11 Creativity and Intelligence: Brain Networks That Link
and Differentiate the Expression of Genius
Rex E. Jung and Richard J. Haier
If you’re so smart, why aren’t you a genius? The simple answer is that
intelligence and creativity are not the same thing and genius apparently
requires both (Jensen, 1998). Psychology has a long history of discussing
this issue, and numerous distinctions have been hypothesized to augment
general definitions of intelligence, creativity, and genius. Empirical testing
of competing ideas, however, depends on measurement. Tests of intelli-
gence and tests of creativity evolved during the twentieth century and both
kinds of tests now have good psychometric qualities. Early research using
electroencephalographic (EEG) techniques and positron emission tomog-
raphy (PET) suggested that (1) intelligence and creativity test scores were
related to neural activity (i.e., excitation) in the frontal lobes and other
areas (with hemispheric differences), and that (2) less activity (i.e., neuro-
nal disinhibition) was related to higher scores for both concepts (see
Runco, 2004, for a review of creativity studies, and see Jung & Haier, 2007,
for a review of intelligence studies). Prior to the advent of neuroimaging
techniques, Eysenck (1995) formulated a theory of creativity and the brain
that proposed the importance of disinhibition (i.e., less neuronal activa-
tion), especially in the frontal lobes. Thus, while the interplay of both
neuronal excitatory and disinhibitory processes characterize studies of
creativity, the focus on neuronal disinhibition, particularly within the
frontal lobes, predates the advent of modern neuroimaging studies.
The widespread availability of sophisticated neuroimaging technologies
and analysis techniques allows new kinds of studies using psychometric
tools to investigate brain characteristics of both concepts. Now we can
address more complex questions. The ultimate aim is to determine the
specific neural networks that underlie intelligence and creativity, in their
various forms and especially as they relate to genius. Two key questions
are (1) whether, and to what extent, such networks overlap and (2) what
unique aspects of the network must be present which make the simultaneous
234 R. E. Jung and R. J. Haier
expression of intelligence and creativity (i.e., genius) relatively rare? These
questions and the implications of tentative answers are the focus of this
chapter. We will present a brain model for intelligence and a model for
creativity and discuss how genius may emerge from the overlapping and
unique aspects of these models.
Before we get to the brain models and the studies on which they are
based, we need to note two points. First is the emerging distinction, within
the cognitive neurosciences, between the association of regions of interest
with general cognitive functioning and the identification of brain net-
works subserving specific cognitive tasks. This is a rather subtle distinction,
but it is an important one for appreciating the potential interplay of intel-
ligence and creativity. Thousands of studies implicate various brain regions
as “central” to numerous cognitive tasks including working memory, visual
attention, episodic memory, and problem solving, to name a few. A review
paper of 275 brain imaging paradigms identified similar brain regions
activated during performance of such cognitive tasks (Cabeza & Nyberg,
2000). Several interesting generalizations emerged from this article: (1)
vastly different cognitive tasks (e.g., space perception, working memory)
engaged similar brain regions; (2) the anterior cingulate is engaged during
a wide range of “demanding” cognitive tasks involving “intention to act”
(or inhibition of action); and (3) contrary to popular belief, specific “brain
regions are not committed to specific functions.” We point to these
statements to illustrate the empirical basis for the shift away from the
phrenology-like idea of one brain area for one cognitive function to a
perspective that focuses on the many brain areas that work together in a
network. While we will be discussing particular regions of interest identi-
fied within individual studies, our overarching goal will be to forge a
network of prospective regions subserving intelligence, creativity, and
Second, predating neuroimaging, there is a long history within the
neurosciences of evaluating brain function through careful examination
of case studies and/or lesion analysis. This is due to the fact that, while
multiple brain areas might serve a given cognitive function, removal of
discrete brain region through disease or injury will reveal brain regions
critical to performance of such functions. Three iconic examples include
(1) Phineas Gage, who survived the passage of an iron rod through his
frontal lobes resulting in profoundly changed personality (Harlow, 1848);
(2) “Tan,” the description of whom led to the localization of expressive
speech areas of the brain (Broca, 1861); and (3) “H.M.,” whose bilateral
temporal surgical lesions led to heightened understanding of memory
Creativity and Intelligence 235
encoding (Scoville & Milner, 1957). Less frequently studied, although
equally important, were the brains of examples of extreme cognitive ability,
such as savant abilities of extraordinary memory or mathematical calcula-
tion and synesthesia (blending of senses such as seeing numbers as colors).
