There are many definitions of intelligence. Some psychologists, who do not like the construct, jokingly define intelligence as the score one obtains on a test of intelligence (IQ test). Others define intelligence as the ability to do well in school. But to most psychologists, and as defined in Webster's Dictionary (Soukhanov & Ellis, 1988), intelligence is the measure of a person's ability to acquire and apply knowledge. Sternberg and O'Hara (1999) suggested several possible relationships between intelligence and creativity: (a) they are the same; (b) one is a subset of another, for example, creativity is a subset of intelligence; (c) they are unrelated; and (d) they are overlapping but independent sets. If intelligence is the measure of a person's cognitive ability to adapt, creativity is the gift that might allow one to better adapt; this would be true of certain forms of creativity (e.g., medical science), and not true of other forms (e.g., painting).
The founder of intelligence tests, Alfred Binet, must have initially thought that creativity and intelligence were the same or closely overlapping because in the first intelligence test he devised in 1896, he used inkblots to explore the imagination of children. Later, according to Sternberg and O'Hara (1999), he discontinued this inkblot test because he was unable to develop a means of scoring it.
Guilford and Christensen (1973), one of the first to study and help generate psychologists' interest in creativity, said that creativity was a subset of intelligence. Guilford attempted to develop psychometric tests that could measure creativity. These tests are similar to those developed by Torrance (1974). Most of these tests assess individuals' ability to develop novel uses of common objects. For example, as mentioned previously, participants would be asked to name in a fixed time interval the different ways in which they might be able to use a brick. Guilford found that students with a low IQ consistently performed poorly on these tests, but for those students with a high IQ, performance on creativity tests did not highly correlate with their performance on IQ tests. After reviewing the relationship between intelligence and creativity, Torrance (1975) suggested that IQ and creativity are only moderately related.
Another means of studying the relationship between creativity and intelligence is to study creative peoples' intelligence. Barron and Harrington (1981) studied architects and found a weak relationship between the creativity of these architects and their IQs. They concluded that for those people with an IQ of about 120 or higher, the IQ does not predict creativity as much as it does if the IQ is below 120. These observations suggest that there might be an IQ threshold: A person's IQ needs to be higher than this threshold to have sufficient intelligence to learn enough about the domain of his or her creativity and to acquire the skills needed to be creative in that domain. Thus, intelligence is a necessary but not sufficient component of creativity.
Other investigators also have studied populations of known creative people and attempted to learn if there is a strong correlation between their estimated eminence as creators and their intelligence. Simonton (1994) and other investigators, such as Herr, Moore, and Hasen (1965), also found that the correlation between intelligence and creativity is weak. This weak correlation, however, might be related to the test that was used to measure intelligence.
Cattell (1963) posited that there are two types of intelligence, which he termed "crystallized" and "fluid." Whereas crystallized intelligence is primarily declarative memories, such as knowing that Albany is the capital of New York, or lexical-semantic knowledge, such as knowing what the word impale means, fluid intelligence is the ability to solve problems. Most intelligence tests, such as the Wechsler Adult Intelligence Scale (Wechsler, 1981), test both crystallized (e.g., vocabulary definitions) and fluid intelligence (e.g., similarities such as "How are a fly and tree similar?"). Cattell thought that although crystallized knowledge is important in creativity, it is fluid intelligence that determines creativity. Although fluid intelligence may be the best predictor of creativity, I know of no formal studies of this relationship. There may different domains of fluid intelligence, such as solving mathematical, rhyming, or imagery problems. In addition, there has been little written about the brain mechanisms of fluid intelligence and cognitive flexibility.
