Neuroanatomy of creative achievement

Journal Pre-proof Neuroanatomy of creative achievement Christopher J. Wertz, Muhammad O. Chohan, Ranee A. Flores, Rex, E. Jung PII:

S1053-8119(19)31078-X

DOI:

https://doi.org/10.1016/j.neuroimage.2019.116487

Reference:

YNIMG 116487

To appear in:

NeuroImage

Received Date: 1 August 2019 Revised Date:

12 December 2019

Accepted Date: 20 December 2019

Please cite this article as: Wertz, C.J., Chohan, M.O., Flores, R.A., Jung, R.,.E., Neuroanatomy of creative achievement, NeuroImage (2020), doi: https://doi.org/10.1016/j.neuroimage.2019.116487. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Inc.

Neuroanatomy of Creative Achievement

1 2

Christopher J. Wertz1, Muhammad O. Chohan1, Ranee A. Flores1, Rex, E. Jung1

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1

University of New Mexico Department of Neurosurgery. Albuquerque, NM USA

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Abstract Very few studies have investigated neuroanatomical correlates of “everyday” creative

9

achievement in cohorts of normal subjects. In previous research, we first showed that scores on

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the Creative Achievement Questionnaire (CAQ) were associated with lower cortical thickness

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within the left lateral orbitofrontal gyrus (LOFG), and increased thickness of the right angular

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gyrus (AG) (Jung et al., 2010). Newer studies found the CAQ to be associated with decreased

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volume of the rostral anterior cingulate cortex (ACC) (Chen, et al., 2014), and that artistic and

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scientific creativity was associated with increased and decreased volumes within the executive

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control network and salience network (Shi et al., 2017). We desired to replicate and extend our

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previous study in a larger cohort (N=248), comprised of subjects studying and working in

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science, technology, engineering, and math (STEM). Subjects were youn (Range = 16-32; Mean

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age = 21.8; s.d. = 3.5) all of whom were administered the CAQ from which we derived artistic

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and scientific creativity factors. All subjects underwent structural MRI on a 3 Tesla scanner from

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which cortical thickness, area, and volume measures were obtained using FreeSurfer. Our results

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showed mostly cortical thinning in relation to total, scientific, and artistic creative achievement

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encompassing many regions involved in the cognitive control network (CCN) and default mode

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network (DMN).

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Introduction

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The science of creative cognition has branched off from broad, behaviorally directed

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studies initially investigating convergent and divergent thinking, (Sternberg & Lubart, 1999;

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Torrance, 1976), to more specific studies designed to measure the construct of creativity and how

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it is manifested in the structure and function of the brain. Currently, creative cognition is broadly

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measured through three domains, creative potential (an individual’s cognitive ability to create

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something that is both novel and useful (Jauk, Benedek, & Neubauer, 2014; Stein, 1953),

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everyday creativity (a regular individual’s ability to create something original in everyday life,

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(Richards, 2010) and creative achievement (an individual’s real-life creative contribution, such

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as writing a screenplay for a film (Carson, Peterson, & Higgins, 2005). The creativity field

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further dissects these constructs, with several domains of assessing creative novelty such as

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divergent thinking, fluency, imagery, reasoning, and insight. Research consistencies regarding

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neural correlates within these creative fields remains sparse and inconclusive, largely lacking

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consensus or replication (Arden, Chavez, Grazioplene, & Jung, 2010; Beaty, Nusbaum, & Silvia,

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2014). The question remains: what best measures certain people’s proficiency to produce work

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that is both novel and useful, and how is this manifested in their brain structure and function?

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Creative achievement driven tasks are a construct of creative cognition that objectively

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measures individuals’ ability to produce work that is both novel and useful (Simonton, 2012).

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The Creative Achievement Questionnaire (CAQ; Carson et al., 2005) offers a reliable (0.81) and

44

valid measure of real-life creative productivity across ten specific domains ranging from culinary

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prowess to scientific innovations. The CAQ is well correlated with measures of divergent

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thinking such as originality and fluency and, while divergent thinking tests predict creative

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success (Torrance, 1988), they are limited in their ability to predict real-life applications. While

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the objective consensus of the CAQ is a considerable strength, one major problem in using the

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CAQ is that scores are always highly skewed. For example, few people in a normal, non-

50

eminent, sample will have higher scores than the average (of zero). Those few people, however,

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have accomplished real-life creative contributions of novelty or usefulness as evidenced by

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patents, published works, and awards. Higher scores on CAQ are therefore eliciting the desired

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effect in researching creative cognition manifested in creative products in the world recognized

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by others in terms of their novelty and utility.

