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The Relation Between Working Memory and Intelligence in Childhood - Case Study Example

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This paper "The Relation Between Working Memory and Intelligence in Childhood" discusses the intelligence that is defined as general cognitive problem-solving skills. It refers to a mental ability involved in reasoning, perceiving relationships and analogies, calculating and learning quickly…
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The Relation Between Working Memory and Intelligence in Childhood
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Consider the relation between working memory and intelligence in childhood. Intelligence is defined as general cognitive problem-solving skills. It refers to a mental ability involved in reasoning, perceiving relationships and analogies, calculating and learning quickly (What is intelligence, BrainMetrix). Researchers have divided intelligence into musical, bodily-kinesthetic, logical-mathematical, linguistic, spatial, interpersonal, and intrapersonal aspects. Intelligence is believed to be inherited. The extent of expression of intelligence depends on the environment. It has been detected in twins that 70% of characteristics are inherited. Genes decide the quality of intelligence. By determining the grey matter volume, cognitive performance is also decided. Intelligence quotient, verbal and spatial qualities are also genetically inherited. The verbal and spatial abilities are also genetically determined (What is intelligence, BrainMetrix). Environment is believed to reduce intelligence. Degradation of brain is fast. Wilhelm Stern said that the ratio of mental age to chronological age is Intelligence Quotient. Intelligence tests do not measure creativity, character or personality. Memory Mechanisms of learning and memory have evolved through the centuries at the molecular level (Dash and Moore, 2007, p. 710). These two mechanisms become significant in present day research where behavioural training becomes necessary as part of many rehabilitation therapies. The training causes changes in neuronal activity and neurotransmitter release leading to “intracellular kinase activity, protein phosphorylation, protein synthesis, and gene expression” (Dash and Moore, 2007, p. 710). The various phases of memory which include “working memory (lasting for seconds), short-term memory (lasting minutes), intermediate-term memory (lasting for hours), and long-term memory (lasting days to a lifetime) are all explainable through the intracellular changes. The cellular and molecular mechanisms answer for implicit and explicit memory. The various methods used for research are the electrophysiological recordings, pharmacological methods, molecular biological methods and genetic methods. The synaptic mechanism for memory was suggested by Tanzi (1893) and Ramon y Cajal (1911). Hebb said that when the axon of one neurone when close to another cell, firing occurs which results in a metabolic change or growth. Pavlov’s experiment where a bell and food were frequently presented together to a dog, whenever the dog saw the bell, it associated it with food and salivated even without the presence of food. This occurred due to a new synaptic activity among the neurons. Glutamate is the prominent transmitter in the brain (Dash and Moore, 2007, p. 711). The medial temporal lobe is involved with explicit memory (including conscious recollection) and consolidation. Spatial memory in explicit memory has been related to the dorsal hippocampal region. Implicit memory has three forms, short-term, intermediate-term and long term. When a stimulus is provided to a sensory neurone, it reaches the motor neurone causing an action. The amygdala is involved in storage of short-term memory apart from fear (Dash and Moore, 2007, p. 718). Intelligence, motivation, personality, abstract thinking and perception are subserved by other regions of the brain away from the hippocampus and amygdala. Short-term memory is associated with the phosphorylation of pre-existing proteins and cell surface ion channels and involves the insertion of AMPA receptors leading to increased synaptic communication. Intermediate memory is characterized by the synthesis of proteins from pre-existing mRNA which causes a lengthened kinase activation and phosphorylation. Long-term memory depends on genes and protein synthesis depending on specific transcription factors (Dash and Moore, 2007, p. 735). Working Memory Working memory is the process of “actively maintaining and integrating information for a relatively short period of time for directing goal oriented action” (Dash and Moore, 2007, p. 723). Recreation or retrieval of previously stored memory is through working memory which is maintained through reverberating neuronal activity. The dorsolateral parahippocampal cortex is involved with working memory. Dopamine plays a significant role in working memory (Brozoski et al, 1979). Depletion in dopamine produced working memory