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Theodore D. Satterthwaite
University of Pennsylvania
PsychiatryDevelopmental psychologyPsychologyCognitionNeuroimaging
214Publications
44H-index
7,225Citations
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Publications 244
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#1Adam Pines (UPenn: University of Pennsylvania)H-Index: 1
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Abstract Diffusion weighted imaging (DWI) has advanced our understanding of brain microstructure evolution over development. Recently, the use of multi-shell diffusion imaging sequences has coincided with advances in modeling the diffusion signal, such as Neurite Orientation Dispersion and Density Imaging (NODDI) and Laplacian-regularized Mean Apparent Propagator MRI (MAPL). However, the relative utility of recently-developed diffusion models for understanding brain maturation remains sparsely i...
1 CitationsSource
#1Laura Han (VU: VU University Amsterdam)H-Index: 3
#2Richard Dinga (Radboud University Nijmegen)H-Index: 2
Last. Klaus Berger (WWU: University of Münster)H-Index: 70
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Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18–75 yea...
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#1Eli J. CornblathH-Index: 5
#2Xiaosong HeH-Index: 9
Last. Elaine H. ZackaiH-Index: 87
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#1Danai Dima (City University London)H-Index: 20
#2Efstathios Papachristou (UCL: University College London)H-Index: 9
Last. Kathryn I. AlpertH-Index: 11
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Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalised on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine the age-related morphometric trajectories of the ventric...
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#1Ganesh B. ChandH-Index: 5
#2Daniel H. WolfH-Index: 39
Last. Alessandro PigoniH-Index: 1
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#1Eli J. CornblathH-Index: 5
#2Arian AshourvanH-Index: 4
Last. Tyler M. MooreH-Index: 25
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#1Sophia Frangou (ISMMS: Icahn School of Medicine at Mount Sinai)H-Index: 62
#2Amirhossein Modabbernia (ISMMS: Icahn School of Medicine at Mount Sinai)H-Index: 23
Last. Dag Alnæs (University of Oslo)H-Index: 18
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Delineating age-related cortical trajectories in healthy individuals is critical given the association of cortical thickness with cognition and behaviour. Previous research has shown that deriving robust estimates of age-related brain morphometric changes requires large-scale studies. In response, we conducted a large-scale analysis of cortical thickness in 17,075 individuals aged 3-90 years by pooling data through the Lifespan Working group of the Enhancing Neuroimaging Genetics through Meta-An...
1 CitationsSource
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