Introduction to Machine Learning in Neuroimaging

Advancements in neuroimaging and the availability of large-scale datasets enable the use of more sophisticated machine learning algorithms. In this chapter, we non-exhaustively discuss relevant analytical steps for the analysis of neuroimaging data using machine learning (ML), while the field of radiomics will be addressed separately (c.f., Chap. 18 -Radiomics). Broadly classified into supervised and unsupervised approaches, we discuss the encoding/decoding framework, which is often applied in cognitive neuroscience, and the use of ML for the analysis of unlabeled data using clustering.