impairments in Rhesus monkeys, as bad as when surgical ablation was done. This deficit could be reversed with L-DOPA. Administration of dopamine by iontophoresis onto the neurons enhanced the working memory (Williams and Goldman-Rakic, 1995 in Dash and Moore, 2007, p. 723). Stimulation of D1 receptors induces a mild stress which can produce much dopamine which can hinder memory but overstimulation can impair working memory. Though mild stress increases the dopamine greatly and hinders working memory, the functions of the inferior temporal cortex or cerebellum become better. Excessive and insufficient dopamine can both therefore hinder working memory, giving rise to an inverted U dependency. Dopamine receptors are metabotropic, G –protein coupled receptors. Their effects are brought on by their action on intracellular enzymes. The D1 type of receptors increase cAMP levels while the D2 reduces it. The working memory is dependent on and sensitive to the D1 receptor which increases cAMP and cAMP dependent PKA or protein kinase A (Dash and Moore, 2007, p. 723). Though PKA is involved with the working memory, inhibition of its action does not interfere with working memory. Excess PKA activity actually interferes with working memory. In the aging, an increase in PKA activity is seen which may answer the questions on loss of working memory in the old. Relationship of Intelligence and Working memory Two differing lines of approach are described to describe the relationship between intelligence and working memory (Ribaupierre and Lecerf, 2006, p. 110). The neo-Piagetian approach resulted from Piaget’s study of intelligence. Though Piaget did not describe fluid intelligence, his work reveals the presence of fluid intelligence. The working memory capacity increases with cognitive development. The second approach focused on individual interests. Here it is assumed that working memory overlaps mostly with fluid intelligence. 2 studies were compared (Ribaupierre and Lecerf, 2006, p. 110). One study tested Piagetian tasks and 2 tasks of neo Piagetian tasks. The other study used the Raven task. It was found in both studies that the intelligence tasks were accounted for by the difference in ages in the working memory tasks (Ribaupierre and Lecerf, 2006, p. 110). Many studies with their origin in cognitive study showed that working memory capacity is related to fluid intelligence (Conway, Cowan, Bunting, Therriault, & Minkoff, 2002; Fry & Hale, 1996). Engle et al used structural modeling to show that there was a relationship between working memory tasks and Gf tasks (with the Raven test or Cattell tests) more than short memory tasks. Using the Braddeley and Hitch’s model, a close relationship was ascertained between Gf and the central executive. Kyllonen and Crystal say that working memory finds relationship with a large number of cognitive tasks (Ribaupierre and Lecerf, 2006, p. 113). Lifespan developmental psychology has also drawn from developmental and social psychology (Ribaupierre and Lecerf, 2006, p. 113). Working memory accounts for age differences in intelligence tasks (Dempster, 1991). Speed processing, inhibition and control processes are the tasks studied. The increase of working memory or attentional capacity could be one causal factor of cognitive development by the suggestions of Neo-Piagetians. Age differences in intelligence tasks may be explained by age differences in working memory or in processing speed. Working memory and fast work together to vouch for the age differences in fluid intelligence (Ribaupierre and Lecerf, 2006, p. 131). Intelligence and fluid analogies Neuroimaging investigations have revealed that intelligence has a relationship to fluid analogizing and the modeling of creative intelligence is related to executive neural functions (Geake, 2008, p. 187). The better fluid analogizing produces a more efficient working memory. A gifted intelligence is the result of an enhanced ability to participate in more fluid analogizing (Dehaene, Kerszberg, & Changeux, 1998). This fluid analogising is closely related to the neural functions that are associated with working memory (Geake and Hansen, 2005). “A gifted person’s high ability at fluid analogizing explains their more efficacious working memory, which in turn supports high levels of creative intelligence” (Geake in press in Geake, 2008, p. 187). Previous research has shown that the intelligent behaviour is associated with analogies (French, 2002). The presumption that intelligence is a fundamental cognitive process which is analogical was drawn from studies of the development of children (Goswami, 2001). Other researchers have indicated that this insightful analogy making is the basic reason for humans achieving success in many endeavours (Goswami, 2001; Holyoak & Thagard, 1995). These include, pattern recognition, indulging in and appreciating humour, inter-language translations, poetry, classroom exercises and even routine speech. Good teachers seek to create analogies for their explanations (Geake, 2003). The ability of gifted