These studies suggest (1) that savant ability comes at the expense of “execu-
tive or integrative (brain) mechanisms” (Snyder & Mitchell, 1999) and (2)
that artistic and musical ability may appear suddenly after left temporal
degeneration (Miller, Boone, Cummings, Read, & Mishkin, 2000) and syn-
esthesia may appear after brain damage (Ro, et al., 2007).
In this chapter, we will review these case studies in more detail and then
review the brain imaging literature relevant to intelligence and creativity.
Our goal is to develop comparative brain models. With a few exceptions,
these reports address either creativity or intelligence. However, we start
with the one major example in the neurological annals who provides
important clues regarding the trifecta of intelligence, creativity, and genius:
A Case Report of Genius
Albert Einstein is perhaps the most revered intellectual icon of the twen-
tieth century, and one of the few figures of human progress for whom we
have retained the brain for scientific study. In his “golden year” he pro-
duced four stunning papers, covering Brownian motion (Einstein, 1905b),
the special theory of relativity (Einstein, 1905d), statistical mechanics
(Einstein, 1905a), and the photoelectric effect (Einstein, 1905c), out of
which his most famous postulate emerged (E = mc2), arguably the most
recognizable formula representing applied genius in human history. He
was sympathetic to the notion of scientific research on his brain, and
underwent EEG recordings during his life. Einstein died on April 18, 1955,
at the age of 76 from a ruptured aortic aneurysm, mentally adept to the
end. His brain was removed on the morning of his death by Thomas S.
Harvey, a pathologist at Princeton Hospital, with the consent of the family
(Brian, 1996) and the estate executor (Highfield & Carter, 1993). The brain
was photographed, measured with calipers, weighed, fixed in formalin for
several months, and subsequently sectioned into about 240 blocks, each
consisting of 10 cm3 of tissue, and embedded in celloidin (Witelson, Kigar,
& Harvey, 1999). The brain was described as unremarkable in appearance,
and the weight (1,230 grams), length (17.2 cm left/16.4 cm right), and
width (7.5 cm left/7.5 cm right) of the cerebral hemispheres were all within
236 R. E. Jung and R. J. Haier
the average range for men his age (Anderson & Harvey, 1996). The travels
and travails of Einstein’s brain following removal are described elsewhere
(Abraham, 2002; Paterniti, 2000), and following several inquiries to Dr.
Harvey regarding the results of the analysis of Einstein’s brain (“Brain of
Einstein continues peregrinations,” 1981; “Brain that rocked physics rests
in cider box,” 1978), other research reports eventually followed.
More detailed morphological characteristics of Einstein’s brain were
systematically compared to the brains of thirty-five male controls (mean
age = 57+/–11; mean full scale intelligence quotient (FSIQ) = 116) possess-
ing normal neurological and psychiatric status (Witelson et al., 1999).
While Einstein’s brain weight was significantly lower than that of a younger
control cohort (1,230 cm versus 1,400 cm), no differences were observed
on measures of corpus callosum area, frontal lobe, and temporal lobe mor-
phology. However, the parietal operculum was not present in Einstein,
resulting in a larger expanse of the inferior parietal lobule, extending some
15 percent wider than similar regions of the controls. This unique mor-
phology, found in none of the control subjects, resulted in a supramarginal
gyrus undivided by a major sulcus (figure 11.1). The inferior parietal lobule
is associated with visuospatial cognition, mathematical reasoning, and
imagery of movement (Crammond, 1997), and its expansion was also
noted in other cases of prominent physicists and mathematicians (Spitzka,
1907). The authors of this comparative study of Einstein’s brain note that
“variation in specific cognitive functions may be associated with the struc-
ture of the brain regions mediating those functions” and conclude that the
parietal lobule may be implicated in visuospatial intelligence (Witelson
et al., 1999, 2152).
