The Neuropsychology and Psychophysiology of Human Intelligence

Vernon, Philip A.; Wickett, John C.; Bazana, P. Gordon; Stelmack, Robert M.

doi:10.1017/cbo9780511807947.013

Cited by 87 publications

(69 citation statements)

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“…Positive and significant correlations between IQ and HC and brain size (absolute or adjusted for height) have been reported by many authors (Nelson & Deutschberger, 1970;Van Valen, 1974;Fisch et al 1976;Susanne, 1979;Rumsey & Rapoport, 1983;Hack & Breslau, 1986;Ounsted et al 1988;Desch et al 1990;Hack et al 1991;Johnson, 1991;Willerman et al 1991;Andreasen et al 1993;Lynn, 1993;Jensen & Johnson, 1994;Reiss et al 1996;Botting et al 1998;Strauss & Dietz, 1998;Pennington et al 2000;Ivanovic et al 2000a,b,c;Rushton, 2000;Rushton & Ankney, 1996, 2000Vernon et al 2000;Wickett et al 2000) and in our present observations. As stated in a previous report, educational drop-out is related to HC, but not to weight or height .…”

Section: Discussionmentioning

confidence: 82%

“…In the 20th century, a positive and significant correlation between HC and brain size and intelligence has been reported by several investigators, suggesting that differences in human brain size are relevant in explaining differences in intelligence, although genetic and environmental factors might also affect these inter-relationships (Nelson & Deutschberger, 1970;Van Valen, 1974;Fisch et al 1976;Susanne, 1979;Hack & Breslau, 1986;Ounsted et al 1988;Desch et al 1990;Hack et al 1991;Johnson, 1991;Willerman et al 1991;Andreasen et al 1993;Jensen & Johnson, 1994;Reiss et al 1996;Botting et al 1998;Strauss & Dietz, 1998;Ivanovic et al 1995aIvanovic et al , 2000aRushton, 2000;Rushton & Ankney, 1996, 2000Vernon et al 2000;Wickett et al 2000). Some of these studies have concluded that head size at 1 year of age is a good predictor of later intelligence (Nelson & Deutschberger, 1970;Fisch et al 1976;Botting et al 1998).…”

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confidence: 98%

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Nutritional status, brain development and scholastic achievement of Chilean high-school graduates from high and low intellectual quotient and socio-economic status

et al. 2002

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The objective of the present study was to investigate the inter-relationships between nutritional status (past and current nutrition), brain development, and scholastic achievement (SA) of Chilean high-school graduates from high and low intellectual quotient (IQ) and socio-economic status (SES) (mean age 18 : 0 (SD 0 : 9) years). Results showed that independently of SES, highschool graduates with similar IQ have similar nutritional, brain development and SA variables. Multiple regression analysis between child IQ (dependent variable) and age, sex, SES, brain volume (BV), undernutrition during the first year of life, paternal and maternal IQ (independent variables) revealed that maternal IQ (P,0 : 0001), BV (P,0 : 0387) and severe undernutrition during the first year of life (P,0 : 0486), were the independent variables with the greatest explanatory power for child IQ variance (r 2 0 : 707), without interaction with age, sex or SES. Child IQ (P,0 : 0001) was the only independent variable that explained both SA variance (r 2 0 : 848) and academic aptitude test variance (r 2 0 : 876) without interaction with age, sex or SES. These results confirm the hypotheses formulated for this study that: (1) independently of SES, high-school graduates with similar IQ have similar variables of nutritional status, brain development and SA; (2) past nutritional status, brain development, child IQ and SA are strongly and significantly inter-related. These findings are relevant in explaining the complex interactions between variables that affect IQ and SA and can be useful for nutritional and educational planning.

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Section: Discussionmentioning

confidence: 82%

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confidence: 98%

Nutritional status, brain development and scholastic achievement of Chilean high-school graduates from high and low intellectual quotient and socio-economic status

et al. 2002

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“…For example, within the normal range of birth weight, various cohort studies have found that heavier neonates have superior cognitive ability at age 7 years (Matte et al, 2001;Jefferis et al, 2002), 8 years (Richards et al, 2001) 11 years (Shenkin et al, 2001) and 18 years (Sorensen et al, 1997). In addition, many studies have identified a positive correlation between head circumference (or brain volume) and cognitive ability (see review (Vernon et al, 2000)). …”

Section: Main Findingsmentioning

confidence: 99%

Season of birth is associated with anthropometric and neurocognitive outcomes during infancy and childhood in a general population birth cohort

