title: Improved explanation of human intelligence using cortical features with second order moments and regression.
abstract: BACKGROUND
  Cortical features derived from magnetic resonance imaging (MRI) provide important information to account for human intelligence. Cortical thickness, surface area, sulcal depth, and mean curvature were considered to explain human intelligence. One region of interest (ROI) of a cortical structure consisting of thousands of vertices contained thousands of measurements, and typically, one mean value (first order moment), was used to represent a chosen ROI, which led to a potentially significant loss of information.
  
  
  METHODS
  We proposed a technological improvement to account for human intelligence in which a second moment (variance) in addition to the mean value was adopted to represent a chosen ROI, so that the loss of information would be less severe. Two computed moments for the chosen ROIs were analyzed with partial least squares regression (PLSR). Cortical features for 78 adults were measured and analyzed in conjunction with the full-scale intelligence quotient (FSIQ).
  
  
  RESULTS
  Our results showed that 45% of the variance of the FSIQ could be explained using the combination of four cortical features using two moments per chosen ROI. Our results showed improvement over using a mean value for each ROI, which explained 37% of the variance of FSIQ using the same set of cortical measurements.
  
  
  CONCLUSIONS
  Our results suggest that using additional second order moments is potentially better than using mean values of chosen ROIs for regression analysis to account for human intelligence.
authors.affiliation: School of Electronic and Electrical Engineering, Sungkyunkwan University, Republic of Korea.
authors.forename: Hyunjin
authors.initials: H
authors.lastname: Park
authors.affiliation: Department of Biomedical Engineering, Hanyang University, Republic of Korea.
authors.forename: Jin-ju
authors.initials: JJ
authors.lastname: Yang
authors.affiliation: Department of Biomedical Engineering, Yonsei University, Republic of Korea.
authors.forename: Jongbum
authors.initials: J
authors.lastname: Seo
authors.affiliation: Bioimaging Research Center, Gwangju Institute of Science and Technology, Republic of Korea.
authors.forename: Yu-yong
authors.initials: YY
authors.lastname: Choi
authors.affiliation: Department of Marine Life Science, Chosun University, Republic of Korea.
authors.forename: Kun-ho
authors.initials: KH
authors.lastname: Lee
authors.affiliation: Department of Biomedical Engineering, Hanyang University, Republic of Korea. Electronic address: ljm@hanyang.ac.kr.
authors.forename: Jong-min
authors.initials: JM
authors.lastname: Lee
mesh_terms: D000328:Adult; D002540:Cerebral Cortex / Q000033:anatomy & histology* / Q000502:physiology*; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional; D007360:Intelligence / Q000502:physiology*; D016018:Least-Squares Analysis; D008279:Magnetic Resonance Imaging; D008297:Male; D013499:Surface Properties; D055815:Young Adult
keywords: Cortical features; Cortical thickness; Curvature; Human intelligence; Partial least squares regression; Second order moments; Sulcal depth; Surface area