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Recent behavioral research on creative achievement has found it to be moderately

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correlated with intelligence – as measured by the intelligence quotient (IQ) – and openness

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(Jauk et al., 2014), as well as artistic and scientific achievement (Kaufman et al., 2016). Another

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study, found that intentional mind wandering was predictive of greater creative achievement

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(Agnoli, Vanucci, Pelagatti, & Corazza, 2018). Relatively few studies have been conducted

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regarding neuroanatomical correlates of creative achievement. Jung et al., first showed that

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individuals with higher scores on the CAQ had lower cortical thickness within the left lateral

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orbitofrontal gyrus (LOFG), and increased thickness of the right angular gyrus, (Jung et al.,

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2010). Subsequent studies demonstrated that the CAQ was associated with increased cortical

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volume of the superior frontal gyrus, ventromedial prefrontal cortex and decreased volume in the

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dorsal and rostral anterior cingulate cortex (ACC), (Chen et al., 2014). Shi et al., further parsed

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two major domains of the CAQ by extracting artistic and scientific factors (Carson et al., 2005;

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Kaufman et al., 2016). They found that decreased volume in the supplementary motor area and

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ACC was associated with artistic creativity, while increased volume in the middle frontal gyrus

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and inferior occipital gyrus was associated with scientific creativity, (Shi, Cao, Chen, Zhuang, &

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Qiu, 2017). Functional connectivity studies using CAQ have found networks negatively

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correlated with medial superior frontal gyrus, middle frontal gyrus, orbitofrontal insula, thalamus

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(Chen et al., 2014). There is no commonality of findings to report across studies, and differences

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could be attributed to methodological differences between studies (the last two of which are from

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the same experimental cohort), including: restriction of creative range, use of different

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covariates, and unbalanced sex distributions.

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Our current study was designed to replicate and extend our previous research by looking

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at CAQ scores in a larger independent healthy young sample across cortical thickness, surface

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area and volume. We also investigated the artistic creativity and scientific two factor model

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suggested by (Carson et al., 2005) and explored by (Shi et al., 2017). Previous research has

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shown both increased and decreased volumes across the salience, executive, default mode

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network (DMN), and cognitive control network (CCN) in relation to high creativity scores

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(Beaty, Christensen, Benedek, Silvia, & Schacter, 2017; Jung, Mead, Carrasco, & Flores, 2013).

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We, therefore, predict findings to be associated with the CCN and DMN, specifically, increased

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gray matter in areas of the superior parietal cortex and decreased prefrontal frontal areas with

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CAQ total. Based on previous work using the CAQ two factor model, we predict similarly

86

decreased gray matter in the ACC with artistic creativity and increased gray matter in the parietal

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cortex as well as the caudal middle frontal gyrus.

88 89

Methods

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Two hundred and sixty science, technology, engineering and mathematics (STEM)

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subjects either working in the field or studying within STEM fields were recruited for the current

92

study. Six subjects were excluded based on missing behavioral data and six subjects were

93

excluded due to incidental MRI findings (e.g., arachnoid cyst), leaving a sample of two hundred

94

and forty-eight.

95

Subjects ranged from (16-32) years of age (21.8 ± 3.5 years), and were well matched by sex (127

96

males, 121 females). They were recruited by postings in various departments and classrooms,

97

around the University of New Mexico, local high schools and various professional STEM related

98

businesses. All subjects signed a consent form approved by the institutional review board of the

99

University of New Mexico prior to participation. Prior to entry into the study, subjects were

100

screened and met no criteria for neurological and psychological disorders that would impact

101

experimental hypotheses (e.g., learning disorders, traumatic brain injury, major depressive

102

disorder). Subjects were also screened for conditions that would prohibit undergoing an MRI

103

scan (e.g., orthodontic braces, claustrophobia). Subjects were compensated $100 for undergoing

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four hours of cognitive testing, encompassing measures of intelligence, creativity, problem

105

solving, personality, and aptitude, as well as a 30-minute MRI.

