Last week on Data Skeptic, we visited the Laboratory of Neuroimaging, or LONI, at USC and learned about their data-driven platform that enables scientists from all over the world to share, transform, store, manage and analyze their data to understand neurological diseases better. We talked about how neuroscientists measure the brain using data from MRI scans, and how that data is processed and analyzed to understand the brain. This week, we’ll continue the second half of our two-part episode on LONI.
The human brain is one of the most amazing machines. To extract patterns from neuroimaging data to help diagnose Alzheimer's disease and other neurological diseases, researchers at LONI use various techniques, including statistical methods and machine learning algorithms. While a lot of progress has been made in diagnosis and treatment of Alzheimer's there is still a long way to go for this class of disease. Even despite the advances in technology, we still under understand it. One of the things we’ll address is how developments in machine learning, and particularly in deep learning, going to affect the neurosciences? This week, we'll hear more from Dr. Arthur Toga, Dr. Meng Law, Farshid Sepehrband and Ryan Cabeen.