Two other studies of Einstein’s brain investigated whether differences
at the cellular level (e.g., neuron/glia) could explain his genius (Anderson
& Harvey, 1996; Diamond, Scheibel, Murphy, & Harvey, 1985). The first
study used the blocks of tissue obtained from frontal and parietal regions,
bilaterally, comprising superior prefrontal and inferior parietal association
cortices. These regions of Einstein’s brain were compared to eleven controls
ranging in age from 47 to 80 years, obtained from a Veteran’s Administra-
tion (VA) hospital and fixed in a manner similar to those obtained from
Einstein. Cell counts were made of neurons, astrocytes, and oligodendro-
cytes, from which a neuronal-to-glial ratio was computed. Glial cells
provide metabolic support (i.e., nutrition) to neurons. Results indicated
that, compared to controls, Einstein had significantly fewer neurons per
glial cells in the left inferior parietal cortex, which the authors interpreted
to suggest “a response by glial cells to greater neuronal metabolic need”
Creativity and Intelligence 237
Photographs of Einstein’s brain (adapted from Falk, 2009). (A) Dorsal view, (B) left
lateral view, (C) right lateral view. Sulci: angular (a2), anterior occipital (a3), ascend-
ing limb of the posterior Sylvian fissure (aSyl), central fissure (red lines), diagonal
(d), descending terminal portion of aSyl (dt), inferior frontal (fi), middle frontal (fm),
superior frontal (fs), horizontal limb of the posterior Sylvian fissure (hSyl), intrapa-
rietal (ip), precentral inferior and superior (pci, pcs), marginal precentral (pma),
medial precentral (pme), postcentral inferior and superior (pti, pts), ascending ramus
of Sylvian fissure (R), subcentral posterior sulcus (scp), middle temporal (tm), supe-
rior temporal sulcus (ts), unnamed sulcus in postcentral gyrus (u). Other features:
branching point between hSyl and aSyl (white dots, B), hand motor cortex knob (K,
shaded in A, C), termination of aSyl (white dots, S). With kind permission of Falk,
D. (2009). New information about Albert Einstein’s brain. Frontiers in Evolutionary
Neuroscience, 1(3): doi: 10.3389/neuro.18.003.2009.
238 R. E. Jung and R. J. Haier
(Diamond et al., 1985). In other words, Einstein had more glial cells per
neuron in this area, suggesting that these neurons might work harder or
more efficiently. The second study focused on determining the density of
a block of tissue from the right prefrontal association cortex, compared to
comparable regions from male controls aged 63 to 79 years. Results indi-
cated increased neuronal packing (i.e., the same number of neurons in a
smaller space), which the authors interpret as potentially “decreasing inter-
neuronal conduction time” and thus potentially facilitating cortical con-
nectivity (Anderson & Harvey, 1996). This would be consistent with greater
efficiency of brain processing in this region. Thus, these studies suggest
that Einstein’s brain differed from others in a frontal-parietal network.
Information processing in the left inferior parietal lobe (especially the
supramarginal gyrus) may have been more powerful and its integration in
the right prefrontal cortex may have been more efficient.
Numerous researchers have critiqued the studies of Einstein’s brain for
various methodological flaws (Galaburda, 1999; Hines, 1998) and, to be
sure, the comparison of one exceptional individual to various controls does
not lead definitively to localization of genius within the brain. Moreover,
not all areas of Einstein’s brain have been studied, and a network approach
calls for understanding how a key area in the parietal lobe is connected to
other areas. We also don’t know if the specific brain findings are related
to Einstein’s intelligence, his creativity, or to his genius.
Brain Networks of Intelligence from Imaging Studies: The P-FIT Theory
People differ in intellectual ability, and these differences are related to
features of the brain as determined by neuroimaging studies of the last
twenty-five years. We reviewed these studies in 2007; at that time there
were thirty-seven studies that used different imaging techniques and dif-
ferent measures of intelligence in samples of different sizes and composi-
tions (Jung & Haier, 2007). Some brain areas were implicated more often
than others across these studies. These areas were distributed across the
brain but were found mostly in parietal and frontal areas. We proposed the
parieto-frontal integration theory (P-FIT) of intelligence, which hypothe-
sized that efficient information flow among these areas, or subgroups of
these areas, was a basis for individual differences in intelligence. The P-FIT
model is shown in figure 11.2. This hypothesis recognizes that humans
gather and process information predominantly through auditory and/or
visual means (usually in combination)—thus the network involves a
sequence of seven broad information-processing events (shown below in
this paragraph in italics). At the start is processing of sensory information
Creativity and Intelligence 239
via the extrastriate cortex and fusiform gyrus, involving recognition and
subsequent imagery of visual input and analysis of auditory syntax input
in Wernicke’s area and surrounding regions. This basic sensory processing
is then fed forward to the angular, supramarginal, and inferior parietal
cortices, wherein structural symbolism and/or abstraction are generated and
manipulated. The parietal cortex then interacts with frontal regions that
serve to hypothesis test various solutions to a given problem. The anterior
cingulate is involved in response selection as well as inhibition of competing
responses. This process is critically dependent on the fidelity of underlying
white matter needed to facilitate rapid and error-free transmission of data
between frontal and parietal lobes. The P-FIT is a “network” perspective,
conforming to Cabeza and Nyberg’s (2000) nascent conceptualization that
several brain regions within more integrative “association zones” (i.e., not
strictly dedicated to sensory or motor functions) of the frontal and parietal
lobes function as cognitive “hubs” subserving multiple cognitive tasks.