106 107

Behavioral Measures

108

All subjects completed the CAQ, a reliable and valid measure of creative achievement across 10

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domains including visual arts, music, creative writing, dance, drama, architecture, humor,

110

scientific discovery, invention, and culinary arts. In each domain the subject places a checkmark

111

next to a concrete achievement. Each domain has a potential point range of 0-7. Several items if

112

checked were denoted with an asterisk where the subject was required to indicate how many

113

times each achievement occurred (e.g., “I have been published in scientific journals”) and then

114

multiplied by item number. The CAQ total score is tallied by summing across the ten domains. A

115

two-factor model was created based on Carson et al., dividing the ten domains into a science and

116

art total score, (Carson et al., 2005). Creative achievement in the arts represented the sum of

117

scores for drama, humor, music, dance, visual arts, creative writing, and theater/film. Creative

118

achievement in the sciences represented the sum of inventions and scientific discovery.

119

To assess general intelligence, subjects were administered the Wechsler Abbreviated

120

Scale of Intelligence (WASI-II). The WASI battery consists of subtests that measure verbal and

121

non-verbal mental abilities that contribute to general intelligence. We derived a Full-Scale

122

Intelligence Quotient (FSIQ) score from performance on the subtests of similarities, matrix

123

reasoning and block design.

124 125

Neuroimaging

126

Structural imaging was obtained at a 3 Tesla Siemens scanner using a 32-channel head coil to

127

obtain a T1 5 echo sagittal MPRAGE sequence [TE = 1.64 ms; 3.5 ms; 5.36 ms; 7.22 ms; 9.08

128

ms; TR = 2530 ms; voxel size = 1.0×1.0×1.0 mm3; FOV = 256 mm; slices = 192; acquisition

129

time = 6:03]. For all scans, each T1 was reviewed for image quality. Cortical reconstruction and

130

volumetric segmentation were performed with the FreeSurfer-v5.3.0 image analysis suite. The

131

methodology for FreeSurfer is described in full in several papers (Fischl et al., 2002, 2004;

132

Ségonne, Pacheco, & Fischl, 2007). Briefly, this process includes automated Talairach

133

transformation, segmentation of the subcortical white matter and deep gray matter volumetric

134

structures, (Fischl et al., 2002, 2004). Segmented data were then parceled into units based on

135

gyral and sulcal structure, resulting in values for cortical thickness, surface area, and volume

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(Desikan et al., 2006; Fischl et al., 2004). The results of the automatic segmentations were

137

quality controlled, and any errors were manually corrected. Volume measures are a combination

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of thickness (a one-dimensional measure) and area (a two dimensional measure) across 33

139

measures per hemisphere (i.e., 66 across the surface of the brain) as well as seven subcortical

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volumes per hemisphere (i.e., 14 across the brain) including bilateral caudate, putamen, globus

141

pallidus, nucleus accumbens, thalamus, amygdala, and hippocampus (Fischl et al., 2002).

142 143

Statistical Analysis

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General linear models were used to assess correlations with CAQ total, art total, and science total

145

scores with cortical volume, area, and thickness. This type of analysis was performed by the

146

Query, Design, Estimate, Contrast (QDEC) interface within FreeSurfer. First, each subject’s

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surface was smoothed using a full-width/half-maximum gaussian kernel of 10 mm. This

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smoothing was done so that all subjects in this study could be displayed on a common template,

149

which is an average brain in Talairach space. Each design matrix consisted of either CAQ total,

150

art total, or science total raw scores as the independent variable and sex, age, FSIQ and the

151

FreeSurfer calculation of total brain volume categorized as BrainSegVolNotVent as covariates

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and the slope used was different offset/intercept, different slope (DODS).Correction for multiple

153

comparisons was performed using a Monte Carlo Null-Z simulation method. For these analyses,

154

a total of 10,000 simulations were performed for each comparison, using a threshold of p = 0.05.

