Technological advances have led to a proliferation of structured big data that have matrix-valued covariates. We are specifically motivated to build predictive models for multi-subject neuroimaging ...

The human brain is responsible for critical functions, including perception, memory, language, thinking, consciousness, and emotions. To understand how the brain works, scientists often use ...

Neuroimaging technology has been shown to hold great promise in helping clinicians link specific symptoms of mental health disorders to abnormal patterns of brain activity. But a new study shows there ...

Researchers demonstrated how a deep learning framework they call 'Brain-NET' can accurately predict a person's level of expertise in terms of their surgical motor skills, based solely on neuroimaging ...

Neuroimaging cohort studies are essential for advancing our understanding of the brain across health and disease. Yet, details about many cohorts are not ...

EDL combines the outputs of several machine learning (ML) models to enhance their generalization performance. The traditional approach to building an ensemble uses deep neural networks (DNNs) in a ...

We currently provide facility use, equipment use, support services, and other resources for over 40 labs conducting funded studies that utilize MRI. We provide assistance with protocol development, ...

Research on neuroinflammatory processes has revolutionized our understanding of the pathophysiology underlying a range of neuropsychiatric and neurological ...

The INC data rate is for optional PetaLibrary storage (beyond what is stored in Flywheel). The rate per TB per year of storage is: $100 TB/year. The data rate includes INC staff helping you clean ...

When developing machine learning models to find patterns in data, researchers across fields typically use separate data sets for model training and testing, which allows them to measure how well their ...