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Learn more: PMC Disclaimer | PMC Copyright Notice Sci Data . 2026 Mar 3;13:578. doi: 10.1038/s41597-026-06897-x Search in PMC Search in PubMed View in NLM Catalog Add to search Exploring curiosity, interest, and surprise: normative ratings of a magic trick video dataset in Italy Erika Marascia Erika Marascia 1 Department of Psychology (DiPsy) University “G. d’Annunzio” - Via dei Vestini, 31 - 66100 Chieti, Italy Find articles by Erika Marascia 1 , Adolfo Di Crosta Adolfo Di Crosta 1 Department of Psychology (DiPsy) University “G. d’Annunzio” - Via dei Vestini, 31 - 66100 Chieti, Italy Find articles by Adolfo Di Crosta 1, ✉ , Pasquale La Malva Pasquale La Malva 1 Department of Psychology (DiPsy) University “G. d’Annunzio” - Via dei Vestini, 31 - 66100 Chieti, Italy Find articles by Pasquale La Malva 1 , Irene Ceccato Irene Ceccato 1 Department of Psychology (DiPsy) University “G. d’Annunzio” - Via dei Vestini, 31 - 66100 Chieti, Italy Find articles by Irene Ceccato 1 , Giulia Prete Giulia Prete 1 Department of Psychology (DiPsy) University “G. d’Annunzio” - Via dei Vestini, 31 - 66100 Chieti, Italy Find articles by Giulia Prete 1 , Rocco Palumbo Rocco Palumbo 1 Department of Psychology (DiPsy) University “G. d’Annunzio” - Via dei Vestini, 31 - 66100 Chieti, Italy Find articles by Rocco Palumbo 1 , Nicola Mammarella Nicola Mammarella 1 Department of Psychology (DiPsy) University “G. d’Annunzio” - Via dei Vestini, 31 - 66100 Chieti, Italy Find articles by Nicola Mammarella 1 , Alberto Di Domenico Alberto Di Domenico 1 Department of Psychology (DiPsy) University “G. d’Annunzio” - Via dei Vestini, 31 - 66100 Chieti, Italy Find articles by Alberto Di Domenico 1 Author information Article notes Copyright and License information 1 Department of Psychology (DiPsy) University “G. d’Annunzio” - Via dei Vestini, 31 - 66100 Chieti, Italy ✉ Corresponding author. Received 2025 Jul 22; Accepted 2026 Feb 12; Collection date 2026. © The Author(s) 2026 Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ . PMC Copyright notice PMCID: PMC13066441 PMID: 41775702 Abstract Epistemic emotions, including curiosity, interest, and surprise, play a crucial role in learning and cognitive processes by bridging motivation and knowledge acquisition. The Magic Curiosity Arousing Tricks (MagicCATs) dataset, comprising 166 magic trick video clips, provides a standardized tool for studying these emotions in experimental settings. This study provides normative ratings for the dataset within an Italian context, based on a sample of 654 participants aged 18–86. Participants evaluated the videos based on clarity, curiosity, interest, surprise, and confidence in solving the trick, using both binary and Likert scales. Rigorous data screening ensured integrity, enhancing the reliability of the findings. The dataset’s ecological validity, dynamic stimuli, and capacity to elicit multiple epistemic emotions offer advantages over traditional methods. By contextualizing MagicCATs within an Italian framework, this study advances the investigation of epistemic emotions by supporting their simultaneous assessment across a broad adult age range. Applications include experimental psychology, neuroscience, and education, with potential implications for mental health and age-related cognitive research. Data and resources are available for replication and further exploration. Subject terms: Human behaviour, Motivation Background & Summary Philosophers and psychologists classify curiosity, interest, and surprise as epistemic emotions due to their intrinsic connection to knowledge acquisition and understanding 1 , 2 . These emotions are closely tied to cognitive processes that drive individuals to seek, acquire, and assimilate new information, making them essential for learning and intellectual growth 3 , 4 . Indeed, curiosity, interest, and surprise play unique but interconnected roles in knowledge acquisition, influencing not only what we choose to learn but also how deeply we process information, serving as a bridge between motivation and cognition 5 , 6 . Although these three epistemic emotions are all related to the acquisition of knowledge, they differ in their specific mechanisms. Curiosity is an intrinsic motivation that drives individuals to alleviate the discomfort of an “information gap” by actively seeking additional information or facts. It is often associated with cognitive engagement in novel or moderately complex activities and stimuli, particularly those that highlight gaps in personal knowledge 7 – 10 . Interest, on the other hand, is conceptualized in various ways: as an emotion characterized by focused attention and positive engagement toward meaningful stimuli 11 , as a dynamic relationship between a person and an object, in which personal values and contextual affordances interact over time 12 , and as a motivational variable that supports sustained engagement, learning, and