McGrath

Saha

Lieberman

et al. 2006

Schizophrenia Research

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The dseason of birthT effect is one of the most consistently replicated associations in schizophrenia epidemiology. In contrast, the association between season of birth and development in the general population is relatively poorly understood. The aim of this study was to explore the impact of season of birth on various anthropometric and neurocognitive variables from birth to age seven in a large, community-based birth cohort. A sample of white singleton infants born after 37 weeks gestation (n = 22,123) was drawn from the US Collaborative Perinatal Project. Anthropometric variables (weight, head circumference, length/height) and various measures of neurocognitive development, were assessed at birth, 8 months, 4 and 7 years of age. Compared to summer/autumn born infants, winter/spring born infants were significantly longer at birth, and at age seven were significantly heavier, taller and had larger head circumference. Winter/spring born infants were achieving significantly higher scores on the Bayley Motor Score at 8 months, the Graham-Ernhart Block Test at age 4, the Wechsler Intelligence Performance and Full Scale scores at age 7, but had significantly lower scores on the Bender-Gestalt Test at age 7 years. Winter/spring birth, while associated with an increased risk of schizophrenia, is generally associated with superior outcomes with respect to physical and cognitive development. D

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“…Besides questions about the structure of intelligence, a lot of research focused on the question of why people perform differently in intelligence tests. A still increasing number of explanations have been investigated, such as brain volume, amplitude and latency of event-related brain potentials, cerebral glucose consumption, and nerve conduction velocity (Vernon, Wickett, Bazana, & Stelmack, 2000). The most widely examined cognitive correlates of psychometric intelligence are speed of information processing (Deary, 2000), attention (Hunt & Lansman, 1982;Schweizer, Moosbrugger, & Goldhammer, 2005), and working memory capacity (WMC; Ackerman, Beier, & Boyle, 2005), with the latter one being of particular interest in the last 20 years.…”

Section: Introductionmentioning

confidence: 99%

Elucidating the Functional Relationship Between Working Memory Capacity and Psychometric Intelligence: A Fixed-Links Modeling Approach for Experimental Repeated-Measures Designs

Thomas¹,

Rammsayer²,

Schweizer³

et al. 2015

ACP

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working memory capacity, fluid intelligence, fixed-links modeling, confirmatory factor analysis numerous studies reported a strong link between working memory capacity (WMc) and fluid intelligence (gf), although views differ in respect to how close these two constructs are related to each other. in the present study, we used a WMc task with five levels of task demands to assess the relationship between WMc and gf by means of a new methodological approach referred to as fixed-links modeling. Fixed-links models belong to the family of confirmatory factor analysis (cFA) and are of particular interest for experimental, repeated-measures designs. With this technique, processes systematically varying across task conditions can be disentangled from processes unaffected by the experimental manipulation. Proceeding from the assumption that experimental manipulation in a WMc task leads to increasing demands on WMc, the processes systematically varying across task conditions can be assumed to be WMc-specific. Processes not varying across task conditions, on the other hand, are probably independent of WMc. Fixed-links models allow for representing these two kinds of processes by two independent latent variables. in contrast to traditional cFA where a common latent variable is derived from the different task conditions, fixed-links models facilitate a more precise or purified representation of the WMc-related processes of interest. By using fixed-links modeling to analyze data of 200 participants, we identified a non-experimental latent variable, representing processes that remained constant irrespective of the WMc task conditions, and an experimental latent variable which reflected processes that varied as a function of experimental manipulation. this latter variable represents the increasing demands on WMc and, hence, was considered a purified measure of WMc controlled for the constant processes. Fixed-links modeling showed that both the purified measure of WMc (β = .48) as well as the constant processes involved in the task (β = .45) were related to gf. taken together, these two latent variables explained the same portion of variance of gf as a single latent variable obtained by traditional cFA (β = .65) indicating that traditional cFA causes an overestimation of the effective relationship between WMc and gf. thus, fixed-links modeling provides a feasible method for a more valid investigation of the functional relationship between specific constructs.

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The Neuropsychology and Psychophysiology of Human Intelligence

Cited by 87 publications

References 0 publications

Nutritional status, brain development and scholastic achievement of Chilean high-school graduates from high and low intellectual quotient and socio-economic status

Nutritional status, brain development and scholastic achievement of Chilean high-school graduates from high and low intellectual quotient and socio-economic status

Season of birth is associated with anthropometric and neurocognitive outcomes during infancy and childhood in a general population birth cohort

Elucidating the Functional Relationship Between Working Memory Capacity and Psychometric Intelligence: A Fixed-Links Modeling Approach for Experimental Repeated-Measures Designs

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