Since our 2007 review, more than fifty additional imaging studies of
intelligence have been published, most supporting the P-FIT model (Deary,
P-FIT theory of intelligence. Numbers indicate Brodmann areas. Blue = left lateral-
ized; purple = bilateral; yellow arrow = arcuate fasciculus.
240 R. E. Jung and R. J. Haier
Penke, & Johnson, 2010). Importantly, these newer studies have become
more sophisticated. They have better image-analysis methods (Li, et al.,
2009; van den Heuvel, Stam, Kahn, & Pol, 2009), use multivariate com-
binations of test batteries to extract intelligence factors (Colom et al.,
2009), and now commonly have large samples of 100 or more subjects
(Tamnes et al., 2010). Developmental studies address P-FIT areas in chil-
dren and adolescents (Karama et al., 2009; Luders et al., 2011; Schmithorst,
2009), and also are increasingly investigating sex differences (Luders
et al., 2008; Tang et al., 2010). Genetic studies have determined that intel-
ligence and brain structures (i.e., gray and white matter) share common
genes (Bishop, Fossella, Croucher, & Duncan, 2008; Chiang et al., 2009;
Liu et al., 2010). The pace of research publications regarding intelligence
and the brain is increasing dramatically (Haier, 2009). These imaging
studies of intelligence and the P-FIT, along with the case study reports,
offer a framework for studies of creativity that may generate a comparable
brain network model.
Case Reports Regarding Creativity: Frontotemporal Dementia and Other
Neurological inquiries regarding creativity converge on the frontal lobes
and their inhibitory interactions with temporal, occipital, and parietal
lobes (TOP) (Flaherty, 2011; Heilman, Nadeau, & Beversdorf, 2003). This
convergence has arisen, at least in part, from several case reports of patients
having developed frontotemporal dementia (FTD) and subsequently expe-
riencing dramatically increased creative capacity (Miller et al., 1998). Ini-
tially, Miller and colleagues reported a few single case reports of creativity
in FTD. They subsequently reported that some 17 percent of their entire
cohort of sixty-nine patients diagnosed with FTD (twelve patients) exhib-
ited increased visual or musical creativity, and that damage to the left
temporal lobe and sparing of the frontal lobes was “a unifying feature of
the patients with ability” (Miller et al., 2000, 461). However, left temporal
lobe lesions are not exclusively associated with de novo artistic expression,
which has also been reported in right temporal lobe epilepsy (Mendez,
2005), a case of Parkinson’s disease treated with dopaminergic agonists
(Schrag & Trimble, 2001), a case of subarachnoid hemorrhage (Lythgoe,
Pollak, Kalmus, de Haan, & Chong, 2005), and in a case of insular ischemia
(Thomas-Anterion et al., 2010). Subsequent systematic study of artistic
ability associated with the various dementias found no general increase in
creativity to be linked with FTD (or semantic or dementia of the Alzheim-
Creativity and Intelligence 241
er’s type), with the authors noting that “despite the existence of these
isolated patients with increased artistic production, however, apathy
leading to diminished creativity is more clinically typical of patients with
FTD, suggesting that these case studies may be the exception rather than
the rule” (Rankin et al., 2007, 49). Thus, these cases suggest that damage
to the temporal lobe may be associated with increased artistic creativity in
only a very small number of people, but this may be an important clue.
Frontal lobe inhibition of the temporal lobe may play a key role, or it may
be an alternative pathway to increased creativity.
Neurologist Alice Flaherty has taken a further step in the conceptualiza-
tion of creative expression with a model of creative drive involving fron-
totemporal and dopaminergic control of idea generation (Flaherty, 2005).
