Fluid and crystallized intelligence
In psychology, fluid and crystallized intelligence (respectively abbreviated Gf and Gc) are factors of general intelligence, originally identified by Raymond Cattell. Concepts of fluid and crystallized intelligence were further developed by Cattell's student, John L. Horn.
Fluid intelligence or fluid reasoning is the capacity to think logically and solve problems in novel situations, independent of acquired knowledge. It is the ability to analyze novel problems, identify patterns and relationships that underpin these problems and the extrapolation of these using logic. It is necessary for all logical problem solving, e.g., in scientific, mathematical, and technical problem solving. Fluid reasoning includes inductive reasoning and deductive reasoning.
Crystallized intelligence is the ability to use skills, knowledge, and experience. It does not equate to memory, but it does rely on accessing information from long-term memory. Crystallized intelligence is one’s lifetime of intellectual achievement, as demonstrated largely through one's vocabulary and general knowledge. This improves somewhat with age, as experiences tend to expand one's knowledge.
The terms are somewhat misleading because one is not a "crystallized" form of the other. Rather, they are believed to be separate neural and mental systems. Crystallized intelligence is indicated by a person's depth and breadth of general knowledge, vocabulary, and the ability to reason using words and numbers. It is the product of educational and cultural experience in interaction with fluid intelligence.
Fluid and crystallized intelligence are thus correlated with each other, and most IQ tests attempt to measure both varieties. For example, the Wechsler Adult Intelligence Scale (WAIS) measures fluid intelligence on the performance scale and crystallized intelligence on the verbal scale. The overall IQ score is based on a combination of these two scales.
Fluid and crystallized intelligence were originally identified by Raymond Cattell. Concepts of fluid and crystallized intelligence were further developed by Cattell's student, John L. Horn. Since Cattell's and Horn's publications, the concepts of fluid and crystallized intelligence have become so ingrained in the field of intelligence that they are no longer routinely attributed to Cattell or Horn—much as Cattell's scree plot became ingrained in the practice of factor analysis or Freud's concept of the subconscious is ingrained in psychology and in the public's perceptions of the mind.
Fluid and crystallized intelligence are discrete factors of general intelligence, or g. Although formally recognized by Cattell, the distinction was foreshadowed by Charles Spearman who originally developed the theory of g and made a similar observation regarding the difference between eductive and reproductive mental ability.
According to Cattell, "...it is apparent that one of these powers… has the 'fluid' quality of being directable to almost any problem. By contrast, the other is invested in particular areas of crystallized skills which can be upset individually without affecting the others." Thus, his claim was that each type, or factor, was independent of the other, though many authors have noted an apparent interdependence of the two.
Fluid versus crystallized
Deficits in fluid intelligence are found on some measures in individuals with Autism spectrum disorders, including Asperger syndrome, whereas enhanced performance on other tasks measuring fluid intelligence has been found in this population.
Crystallized intelligence is possibly more amenable to change as it relies on specific, acquired knowledge. When learning new facts, someone's fund of knowledge is expanded. Vocabulary tests and the verbal subscale of the WAIS are considered good measures of Gc. Crystallized intelligence relates to the study of aging. Belsky claims this declines with age. In life, knowledge that is not used can be forgotten. Belsky believes that there is at least one age of maximum crystallized intelligence; after which forgetting exceeds the rate at which knowledge is acquired.
Some researchers have linked the theory of fluid and crystallized intelligence to Piaget's conception of operative intelligence and learning. Fluid ability and Piaget's operative intelligence both concern logical thinking and the education of relations. Crystallized ability and Piaget's treatment of everyday learning reflect the impress of experience. Like fluid ability's relation to crystallized intelligence, Piaget's operativity is considered to be prior to, and ultimately provides the foundation for, everyday learning.
Fluid intelligence generally correlates with measures of abstract reasoning and puzzle solving. Crystallized intelligence correlates with abilities that depend on knowledge and experience, such as vocabulary, general information, and analogies. Paul Kline identified a number of factors that shared a correlation of at least r=.60 with Gf and Gc. Factors with [clarify] of greater than 0.6 on Gf included induction, visualization, quantitative reasoning, and ideational fluency. Factors with median loadings of greater than 0.6 on Gc included verbal ability, language development, reading comprehension, sequential reasoning, and general information. It may be suggested that tests of intelligence may not be able to truly reflect levels of fluid intelligence. Some authors have suggested that unless an individual was truly interested in the problem presented, the cognitive work required may not be performed because of a lack of interest. These authors contend that a low score on tests which are intended to measure fluid intelligence may reflect more a lack of interest in the tasks rather than inability to complete the tasks successfully.
