A longstanding controversy in the field of emotion research has concerned whether emotions are better conceptualized in terms of discrete categories, such as fear and anger, or underlying dimensions, such as arousal and valence. In the domain of neuroimaging studies of emotion, the debate has centered on whether neuroimaging findings support characteristic and discriminable neural signatures for basic emotions or whether they favor competing dimensional and psychological construction accounts. This review highlights recent neuroimaging findings in this controversy, assesses what they have contributed to this debate, and offers some preliminary conclusions. Namely, although neuroimaging studies have identified consistent neural correlates associated with basic emotions and other emotion models, they have ruled out simple one-to-one mappings between emotions and brain regions, pointing to the need for more complex, network-based representations of emotion.
Figure - Levels of mapping between emotion models and the brain. The left panel illustrates the most commonly proposed one-to-one mappings between elements of emotion theories and individual brain regions. For example, amygdala activation typically correlates with emotional arousal, whereas activation in the orbitofrontal cortex correlates with emotional valence. As noted in the text, these one-to-one mappings run afoul of numerous experimental findings that show that, for example, fear consistently activates regions other than the amygdala, and the amygdala in turn is associated with several emotion processes. Such difficulties with one-to-one mappings have motivated a shift to more complex interrelationships, such as functional networks. For example, in the right panel, network mappings may involve individual brain regions (small rectangles) participating in networks that carry out the processing mediating different emotions. An individual region, such as the amygdala (red rectangle) can participate in multiple networks and that region's role can be modulated according to the currently active network configuration. These network dynamics have important implications for evaluating the neuroimaging evidence for different emotion theories.