She takes a neurological perspective, focused on the behaviors central to
creativity, and weaves together a compelling tapestry from careful study of
individual patients. The key features of this model include (1) incorpora-
tion of the limbic system as the “driver” of creative pursuits, (2) the notion
that creativity is domain independent (i.e., a common component spans
creative expressions as varied as artists, scientists, musicians, and so on),
and (3) a prediction of similar neurological underpinnings across normal
controls, psychiatric patients, and lesion patients. For example, patients
with temporal lobe epilepsy were often noted to have a strong drive to
write (called “hypergraphia”), also noted in some manic patients, as well
as in frontotemporal lobe dementia (FTLD). What these patients had in
common was dysfunction of the temporal lobe, which normally inhibits
frontal lobe functioning (Menzel et al., 1998). Thus, overt lesions or mild
dysfunction to the temporal lobes served to “disinhibit” frontal interac-
tions with other nodes (i.e., language/visuospatial) underlying behavioral
output, with right-hemisphere lesions producing higher incidence of
hypergraphia, and left lesions producing increased visual and musical
output. She also hypothesizes a role for dopamine in novelty-seeking and
goal-directed behavior (Mink, 1996). Finally, the frontal lobes are hypoth-
esized to block creative drive when lesioned or dysfunctional (e.g., in
depression, anxiety, Wernicke’s aphasia). What Flaherty’s model introduces
to the picture is the notion of mutually inhibitory nodes (i.e., frontal,
temporal, subcortical) within a network of brain regions subserving creativ-
ity. This model can be tested with neuroimaging.
Neuroimaging of Creativity and the “Frontal Disinhibition Model”
Brain studies of creativity have not advanced as rapidly as those of intel-
ligence, but results so far are informative and summarized in three recent
242 R. E. Jung and R. J. Haier
reviews (Arden, Chavez, Grazioplene, & Jung, 2010; Dietrich & Kanso,
2010; Sawyer, 2011). Arden et al.’s review of forty-five brain-imaging
studies of creative cognition did not reveal much consistency among
studies. Given the wide range of measures used to assess creativity and the
measurement error inherent across the various neuroimaging measures,
they conclude that “it is impossible to know whether any results should
be attributed to the measures, to the imaging modality or to unreliability
in one or both” (152). Dietrich and Kanso reviewed neuroimaging experi-
ments of divergent thinking, artistic creativity, and insight from sixty-three
research articles, including the forty-five papers reviewed by Arden et al.
(Dietrich & Kanso, 2010). They, too, found that “creative thinking does
not appear to depend on any single mental process or brain region, and it
is not especially associated with the right hemisphere, defocused attention,
low arousal, or alpha synchronization, as sometimes hypothesized” (845).
However, they did offer some general conclusions, albeit of a highly quali-
fied nature: “Tasks purportedly involving creative cognition induce changes
in prefrontal activity” (ibid.). These changes include both increases and
decreases, span all (or most?) of frontal lobe regions, and are not exclusive
to the frontal lobes; thus, creativity may not be either “localized” or even
“localizable.” Sawyer’s review of the cognitive neuroscience of creativity
similarly notes that (1) “the entire brain is active when people are engaged
in creative tasks,” (2) “left and right hemispheres are equally activated in
most creative tasks,” (3) and “the same brain areas are active that are active
in many everyday tasks” (149). All three reviews suggest that the construct
of “creativity” would benefit greatly from further parsing into subcompo-
nents from which more fine-grained cognitive neurosciences results might
emerge. However, all three reviews rely almost exclusively on functional
(i.e., EEG, functional magnetic resonance imaging [fMRI]) studies. All func-
tional imaging studies are influenced by task demands during image acqui-
sition. Thus, the inability to localize a network of underlying creativity
may have as much to do with methodological vagaries related to task and
acquisition techniques as with construct problems. Structural and lesion
studies avoid task demand problems.
Luckily for the construct of creativity, divergent thinking has long been
parsed into subcomponents comprised of fluency (i.e., the raw number of
items produced), flexibility (i.e., different conceptual categories produced),
and originality (i.e., novel responses produced). The notion of “originality”
permeates the creativity literature (Runco & Charles, 1993), and one recent
study provides important insights (Shamay-Tsoory, Adler, Aharon-Peretz,
Perry, & Mayseless, 2011). Forty patients with localized brain damage (i.e.,
Creativity and Intelligence 243
lesions) to various regions, and seventeen matched controls, completed
the Torrance Test of Creative Thinking and the Alternate Uses Test, both
reliable and valid measures of one aspect of divergent thinking. In those
subjects with medial frontal lesions, and particularly right medial frontal
lesions, originality scores (the “novel” part of “novel and useful”) across
measures were significantly reduced. Similarly, in those subjects with left
parietal lobe lesions, originality scores were significantly higher, even sig-
nificantly higher than normal control subjects. The authors interpret their
findings to support a right lateralized frontoparietal network of brain
regions supporting originality, with “lesions in the right hemisphere
(being) associated with impaired creativity, whereas damage to the left
hemisphere (being) associated with somewhat increased creativity.” Taken
together with the studies showing left temporal lobe degeneration associ-
ated with increased artistic and musical creativity in patients with FTD,
this study suggests that lower brain integrity within left hemisphere brain
structures—particularly left anterior temporal and inferior parietal lobes—
serves to “disinhibit” other brain regions associated with increased novelty
generation as measured by both artistic endeavors, and psychometric tests
of divergent thinking.
