"Emotional granularity describes an individual's ability to create instances of emotion that are diverse and context-specific. Considerable evidence suggests that higher granularity is a protective factor for mental and physical well-being. Despite this evidence, however, research on granularity is lacking in three critical respects. First, a fuller definition of emotional granularity is needed that situates it with regard to neighboring individual difference constructs in affective science. A more nuanced understanding of the features that describe granularity is necessary for future research to be able to make tailored predictions about granularity's relationship with health and well-being. In Chapter 1, I offer a unifying framework for understanding and studying the mental representation of one's own emotional experience. To create this framework, I used domain-general accounts of expertise to deductively generate a list of core features. I then used this framework to structure the findings from a systematic review of constructs for the mental representation of emotional experience, including emotional granularity. This approach, I argue, has the capacity to not only organize scientific knowledge, but reveal potential underlying mechanisms and motivate future programs of research and intervention. Second, measures of emotional granularity are needed that capture various dimensions of granularity and intra-individual fluctuations therein. Multi-dimensional and time-varying estimates of granularity are necessary to represent the complex dynamics of emotional experience. In Chapter 2, I study granularity using measures provided by network analyses. I used experience sampling data to generate person-specific (i.e., idiographic) networks, and characterized these networks using a variety of network measures, estimated based on the average network structure as well as the change in network structure over time. I found that network measures of granularity predicted self-reported anxiety and depression, even when controlling for other variables known to be associated with mood symptoms, such as self-reported alexithymia and emotional reactivity. These findings serve as a proof-of-concept demonstration of the efficacy of network analysis for describing the dynamic structure of emotional experience. Third, the relationship between emotional granularity and mechanisms underlying physical health is under-investigated. Investigations that incorporate peripheral physiology into the study of granularity can be used to test specific hypotheses about the biological underpinnings of emotional experience and their implications for health. In Chapter 3, I investigated the relationship between granularity and cardiovascular physiological activity using data collected using experience sampling with ambulatory peripheral physiological monitoring. I compared granularity with three variables: respiratory sinus arrhythmia during seated rest, the number of patterns of physiological activity discovered during seated rest, and the performance of classifiers trained on event-related changes in physiological activity. Individuals with higher granularity exhibited more, and more specific, patterns of physiological activity during seated rest as well as during emotional events. These findings are consistent with constructionist accounts of emotion, which propose concepts as a key mechanism underlying individual differences in emotional experience and physical health"--Author's abstract.