Measurement of fluid intelligence
There are various measures that assess fluid intelligence. The Cattell Culture Fair IQ test, the Raven Progressive Matrices (RPM), and the performance subscale of the WAIS are measures of Gf. The RPM is one of the most commonly used measures of fluid abilities. It is a non-verbal multiple choice test. Participants have to complete a series of drawings by identifying relevant features based on the spatial organization of an array of objects, and choosing one object that matches one or more of the identified features. This task assesses the ability to consider one or more relationships between mental representations or relational reasoning. Propositional analogies and semantic decision tasks are also used to assess relational reasoning.
Standardized IQ tests such as those used in psychoeducational assessment also include tests of fluid intelligence. In the Woodcock-Johnson Tests of Cognitive Abilities, Gf is assessed by two tests: Concept Formation (Test 5) in the Standard Battery and Analysis Synthesis (Test 15) in the Extended Battery. On Concept Formation tasks, the individual has to apply concepts by inferring the underlying "rules" for solving visual puzzles that are presented in increasing levels of difficulty. Individuals at the preschool level have to point to a shape that is different from others in a set. As the level of difficulty increases, individuals increasingly demonstrate an understanding of what constitutes a key difference (or the "rule") for solving puzzles involving one to one comparisons, and on later items identifying common differences among a set of items. For more difficult items, individuals need to understand the concept of "and" (e.g. solution must have some of this and some of that) and the concept of "or" (e.g. to be inside a box, the item must be either this or that). The most difficult items require fluid transformations and cognitive shifting between the various types of concept puzzles that the examinee has worked with previously.
Concept Formation tasks assess inductive reasoning ability. In the Analysis-Synthesis test, the individual has to learn and orally state the solutions to incomplete logic puzzles that mimic a miniature mathematics system. The test also contains some of the features involved in using symbolic formulations in other fields such as chemistry and logic. The individual is presented with a set of logic rules, a "key" that is used to solve the puzzles. The individual has to determine the missing colors within each of the puzzles using the key. Complex items present puzzles that require two or more sequential mental manipulations of the key to derive a final solution. Increasingly difficult items involve a mix of puzzles that require fluid shifts in deduction, logic, and inference. Analysis Synthesis tasks assess general sequential reasoning.
In the Wechsler Intelligence Scale for Children-IV (WISC IV), the Perceptual Reasoning Index contains two subtests that assess Gf: Matrix Reasoning, which involves induction and deduction, and Picture Concepts, which involves induction. In the Picture Concepts task, children are presented a series of pictures on two or three rows and asked which pictures (one from each row) belong together based on some common characteristic. This task assesses the child's ability to discover the underlying characteristic (e.g. rule, concept, trend, class membership) that governs a set of materials. Matrix Reasoning also tests this ability as well as the ability to start with stated rules, premises, or conditions and to engage in one or more steps to reach a solution to a novel problem (deduction). In the Matrix Reasoning test, children are presented a series or sequence of pictures with one picture missing. Their task is to choose the picture that fits the series or sequence from an array of five options. Since Matrix Reasoning and Picture Concepts involve the use of visual stimuli and do not require expressive language, they are considered to be non-verbal tests of Gf.
Within the corporate environment, fluid intelligence is a predictor of a person's capacity to work well in environments characterised by complexity, uncertainty, and ambiguity. The Cognitive Process Profile (CPP) measures a person's fluid intelligence and cognitive processes. It maps these against suitable work environments according to Elliott Jacques Stratified Systems Theory.
Development and physiology
Fluid intelligence, like reaction time, typically peaks in young adulthood and then steadily declines. This decline may be related to local atrophy of the brain in the right cerebellum. Other researchers have suggested that a lack of practice, along with age-related changes in the brain may contribute to the decline. Crystallized intelligence typically increases gradually, stays relatively stable across most of adulthood, and then begins to decline after age 65. The exact peak age of cognitive skills remains elusive, it depends on the skill measurement as well as on the survey design. Cross-sectional data shows typically an earlier onset of cognitive decline in comparison with longitudinal data. The former may be confounded due to cohort effects while the latter may be biased due to prior test experiences.
Improving fluid intelligence with training on working memory
According to David Geary, Gf and Gc can be traced to two separate brain systems. Fluid intelligence involves both the dorsolateral prefrontal cortex, the anterior cingulate cortex, and other systems related to attention and short-term memory. Crystallized intelligence appears to be a function of brain regions that involve the storage and usage of long-term memories, such as the hippocampus.
Some researchers question whether the results of training are long lasting and transferable, especially when these techniques are used by healthy children and adults without cognitive deficiencies. A recent meta-analytical review conducted by researchers from the University of Oslo concluded that "memory training programs appear to produce short-term, specific training effects that do not generalize."