We recently completed three “structural” imaging studies of creative
cognition that have several advantages compared to the lesion studies
reviewed above: (1) they are applied to large (i.e., >50) samples of healthy,
young individuals; (2) they use reliable and valid measures of intelligence
(Wechsler Scales), creativity (i.e., Alternate Uses Test; Creative Achievement
Test), and personality (i.e., NEO-FFI) (Costa & McCrae, 1992); (3) they use
neuroimaging measures that are not dependent upon task-related func-
tional changes; and (4) they also assess “originality” as distinct from
“fluency” or “flexibility” factors of divergent thinking. In our first study,
we probed the relationship between creative cognition and concentration
of N-acetyl-aspartate, a marker of neuronal integrity, in a sample of fifty-six
healthy people using proton magnetic resonance spectroscopy (MRS)
(Jung, Gasparovic, Chavez, Flores et al., 2009). Three divergent thinking
tasks (i.e., Alternate Uses Test) were ranked by three judges to create a
creativity index using the consensual assessment technique (Amabile,
1982). N-acetyl-aspartate concentration was inversely correlated with cre-
ative cognition in the right anterior cingulate for high IQ subjects (>116
FSIQ), but positively correlated with creative cognition in the left anterior
cingulate for average IQ subjects (<116 FSIQ). This finding is consistent
with the notion of a threshold effect for creativity—high intelligence is
necessary but not sufficient for creativity.
244 R. E. Jung and R. J. Haier
In our second study, we assessed cortical thickness in a cohort of sixty-
one young adults, including the fifty-six from the spectroscopy study,
using both measures of divergent thinking and creative achievement (Jung,
Segall et al., 2010). We found cortical thickness in a region in the lingual
gyrus was negatively associated with a psychometric measure of creative
cognition, but was positively correlated with a different region in the right
posterior cingulate. On measures of creative achievement, less gray matter
volume in the left lateral orbitofrontal region was associated with higher
creative achievement, but higher volume in the right angular gyrus cor-
related with creative achievement.
In our third study, we examined white matter integrity with a technique
called diffusion tensor imaging (DTI), which measures the movement of
water through myelinated axons. In a sample of seventy-two healthy
young adults (including all of the previous subjects), we found an inverse
relationship between white matter “integrity” (measured as “fractional
anisotropy”) and creative cognition in numerous regions within the left
hemisphere, including the inferior frontal white matter and the superior
longitudinal fasciculus (Jung, Grazioplene, Caprihan, Chavez, & Haier,
2010). The same relationship appeared in a small region within the right
inferior frontal white matter and the anterior thalamic radiation. These
three structural studies point to a decidedly left lateralized, frontosubcorti-
cal, and disinhibitory network of brain regions underlying creative cogni-
tion and achievement. These areas are summarized in figure 11.3 as part
of the proposed F-DIM model of creativity. We describe this as a “model”
as opposed to the P-FIT “theory” because it is based on a relatively few
structural and lesion studies and is not readily testable until more experi-
mental studies yield theoretical congruence.
These studies suggest to us that “less is more” with regard to creative
cognition as measured by divergent thinking measures, particularly within
frontosubcortical networks hypothesized to be central to creativity by
several independent threads of thought (Dietrich, 2004; Flaherty, 2005;
Heilman et al., 2003). The brain networks involved are likely disinhibitory
in nature (Eysenck, 1995), with lesions and/or network degradation (i.e.,
cortical thinning, lower white matter coherence) located within a specific
network, producing increased behavioral output. Central aspects of the
network appear to include the frontal and temporal lobes, with cortical
“tone” being modulated via interactions between the frontal lobes, basal
ganglia and thalamus (part of the dopamine system) through white-matter
Creativity and Intelligence 245
The story with intelligence may be similar—greater gray matter and
better white-matter integrity go with higher scores but so does decreased
function, which may reflect greater efficiency. That is to say that for both
intelligence and creativity, we must look not only to increased neural tissue
or activity in key brain regions (e.g., frontal lobes), but perhaps also to
some mismatch between mutually excitatory and inhibitory brain regions
(e.g., temporal lobes) that form a network subserving such complex human
behaviors as creativity (e.g., planning, insight, inspiration). This notion of
a delicate interplay of both increases and decreases in neural mass, white-
matter organization, biochemical composition, and even functional activa-
tions within and between brain lobes and hemispheres is an important
concept. Indeed, it is the rare brain that has highly developed networks of
brain regions subserving intelligence (figure 11.2), and (concurrently) the
somewhat underdeveloped network of brain regions associated with disin-
hibitory brain processes associated with creative cognition (figure 11.3).