children is to create metacognitive explanations through their fluid analogizing (Geake, 2008, p. 188). Which brain processes support fluid analogizing? Frontal functioning has been implicated by research using the Ravens Progressive Matrix, a visuo-spatial test (Kroger et al, 2002). fMRI has been used for imaging. A second relationship has been postulated between analogic depth response and intelligence measures. Neural activations for difficult fluid analogies were found in left superior frontal gyrus, bilaterally in the inferior and middle frontal gyri and in the anterior cingulate/paracingulate cortex (Geake, 2008, p. 189). Reasoning tasks like “ inductive syllogisms, syntactic hierarchies and linguistic creativity”are subserved in these areas. Brodman’s area which includes Broca’s area of speech is the activated area. A meta-analysis of 20 neuroimaging studies of cognition showed the involvement of frontal cortical neurophysiology in high intelligence (Duncan and Owen, 2000). The activations were all in the bilateral inferior pre-frontal cortex. The cells in the pre-frontal cortex have the ability to be activated by different inputs probably due to the dense interconnections in this area (Duncan, 2001, p. 824). Executive functioning has been considered a feature of working memory with the basic process of intelligence (Gray and Thompson, 2004). Focused frontal information processing supports the same process in other parts of the brain through persistent activation from other parts of the brain. Temporary states of concern towards a particular problem would be the result of combined activation. Overlapping regions of frontal cortex may be involved in the persistent engagement of the problem. This would lead to the idea that a high demand on working memory is essential for sustained and focused thinking (Geake, 2005, p. 191). The lateral areas of the frontal lobes have a main function of attentional focus and selective inhibition (Baddeley and Sala, 1998). A gifted child is one whose enhanced frontal activity allows it to understand what steps to take to solve an intellectual problem. The neural feature of intellectual giftedness is the efficient frontal functioning, fluid analogising being the cognitive process which allows the various facets of working memory to function. Neuroimaging studies have also provided other evidences of supporting the role of frontal cortex in higher order thinking (Geake, 2008, p. 191). Retrieval of rule based knowledge is associated with the left superior frontal gyrus (Goel and Dolan, 2001). Executive functioning which involves the learning of new rules is subserved by the middle frontal gyrus (Strange, Henson, Friston, & Dolan, 2001). The anterior pre-frontal cortex has the function of resolution of sub-goals (Koechlin, Basso, Pietrini, Panzer, & Grafman, 1999). Task complexity is integrated relationally by the left ventral inferior prefrontal cortex (Christoff et al, 2001) especially when this task has to be selected from among many options (Kroger et al, 2002). Processing distant associations for creative thought and problem solving involves the activation of the right superior frontal gyrus and the adjacent middle frontal areas (Jung-Beeman, Bowden, Haberman, et al, 2004). Anterior cingulate and paracingulate gyrus have been associated with the transmission of attentional resources to higher order decision making (Kroger et al, 2002). Differences have also been noticed in the neuroanatomy in the focal density of white and grey matter of high IQ subjects and those with average IQ. Most of the brain cell density associated with IQ was found in the frontal (Haier, Jung, Yeo, Head, & Alkire, 2004). Another study showed that the thickness of the cerebral cortex was more significantly related to intelligence than the cortical thickness (Shaw, Greenstein, Lerch, et al., 2006). Thickness was lesser in the younger years but it reached suitably thick proportions at puberty for the gifted children especially in the pre-frontal regions. Fluid analogizing could be explored in order to inter-relate problem and context. A study found that gifted children have a neural net work which is more “spatially and temporally coordinated” (Zhang, Shi, Luo, Zhao, and Yang, 2006 in Geake, 2008, p. 191). A better coordinated network would mean that more analogical combinations are possible and thereby more creative intelligent individuals would be around to keep their ideas and concepts active in working memory. High intelligence would probably signify a frontal functioning within a fronto-parietal network. Mathematically gifted male adolescents have been found to have bilateral activation of parietal lobes and frontal cortex with increased activation of the anterior cingulate during mental rotation as evidenced from fMRI (Geake, 2008, p. 191). The intermodular neural network of gifted people have a better and superior ability to process information and think creatively. Their executive capability is thereby enhanced. Creative thinking involves the processes of making critical