The Biostatistics &Neuroinformatics (BNI) Core serves as a centralized resource for biostatistical consulting and data management for all scientific projects proposed in this application. The core serves as a resource for data management and quality control, through a set of comprehensive neuroinformatics tools. The core personnel provide support to each of the junior principal investigators (PI) at all levels of investigation, beginning with the formulation of specific hypotheses, reviewing the design of studies, and evaluating the utility of measurement techniques. Support and consultation continues with the interpretation, presentation, and publication of the results, as well as throughout the grant application process.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Exploratory Grants (P20)
Project #
Application #
Study Section
Special Emphasis Panel (ZGM1-TWD-Y)
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
The Mind Research Network
United States
Zip Code
Zille, Pascal; Calhoun, Vince D; Stephen, Julia M et al. (2017) Fused estimation of sparse connectivity patterns from rest fMRI. Application to comparison of children and adult brains. IEEE Trans Med Imaging :
Meng, Xing; Jiang, Rongtao; Lin, Dongdong et al. (2017) Predicting individualized clinical measures by a generalized prediction framework and multimodal fusion of MRI data. Neuroimage 145:218-229
Bernard, Jessica A; Goen, James R M; Maldonado, Ted (2017) A case for motor network contributions to schizophrenia symptoms: Evidence from resting-state connectivity. Hum Brain Mapp 38:4535-4545
Gupta, Cota Navin; Castro, Eduardo; Rachkonda, Srinivas et al. (2017) Biclustered Independent Component Analysis for Complex Biomarker and Subtype Identification from Structural Magnetic Resonance Images in Schizophrenia. Front Psychiatry 8:179
Arbabshirani, Mohammad R; Plis, Sergey; Sui, Jing et al. (2017) Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls. Neuroimage 145:137-165
He, Hao; Sui, Jing; Du, Yuhui et al. (2017) Co-altered functional networks and brain structure in unmedicated patients with bipolar and major depressive disorders. Brain Struct Funct 222:4051-4064
Vergara, Victor M; Mayer, Andrew R; Damaraju, Eswar et al. (2017) The effect of preprocessing pipelines in subject classification and detection of abnormal resting state functional network connectivity using group ICA. Neuroimage 145:365-376
Faghiri, Ashkan; Stephen, Julia M; Wang, Yu-Ping et al. (2017) Changing brain connectivity dynamics: From early childhood to adulthood. Hum Brain Mapp :
de Lacy, N; Doherty, D; King, B H et al. (2017) Disruption to control network function correlates with altered dynamic connectivity in the wider autism spectrum. Neuroimage Clin 15:513-524
Lerman-Sinkoff, Dov B; Sui, Jing; Rachakonda, Srinivas et al. (2017) Multimodal neural correlates of cognitive control in the Human Connectome Project. Neuroimage 163:41-54

Showing the most recent 10 out of 168 publications