About The UI NeuroRepository

Diseases of the nervous system are each unique requiring disease specific methods for studying their processes and effects on the human brain. Utilizing a systems biology approach, the UI Neurorepository allows for the construction of disease specific diverse data sets of multiple systems through the integration of clinical and molecular data derived from resected tissues. This approach includes the collection of anatomic and metabolic data from imaging studies; electrical data from both scalp and brain surface and depth recordings; high-throughput technology such as functional genomics, proteomics, metabolomics; and clinical and neuropsychological data.

Consisting of an Investigator Database of de-identified datasets, a biorepository, and resources to foster collaborative efforts, the UI Neurorepository provides a novel translational environment for a broad range of investigators including neuroscientists, neuropsychological scientists, geneticists, as well as computer and imaging scientists.

The diseases we are currently focusing most on include, but are not limited to:

Through the UI NeuroRepository, investigators have access to the following:

• Database of neurological disease specific nodes that contain clinical, molecular and imaging data. A detailed catalog of the resected tissue with direct links to associated data is also contained within the database. Radiological, pathological, and histological images for each block of tissues that are also stored within the database.
• Biorepository of neurological tissue and biofluids. The Neurorepository houses a catalog of tissues from which the data within the database is derived. For tissue that is not stored within the Neurorepository, contact information for the custodian of the tissue is maintained.
• Resource for cross domain heterogenous data analysis. Statistical analysis of big data to produce correlations across multiple data domains (ie. clinical, imaging, pathology). Generation of 3D image mapping.
• Environment for computer and imaging scientists to create and improve algorithms for big data and imaging analysis.
• Mechanism to increase the magnitude of research studies by providing a mechanism to expand subject recruitment and investigator involvement across Chicagoland. Increases the ability for non-UIC collaborators to provide identify, obtain, and share relevant data and specimens to aid current and future research studies.
• Collaborative network that allows investigators from multiple disciplines (neurology, psychiatry, pathology, radiology, computer science, etc.) to interact, share their data, and advance the study of multiple diseases.