Neuroanatomical correlates of intellectual ability across lifespan Anchor Study Neuroanatomical correlates of intellectual ability across lifespan By Suzanne Goh, Ravi Bansal, Dongrong Xu, Xuejun Hao, Jun Liu, Bradley S. Peterson

Aim/Goal To determine the correlation of cortical thickness in the cerebrum of the human brain with FSIQ (Full Scale Intelligence quotient) and determine the moderating effects of sex and age. To use the results of the cortical findings to determine whether they were supported by differences in white matter volume. http://tinyurl.com/62tqytz http://tinyurl.com/64hzge4

Participants and Sample Size The participants of this cross-sectional study included 105 healthy people (no current or past psychiatric/neurological disorder) selected randomly from a telemarketing database. Mean age - 17.7 years Age range 7-57 years (children < 18years = 62%) FSIQ of 70 and higher Gender Females - 45.7%, Males - 54.3% http://tinyurl.com/3kju2v6

Methodology/Research Design

Neuropsychological Assessment –Intelligence Testing Different instruments were used based on research study protocol. All instruments tested similar domain of cognitive function. Intelligence testing was done on the same day of Magnetic Resonance Imaging (MRI) or within 1 month. Wechsler Intelligence scales, age determined which version was used. -For 51 children - Wechsler Intelligence Scale for Children (WISC-III) -For 34 adults - Wechsler Adult Intelligence Scale revised (WAIS-R) -For 3 children & 6 adults - Wechsler Abbreviated Scale of Intelligence(WASI) Kaufmann Brief Test of Intelligence (K-BIT) -For 11 children

Image Acquisition and Processing MR Image Acquisition - 1.5 Tesla Scanner was used to acquire anatomical image. - Cantho-meatal landmarks used to standardized head positioning. - 3-dimensional spoiled gradient recall sequence used to acquire image. http://tinyurl.com/3gtl9o9

Image Acquisition and Processing MR Image Processing Brain and non-brain tissues were separated using an automated tool and manual editing. Cortical gray matter was isolated using representative values of gray and white matter together with 3 orthogonal views on Sun Ultra 10 workstation (ANALYZE 7.5 software). The gray scale values of pure representations of cortical gray and white matter was sampled bilaterally in 4 locations using 8x8 pixel array. http://tinyurl.com/44gzs63

Image Acquisition and Processing MR Image Processing continued Average calculated for each tissue type to reduce bias. Mean threshhold value used to provide rough classification of gray and white matter throughout the cerebrum. This classification was hand-edited in 3 orthogonal views to remove subcortical gray matter and rims of the ventricles. White matter was isolated. Images were flipped to remove bias , then corrected.

Image Acquisition and Processing Template Selection – To select the most appropriate template Selected template brain of participant that most demographically represented all healthy controls. Average brain is not used as template inorder to ensure accuracy. Brains for all other participants were coregistered to template brain using a rigid body similarity transformation. Coregistered brains were then nonlinearly transformed to the template brain using a high-dimensional, non-rigid warping algorithm based on fluid dynamics. Each brain now the same shape and size as template brain, permitted identification of points on all participants’ cerebral surfaces to compare with corresponding points on template. Distance was computed between points on brain surfaces using least square analysis. The cerebrum for which all points across its surface was closest to the average computed distance was reselected as the template brain. Processes were repeated.

Image Acquisition and Processing Calculation of cortical thickness Coregistered brain - cortical mantel 3-dimensional morphological operator to distance transform the brain without the cortex from coregistered brain. Cortical thickness was calculated as the smallest distance of each point on the external cortical surface from the outermost surface of the white matter in the coregistered brain. Cclculation of cortical thickness was controlled for whole brain volume. http://tinyurl.com/64hzge4

Image Acquisition and Processing Volume-preserved warping (VPW) VPW warped a binarized image of the brain to form a spatially normailized image that has varying pixel intensities. Voxel-wise statistical analyses performed to detect regions of significant correlation between local brain volume and FSIQ.

Results Cortical thickness and FSIQ In localized regions of the prefrontal cortices ( left ventromedial and right dorsolateral prefrontal cortices), an inverse correlation between cortical thickness and FSIQ was found. Specific areas include left anterior cingulate gyrus, left orbitofrontal cortex, left subgenal gyrus and right middle frontal gyrus. http://www.psych-it.com.au/Psychlopedia/article.asp?id=191 http://tinyurl.com/3vvobnk

Results continued Cortical thickness and FSIQ Gender and FSIQ Gender-modified correlations in many regions but primarily in the frontal regions. These include the Broca’s area, left cingulate cortex and right medial prefrontal gyrus. Correlation for cortical thickness differed for males and females in prefrontal regions. - Females showed a positive correlation in nearly all regions - Males showed an inverse correlation. Exception – left anterior cingulate cortex showed a positive correlation for males and negative for females. http://tinyurl.com/67a5c25 http://tinyurl.com/3woz5dg

Results continued White matter Total Brain Volume A significant FSIQ-by-age interaction was detected in the right frontal white matter volume and in the white matter underlying the dorsolateral prefrontal cortex adults but not in children. An inverse correlation was found, that increased with age. In the left periventricular matter of adults a positive correlation was detected between FSIQ and white matter volume. Observation due to fibers of the superior corona radiata, superior longitudinal fasciculus and anterior portion of the corpus callosum. No FSIQ-by-sex correlation observed. Total Brain Volume FSIQ correlated positively with total brain volume

Implication of Results The inverse correlation between cortical thickness and FSIQ in the prefrontal cortex could be as a consequence of - The inverse correlation between white matter volume and FSIQ, means that smaller volumes of white matter influenced higher FSIQ in adults. The findings from gray and white matter volume therefore further reinforce the idea that synaptic pruning in adults accounts for their inter-intellectual differences in adults Correlation of cortical thickness with FSIQ in the Broca’s area in females possibly reflects why females have an advantage over males for verbal fluency. Inter-individual differences in intellectual ability observed in adults Synaptic pruning/ increase myelin coating of fibers in lower cortical areas, leading to cortical thinning Late maturation of prefrontal cortex

Parieto-Frontal Integration Theory of Intelligence The findings of this study overlap with finding from other studies to indicate that the frontal and parietal regions compose the primary neurological substrate for “g” , general intelligence as well as the necessary skills to perform many cognitive functions. Anchor study findings therefore support the Parieto-Frontal Integration Theory of Intelligence. - inverse correlation between cortical thickness and intelligence - gender specific patterns correlated with intelligence - cortical and white matter are involved in intelligence This theory states that the frontal and parietal lobes in the brain are the primary areas involve in intelligence. (http://www.science20.com/news_account/parieto_frontal_integration_theory_p_fit_a_neural_basis_of_intelligence)

Discussion Questions How reflective is the anchor study “ Neuroanatomical correlates of intellectual ability across the lifespan,of Gardner’s, “Myths and realities of multiple intelligence”?. Gardner wrote, “I would recommend that any intelligence be assessed by a number of complementary approaches that consider the core components of an intelligence.” Analyzing this statement, how would you suggest the implementation of assessment based on Gardner’s Multiple Intelligence? In the anchor text, the effects of age on intelligence was studied. How then does the theory nature vs. nurture impact intelligence across lifespan?