Such a finely tuned seesaw of complex higher and lower brain fidelity,
F-DIM model of creativity. Numbers indicate Brodmann areas. Blue = left lateralized;
green = medial; purple = bilateral; yellow arrow = anterior thalamic radiation.
246 R. E. Jung and R. J. Haier
balanced in dynamic opposition, would almost guarantee the rare occur-
rence of genius.
Why are we able to create a model for a network of creativity in the
brain whereas three reviews (including our own) failed to do so? There are
several reasons why the structural imaging and lesion studies might provide
a more coherent model. First, the “lesion” method of cognitive neurosci-
ence has long been considered the “gold standard” of methodology,
showing the critical node necessary to a given cognitive task (Broca, 1861).
Second, the “structural” techniques have all been demonstrated to have
extremely high levels of reliability as measured with interclass correlations,
with proton magnetic resonance spectroscopy being 0.98 (Gasparovic
et al., in press), diffusion tensor imaging being 0.80 (Danielian, Iwata,
Thomasson, & Floeter, 2010), and structural magnetic resonance imaging
(sMRI) being 0.96 (Wonderlick et al., 2009); a major review of functional
techniques (which predominated in the creativity reviews) revealed only
modest reliability of 0.50 (Bennett & Miller, 2010). Similarly, our model
focuses exclusively on measures of divergent thinking and achievement,
such as the multiple uses test and creative achievement questionnaire,
both of which have high reliability and validity (Domino & Domino,
2006). In contrast, many of the measures used in the creativity reviews
were “home grown,” extraordinarily diverse, and consisted of measures
with unknown (and unknowable) reliability and/or validity, such as (1)
composing a piece of music mentally (Petsche, 1996), (2) imagining a new
design for a pen (Kowatari, et al., 2009), or (3) developing hypotheses about
variations in quail eggs (Jin, Kwon, Jeong, Kwon, & Shin, 2006), to name
a few. The use of standardized measures of divergent thinking (i.e., multiple
uses test, Torrance Test of Creative Thinking), combined with lesion analy-
sis and/or reliable imaging methodology (e.g., MRS, DTI, sMRI, and even
fMRI), will help advance the field.
Brain Networks of Genius
Is There Brain Overlap for Intelligence and Creativity?
Given its rare and often idiosyncratic nature, it is not surprising that there
is no systematic study of genius in the brain imaging literature. Our brain
models of intelligence and creativity serve as a first approximation for
identifying networks possibly related to genius. Particular regions within
the network are customarily described in terms of Brodmann areas (BAs)
in reference to Korbinian Brodmann, who first created a detailed cartogra-
phy of the human brain in 1905 (Brodmann, 1905). Looking at figures
Creativity and Intelligence 247
11.2 and 11.3, a qualitative analysis would suggest overlap between the
P-FIT and F-DIM areas in four regions, including BAs 18/19 in the occipital
lobe, BA 39 (the angular gyrus) in the parietal lobe, and BA 32 (the anterior
cingulate gyrus) in the frontal lobe. Note that although there is overlap in
these relatively large areas, only the anterior cingulate appears to show a
consistent picture of higher fidelity associated with higher ability for both
intelligence and creativity.
The anterior cingulate gyrus is a region of the brain ubiquitous in its
involvement in numerous cognitive neuroscientific studies (Cabeza &
Nyberg, 2000). However, the role of the anterior cingulate in intelligence,
creativity, and genius might be more specific (Colom, Jung, & Haier, 2006;
Frangou, Chitins, & Williams, 2004; Gong et al., 2005; Jung, Gasparovic,
Chavez, Caprihan et al., 2009; Jung, Segall et al., 2010; Pfleiderer et al.,
2004). The anterior cingulate cortex has been demonstrated to contain a
unique type of spindle cell, found only in large hominoids, with double
the frequency in humans than in great apes, suggesting strong selection
pressures in this particular brain structure (Nimchinsky et al., 1999). The
anterior cingulate gyrus appears to have some level of specificity with
respect to the ability of our species to (1) down-regulate and/or activate
broad networks of brain regions in service of divergent thinking, and sub-
sequently (2) up-regulate and/or focus resources within frontal lobe net-
works in service of convergent thinking and/or persistence in pushing a
new idea out into the world. Future studies will help further parse structure-
function relationships within the anterior cingulate cortex if undertaken
in subjects selected for high intelligence, or high creativity, or genius.