comparisons, conjoining events, refreshing memory, discarding irrelevant information, evaluating and judging. The intelligent perform better at tests as they think deeply and know what to take and what to discard for solving the tasks and problems. Long term memory retrieval, ability to transfer and apply and innovation allow the gifted to have a flourishing creative intelligence (Geake, 2008, p. 191). The musical prodigies which are a group of the gifted use fluid analogies to perform well in musical concerts. References: Baddeley, A., & Sala, S. D. (1998). Working memory and executive control. In A. C. Roberts, T. W. Robbins, & L. Weiskrantz (Eds.), Theprefrontal cortex: Executive and cognitive functions (pp. 9–21). Oxford, England: Oxford University Press. Brozoski TJ, Brown RM, Rosvold HE, Goldman PS. 1979. Cognitive deficit caused by regional depletion of dopamine in prefrontal cortex of rhesus monkey. Science 205: 929-932. Christoff, K., Prabhakaran, V., Dorfman, J., Zhao, Z., Kroger, J. K., Holyoak, K. J., et al. (2001). Rostrolateral prefrontal cortex involvement in relational integration during reasoning. Neuroimage, 14, 1136–1149. Dash, P. and Moore, A.N. (2007). “Neurochemistry and Molecular Neurobiology of Memory”. Chapter 19 in Handbook of Neurochemistry and Molecular Neurobiology Behavioral Neurochemistry, Neuroendocrinology and Molecular Neurobiology, (Eds.) Abel Lajtha, Springer Science and Business Media, New York. Dehaene, S., Kerszberg, M., & Changeux, J.-P. (1998). A neuronal model of a global workspace in effortful cognitive tasks. Proceedings of theNational Academy of Sciences USA, 95, 14529–14534. Dempster, F. N. (1991). Inhibitory processes: A neglected dimension of intelligence. Intelligence, 15, 157-173. Duncan, J. (2001). An adaptive coding model of neural function in prefrontal cortex. Nature Reviews Neuroscience, 2, 820–829. Duncan, J., & Owen, A. M. (2000). Common regions of the human frontal lobe recruited by diverse cognitive demands. Trends in Neuroscience, 23, 475–483. Geake, J. G. (2003). Adapting middle level educational practices to current research on brain functioning. Journal of the New England League of Middle Schools, 15(2), 6–12. Geake, J. G. (in press). Neuropsychological characteristics of academic and creative giftedness. In L. V. Shavinina (Ed.), International handbook of giftedness. Springer Science. Geake,J.G. (2008). High Abilities at Fluid Analogizing: A Cognitive Neuroscience Construct of Giftedness, Roeper Review, 30:187–195, 2008, The Roeper Institute DOI: 10.1080/02783190802201796, Routledge, Taylor and Francis group. Geake, J. G., & Hansen, P. C. (in press). Structural and Functional Neural correlates of high creative intelligence as determined by abilities at fluid analogising: An fMRI study. Paper presented at the Society for Neuroscience Annual Meeting, Atlanta, GA. Goel, V., & Dolan, R. J. (2001). Functional neuroanatomy of three-term relational reasoning. Neuropsychologia, 39, 901–909. Goswami, U. (2001). Analogical reasoning in children. In D. Gentner, K. J.Holyoak, & B. N. Kokinov (Eds.), The analogical mind: Perspectives from cognitive science (pp. 437–470). Cambridge, MA: MIT Press. Gray, J. R., & Thompson, P. M. (2004). Neurobiology of intelligence: Science and ethics. Nature Reviews Neuroscience, 5, 471–482. Haier, R. J., Jung, R. E., Yeo, R. A., Head, K., & Alkire, M. T. (2004). Structural brain variation and general intelligence. NeuroImage, 23(1), 425–433. Holyoak, K. J., & Thagard, P. (1995). Mental leaps: Analogy in creative thought. Cambridge MA: MIT Press. Jung-Beeman, M., Bowden, E. M., Haberman, J., Frymiare, J. L., Arambel-Liu, S., Greenblatt, R., et al. (2004). Neural activity when people solve verbal problems with insight. Public Library of Science Biology, 2, 0500–0510. Koechlin, E., Basso, G., Pietrini, P., Panzer, S., & Grafman, J. (1999). The role of the anterior prefrontal cortex in human cognition. Nature, 399, 148–151. Kroger, J. K., Sabb, F. W., Fales, C. L., Bookheimer, S. Y., Cohen, M. S., & Holyoak, K. J. (2002). Recruitment of anterior dorsolateral prefrontal cortex in human reasoning: A parametric study of relational complexity. Cerebral Cortex, 12, 477–485. Ribaupierre, A.de and Lecerf, T. (2006). “Relationships between working memory and intelligence from a developmental perspective: Convergent evidence from a neo-Piagetian and a psychometric approach. European Journal of Cognitive Psychology, 2006, 18 (1), 109-137 Psychology Press, Taylor and Francis Group Shaw, P., Greenstein, D., Lerch, J., Clasen, L., Lenroot, R., Gogtay, N., Evans, A., Rapoport, J., & Giedd, J. (2006). Intellectual ability and cortical development in children and adolescents. Nature, 440(7084): 676–679. Strange, B. A., Henson, R. N., Friston, K. J., & Dolan, R. J. (2001). Anterior prefrontal cortex mediates rule learning in humans. Cerebral Cortex, 11, 1040–1046. What is Intelligence. Retrieved on 16/2/09. http://www.brainmetrix.com/intelligence Brain Metrix.com Read More
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