155

This is the probability of forming a maximum cluster of that size or larger during the simulation

156

under the null hypothesis and presents the likelihood that the cluster of vertices would have

157

arisen by chance. Multiple regressions were performed on subcortical volume measures, against

158

each factor (CAQ, art, science total scores), controlling for total brain volume, age, sex and

159

FSIQ. We used R version 3.5.3 for Windows for all behavioral statistical analysis.

160 161

162 163

Results CAQ total score, art total, and science total were all highly skewed and therefore any

164

outliers greater than three standard deviations from the mean were excluded by variable.

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Behavioral characteristics are presented in Table1). Previous studies on creative achievement

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have specifically found it to be moderately correlated with intelligence. In our sample,

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CAQ total was weakly correlated with FSIQ (r = 0.06, p = 0.35). As expected, the art factor

168

score was weakly correlated with FSIQ (r = 0.004, p = 0.95) and the science factor was

169

significantly correlated with FSIQ (r = 0.13, p = 0.05). Our sample was selected to sample

170

STEM populations, among whom CAQ-IQ scores are known to be more highly correlated;

171

therefore, controlling for IQ was deemed necessary for accurate interpretation of results. It

172

should be noted, when we ran the same analyses without controlling for IQ, CAQ total did

173

not have any significant associations with cortical structures, artistic creativity findings

174

remained the same, and scientific creativity retained largely the same findings except for

175

right hemisphere postcentral, and precentral regions. The significant associations remained

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negative, which is consistent with findings when controlling for IQ.

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Subcortical Analysis

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A series of multiple regression analyses investigated subcortical volume correlates with CAQ

179

total, art total and sci total. We regressed all subcortical volume measures, against each measure

180

controlling for total brain volume, age, sex and FSIQ. CAQ total score was predicted by a model

181

that included increased left hippocampus and increased posterior corpus callosum volumes (F =

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3.1, p = 0.006; r2 = 0.07). A model including decreased left amygdala and increased left caudate

183

volume predicted artistic creativity total score (F = 2.24, p = 0.040; r2 = 0.05). Scores on

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scientific creativity factor were predicted by a model including increased mid-anterior corpus

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callosum and decreased left thalamus volumes (F = 8.41, p <0.001; r2 = 0.18).

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Behavioral Demographics

Mean

Std. Dev.

Range

FSIQ

111.6

11.9

80-153

CAQ Total

16.7

14.9

0-74

CAQ Art

9.6

9.8

0-66

CAQ Science

4.3

5.1

0-24

187 188

Table 1. Descriptive statistics of participant’s demographics and behavioral measures.

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Cortical Analysis

190

CAQ Cortical Analysis

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The results of whole brain cortical analysis with CAQ total score showed significantly decreased volume

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in the left insula extending into the superior temporal gyrus after multiple comparisons correction (p <

193

0.05). Table 2 and Fig.1 present the results of the statistical maps and linearity. r = -0.114

194

L L Insula Volume

195 196 197

CAQ Volume

198 199 200

-5.00 -2.50 0.00

2.50

5.00

CAQ_Total

201 202 203

Figure 1. Statistical map showing significantly decreased cortical volume with CAQ total scores overlaying the Desikan-Killianey atlas.

Cortical Surface

Max

Size(mm2)

TalX

TalY

TalZ

CWP

Vtxs

Gyrus

Volume

-2.704

1137.90

-36.6

-5.6

-10.3

0.03960

2250

insula

204 205 206 207 208

Table 2. Creative Achievement Questionnaire: Regions surviving Monte Carlo simulation (p < 0.05). Size (mm2) = size of region in square millimeters; TalX = Talairach region X plane; TalY = Talairach region Y plane; TalZ = Talairach region Z plane; CWP cluster-wise probability; Vtxs = number of contiguous vertices.

209

Artistic Creativity Cortical Analysis

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The results of whole brain cortical analysis with CAQ artistic creativity total score showed significantly

211

decreased thickness in the left superior temporal gyrus extending into the middle temporal gyrus and right

212

superior parietal gyrus, after multiple comparisons correction (p < 0.05). Table 3 and Fig.2 present the

213

results of the statistical maps and linearity.

