Emotion regulation is defined as changing or maintaining one’s emotions. The Selection, Optimization, and Compensation model of Emotion Regulation (SOC-ER) posits that emotion regulation is influenced by external factors, such as properties of a stimulus, and internal factors, such as cognitive processes. The purpose of this series of studies was to distinguish how external and internal factors contribute to emotion regulation. In Study 1, I identified how ambivalence, an external factor, influences emotion regulation choice. I predicted that participants would be more likely to choose to reappraise ambivalent images compared to non-ambivalent images. Studies 2 and 3 examined how internal factors influence emotion regulation ability. In Study 2, I combined brain imaging and behavioural tasks to determine brain activity produced during emotion regulation could be used to predict individual differences in working memory performance. I predicted that differences in brain activity between reappraise and view conditions would predict working memory scores. In Study 3, I used intrinsic network functional connectivity to evaluate whether differences in network connectivity could be used to predict whether one is reappraising or viewing a negative stimulus. I expected network connectivity to predict emotion regulation ability greater than chance, and that networks associated with emotion (salience network), networks associated with cognitive control (attention control network, frontoparietal networks), and the default mode network would make a reliable contribution to significant classification. Our hypotheses for Studies 1 and 2 were supported, and Study 3 was partially supported. This study has contributed new knowledge to the literature on the neurocognitive mechanisms of emotion regulation by testing predictions derived from the SOC-ER model, which can help identify ways to improve one’s emotion regulation.