The algorithm and data analysis (ADA) core of this phase II COBRE will fulfill the need for centralized image analysis resources that will be used to support all five projects. These resources include tools designed for measurement and analysis of sMRI, MRS, fMRI, DTI, genetics, EEG and MEG data. The ADA Core will play a leading role in developing and providing software that is needed to solve basic image analysis problems that arise when working with MR and MEG/EEG data. This will be accomplished by providing a core set of tools and approaches for analysis of imaging and genetic data. The core set of resources includes expertise and tools for analyzing all first level-imaging data (automated pipeline preprocessing) as well as advanced algorithms for network-based functional and structural connectivity measures to address in a comprehensive way the scientific questions being asked in each of the projects. We will work with the tools developed locally as well as widely-used tools developed by other groups to enable network-based analysis, data-fusion of multimodal data, and prediction/classification approaches. Importantly, a key aspect of this COBRE and the ADA core is focused on combining multimodal data as each project will work with two or more modalities. An additional area of emphasis will be on the development of realistic simulation approaches, to enable comparisons of algorithms, optimization of parameters, and to provide intuition about how new algorithms work. Finally, the ADA core will also provide essential training to junior investigators about data analysis of brain imaging and genetic data. This will ensure junior investigators are informed about the various algorithms, understand how to make analysis choices given a particular hypothesis, and have a basic idea of how to implement such algorithms themselves. The director of the ADA Core is Dr. Calhoun, who has over 20 years of experience in developing tools and approaches for working with unimodal and multimodal imaging and genetics data. Codirector Dr. Cheryl Aine has extensive experience in unimodal and multimodal imaging with MEG/EEG and codirector Dr. Julia Stephen, a graduate of the phase I COBRE, is currently the director of the MEG facility at MRN and has considerable experience in combining MEG and fMRI data, as well as EEG and MEG data in clinical groups.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Exploratory Grants (P20)
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Special Emphasis Panel (ZGM1-TWD-Y)
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The Mind Research Network
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van Erp, Theo G M; Walton, Esther; Hibar, Derrek P et al. (2018) Cortical Brain Abnormalities in 4474 Individuals With Schizophrenia and 5098 Control Subjects via the Enhancing Neuro Imaging Genetics Through Meta Analysis (ENIGMA) Consortium. Biol Psychiatry 84:644-654
Faghiri, Ashkan; Stephen, Julia M; Wang, Yu-Ping et al. (2018) Changing brain connectivity dynamics: From early childhood to adulthood. Hum Brain Mapp 39:1108-1117
Alam, Md Ashad; Lin, Hui-Yi; Deng, Hong-Wen et al. (2018) A kernel machine method for detecting higher order interactions in multimodal datasets: Application to schizophrenia. J Neurosci Methods 309:161-174
Chen, Jiayu; Hutchison, Kent E; Bryan, Angela D et al. (2018) Opposite Epigenetic Associations With Alcohol Use and Exercise Intervention. Front Psychiatry 9:594
Anderson, Nathaniel E; Harenski, Keith A; Harenski, Carla L et al. (2018) Machine learning of brain gray matter differentiates sex in a large forensic sample. Hum Brain Mapp :
Chen, Zikuan; Calhoun, Vince (2018) Effect of Spatial Smoothing on Task fMRI ICA and Functional Connectivity. Front Neurosci 12:15
Liu, Jingyu; Chen, Jiayu; Perrone-Bizzozero, Nora I et al. (2018) Regional enrichment analyses on genetic profiles for schizophrenia and bipolar disorder. Schizophr Res 192:240-246
Chen, Zikuan; Robinson, Jennifer; Calhoun, Vince (2018) Brain functional BOLD perturbation modelling for forward fMRI and inverse mapping. PLoS One 13:e0191266
Plis, Sergey M; Amin, Md Faijul; Chekroud, Adam et al. (2018) Reading the (functional) writing on the (structural) wall: Multimodal fusion of brain structure and function via a deep neural network based translation approach reveals novel impairments in schizophrenia. Neuroimage 181:734-747
Walton, E; Hibar, D P; van Erp, T G M et al. (2018) Prefrontal cortical thinning links to negative symptoms in schizophrenia via the ENIGMA consortium. Psychol Med 48:82-94

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