developmental trajectories by promoting persistence and self-regulated exploration 13 . Within this framework, interest is not limited to momentary affective reactions but can evolve from situational states triggered by environmental factors into more stable, individual dispositions that guide long-term knowledge acquisition and goal-directed behavior. The terms curiosity and interest are often used interchangeably, and they are frequently treated as synonyms in dictionaries. However, the distinction between curiosity and interest lies in their relationship to knowledge: curiosity is typically associated with a moderate amount of information about something or someone 8 , whereas interest can persist across both low and high levels of knowledge 13 . Additionally, curiosity and interest differ in their underlying goals: curiosity is primarily driven by the need to reduce uncertainty and fill information gaps 10 , while interest is more closely tied to sustained attention and the pursuit of enjoyment 13 . Distinct from both curiosity and interest, surprise is an epistemic emotion that arises from unexpected or novel events and serves as a key mechanism for cognitive re-evaluation and belief updating 14 . It arises from a mismatch between expectations and reality, prompting attentional and memory processes that facilitate the integration of new information 14 , 15 . Surprise not only drives adaptive learning by motivating exploratory behavior to resolve uncertainty but also plays a pivotal role in decision-making by recalibrating belief systems in dynamic environments 16 , 17 . Collectively, these emotions enhance attentional focus, promote deeper cognitive processing, and improve memory encoding 18 – 20 . Epistemic emotions not only bridge motivation and cognition but also influence the neural mechanisms underlying learning. Research has shown that curiosity activates regions of the brain associated with the reward system, including the striatum and prefrontal cortex, both involved in motivation and reinforcement learning 19 , 21 . For example, Kang et al . 19 demonstrated that epistemic curiosity activates the caudate nucleus and other reward-related cortical areas, enhancing memory retention for information presented during high curiosity states. The activation of the reward system not only enhances intrinsic motivation but also predicts the degree of memory improvement. Similarly, findings from Gruber et al . 21 revealed that high curiosity states enhance activity in the dopaminergic circuit, which in turn strengthens memory encoding in the hippocampus. Notably, this mechanism applies not only to information directly relevant to the source of curiosity but also to incidental materials encountered during high curiosity states. Interest and surprise further contribute to these neural mechanisms by modulating attentional and emotional processing. Drawing on the theoretical framework proposed by Silvia 11 and neurocognitive evidence reported by Mannarelli et al . 22 , interest appears to be associated with the engagement of fronto-parietal brain networks involved in executive control, sustained attention, and effort regulation. These regions support the maintenance of goal-directed activity over time, enabling individuals to remain cognitively engaged with demanding tasks and to allocate attentional resources in a stable and controlled manner. In contrast, surprise engages the amygdala and hippocampus, key regions involved in emotional salience detection and memory processing. When individuals are confronted with unexpected or expectancy-violating stimuli, these neural systems contribute to the rapid reallocation of attentional resources, enhancing the prioritization of novel information. The amygdala supports the detection of motivational relevance and emotional significance, while the hippocampus facilitates the encoding and integration of new information into existing memory representations. Through this coordinated activity, surprise promotes cognitive updating by enabling the incorporation of potentially important information into established cognitive frameworks, thereby supporting adaptive learning and belief revision 23 , 24 . Together, these neural responses underscore the crucial role of epistemic emotions in optimizing cognitive processes. Despite their significance, studying curiosity, interest, and surprise in controlled experimental settings has involved methodological challenges, particularly in the identification and construction of stimuli capable of reliably eliciting these emotions under laboratory conditions. While a variety of paradigms have since been developed to evoke epistemic emotions, each with specific advantages and limitations, the design of stimuli that balance experimental control with ecological validity has remained a central concern in this line of research. Early experimental approaches primarily relied on perceptual puzzles and visual ambiguities to investigate how