Where Are the Unique Areas of Nonoverlap between Figures 11.2 and
Mostly, the areas shown in figures 11.2 and 11.3 do not overlap. Figure
11.2 represents a network of regions largely lateral (on the outer surface)
and superior (toward the top half of the brain) in their distribution, whereas
figure 11.3 represents a network of largely inferior (toward the lower half)
and more medial (on the inner surfaces of the brain). For example, while
intelligence was found to be associated with posterior brain regions includ-
ing the extrastriate and fusiform gyri near the lateral occipital lobes, many
creativity studies (including our structural studies) find associations with
the cuneus and precuneus on the medial wall between the two hemi-
spheres of the brain. Intelligence is associated with integrity of the dorso-
lateral prefrontal cortex: creative achievement with lower volumes of the
orbitofrontal cortex, and increased creative drive in FTLD with damage to
248 R. E. Jung and R. J. Haier
the left anterior temporal lobe. Intelligence is associated with integrity of
white-matter tracts including the arcuate fasciculus and corpus callosum;
divergent thinking and openness to experience were associated with lower
measures of integrity within white-matter tracts linking the thalamus with
frontal projection zones.
Intelligence and creativity appear to involve largely different brain net-
works. Tentatively, we interpret the former, focused on network integrity,
to facilitate knowledge acquisition and retention, and the latter, focused
on disinhibition of networks, to facilitate the generation of novel associa-
tions between knowledge stores. Whether there is a specific network for
genius is not yet apparent.
The Mystery of the Einstein Area
One interesting anomaly when comparing figures 11.2 and 11.3 regards
the inferior parietal lobule (BA 39). In studies of intelligence, this region
has been implicated in better performance across studies, with greater
volume, higher levels of the neuronal marker N-acetylaspartate, and greater
functional activation all showing positive associations with measures of
intelligence. In the “lesion” study of creativity reviewed above, however,
subjects with damage to the left inferior parietal lobule performed better
on measures of originality—some even performing better than normal
control subjects. How can this be? Wasn’t Einstein’s brain unique by virtue
of his inferior parietal lobule? But there is the rub: Einstein did not have
a normal inferior parietal lobule, and the “abnormalities” were related to
glial cells as opposed to neurons. Recall that Einstein had a 15 percent
wider parietal lobe than controls and no parietal operculum (Witelson
et al., 1999). However, subsequent studies showed that this greater parietal
bulk was not comprised of neurons, but rather a higher number of glial
cells—the support matrix of the brain (Diamond et al., 1985). Glial cells
have customarily been viewed as the “glue” (literally what “glia” translates
to) that holds the brain together. However, glial cells comprise 85 percent
of the total brain volume, and we are entering into an era where the
neuron doctrine of brain function is being slowly adapted to include the
“glial doctrine,” with recent studies demonstrating long-range communi-
cation between glial populations and glial modulation of neuronal tone
(Fields & Stevens-Graham, 2002). Thus, Einstein’s brain is not entirely
inconsistent with a “lesion” model of genius comprising a network of brain
regions, some with greater neuronal fidelity, some with lowered (i.e., dis-
Creativity and Intelligence 249
Complex phenomena like intelligence, creativity, and genius can be studied
scientifically with modern neuroscience methods even as their definitions
evolve with better empirical observations. Indeed, very clever individuals,
such as Hans Eysenck, formulated hypotheses regarding genius without
the benefit of sophisticated neuroimaging techniques that we now take for
granted. These hypotheses were not too far off the mark given the benefit
of careful interrogation with the tools and techniques of the modern neu-
roscientist. This has always been the case in science, whether investigating
the nature of an atom or a gene or a memory. Such investigations typically
raise more questions than they resolve; however, asking the right questions
is key. Will an understanding of the neural basis of intelligence or creativ-
ity, or even genius, change how we approach education? There are already
moves in this direction based on very tentative data (Ramsden et al., 2011)
but much more research is necessary. As always, caution is required, but
the future of creativity research looks bright indeed.
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