Functional Magnetic Resonance Methods for Mapping 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 briefly reviewing core fMRI fundamentals, including the biophysics of the blood-oxygen-level-dependent (BOLD) signal and key limitations. 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, and intersubject correlation analysis. For each, I describe how the method works 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.