Alzheimer’s Disease Neuroimaging Initiative (ADNI)
The Alzheimer’s Disease Neuroimaging Initiative (ADNI) is a global effort to develop treatments for Alzheimer’s Disease through research collaboration and data sharing. This multisite longitudinal study analyzes clinical, imaging, genetic, and cognitive biomarkers to examine the brain’s structural and functional changes as it progresses through the disease. Data from international studies is aggregated in a centralized database, the LONI Image and Data Archive.
Visit the ADNI website to learn more.
Big Data to Knowledge (BD2K): Big Data for Discovery Science Center (BDDS)
The Big Data for Discovery Science Center (BDDS) is an NIH-support undertaking involving close collaboration between the INI, USC’s Information Sciences Institute, the Computation Institute at the University of Chicago, and the Institute for Systems Biology in Seattle, Washington. The initiative seeks to train investigators around the world how to maximize existing datasets, and provides them with the resources to do so. BDDS sponsors training seminars and provides researchers with access to its Knowledge Discovery Interface (KDI), an intuitive training system comprising lectures, tutorials, and other educational material.
Visit the BDDS website to learn more.
Big Data to Knowledge (BD2K): Enhancing Neuro Imaging Genetics through Meta Analysis (ENIGMA)
The Enhancing Neuro Imaging Genetics through Meta Analysis (ENIGMA) Consortium, based at INI’s Imaging Genetics Center (IGC), performs the largest-ever studies of the human brain, analyzing brain scans of more than 53,000 people worldwide. This collaborative group, led by IGC Director and INI Associate Director Paul Thompson, studies 22 brain diseases in 37 countries, focusing on the interaction between brain health and genetics. ENIGMA has published the largest-ever neuroimaging studies of schizophrenia, major depression, bipolar disorder, and obsessive-compulsive disorder.
Visit the ENIGMA website to learn more.
Global Alzheimer’s Association Interactive Network (GAAIN)
The Global Alzheimer’s Association Interactive Network (GAAIN) advances research into the causes, prevention and treatment of Alzheimer’s and related neurodegenerative diseases through a global cooperative of sharing, investigation and discovery. The GAAIN platform is the first open-access, federated Alzheimer’s Disease data discovery platform of its kind, aimed at fostering collaboration between study investigators through data sharing. Researchers can use the platform to discover clinical, genetic, imaging, and other data collected across many independent studies, as well as to build cohorts and conduct preliminary analyses.
Visit the GAAIN website to learn more.
Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx)
The Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx) is a five-year, $21.7 million collaboration funded by NIH and uniting researchers from USC, UCLA, University of Melbourne, University of Eastern Finland, and the Albert Einstein College of Medicine, in an effort to prevent or cure posttraumatic epilepsy. Epilepsy and other seizure disorders currently afflict more than 5.1 million Americans, but clinicians cannot yet predict which patients will develop epilepsy following traumatic brain injury. INI’s primary role in the study involves the harmonization and processing of data.
Visit the EpiBioS4Rx website to learn more.
The Human Connectome Project (HCP)
The Human Connectome Project (HCP) is a five-year collaboration that aims to provide an unparalleled compilation of neural data, an interface to graphically navigate this data, and the opportunity to achieve never-before-realized conclusions about the living human brain. HCP researchers are working together to map the brain’s major pathways, circuits, regions, and functions. One of the project’s two consortia comprises LONI and the Martinos Center for Biomedical Imaging at Massachusetts General Hospital; the two centers are responsible for acquiring and processing imaging data, as well as developing novel algorithms for analysis and graphical means for interactively navigating brain connectivity.
Visit the HCP website to learn more.
The Mouse Connectome Project (MCP)
The Mouse Connectome Project (MCP) is an NIH-funded venture that aims to create a complete mesoscale connectivity atlas of the mouse brain and to subsequently generate its global neural networks. Using fluorescent dyes as tracers and novel computational informatics tools for analysis, the project will provide researchers with a better understanding of how various brain structures organize into networks and communicate with one another. The MCP team includes neuroanatomists, computer scientists, and web programmers.
Visit the MCP website to learn more.
The Parkinson’s Progression Markers Initiative (PPMI)
The Parkinson’s Progression Markers Initiative (PPMI) is the Michael J. Fox Foundation’s flagship biomarkers study, which seeks to identify biomarkers of Parkinson’s Disease progression. The longitudinal study follows more than 1,000 research participants in 33 clinical sites across the United States, Europe, Israel, and Australia. One important product of the study is a shared database where researchers can access a repository of imaging, clinical, and behavioral data, as well as biospecimens. The identification of reliable biomarkers will help identify possible cures for Parkinson’s Disease.
Visit the PPMI website to learn more.
The Laboratory of Neuro Imaging Resource (LONIR) develops, optimizes and shares innovative solutions for the investigation of imaging, genetics, behavioral, and clinical data. This includes researching and implementing better ways to share and manage data, as well as creating new algorithms for processing brain scans with increased speed and accuracy. Through LONIR, LONI has partnered with hundreds of biomedical investigators around the world and developed tools to advance their research projects. The LONIR team also hosts a range of training seminars for faculty, postdoctoral researchers, graduate and undergraduate students, as well as K-12 groups to educate these groups about the field of neuroinformatics.
Visit the LONIR website to learn more and access software tools and atlases.
The Data Archive for the BRAIN Initiative (DABI) ingests, harmonizes, aggregates, stores, visualizes and disseminates a diverse array of data, including electroencephalography (EEG) data and eletrocorticography (ECoG) data collected using electrodes implanted inside the brain. Conditions such as treatment-resistant depression, Parkinson’s disease, and epilepsy are currently under investigation. DABI is designed to help BRAIN Initiative researchers fulfill data-sharing directives from federal agencies and their respective institutions. The archive also accommodates data from MRI scans, PET scans and behavioral and clinical assessments in order to create a more complete picture of the human brain in health and disease.
Visit the DABI website to learn more.
The Health and Aging Brain among Latino Elders (HABLE) study is a collaborative effort between the INI and Sid O’Bryant, PhD, of the University of North Texas Health Science Center to study Alzheimer’s disease in Mexican-Americans, a group underrepresented in aging research. The team is performing cognitive tests, blood work and brain scans on 2,000 participants—half Mexican-American and half non-Hispanic white—twice over a five-year period to monitor changes in health and behavior over time. INI is responsible for storing, processing and analyzing the 4,000 brain scans collected during the study.
The Brain Initiative Cell Census Network (BICCN) is an arm of the BRAIN Initiative that seeks to create a comprehensive list of cell types in the brain. After joining the effort in 2017, INI is working to create a cell-type atlas of the mouse brain, leading the anatomical analysis by documenting and describing the structure and connections of various brain cells. The institute is also contributing to other components of the project that analyze connectivity, transcriptomes and epigenomics.
Visit the CIC website to learn more about the institute’s involvement with the BICCN.