individuals respond to incomplete or ambiguous stimuli. Classic studies introduced ambiguous figures, such as Rubin’s vase or the Necker cube, which create perceptual conflicts and stimulate cognitive efforts to reconcile competing interpretations 25 , 26 . Over time, subsequent research expanded the range of perceptual stimuli to include visual illusions, ambiguous images, and virtual environments allowing researchers to examine how epistemic emotions, particularly curiosity and interest, but also surprise, are engaged during the resolution of perceptual uncertainty and expectation violations 13 , 27 , 28 . Among such approaches, trivia questions have become one of the most widely used stimuli in experimental research on curiosity because they create information gaps, a core driver of curiosity, by presenting participants with knowledge gaps they perceive as relevant 10 . This approach has allowed researchers to manipulate curiosity levels and study its effects on learning and memory 29 – 35 . In parallel, interest has most commonly been investigated using learning and knowledge-acquisition tasks designed to elicit sustained engagement with meaningful content, such as educational texts or problem-solving activities. Within these paradigms, interest has been shown to support attention, persistence, and deeper encoding, thereby enhancing memory and learning outcomes 11 , 13 , 36 , 37 . By comparison, the role of surprise-related appraisal processes during information processing has been examined in experimental work showing that expectancy violations embedded in controlled experimental contexts, based on numerical statements and plausibility judgments, can modulate cognitive outcomes such as memory as a function of the perceived plausibility of the presented information 38 . Recent research has highlighted the importance of examining multiple epistemic emotions simultaneously, moving beyond paradigms that focus on a single emotional state. Although individual studies often examine different subsets of epistemic emotions, converging evidence indicates that these emotions co-occur and dynamically interact during learning and sensemaking processes. For example, work using dynamic motion stimuli has shown that expectancy violations associated with surprise can increase interest and sustain engagement 39 . Similarly, research in educational contexts has documented joint trajectories of curiosity, surprise, and related epistemic states during scientific reasoning activities 40 , while process-oriented approaches suggest that epistemic emotions evolve over time and are shaped by metacognitive and feedback-related factors 6 . Narrative reviews further converge in emphasizing that epistemic emotions rarely operate in isolation and that their combined effects are central to attention, learning, and knowledge updating 41 . Within this framework, the Magic Curiosity Arousing Tricks (MagicCATs) dataset introduced by Ozono and colleagues 42 represents a methodological advance. By using short video clips of magic tricks, MagicCATs provides a standardized and ecologically valid set of stimuli capable of eliciting curiosity, interest and surprise concurrently, fostering a rich and dynamic emotional experience that closely mirrors real-world scenarios 43 . In fact, due to the violation of expectations, magic tricks create a conflict between belief and reality, driving viewers to seek an explanation for the apparently impossible events 44 , 45 . Additionally, the engaging and immersive nature of magic tricks helps sustain participants’ attention over extended periods. From a methodological perspective, unlike paradigms focused on a single emotional state, MagicCATs supports the simultaneous examination of multiple epistemic emotions, in line with contemporary theoretical and empirical perspectives that promote the study of these emotions as dynamically interrelated rather than functionally independent. Notably, the inclusion of ratings on multiple epistemic emotions constitutes a key strength of the MagicCATs dataset. Recent research has increasingly emphasized the importance of examining epistemic emotions jointly rather than in isolation, showing that their co-occurrence and interaction play a critical role in shaping attention, motivation, and learning processes 46 – 48 . In this context, MagicCATs enables the investigation of how curiosity, interest, and surprise dynamically interact in response to the same stimulus, offering a more comprehensive approach than paradigms designed to target a single epistemic emotion. This multi-emotional approach is particularly relevant given that, in everyday cognitive functioning, individuals rarely experience epistemic emotions in isolation. Rather, curiosity, interest, and surprise tend to co-occur and jointly shape attention, exploration, and learning-related behavior as part of an integrated emotional–cognitive response to complex and novel situations. By allowing the simultaneous