In a controversial study, Susanne M. Jaeggi and her colleagues at the University of Michigan, found that healthy young adults who practiced a demanding working memory task (dual n-back) approximately 25 minutes per day for between 8 and 19 days, had statistically significant increases in their scores on a matrix test of fluid intelligence taken before and after the training than a control group who did not do any training at all.
A second study conducted at the University of Technology in Hangzhou, China, supports Jaeggi's results independently. After student subjects were given a 10 day training regimen based on the dual n-back working memory theory, the students were tested on Raven's Standard Progressive Matrices. Their scores were found to have increased significantly.
Subsequent studies on n-back, namely by Chooi & Thompson and Redick et al. do not support Jaeggi's claims. Although participants' performance on the training task improved, results from latter did not suggest any significant improvement in the mental abilities tested, especially fluid intelligence and working memory capacity.
- Outline of human intelligence
- Raymond Cattell
- CHC theory
- General intelligence factor
- Three stratum theory
- Cattell, R. B. (1971). Abilities: Their structure, growth, and action. New York: Houghton Mifflin. ISBN 0-395-04275-5.
- Cattell, R. B. (1971). Abilities: Their structure, growth, and action. New York: Houghton Mifflin. ISBN 0-395-04275-5.[page needed]
- Cattell, R. B. (1987). Intelligence: Its structure, growth, and action. New York: Elsevier Science.[page needed]
- Spearman, Charles B. (2005). The Abilities of Man: Their Nature and Measurement. The Blackburn Press. ISBN 1-932846-10-7.
- Cavanaugh, J. C.; Blanchard-Fields, F (2006). Adult development and aging (5th ed.). Belmont, CA: Wadsworth Publishing/Thomson Learning. ISBN 0-534-52066-9.[page needed]
- Cattell, Raymond B. (1963). "Theory of fluid and crystallized intelligence: A critical experiment". Journal of Educational Psychology 54: 1–22. doi:10.1037/h0046743.
- Suchy, Yana; Eastvold, Angela; Whittaker, Wilson J.; Strassberg, Donald (2007). "Validation of the Behavioral Dyscontrol Scale-Electronic Version: Sensitivity to subtle sequelae of mild traumatic brain injury". Brain Injury 21 (1): 69–80. doi:10.1080/02699050601149088. PMID 17364522.
- Hayashi, Mika; Kato, Motoichiro; Igarashi, Kazue; Kashima, Haruo (2008). "Superior fluid intelligence in children with Asperger's disorder". Brain and Cognition 66 (3): 306–10. doi:10.1016/j.bandc.2007.09.008. PMID 17980944.
- Soulières, Isabelle; Dawson, Michelle; Gernsbacher, Morton Ann; Mottron, Laurent (2011). Skoulakis, Efthimios M. C, ed. "The Level and Nature of Autistic Intelligence II: What about Asperger Syndrome?". PLoS ONE 6 (9): e25372. Bibcode:2011PLoSO...625372S. doi:10.1371/journal.pone.0025372. PMC 3182210. PMID 21991394.
- Dawson, M.; Soulieres, I.; Ann Gernsbacher, M.; Mottron, L. (2007). "The Level and Nature of Autistic Intelligence". Psychological Science 18 (8): 657–62. doi:10.1111/j.1467-9280.2007.01954.x. PMID 17680932.
- Belsky, Janet (1999). The Psychology of Aging: Theory, Research, and Interventions. Pacific, CA: Brooks/Cole Publishing.
- Ackerman, Phillip L. (1996). "A theory of adult intellectual development: Process, personality, interests, and knowledge". Intelligence 22 (2): 227–57. doi:10.1016/S0160-2896(96)90016-1.
- Papalia, D.; Fitzgerald, J.; Hooper, F. H. (1971). "Piagetian Theory and the Aging Process: Extensions and Speculations". The International Journal of Aging and Human Development 2: 3–20. doi:10.2190/AG.2.1.b.
- Schonfeld, Irvin S. (1986). "The Genevan and Cattell-Horn conceptions of intelligence compared: Early implementation of numerical solution aids". Developmental Psychology 22 (2): 204–12. doi:10.1037/0012-1618.104.22.168.
- Kline, P. (1998). The new psychometrics: Science, psychology and measurement. London: Routledge.[page needed]
- Messick, Samuel (1989). "Meaning and Values in Test Validation: The Science and Ethics of Assessment". Educational Researcher 18 (2): 5–11. doi:10.3102/0013189X018002005. JSTOR 1175249.
