Functional Magnetic Resonance Methods for Mapping for the Neural Underpinnings of Emotion

In this chapter I provide a concise methodological overview of how functional magnetic resonance imaging (fMRI) can be used to investigate the neural bases of emotion. I begin by reviewing core fMRI fundamentals, including the biophysics of the blood-oxygen-level-dependent (BOLD) signal, key limitations, and trade-offs relative to other neuroimaging modalities. I then outline three broad classes of fMRI designs commonly used in affective science: task-based paradigms that model specific affective processes through experimental manipulations; resting-state paradigms that characterize intrinsic functional architecture; and naturalistic paradigms that leverage complex, dynamic stimuli such as films or narratives to better approximate real-world affective experience. Finally, I survey a set of analytic approaches that can be paired with these designs, including mass-univariate contrast testing, decoding, voxel-wise encoding models, connectome-based predictive modeling, graph theoretic methods, regional homogeneity, and intersubject correlation analysis. For each, I describe how the method works, practical implementation considerations, and the kinds of inferences it affords about affective phenomena. Collectively, these tools illustrate the expanding methodological repertoire available for mapping emotion onto brain function.