assessment of these emotions within the same stimulus context, MagicCATs provides a methodological framework that more closely approximates real-world epistemic experiences and supports a more ecologically valid investigation of epistemic emotion dynamics. Finally, the standardization and reproducibility of MagicCATs ensure that the dataset can be reliably employed across studies, fostering comparability and supporting the development of cumulative research in the field of epistemic emotions. Given the importance of MagicCATs in advancing research on epistemic emotions, this study aims to provide normative ratings for the dataset within an Italian sample, with a specific focus on the simultaneous assessment of curiosity, interest, and surprise. This approach allows us to examine how multiple epistemic emotions elicited by the same stimuli are experienced and evaluated within a specific cultural context. This objective is grounded in the understanding that emotional and cognitive responses to stimuli are often shaped by broader cultural and socio-historical frameworks, which influence how novelty, expectation violations, and complexity are perceived and interpreted 49 , 50 . Normative ratings of MagicCATs in an Italian sample therefore contribute not only to assessing the dataset's generalizability across populations, but also to exploring whether the joint dynamics of curiosity, interest, and surprise observed in previous research extend to different cultural contexts. Additionally, age-related factors may play a role in how individuals experience and respond to stimuli that elicit epistemic emotions. For example, emotional valence has been shown to affect temporal source memory differently in older adults, underscoring the importance of considering lifespan cognitive dynamics in emotion research 51 . By accounting for cultural and age-related variables, this study contributes to a deeper understanding of how curiosity, interest, and surprise are elicited and interact across the lifespan within the Italian context. Methods Participants A total of 867 participants from central and southern Italy were initially recruited for the study through word of mouth, social media, and posted advertisements. Before the experimental session, participants aged 65 or older completed the Montreal Cognitive Assessment (MoCA) 52 , and only those scoring above 24, reflecting the absence of significant cognitive impairments, were included in the study 53 . All participants provided informed consent in accordance with the Declaration of Helsinki 54 . Consent was obtained in paper form prior to participation and included agreement to take part in the study and to the collection and anonymized sharing of their data for research purposes. No personally identifiable information was collected. Signed consent forms were securely stored in a locked location and separated from study data to ensure participant anonymity. The study received approval from the Institutional Review Board of Psychology (IRBP) of the Department of Psychology, “G. d’Annunzio” University of Chieti-Pescara (protocol number: 24041). Following the procedure outlined by Ozono and colleagues 42 , a rigorous screening process was conducted to ensure data integrity and reliability before proceeding with the main analysis. As a result, 213 participants were excluded based on the following criteria. First, those who took significantly longer than average to complete the experiment (more than + 2 SD) were excluded, although no participants were excluded for completing the experiment in less than −2 SD of the average time. Next, participants who gave identical ratings to more than three questions and who displayed systematic response patterns across all trials were removed. Additionally, we excluded participants who responded “no” to the question assessing the “clarity of the trick” for all the presented video clips, which assessed their understanding of the perceptual illusions presented (see below). These criteria were designed to exclude participants who either failed to engage with the task as intended or provided unreliable responses, ensuring the integrity and quality of the data. This comprehensive exclusion process resulted in a final sample of 654 participants, including 160 males and 494 females (mean age = 36.28, SD = 17.03, range = 18–86). Notably, although the final sample was not intended to be nationally representative of the Italian adult population, it constitutes a well-characterized Italian adult sample, with a large size and a broad age range. Table “Italian_Participants_Data” provides demographic information for each participant. MagicCATs stimuli The MagicCATs (Magic Curiosity Arousing Tricks) dataset, developed by Ozono et al . 