Last year, Kyle had a chance to visit the Laboratory of Neuroimaging, or LONI, at USC, and learn about how some researchers are using data science to study the function of the brain. We’re going to be covering some of their work in two episodes on Data Skeptic. In this first part of our two-part episode, we'll talk about the data collection and brain imaging and the LONI pipeline. We'll then continue our coverage in the second episode, where we'll talk more about how researchers can gain insights about the human brain and their current challenges. Next week, we’ll also talk more about what all that has to do with data science machine learning and artificial intelligence. Joining us in this week’s episode are members of the LONI lab, which include principal investigators, Dr. Arthur Toga and Dr. Meng Law, and researchers, Farshid Sepherband, PhD and Ryan Cabeen, PhD.
To start off, we’ll be going over LONI’s primary data generating processes: the magnetic resonance imaging machine, or MRI machine. The MRI is a fantastic example of how a measurement tool gets pushed to extremes. In the case with the MRI, neuroscientists try to get clearer and clearer images of the brain’s finer details. But what exactly is it measuring when one gets the raw data? What does an MRI image represent? Farshid will talk more about what an MRI represents and the steps his colleagues at LONI take to get that data into a format for analysis. We'll then learn about the LONI pipeline and computational tools being used in the lab from Ryan.