Deep learning and statistics in neuroimaging research

COEX 

In this talk, we discuss the distinctions between statistical and machine learning approaches to data analysis, and the specific challenges deep learning presents. After reviewing a prediction-focused vs. inference-focused orientation to modelling, we provide a selective review of the contributions deep learning has made to neuroimaging. We then will discuss particular limitations of deep learning, including interpretability and bias. We will conclude with potential solutions to address these limitations.