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Creativity and Intelligence: Brain Networks That Link and Differentiate the Expression of Genius


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Based on neuro-imaging findings, we present a brain model for intelligence and a model for creativity and discuss how genius may emerge from the overlapping and the unique aspects of these models. Intelligence is associated with integrity of the dorsolateral prefrontal cortex and creative achievement with lower volumes of the orbitofrontal cortex. Increased creative drive sometimes associated with frontotemporal dementia is related to damage in the left anterior temporal lobe. Intelligence is also associated with integrity of white-matter tracts including the arcuate fasciculus and corpus callosum. Divergent thinking and openness to experience are associated with lower measures of integrity within white-matter tracts linking the thalamus with frontal projection zones. Although there is some overlap, intelligence and creativity appear to involve largely different brain networks. The intelligence findings suggest the importance of network integrity that may facilitate knowledge acquisition and retention. The creativity findings suggest a disinhibition of networks that facilitates the generation of novel associations among knowledge stores. Whether there is a specific network for genius is not yet apparent. Complex phenomena like intelligence, creativity, and genius can be studied scientifically with modern neuroscience methods even as their definitions evolve with better empirical observations.
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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:
Albert Einstein.
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
Figure 11.1
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,
Figure 11.2
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,
Figure 11.3
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-
inhibitory) characteristics.
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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... Thus, these reviews also rejected the (historical) view that creative cognition would depend exclusively upon the right hemisphere. It was further acknowledged that lower integrity or damage of brain structure can lead to enhanced creativity in certain cases (e.g., Jung & Haier, 2013 ). ...
... This might help to discern the unique features of "creative brains" from those of "intelligent brains" (cf. Jung & Haier, 2013 ). Despite creative idea generation involving many P-FIT areas on a functional level, the long-term structural correlates seem to tap more into DMN regions, which might extend our understanding of the creative person: creative individuals are not only of above-average intelligence (e.g., Jauk et al., 2013 ), but they also seem to display a higher engagement of default-mode processes in everyday life. ...
This chapter deals with the relationship between intelligence and creativity from a neuroscientific perspective. The common and differential aspects of the two constructs are first illustrated on the basis of behavioral findings, and it is suggested that both cognitive constructs draw on similar elementary-cognitive processes. These findings are then reevaluated from the view of cognitive neuroscience, which provides additional support for the behavioral findings, but also helps to better understand the factors that discern creativity from intelligence. The interplay of both constructs is illustrated based on functional connectivity studies. Finally, structural neuroimaging studies are reviewed, which point to relatively stable interindividual differences in brain morphology in relation to creativity. The findings are summarized in the light of dual-process models of human cognition, which emphasize the necessity of controlled and spontaneous processes for creativity. Psychometric Research on the Relationship Between Intelligence and Creativity There is a long-standing debate on whether intelligence and creativity are different, overlapping, or conjoint abilities (e.g., Sternberg & O’Hara, 1999). Creativity, in terms of cognitive creative potential, is commonly defined in terms of the ability to produce novel and useful ideas (Barron, 1955; Runco & Jaeger, 2012; Stein, 1953; see also Diedrich, Benedek, Jauk, & Neubauer, 2015). Guilford, who was one of the first to conceptualize human creativity in terms of a normally distributed trait - divergent thinking ability - conceived creativity as a subset of general intelligence in his well-known structure of intellect model (Guilford, 1967), thus putting emphasis on the similarity between both constructs. On the contrary, other early accounts of creativity emphasized the independence of the two constructs (e.g., Getzels & Jackson, 1962; Wallach & Kogan, 1965). As Silvia (2015) points out in his in-depth methodological review, these different conceptualizations might originate from substantially diverging approaches to the operationalization of creativity. Creative potential is commonly evaluated by means of divergent thinking tasks (e.g., “find many creative uses for a brick”). While Guilford took many criteria into account to score divergent thinking tasks, among them the originality (quality) of responses, Wallach and Kogan (1965) focused on the scoring of unique responses in terms of statistical infrequency, thereby disregarding their quality. Guilford’s approach led him to conclude that intelligence and creativity are highly related abilities, while Wallach and Kogan assumed that they are essentially unrelated.
... Expansion, by contrast, is conceptualized as a domain-general mechanism of broadening cognitive-processing capacity, for example by means of activation increases in task-independent areas that mediate working memory (e.g., dorsolateral prefrontal cortex), attention (e.g., anterior cingulate cortex), the default mode of activity (areas of the default mode network [DMN] such as the posterior cingulate cortex, temporoparietal junction, and medial prefrontal cortex), or associative memory (e.g., hippocampus, parahippocampal gyrus, anterior temporal lobe). Perhaps the most discussed mechanism of expansion in the creativity literature is "frontal disinhibition" (Carson, 2014;Jung & Haier, 2013) or the release of inhibitory top-down executive control by the frontal cortex so as to foster an openness to novel ideas and associations. ...
