Sex differences in the development of neuroanatomical functional connectivity underlying intelligence found using Bayesian connectivity analysis
Introduction
An increasing body of literature points to sexual dimorphism in the neuroanatomical correlates of intelligence, hypothesized to be the result of women possessing more neuronal processes but fewer neurons compared to men (de Courten-Myers, 1999), as well as an 8–10% smaller overall brain size (Nopoulos et al., 2000, Rabinowicz et al., 1999). These factors appear to contribute to a greater association in women between white matter properties and intelligence (Gur et al., 1999). In a voxel-based morphometry (VBM) study (Haier et al., 2005), women showed more areas in which white matter density was correlated with IQ in comparison to men, who displayed more areas with gray matter density associated with IQ. Magnetic resonance spectroscopy (MRS) studies have found regions in which N-acetyl-aspartate (NAA) concentrations were only associated with intelligence in women but not in men, including the left occipito-parietal white matter (Jung et al., 2005), and left prefrontal cortex (Pfleiderer et al., 2004). A recent functional MRI (fMRI) study (Schmithorst and Holland, 2006) showed a developmental aspect to this sexual dimorphism, hypothesized to be associated with gray matter pruning (Casey et al., 2000, Courchesne et al., 2000, Giedd et al., 1999), as well as disparate trajectories between boys and girls in overall brain maturation and growth (Lynn, 1994, Lynn, 1999, Lynn et al., 2000). Girls showed a trend in development toward an increasing association with age of functional connectivity with intelligence, at least in the left hemisphere; while the opposite trend was shown in boys, with an increasing association with age of localized cortical function with intelligence. That study, however, utilized a silent verb-generation task, which predominantly recruits the left hemisphere of the brain for most subjects (Holland et al., 2001).
Sex differences associated with cognitive performance have been found in the splenium of the corpus callosum (Davatzikos and Resnick, 1998), leading us to expect a similar effect (e.g., increasing reliance with age on inter-hemispheric functional connectivity in girls, with the opposite effect in boys) in a task which recruits both hemispheres. In order to investigate this hypothesis, we re-analyzed data obtained from a large-scale fMRI study in children investigating narrative comprehension (Schmithorst et al., 2006). Since investigation of sex-related differences, especially in children, likely requires a very large sample size (Plante et al., 2006) due to the small effect size, a reanalysis of this data set, using a specially tailored data analysis strategy, was determined to be the best way to investigate the above hypothesis. The particular data set used is ideal for investigation of sex differences in the relationship of inter-hemispheric functional connectivity and intelligence, and any developmental effect, due to the large sample size (> 300 children), the age range (5–18 years), and the specific task employed (narrative processing), which from our previous analysis involving Independent Component Analysis has been shown to recruit bilateral networks in the brain (Schmithorst et al., 2006).
We employ a newly developed Bayesian methodology for modeling functional connectivity (Patel et al., 2006a, Patel et al., 2006b) which is completely data-driven and hypothesis unconstrained. The method eliminates the necessity of providing a predetermined model of connectivity as demanded by Structural Equation Modeling (SEM) (McIntosh and Gonzalez-Lima, 1994, Solodkin et al., 2004) or Dynamic Causal Modeling (DCM) (Friston et al., 2003, Penny et al., 2004a, Penny et al., 2004b). We have modified the method in order to be able to investigate between-subjects and between-groups differences. The benefit of the Bayesian methodology is that it allows the calculation of a posterior probability that the hypothesis of interest is true, rather than simply a rejection of the null hypothesis, as in standard frequentist statistics; moreover, the Bayesian methodology provides an upper bound on the rate of false discovery of significant functional connections (Friston and Penny, 2003).
Section snippets
Materials and methods
As described above, the present paper re-analyzes fMRI data originally analyzed using Independent Component Analysis (Schmithorst et al., 2006). The task used was that of narrative comprehension, and the subjects consisted of normal children ages 5–18. We refer the reader to our previous paper for a complete description of the task, subjects, and data pre-processing but provide a detailed summary here.
The fMRI scan paradigm consisted of a 30-s on–off block design. One story, read by an adult
Results
For the voxelwise fMRI analysis involving all 303 subjects, and for the Bayesian connectivity analysis involving 296 subjects, there was no significant difference between boys and girls for full-scale IQ (p > 0.7, independent t-test), age (p > 0.4, independent t-test), or performance (p > 0.29, Mann–Whitney U-test). There was a significant association between performance and full-scale IQ for the voxelwise fMRI analysis and for the Bayesian connectivity analysis involving 296 subjects (Spearman's R =
Discussion
Previous studies investigating possible sex-related differences in the cortical activation subserving language processing have found disparate results (Sommer et al., 2004). Some studies have found moderate differences in adults (Kansaku et al., 2000, Phillips et al., 2001, Pugh et al., 1996, Shaywitz et al., 1995); however, a different study (Frost et al., 1999) failed to find any significant differences, even with a relatively large sample size. A recent study performed on children (Plante et
Conclusion
Possible sex differences in the neuroanatomical bases for intelligence in children were investigated in a large cohort of children ages 5–18 using the fMRI paradigm of passive story listening. To investigate functional connectivity differences, a recently published Bayesian technique for modeling functional connectivity was modified for the investigation of individual differences. Girls showed a greater reliance on connectivity between the left posterior superior temporal gyrus and Wernicke's
Acknowledgments
This research was supported by a grant by the U.S. National Institutes of Health, National Institute of Child Health and Development, #R01-HD38578. The authors thank Dr. Anna Byars, PhD, for assistance in the administration of the Wechsler Full-Scale IQ tests, Drs. Richard Strawsburg, M.D. and Mark Schapiro, M.D., for performing the neurological examination, and Dr. William Ball, M.D., for reading the structural scans.
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