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Contemporary research on emotions (“dispositions to action,” Lang, 1995), primarily focuses on emotion regulation (McRae and Gross, 2020), emotional intelligence (Gong and Jiao, 2019), and the relationship between emotion and social cognition (Stevens and Jovanovic, 2019). Technological advances have allowed researchers to identify the neurobiological processes underlying the emotions, in particular, functional magnetic resonance imaging (fMRI, Weber-Goericke and Muehlhan, 2019), electrophysiological techniques (Gantiva et al., 2019), and virtual reality (Wechsler et al., 2019). Notwithstanding these major progresses, there is awareness of the need to continue developing methodologies that further integrate behavioral measures and increase ecological validity. For example, using dynamic stimuli (eg, videos) and not just photographs, as well as combining recording techniques that allow to understand neuronal activity underlying emotion over the course of time (eg, EEG in conjunction with fMRI, Pavlova, 2017). The study of emotions is currently one of the more developed fields in behavioral sciences, which is showing a high potential for integration across disciplines and research areas, for example trough computational models and creation of virtual reality environments (de Gelder, 2017). Basic and applied efforts to understand the interplay of emotion and learning are two of those fruitful areas of interaction (Hascher, 2010; Tyng et al., 2017; Wortha et al., 2019). Mounting evidence indicates that emotion modulates encoding and helps retrieval of information efficiently. Also, now there is evidence that emotion strongly affects …