex associations described above in future studies. In addition, our study population was unbalanced towards males because the parent population was unbalanced towards males and it was hard to gather female subjects. Thus we did not and could not investigate the sex-specific relationship between regional gray matter volume and creativity. Previous VBM studies have shown differences both in regional gray matter volume between males and females (Cahill, 2006) and in the relationship of regional gray matter volume to cognitive function (Haier et al., 2005). It is possible that the relationship between regional gray matter structure and creativity differ between females and males. Furthermore, an unbalanced sex ratio might introduce a bias in the downstream analysis.

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Finally, VBM has been criticized because of a few methodological limitations. First, spatial normalization in VBM cannot perfectly register individuals (Nieto-Castanon et al., 2003) and VBM cannot comprehensively differentiate changes in tissue content from local misregistration of images (Bookstein, 2001). Second, VBM as currently implemented also assumes simple linear relationships that are qualitatively similar throughout the brain, and it thus may be insensitive to other types of relationships (Davatzikos, 2004). Although the theory behind these criticisms is correct, it has been pointed out that these caveats appear to have limited applicability to real imaging data (Ashburner and Friston, 2001). Furthermore, direct comparisons have shown that VBM produces data that is comparable with that of ROI analyses (Good et al., 2002; Testa et al., 2004). Acknowledgments We thank Y. Yamada for operating the MRI scanner, M. Asano, H. Ambo, and J. Tayama for helping find the testers for the psychological tests, the participants, and testers for the psychological tests for their participation in this study, and all our other colleagues in IDAC, Tohoku University for their support. This study was supported by JST/RISTEX, JST/CREST. Appendix A This appendix presents sample answers to a problem in the S-A creativity test, and the manner in which they were scored. Sample question: ‘Other than for storing milk, how can we use milk bottles? Sample answers: 1. 2. 3. 4. 5. 6.

Make a hole in it and use it as a coin bank.” Use it as a weight. Use it as an instrument. Use it as an object for shooting. Beat on it and make a sound. Eat it. The manner in which they were scored is as follows. (1) Inappropriate answers were excluded. In this case, the sixth answer (Eat it) was excluded. (2) If the answer is included in categories on the criteria table, the answer is categorized and elaborate scoring is performed based on the table. Each category has an originality score. In the criteria table, the score is determined on the basis of how rare the category of certain answers is (If the category of a certain answer appears in more than 5 % of the answers, the category has 0 originality points. If the category of a certain answer appears in less than 5%, but more than 1 % of the answers, the category has 1 originality point. If the category of a certain answer appears in less than 1 % of the answers, the category has 2 originality points.). (3) If the answer is not included in the categories on the criteria table, and if it cannot be considered to belong to the same category as any of the other answers that are not included in the categories on the criteria table, then it is categorized as a new category and scoring of Elaboration score is performed in a similar manner to that of the criteria table. Scores of each answer are as follows. (1) Make a hole in it and use it as a coin bank.” Category: To use it as a vessels Originality of the category = 0, Category number = 1, Elaboration = 2 (2) Use it as a weight. Category: To use it as a measure or to use its shape or weight Originality of the category = 1, Category number = 2, Elaboration = 1

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