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Outputs (3)

Brain structural covariance network differences in adults with alcohol dependence and heavy-drinking adolescents (2021)
Journal Article
Ottino-González, J., Albaugh, M. D., Cao, Z., Cupertino, R. B., Schwab, N., Spechler, P. A., …Garavan, H. (2022). Brain structural covariance network differences in adults with alcohol dependence and heavy-drinking adolescents. Addiction, 117(5), 1312-1325. https://doi.org/10.1111/add.15772

BACKGROUND AND AIMS: Graph theoretic analysis of structural covariance networks (SCN) provides an assessment of brain organization that has not yet been applied to alcohol dependence (AD). We estimated whether SCN differences are present in adults wi... Read More about Brain structural covariance network differences in adults with alcohol dependence and heavy-drinking adolescents.

The Human Connectome Project: A retrospective (2021)
Journal Article
Elam, J. S., Glasser, M. F., Harms, M. P., Sotiropoulos, S. N., Andersson, J. L., Burgess, G. C., …Van Essen, D. C. (2021). The Human Connectome Project: A retrospective. NeuroImage, 244, Article 118543. https://doi.org/10.1016/j.neuroimage.2021.118543

The Human Connectome Project (HCP) was launched in 2010 as an ambitious effort to accelerate advances in human neuroimaging, particularly for measures of brain connectivity; apply these advances to study a large number of healthy young adults; and fr... Read More about The Human Connectome Project: A retrospective.

Predicting Depression Onset in Young People Based on Clinical, Cognitive, Environmental, and Neurobiological Data (2021)
Journal Article
Toenders, Y. J., Kottaram, A., Dinga, R., Davey, C. G., Banaschewski, T., Bokde, A. L., …Schmaal, L. (2022). Predicting Depression Onset in Young People Based on Clinical, Cognitive, Environmental, and Neurobiological Data. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 7(4), 376-384. https://doi.org/10.1016/j.bpsc.2021.03.005

Background
Adolescent onset of depression is associated with long-lasting negative consequences. Identifying adolescents at risk for developing depression would enable the monitoring of risk-factors and the development of early intervention strategi... Read More about Predicting Depression Onset in Young People Based on Clinical, Cognitive, Environmental, and Neurobiological Data.