214 215 216

219 220 221

-5.00 -2.50 0.00

2.50

R Superior Parietal

218

5.00

CAQ Artistic Creativity

222 223 224

r = -0.153

r = -0.102

L Superior Temporal

217

R Thickness

L Thickness

Figure 2. Statistical maps showing significantly decreased cortical thickness with artistic creativity overlaying the Desikan-Killianey atlas.

225 Cortical Surface

Max

Size(mm2)

TalX

TalY

TalZ

CWP

Vtxs

Gyrus

Thickness

-2.871

1583.53

-44.7

5.9

-19.8

0.00580

3233

LH superior temporal

Thickness

-2.883

536.50

24.1

-73.3

32.2

0.02050

769

RH superior parietal

226 227 228 229 230

Table 3. Creative Achievement Factor Artistic Creativity: Regions surviving Monte Carlo simulation (p < 0.05). Size (mm2) = size of region in square millimeters; TalX = Talairach region X plane; TalY = Talairach region Y plane; TalZ = Talairach region Z plane; CWP cluster-wise probability; Vtxs = number of contiguous vertices.

231

Scientific Creativity Cortical Analysis

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The results of whole brain cortical analysis with CAQ scientific creativity total score showed significantly

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decreased surface area in the left insula gyrus extending into regions of the superior temporal gyrus,

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transverse temporal gyrus, and another significant region in the precentral and postcentral gyrus. In the

235

right hemisphere we found significantly decreased area in numerous regions of the brain including left

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superior frontal gyrus extending into the caudal middle frontal gyrus, middle temporal gyrus extending

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into the superior temporal gyrus, cingulate gyrus, and pars-opecularis gyrus extending into the insula and

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precentral gyrus. We also found a sole positive significant correlation in the right hemisphere postcentral

239

gyrus extending into the superior parietal gyrus with volume, after multiple comparisons correction (p <

240

0.05). Table 4 and Fig. 3 and 4, present the results of the statistical maps and linearity.

R Are L Insula area

242 243 244 245

r = -0.149

r = -0.122 R Superior Frontal area

L 241

246 -5.00 -2.50 0.00

247 248 249

2.50 5.00

CAQ Scientific Creativity

Figure 3. Statistical maps showing significantly decreased cortical surface area with scientific creativity overlaying the Desikan-Killianey atlas.

L

R Postcental Volume

r = 0.196

-5.00 -2.50 0.00 2.50 5.00

CAQ Scientific Creativity 250 251 252

Figure 4. Statistical maps showing significantly increased cortical volume with scientific creativity overlaying the Desikan-Killianey atlas.

Cortical Surface

Max

Size(mm2)

TalX

TalY

TalZ

CWP

Area

-3.871

3138.68

-33.7

-8.8

9

0.00010

7748

LH insula

Area

-3.131

1178.73

-19.3

-21.2

55.6

0.01860

2851

LH precentral

Area

-3.617

1756.45

19.8

25.3

41.1

0.00110

3149

RH superior frontal

Area

-3.228

1583.37

44

-26.7

-3.5

0.00280

3214

RH superior temporal

Area

-3.169

1118.04

48.1

-0.6

9.4

0.03150

2786

RH precentral

Area

-2.624

1225.18

9.1

-31.5

27.8

0.01810

3009

RH isthmus cingulate

Volume

4.248

639.44

16.4

-28.8

69.1

0.00770

1595

RH postcentral

Vtxs

Gyrus

253 254 255 256

Table 4. Creative Achievement Factor Scientific Creativity: Regions surviving Monte Carlo simulation (p < 0.05). Size (mm2) = size of region in square millimeters; TalX = Talairach region X plane; TalY =

257 258

Talairach region Y plane; TalZ = Talairach region Z plane; CWP cluster-wise probability; Vtxs = number of contiguous vertices.

259

Discussion

260

The current study sought to replicate and extend our previous cortical structural findings

261

by exploring the relationship with creative achievement in a normal non-eminent sample. Our

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results failed to replicate our previous findings of decreased cortical thickness in the left

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orbitofrontal cortex or increased thickness in the right angular gyrus. We adopted a more

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complex analysis strategy involving thickness, area, and volume, and instead discovered several

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new brain regions, where highly creative individuals exhibited cortical structural differences,

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across a wide network previously implicated in creativity research. Indeed, we found numerous

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regions to overlap both the DMN (bilateral superior temporal gyri and isthmus cingulate gyrus)

268

and CCN (insula, superior parietal and preSMA). Perhaps more surprisingly, we only found

269

increased volume in relation to scientific creativity in the right postcentral gyrus.

