Improved explanation of human intelligence using cortical features with second order moments and regression
- Title
- Improved explanation of human intelligence using cortical features with second order moments and regression
- Author
- 이종민
- Keywords
- Cortical features; Second order moments; Human intelligence; Partial least squares regression; Cortical thickness; Sulcal depth; Curvature; Surface area
- Issue Date
- 2014-04
- Publisher
- Elsevier B.V
- Citation
- Computers in Biology and Medicine 1 April 2014, 47, 139-146
- Abstract
- BackgroundCortical 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.MethodsWe 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).ResultsOur 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.DiscussionOur 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.
- URI
- https://www.sciencedirect.com/science/article/pii/S0010482514000341http://hdl.handle.net/20.500.11754/51109
- ISSN
- 0010-4825
- DOI
- 10.1016/j.compbiomed.2014.02.003
- Appears in Collections:
- COLLEGE OF ENGINEERING[S](공과대학) > ELECTRICAL AND BIOMEDICAL ENGINEERING(전기·생체공학부) > Articles
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