- Raven, J.; Raven, J. C.; Court, J. H. (2003) . "Section 1: General Overview". Manual for Raven's Progressive Matrices and Vocabulary Scales. San Antonio, TX: Harcourt Assessment.[page needed]
- Bornstein, Joel C.; Foong, Jaime Pei Pei (2009). "MGluR1 Receptors Contribute to Non-Purinergic Slow Excitatory Transmission to Submucosal VIP Neurons of Guinea-Pig Ileum". Frontiers in Neuroscience 3: 46. doi:10.3389/neuro.21.001.2009. PMC 2695390. PMID 20582273.
- Wright, Samantha B.; Matlen, Bryan J.; Baym, Carol L.; Ferrer, Emilio; Bunge, Silvia A. (2007). "Neural correlates of fluid reasoning in children and adults". Frontiers in Human Neuroscience 1: 8. doi:10.3389/neuro.09.008.2007. PMC 2525981. PMID 18958222.
- Ferrer, Emilio; O'Hare, Elizabeth D.; Bunge, Silvia A. (2009). "Fluid reasoning and the developing brain". Frontiers in Neuroscience 3 (1): 46–51. doi:10.3389/neuro.01.003.2009. PMC 2858618. PMID 19753096.
- Woodcock, R. W.; McGrew, K. S.; Mather, N (2001). Woodcock Johnson III. Itasca, IL: Riverside.[page needed]
- Schrank, F. A.; Flanagan, D. P. (2003). WJ III Clinical use and interpretation. Scientist-practitioner perspectives. San Diego, CA: Academic Press.[page needed]
- Wechsler, D. (2003). WISC-IV technical and interpretive manual. San Antonio, TX: Psychological Corporation.[page needed]
- Flanagan, D. P.; Kaufman, A. S. (2004). Essentials of WISC-IV assessment. Hoboken, NJ: John Wiley.[page needed]
- Lee, Jun-Young; Lyoo, In Kyoon; Kim, Seon-Uk; Jang, Hong-Suk; Lee, Dong-Woo; Jeon, Hong-Jin; Park, Sang-Chul; Cho, Maeng Je (2005). "Intellect declines in healthy elderly subjects and cerebellum". Psychiatry and Clinical Neurosciences 59 (1): 45–51. doi:10.1111/j.1440-1819.2005.01330.x. PMID 15679539. hdl:10371/27902.
- Desjardins, Richard; Warnke, Arne Jonas (2012). "Ageing and Skills". OECD Education Working Papers. doi:10.1787/5k9csvw87ckh-en.
- Kyllonen, Patrick C.; Christal, Raymond E. (1990). "Reasoning ability is (little more than) working-memory capacity?!". Intelligence 14 (4): 389–433. doi:10.1016/S0160-2896(05)80012-1.
- Geary, D. C. (2005). The origin of mind: Evolution of brain, cognition, and general intelligence. Washington, DC: American Psychological Association.
- Todd W. Thompson et al. (2013). "Failure of Working Memory Training to Enhance Cognition or Intelligence". PLoS ONE 8 (5).
- Melby-Lervåg, Monica; Hulme, Charles (2012). "Is Working Memory Training Effective? A Meta-Analytic Review". Developmental Psychology 49 (2): 270–91. doi:10.1037/a0028228. PMID 22612437.
- Jaeggi, Susanne M.; Buschkuehl, Martin; Jonides, John; Perrig, Walter J. (2008). "Improving fluid intelligence with training on working memory". Proceedings of the National Academy of Sciences 105 (19): 6829–33. Bibcode:2008PNAS..105.6829J. doi:10.1073/pnas.0801268105. JSTOR 25461885. PMC 2383929. PMID 18443283.
- Qiu, Feiyue; Wei, Qinqin; Zhao, Liying; Lin, Lifang (2009). "Study on Improving Fluid Intelligence through Cognitive Training System Based on Gabor Stimulus". 2009 First International Conference on Information Science and Engineering. pp. 3459–62. doi:10.1109/ICISE.2009.1124. ISBN 978-1-4244-4909-5.
- Chooi, Weng-Tink; Thompson, Lee A. (2012). "Working memory training does not improve intelligence in healthy young adults". Intelligence 40 (6): 531–42. doi:10.1016/j.intell.2012.07.004.
- Redick, Thomas S.; Shipstead, Zach; Harrison, Tyler L.; Hicks, Kenny L.; Fried, David E.; Hambrick, David Z.; Kane, Michael J.; Engle, Randall W. (2012). "No Evidence of Intelligence Improvement After Working Memory Training: A Randomized, Placebo-Controlled Study". Journal of Experimental Psychology: General. doi:10.1037/a0029082. PMID 22708717.