270

The general pattern across morphological studies within the creative achievement

271

tends to show decreased volume (particularly within the DMN) more than increased

272

volumes (Jung et al., 2013). It has been hypothesized that cortical thinning represents greater

273

efficiency and lower levels of plasticity the more proficiently one acquires a particular skill (Jung

274

et al., 2010). However, studies looking at creative potential prominently find increased

275

volume in several areas including the bilateral precuneus, posterior cingulate cortex and

276

the bilateral caudate (Fink et al., 2014; Jauk, Neubauer, Dunst, Fink, & Benedek, 2015).

277

Our results showed decreased volume to be associated with higher CAQ total scores in the left

278

insula extending into the superior temporal gyrus, and increased volume in the left hippocampus

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and posterior corpus callosum. The left hemisphere regions associated with CAQ, including the

280

insula and superior temporal gyrus have been shown to overlap with the DMN and salience

281

networks respectively (Beaty et al., 2017), and are implicated in fMRI studies looking at verbal

282

creativity (Boccia, Piccardi, Palermo, Nori, & Palmiero, 2015). Left insular activation was found

283

during a brainstorming task in a study looking at neuro-correlates of creative writing (Shah et al.,

284

2013). The left superior temporal lobe has been found to be active during imagination type tasks

285

(Huang et al., 2013), and decreased volume has been correlated with high imagination ability,

286

(Jung, Flores, & Hunter, 2016). Finally, research has demonstrated a role for the hippocampus in

287

creativity, as patients with lesions to the hippocampus are found to have lower scores on

288

measures of divergent thinking (Duff, Kurczek, Rubin, Cohen, & Tranel, 2013). Our finding of

289

increased volume in relation to creative achievement in the posterior corpus callosum is in

290

contrast to other studies finding an inverse relationship in size with higher divergent thinking

291

scores (Gansler et al., 2011).

292

Within the artistic creativity measure we found an inverse relationship with thickness in

293

the left superior temporal gyrus extending into the middle temporal gyrus and right superior

294

parietal gyrus. As previously noted, the left superior-middle temporal gyrus is involved in verbal

295

creativity and imagination. The right superior parietal lobule is involved in mentally re-ordering

296

the sequence of visual stimuli, (Gansler et al., 2011). Zhu et al., found the bilateral superior

297

parietal cortex to be inversely associated with verbal and visual creativity (Zhu et al., 2017). We

298

also observed higher artistic creativity in relation to decreased left amygdala volume and

299

increased volume in the left caudate. The amygdala has been implicated in artistic creativity, is

300

associated with spontaneous and emotional functioning, and has been implicated in numerous

301

musical creativity studies (Bashwiner, Wertz, Flores, & Jung, 2016; McPherson, Barrett, Lopez-

302

Gonzalez, Jiradejvong, & Limb, 2016). Finally, increased left hemispheric activation in the left

303

caudate nucleus was observed in expert creative writers in contrast to non-experts (Erhard,

304

Kessler, Neumann, Ortheil, & Lotze, 2014). Within scientific creativity, we found several inverse relationships with surface area and

305 306

high scientific creative scores. We found significantly decreased surface area in the left insula

307

and precentral gyrus. Left precentral gyrus is activated during visuo-spatial creativity tasks

308

(Boccia et al., 2015). The insula is involved in general and fluid intelligence (Haier, Jung, Yeo,

309

Head, & Alkire, 2004; Woolgar et al., 2010). The right hemisphere findings revealed several

310

negative correlations in the superior frontal gyrus, which has also been found with higher

311

divergent thinking performance anticorrelated within the superior frontal regions. However,

312

other studies have found increased volume in right superior frontal gyrus to be correlated with

313

creativity and cognitive flexibility (Kühn et al., 2014). Scientific creative achievement is

314

hypothesized to rely more heavily on convergent thinking processes in the pursuit of solving one

315

specific goal. Indeed, many of our findings overlap with previous work with convergent

316

thinking. For example, Jung-Beeman et al., 2004 found that solving problems through a modified

317

form of Mednick’s test activated the right anterior superior temporal gyrus (Jung-Beeman et al.,

318

2004).