The major purpose of this book is to discuss the brain mechanism that might be important for creativity, and because intelligence appears to be a necessary component, I want to mention some of the brain mechanisms that might be important for intelligence. Unfortunately, the brain mechanisms that account for intelligence are not well understood. According to Donald Hebb (1949) the critical element in learning is the ability to change the strength of the connections between neurons. A corollary of this hypothesis might be that the more neurons with which a person is endowed, the greater the ability to learn. Some intelligence tests were primarily developed to predict how well a student would perform in school, and a student's performance in school is heavily dependent on the ability to learn. Thus, a highly intelligent person might have more neurons than someone who is less intelligent, and this difference could be reflected in the size of their brains. Partial support for this hypothesis came from the work of Rosenzweig and his coworkers (Rosenzweig, 1972; Rosenzweig & Bennett, 1996), who found that rodents who were put in an enriched environment at a young age and who subsequently could learn better than the animals not exposed to an enriched environment (controls) had brains that weighed more than the brains of the control animals and even had larger heads. Studies of humans reveal that diseases that reduce the number of neurons are associated with a loss of intelligence and that people who have extremely small heads often have below normal intelligence. Measuring head size to estimate intelligence would save society a lot of money. Except for the extremes (e.g., microcephaly), however, there is only a weak relationship or no significant relationship between IQ and the size of the head or brain (Tramo et al., 1998).
Although there is no simple relationship between head size or brain size and IQ, Rosenzweig (1972) found in his classic enrichment studies that the animals raised in enriched environments were more intelligent. On postmortem examination, they found that when these experimental animals, which were raised in an enriched environment, were compared with control animals, the experimental animals had an increase in the thickness of their cerebral cortex. This increased thickness might reflect an increase in the number of synaptic contacts. On microscopic examination, he found that the number of dendritic spines (see Figure 2.1) was also greater in the experimental animals,
thereby providing support for the connectivity postulate of intelligence. This increase in neuronal connectivity could increase the potential for the development of the neuronal networks that are important for learning and the storage of knowledge.
Charles Spearman (1905), one of the founders of the psychometric approach to intelligence, noted that, independent of the cognitive tests that he and other investigators used to measure intelligence, performance on that one test strongly correlated with performance on other cognitive tests that measure mental ability in different domains. On the basis of this predictability, Spearman posited that in addition to specific abilities that are needed to perform on test (5 factor) domains, there is a general intellectual ability that he called the g factor. Concordance studies of twins and siblings has revealed that monozy-gotic twins reared apart have IQs that correlate more closely than siblings reared together. This positive concord suggests that there may be a biological factor or factors that determine general intelligence other than environmental exposure.
Carly, Golding, and Hall (1995) reviewed research of the biological factors that might account for differences in human intelligence and noted that the results of event-related potential (ERP) studies suggest that people with high IQ test scores show faster responses in some test conditions and might have less variability in their ERPs. This ERP data would suggest that high intelligence is related to faster neural conduction speed. Carly et al. also noted that functional imaging studies suggest that people with higher IQs have lower cerebral metabolic rates during mentally active conditions. This finding suggests that brighter people have more efficient brains. Carly et al., however, concluded that despite some well-replicated findings in the search for the biological basis of human intelligence, there is a dearth of explanatory accounts to link differences in cognitive performance with variance in brain mechanisms. Although the biological basis of general intelligence, or the g factor, has not been determined, there are some candidates.
Central nervous system proteins called nerve growth factors could influence the degree of neuronal connectivity, and the degree of connectivity might be a possible determinant of intelligence. For example, in a study of the effects of environmental enrichment on levels of brain nerve growth factor, its receptors, and their relationships to cognitive function, Pham and coworkers (1999) found that animals placed in the enriched condition had significantly higher levels of nerve growth factor when compared with the control animals housed in unenriched environments. Thus, it could be posited that one of the biological controls of the g factor is nerve growth factor. The brain levels of these growth factors are probably influenced both genetically and environmentally. To my knowledge, however, no one has demonstrated that the differences in human intelligence are related to the size or number of synaptic contacts, or differences in nerve growth factors, because the methods to study these variables are still not fully developed.
Recently Duncan and associates (2000) attempted to determine the neural basis for "general intelligence," or Spearman's g, using positronemission tomography (PET). These investigators physiologically imaged participants' brains while they were performing spatial, verbal, and perceptuo-motor tasks that have high g involvement and also had participants perform other matched control tasks that have low g involvement. They reported that, in contrast to the common view that g reflects a broad sample of major cognitive functions, high g tasks were not associated with the diffuse recruitment of multiple brain regions but instead associated with selective recruitment of lateral frontal cortex in one or both hemispheres. On the basis of these results, Duncan et al. concluded that "general intelligence" derives from a specific frontal system important in the control of diverse forms of behavior.