Full-text available
One of the central questions about the cognitive neuroscience of creativity is the extent to which creativity depends on either domain-specific or domain-general mechanisms. To address this question, we carried out two parallel activation likelihood estimation meta-analyses of creativity: 1) a motoric analysis that combined studies across five domains of creative production (verbalizing, music, movement, writing, and drawing), and 2) an analysis of the standard ideational task used to study divergent thinking, the Alternate Uses task. All experiments contained a contrast between a creative task and a matched non-creative or less-creative task that controlled for the sensorimotor demands of task performance. The activation profiles of the two meta-analyses were non-overlapping, but both pointed to a domain-specific interpretation in which creative production is, at least in part, an enhancement of sensorimotor brain areas involved in non-creative production. The most concordant areas of activation in the motoric meta-analysis were high-level motor areas such as the pre-supplementary motor area and inferior frontal gyrus that interface motor planning and executive control, suggesting a means of uniting domain-specificity and -generality in creative production.
... Neuroscience has shown that diligent application of divergent thinking strategies, not just occasional workshops or intensives, do effectively train the brain to think more creatively about everyday problem solving at work, school or home (Jung & Haier, 2013). This supports the argument that creativity is developmental in nature and strengthened by routine practice and regular exposure to creative works. ...
... Combinations of intelligence, creativity, and personality variables have been hypothesized to underlie exceptional ability, including extremely high creative achievement (aka. the study of genius; Jung and Haier, 2013). As high creative achievers are seen to reside at the extremes of the ranges of intelligence, creativity, and certain personality traits (e.g., openness), it is plausible that such individuals' brain morphometry would also lie at structural extremes, at least in certain brain regions within which brain-behavior relationships have been demonstrated in normal samples. ...
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Nearly everyone has the ability for creative thought. Yet, certain individuals create works that propel their fields, challenge paradigms, and advance the world. What are the neurobiological factors that might underlie such prominent creative achievement? In this study, we focus on morphometric differences in brain structure between high creative achievers from diverse fields of expertise and a ‘smart’ comparison group of age-, intelligence-, and education-matched average creative achievers. Participants underwent a high-resolution structural brain imaging scan and completed a series of intelligence, creative thinking, personality, and creative achievement measures. We examined whether high and average creative achievers could be distinguished based on the relationship between morphometric brain measures (cortical area and thickness) and behavioral measures. Although participants’ performance on the behavioral measures did not differ between the two groups aside from creative achievement, the relationship between posterior parietal cortex morphometry and creativity, intelligence, and personality measures depended on group membership. These results suggest that extraordinary creativity may be associated with measurable structural brain differences, especially within parietal cortex.
... R.E. Jung and Haier (2013) looked at frontotemporal dementia and brain lesion studies in relation to creativity and found that "lower brain integrity within left hemisphere brain structuresparticularly left anterior temporal and inferior parietal lobes-serves to "disinhibit" other brain regions associated with increased novelty generation" (p. 243). ...
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The Jungian theories of creativity, like much of Jungian psychology, emphasize the relationship between the conscious mind and the unconscious. This paper explores and elucidates the intriguing parallels between this Jungian framework and recent models that have emerged in the neuroscience of creativity.
... For example, it is possible that an antagonistic relationship between default and executive systems characterizes their involvement at the microscale level (i.e., in the order of milliseconds), whereas a synergistic relationship characterizes their involvement at the macroscale level (i.e., in the order of seconds) with connectivity patterns changing multiple times throughout the task. Given that traditional neuroimaging methods lack the capacity to capture neural events with millisecond temporal resolution, this limitation must be taken into account when discussing the potential relationship between these networks (see also Jung et al., 2009 ;Jung & Haier, 2013 ). Future research is invited to examine with more precision the dynamic interactions between the proposed generative and analytic brain systems in space and time, to determine the infl uence of individual diff erences in network engagement, and to delineate the specifi c contributions of particular network components to diff erent aspects of creative thought. ...
At first glance, the experimental study of a topic as complex as creativity would seem like a formidable task for a cognitive neuroscientist. For one, the methods of cognitive neuroscience are best suited for cognitive processes we can clearly isolate in space and time and which can be reliably elicited with simple experimental manipulations in the laboratory. Although creativity falls far from satisfying these methodological constraints, the status of creative thought as a hallmark of the human mind has invited numerous investigations on the neural bases of creativity for nearly two decades. Cognitive neuroscience research on creativity has provided an extensive body of work highlighting the neural underpinnings of concepts key to creativity, such as divergent thinking and insight, that are theorized to underlie our ability to generate ideas deemed novel and appropriate to satisfy current goals. On the other hand, it has also become apparent that a lack of consensus on the operationalization of these concepts and their measurement, as well as the substantial variability in the use of definitions, creativity tasks, and experimental paradigms across studies, have brought issues of interpretation of the ensuing data for our understanding of the neural mechanisms of creativity to the fore (Abraham, 2013; Chrysikou, in press). To address these concerns, modern experimental and neuroscience research on creativity has recently begun to transition from the study of hard-to-define concepts, such as divergent thinking, to investigations of specific cognitive and neural processes (e.g., attention, memory, executive function) hypothesized to underlie creative thought (Abraham, 2014; Dietrich, 2007a,2007b; Smith, Ward, & Finke, 1995; Ward, 2007; see also Kounios & Beeman, 2014; Weisberg, 2006). Cognitive neuroscience studies have revealed that creative thinking is associated with the involvement of an extensive network of regions that are widely distributed across the brain, and which reflect the complex set of diverse cognitive processes involved in creative cognition. A key question for this research pertains to the importance of executive functions or cognitive control processes for creativity and the attendant involvement of prefrontal cortical structures during creative ideation. Indeed, a point of convergence across the majority of recent work on the neural bases of creative thinking is the significance of the prefrontal cortex (PFC) for creative thought (e.g., Gonen-Yaacovi et al., 2013; see Dietrich & Kanso, 2010 for a review).
