# Algorithm and Data Analysis (ADA) Core > **NIH NIH P30** · LOVELACE BIOMEDICAL RESEARCH INSTITUTE · 2021 · $362,860 ## Abstract Project Summary/Abstract The algorithm and data analysis (ADA) core of this phase III COBRE will provide basic and advanced centralized image analysis resources for processing multimodal imaging data. These resources include tools designed for basic and advanced analysis of structural MRI (sMRI), MR spectroscopy (MRS), function MRI (fMRI), diffusion MRI (dMRI), magnetoencephalography (MEG), electroencephalography (EEG), and genetics 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. 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 enabling investigators to leverage additional information via joint analysis of multiple modalities (data fusion). 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 about data analysis of brain imaging and genetic data, as well as mentoring for specific projects. This will ensure investigators and potential core users 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. Co-director Dr. Cheryl Aine has extensive experience in unimodal and multimodal imaging with MEG/EEG. 1 ## Key facts - **NIH application ID:** 10173823 - **Project number:** 5P30GM122734-05 - **Recipient organization:** LOVELACE BIOMEDICAL RESEARCH INSTITUTE - **Principal Investigator:** Andrew Robert Mayer - **Activity code:** P30 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2021 - **Award amount:** $362,860 - **Award type:** 5 - **Project period:** 2018-05-18 → 2023-04-30 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10173823 ## Citation > US National Institutes of Health, RePORTER application 10173823, Algorithm and Data Analysis (ADA) Core (5P30GM122734-05). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10173823. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*