Functional imaging and brain lesion studies have repeatedly demonstrated that the lateral frontal lobes play a critical role in what has been termed "executive functions," such as managing the allocation of resources, mediating goal-oriented behaviors, as well as working memory. Thus, it is not surprising that in many cognitive tasks these frontal areas would show activation. On the basis of studies of patients who underwent frontal lobotomies for the treatment of mental illness, researchers have repeatedly demonstrated that ablation of the frontal lobe does not severely influence performance on standardized intelligence tests (Valenstein, 1973). Thus, factors other than frontal lobe function might be important in the neural basis of intelligence.
It is also possible that nonstructural factors might also influence the g factor of intelligence. If, according to Hebb's law (neurons that fire together wire together), learning and memory are based on modifications of synaptic strength between neurons that are simultaneously active, an increase in the sensitivity of synaptic coincidence detector would lead to better learning and memory. The N-methyl-D-aspartate (NMDA) gated ion channel is a neural depolarization coincidence detector (detects when neurons fire together) and the influx of calcium through this channel enables an increase in synaptic strength. Thus, the enhanced NMDA gated ion channel activity could enhance learning and memory. Tang and coworkers (1999) demonstrated in trans-genic mice that overexpression of the gene for the NMDA receptor in the forebrains of these mice, which leads to an increase in NMDA ion channel density, is associated with superior learning ability, as assessed by various behavioral tasks. Thus, differences in the NMDA gaited ion channels might represent a unifying mechanism for associative learning and memory. These observations suggest that genetic control of cognitive attributes such as intelligence can be mediated neurochemically.
Since the pioneering reports of Paul Broca, studies of patients with discrete brain lesions suggest that a person can have specific cognitive disabilities. Developmental disorders can also be associated with specific cognitive disabilities. For example, there are children with specific disabilities in reading, math, drawing, music, and route finding. Some of these children become creative geniuses. For example, as previously mentioned, there are many great artists, such as Picasso, who did not do well in school because of language disabilities and, as it was noted in chapter 1, even mathematical geniuses such as Einstein have had language learning disabilities. Thus, the g factor alone cannot explain specific disabilities or specific talents, and several theorists have placed more of an emphasis on special factors. For example, Howard Gardner (1985), who popularized the concept of "multiple intelligences," had worked with neuropsychologists and behavioral neurologists such as Edith Kaplan, Norman Geschwind, and Harold Goodglass at the Jamaica Plain Veteran Administration Medical Center in Massachusetts. These clinician-scientists knew the classical localizationist papers that were published in the late-19th and early-20th centuries by clinician-scientists such as Paul Broca, Karl Wernicke, Kurt Lichtheim, and Hugo Liepmann. They not only resurrected the contributions of these pioneers but also advanced our knowledge about the modular organization and localization of different cognitive functions. On the basis of this knowledge, Gardner (1985) suggested that people have multiple intelligences. Although Gardner's concept of multiple intelligences had a great influence on educators, this concept was not new when he described it. For example, in 1938 Thurstone criticized Spearman's (1927) theory of intelligence. Spearman suggested that intelligence is a single entity, but Thurstone instead suggested that intelligence consists of several primary abilities and these primary abilities, were separate and distinct. In Gardner's first book about multiple intelligences, he listed seven abilities: linguistic, logical, mathematical, musical, body kinesthetic, spatial, and interpersonal. In his 1938 book, Thurstone also suggested that there were seven major "vectors" of the mind. In a more recent book, Gardner (1999) listed several more (e.g., spiritual) but has not reached the 150 forms of intelligences posited by J. P. Guilford.
There are many forms of creativity. Whereas some depend on language skills, others might depend on visuospatial or musical skills. Thus, if creativity in a certain field were related to intelligence, it would appear to be related to a specific factor or a special form of intelligence. In the next chapter we discuss what might be the neurological bases of these special talents.
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Enchanted Learning Experiences -Why They Should Be The Norm For Our Children. The latter part of the twentieth century has seen more discoveries about the human brain than in all previous history of mankind. It is as though we have been paddling in the shallows of a vast ocean hitherto unaware of its existence.