Draw In Order to See is the first book to survey the history of architectural design using the latest research in cognitive science and embodied cognition. Beginning with a primer on visual perception, cognitive science, design thinking, and modes of conception used by groups of architects in their practices, Mark Alan Hewitt surveys a 12,000-year period for specific information about the cognitive schemata used by Homo sapiens to make their buildings and habitats. The resulting history divides these modes of thinking into three large cognitive arcs: crafting, depicting, and assembling, within specific temporal frames. His analysis borrows from Merlin Donald’s thesis about mimetic and symbolic cognition as critical to the emergence of the modern mind, and further employs theories of enactment and embodiment to clarify their relationship to architecture. Individual chapters treat the emergence of depiction during the Renaissance, the education of architects in the modern era, Baroque illusionism and scenography, the breakdown of artisanal literacy during the Enlightenment, and modern experiments with models, montage, and illusions of movement. The author concludes with a critique of contemporary design and education, and promotes design with embodiment as a tonic for a profession in crisis, facing the challenges of climate change, energy shortages, inequality, and housing a population of over seven billion in the coming decades. This groundbreaking and valuable study presents a clear view of current research in two related fields that have not heretofore been compared, and outlines a strategy for future research. An extensive bibliography offers readers an up-to-date reference to both the science and the architectural history behind the text.
Creativity is the generation of an idea or artifact judged to be novel and high-quality by a knowledgeable social group, and is often said to be the pinnacle of intelligence. Several computational creativity systems of various designs are now being demonstrated and deployed. These myriad design possibilities raise the natural question: are there fundamental limits to creativity? Here we define a mathematical abstraction to capture key aspects of combinatorial creativity and study fundamental trade-offs between novelty and quality. The functional form of this fundamental limit resembles the capacity-cost relationship in information theory, especially when measuring novelty using Bayesian surprise—the relative entropy between the empirical distribution of an inspiration set and that set updated with the new idea or artifact. As such, we show how information geometry techniques provide insight into the limits of creativity and find that the maturity of the creative domain directly parameterizes the fundamental limit. This result is extended to the case when there is a diverse audience for creativity and when the quality function is not known but must be estimated from samples.
Jensen analyses the complex strategies used to communicate posttraumatic autobiographical experience through the limiting frames of autography and poetry. Outlining the latest neuroscientific understandings of the relations between mental illness and the creative drive, Jensen demonstrates how both poetry and autography have arisen alongside traumatic historical contexts: while poetry traditionally communicated the horrors of war and imprisonment, autography has been used to tell stories of genocide, rape, incest, anorexia, and pedophilia. Jensen argues that often in posttraumatic autobiographical works in these strict forms a remembered, intrusive scene of violent incursion upon the mind and body is “spoken out” verbally or visually in a manner similar to ekphrástic poetic renderings of a painting or sculpture. Drawing attention to this form of ekphrásis as the business of posttraumatic poetry and autography, Jensen concludes that in both forms, metaphor is used to reread powerful images and provide a rhetorical bridge between affective realms.
This is a portrait of Albert Einsten, looking at his life and work from a personal perspective. This biography uncovers Einstein's relationships with his family and the three most important women in his life - his first and second wives and his mother. Drawing from archival evidence from Berlin, Zurich, Boston, Edinburgh and Oxford, and on unpublished papers and interviews with scholars, family and friends, it convincingly challenges the carefully cultivated image of Einsten as a modern saint.
Twenty years have passed since the first neuro-imaging study of intelligence. Researchers from around the world are now using a variety of imaging techniques to investigate the neural basis of intelligence, establishing the field of “neuro-intelligence”. The papers in this special issue help usher in the next phase of neuro-intelligence research. Among other issues, they illustrate some of the progress made in identifying key brain areas and in elucidating the concept of brain efficiency. Samples include children, adults, and seniors. Imaging includes structural assessments and functional determinations during cognitive tests of memory and processing speed. Intelligence measures address g and other factors. Some brain/intelligence relationships apparently differ for males and females. The data are intriguing. The field is maturing. The pace is quickening. As intelligence research engages 21st century neuroscience, new hypotheses and new controversies are inevitable. What a terrific time to work in this field.