TY - JOUR
T1 - Joint Bayesian-Incorporating Estimation of Multiple Gaussian Graphical Models to Study Brain Connectivity Development in Adolescence
AU - Zhang, Aiying
AU - Cai, Biao
AU - Hu, Wenxing
AU - Jia, Bochao
AU - Liang, Faming
AU - Wilson, Tony W.
AU - Stephen, Julia M.
AU - Calhoun, Vince D.
AU - Wang, Yu Ping
N1 - Funding Information:
The work was supported in part by NIH under Grant R01GM109068, Grant R01MH104680, Grant R01MH107354, Grant P20GM103472, Grant 2R01EB005846, and Grant 1R01EB006841 and in part by NSF under Grant 1539067.
Publisher Copyright:
© 1982-2012 IEEE.
PY - 2020/2
Y1 - 2020/2
N2 - Adolescence is a transitional period between the childhood and adulthood with physical changes, as well as increasing emotional development. Studies have shown that the emotional sensitivity is related to a second period of rapid brain growth. However, there is little focus on the trend of brain development during this period. In this paper, we aim to track functional brain connectivity development from late childhood to young adulthood. Mathematically, this problem can be modeled via the estimation of multiple Gaussian graphical models (GGMs). However, most existing methods either require the graph sequence to be fairly long or are only applicable to small graphs. In this paper, we adapted a Bayesian approach incorporating joint estimation of multiple GGMs to overcome the short sequence difficulty, which is also computationally efficient. The data used are the functional magnetic resonance imaging (fMRI) images obtained from the publicly available Philadelphia Neurodevelopmental Cohort (PNC). They include 855 individuals aged 8-22 years who were divided into five different adolescent stages. We summarized the networks with global measurements and applied a hypothesis test across age groups to detect the developmental patterns. Three patterns were detected and defined as consistent development, late puberty, and temporal change. We also discovered several anatomical areas, such as the middle frontal gyrus, putamen gyrus, right lingual gyrus, and right cerebellum crus 2 that are highly involved in the brain functional development. The functional networks, including the salience, subcortical, and auditory networks are significantly developing during the adolescent period.
AB - Adolescence is a transitional period between the childhood and adulthood with physical changes, as well as increasing emotional development. Studies have shown that the emotional sensitivity is related to a second period of rapid brain growth. However, there is little focus on the trend of brain development during this period. In this paper, we aim to track functional brain connectivity development from late childhood to young adulthood. Mathematically, this problem can be modeled via the estimation of multiple Gaussian graphical models (GGMs). However, most existing methods either require the graph sequence to be fairly long or are only applicable to small graphs. In this paper, we adapted a Bayesian approach incorporating joint estimation of multiple GGMs to overcome the short sequence difficulty, which is also computationally efficient. The data used are the functional magnetic resonance imaging (fMRI) images obtained from the publicly available Philadelphia Neurodevelopmental Cohort (PNC). They include 855 individuals aged 8-22 years who were divided into five different adolescent stages. We summarized the networks with global measurements and applied a hypothesis test across age groups to detect the developmental patterns. Three patterns were detected and defined as consistent development, late puberty, and temporal change. We also discovered several anatomical areas, such as the middle frontal gyrus, putamen gyrus, right lingual gyrus, and right cerebellum crus 2 that are highly involved in the brain functional development. The functional networks, including the salience, subcortical, and auditory networks are significantly developing during the adolescent period.
KW - Aldolescence
KW - Gaussian graphical models (GGMs)
KW - brain development
KW - brain functional connectivity
KW - fMRI
KW - joint estimation
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U2 - 10.1109/TMI.2019.2926667
DO - 10.1109/TMI.2019.2926667
M3 - Article
C2 - 31283500
AN - SCOPUS:85079098490
SN - 0278-0062
VL - 39
SP - 357
EP - 365
JO - IEEE transactions on medical imaging
JF - IEEE transactions on medical imaging
IS - 2
M1 - 8754707
ER -