319

The literature regarding the neuroscience of creativity is in a nascent stage, characterized

320

by disparate and divergent findings across laboratories. Previous research within the

321

neuroscience of intelligence has found similar dissimilarities to be associated with such

322

seemingly subtle effects as those associated with analysis techniques and covariates chosen

323

(Martínez et al., 2017). Thus, it is not surprising that we have found results different from those

324

found previously, as such differences can be caused by different analysis packages, sample

325

characteristics, and covariates applied. Similarly, our sample focused on STEM subjects, while

326

previous samples looked at more broadly distributed subject cohorts. Finally, the interplay

327

between intelligence (or IQ) and creativity, is an important one, with the potential interaction

328

providing potential differences between studies that either use IQ as a covariate and those that do

329

not. A special issue has recently been published in Neuropsychologia with several perspectives

330

regarding the “common ground and differences” between these two cognitive constructs

331

(Benedek, Jung, & Vartanian, 2018). There are only a handful of studies in existence regarding

332

structural correlates regarding the CAQ, and further research in this area will be critical to

333

establish convergence over time, as has been evident in creative neuroscience more broadly

334

(Jung et al., 2013). However, as currently comprised, the literature regarding structural correlates

335

of the CAQ now shows both increased and decreased volume in relation to higher creative

336

achievement (Chen et al., 2014; Jung et al., 2010; Shi et al., 2017).

337

Previous studies in creativity neuroscience have implicated broad regions overlapping

338

significantly with the DMN (Bashwiner et al., 2016; Beaty, Benedek, Kaufman, & Silvia, 2015;

339

Kühn et al., 2014) and the CCN (Chrysikou, Weber, & Thompson-Schill, 2014; Li, Yang, Zhang,

340

Li, & Qiu, 2016). The current findings appear to conform with the hypothesis regarding dynamic

341

interplay between DMN and CCN (mediated by the SN) as our results implicated several areas

342

across these broad networks. Thus, these two specific subdomains of creativity require a

343

dynamic interconnection of the DMN and CCN in order to achieve success in the creative arts

344

and sciences.

345

There are several limitations to the current study. Our sample was restricted to a healthy

346

normal population and was focused on individuals expressing interest in scientifically inclined

347

students and professionals. While the CAQ is a valid and reliable measure of creative

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achievement, our sample, comprised of mostly college students, have had fewer opportunities to

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express their potential due to their relatively young age and low professional status. The CAQ is

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always skewed in its distribution, with occasional extreme outliers. We chose to remove such

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outliers (+3 s.d.) although these individuals could represent true creative accomplishment.

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Removing high achievers therefore could have impacted our results. We re-ran the analysis

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with those 6 outliers included in the sample and found significantly decreased surface area

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in the posterior cingulate gyrus. However, to have 6 subjects drive the overall relationship

355

would not, in our opinion, represent the balance of the findings across the remaining 248

356

subjects; therefore, we ultimately decided to remove them from the analysis. Future studies

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focused on such extreme outliers could be helpful in understanding brain organization in

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extremely high creative achievement. Finally, we failed to replicate the findings of both our

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previous study and that of another group, although we have provided several methodological

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reasons why the current results might differ. Future research will be necessary to support the

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relationships observed between brain structure and creative achievement. We would encourage

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researchers to use methods designed to parse cortical thickness, area, and volume (e.g.,

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FreeSurfer) as opposed to voxel intensities, the former of which, arguably, gets closer to

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biological variables of interest. We would further encourage researchers to include age, sex, total

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brain volume, and intellectual functioning (e.g., IQ). This last variable is particularly important

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to include as a covariate, given its significant relationship to variables of interest to creativity

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research (e.g., divergent thinking, CAQ), as well as established brain-IQ relationships which

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could potentially confound the variable of interest (R.E. Jung & Haier, 2007).

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