TY - GEN
T1 - Connectivity in math-gifted adolescents
AU - Baker, Mary
AU - Kapse, Kushal
AU - McMahon, Allison
AU - O'Boyle, Michael
N1 - Copyright:
Copyright 2012 Elsevier B.V., All rights reserved.
PY - 2012
Y1 - 2012
N2 - Major challenges in brain research include understanding how the brain retrieves, processes, and transmits information along with understanding how information is stored. Therefore, connectivity analyses are vital in exploring information flow and temporal interactions between particular brain regions. This paper presents the results of two different types of connectivity analysis on previously acquired fMRI data of mathematically gifted adolescents and control subjects performing a mental rotation task. It has been hypothesized that mathematically gifted children rely on the parietal region and right hemisphere, along with utilizing inter-hemispheric interactions that may be a more efficient network during mental rotation tasks. Granger causality and dynamic causal modeling (DCM) were used to model the connectivity in the two groups. The model outputs are compared with connectivity paths determined from structural equation modeling (SEM) in a previous study [1]. Although these methods can be used as confirmatory and/or exploratory tools, they may provide complementary, rather than redundant, information about connectivity networks within the brain.
AB - Major challenges in brain research include understanding how the brain retrieves, processes, and transmits information along with understanding how information is stored. Therefore, connectivity analyses are vital in exploring information flow and temporal interactions between particular brain regions. This paper presents the results of two different types of connectivity analysis on previously acquired fMRI data of mathematically gifted adolescents and control subjects performing a mental rotation task. It has been hypothesized that mathematically gifted children rely on the parietal region and right hemisphere, along with utilizing inter-hemispheric interactions that may be a more efficient network during mental rotation tasks. Granger causality and dynamic causal modeling (DCM) were used to model the connectivity in the two groups. The model outputs are compared with connectivity paths determined from structural equation modeling (SEM) in a previous study [1]. Although these methods can be used as confirmatory and/or exploratory tools, they may provide complementary, rather than redundant, information about connectivity networks within the brain.
KW - Granger causality
KW - SEM
KW - dynamic causal modeling
KW - fMRI
UR - http://www.scopus.com/inward/record.url?scp=84862836129&partnerID=8YFLogxK
U2 - 10.1109/SSIAI.2012.6202461
DO - 10.1109/SSIAI.2012.6202461
M3 - Conference contribution
AN - SCOPUS:84862836129
SN - 9781467318303
T3 - Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation
SP - 93
EP - 96
BT - 2012 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2012, Proceedings
Y2 - 22 April 2012 through 24 April 2012
ER -