42 , was used as the experimental stimulus set in this study. The dataset consists of 166 short video clips of magic tricks performed by professional magicians, specifically designed to elicit varying levels of epistemic emotions such as curiosity, interest, and surprise. The tricks were carefully curated to ensure diversity in both materials (e.g., playing cards, coins, sponges) and techniques (e.g., vanishing, teleportation, prediction). A sample video providing an overview of the MagicCATs stimuli is publicly accessible at the following https://youtu.be/ehgSKYxVL3M . Previous research on curiosity and interest has often compared stimuli eliciting high versus low levels of these emotions 19 , 21 , 36 , highlighting the importance of ensuring sufficient inter-stimulus variability. To this end, the dataset includes not only highly surprising and engaging tricks but also those that evoke more moderate responses. Each video was meticulously edited by Ozono et al . 42 to maintain consistency in visual and technical attributes. All clips share a standardized dark background, a resolution of 720 × 404 pixels, and framing that focuses on the trick itself. To minimize distractions, audio was removed, and magicians’ faces were obscured as much as possible. In some videos, English subtitles were added to facilitate understanding of the trick, for example, when the magician asked someone to perform an action such as writing on a banknote or thinking of a number. The dataset also provides both long and short versions of 21 selected clips, allowing for flexibility in experimental designs. Video durations range from 8 to 155 seconds, with a mean length of 37.3 seconds (median = 31, SD = 23.5). Excluding the long versions, durations range from 8 to 105 seconds, with a mean length of 33.1 seconds (median = 30, SD = 19.8). For the present study, the only modification made to the original dataset was the translation of the English subtitles into Italian to ensure that the content was understandable for our Italian-speaking participants (see Table “MagicCATs_Italian subtitle”). No other changes were made to the original video clips or their editing, both were retained as described by Ozono et al . 42 . Following the methodological approach established by Ozono et al . 42 , the 166 magic trick video clips were divided into nine distinct stimulus lists (Lists 1–9) to ensure systematic and balanced exposure across participants. Lists 1 and 2 contained 21 videos each, including both long and short versions of selected tricks. To avoid overlap, the short version of a given trick was assigned to one list, while the corresponding long version was placed in the other. This distribution ensured comparable total durations for the two lists, ranging from 16 to 17 minutes. The remaining 124 video clips were distributed across Lists 3–9, with each list containing 17 or 18 different videos, resulting in viewing durations of approximately 9 to 10 minutes. Within each list, the presentation order of the clips was randomized to minimize potential sequence effects and maintain stimulus variability. Further details about the MagicCATs stimuli are provided in Table “Magic ID_Detailed information”. The Table is reproduced from Ozono et al . 42 under the Creative Commons Attribution license (CC BY). Normative rating procedure for MagicCATs Adopting the methodological approach described by Ozono et al . 42 , the dataset was organized into nine distinct lists, containing a total of 166 videos. Each participant viewed only two of the nine lists, with the presentation order of the videos randomized within each list. For each video clip, participants were asked to provide ratings on five dimensions: (a) whether the trick was clear and understandable (clarity of the trick), (b) the level of surprise elicited by the magic trick (surprise in response to the trick), (c) their interest in the trick, reflecting the degree of engagement (interest in the trick), (d) their confidence in deducing the solution, i.e., their perceived ability to figure out the trick (confidence in the solution), and (e) their curiosity about how the trick was performed (curiosity in the solution). Clarity of the trick was rated using a binary response scale (Yes/No) to assess participant comprehension of the magic trick and to serve as a criterion for excluding ambiguous or unclear responses. The remaining four dimensions were rated on 10-point Likert scales, where 1 indicated “not at all” and 10 indicated “very much.” At the end of the video session, participants also completed two additional questions: they rated their general interest in magic tricks (interest in magic) on a 10-point scale (1 = not at all, 10 = very much), and indicated whether they practiced magic tricks themselves (personal performance of magic) on a 3-point scale (1 = not at all, 2 = a little bit, 3 = frequently). All participants confirmed that they had never seen the videos prior to the study. Data Records All data are available on Figshare platform 55 . Data processing steps, including the computation of descriptive statistics (means and standard deviations), were performed using Microsoft Excel with standard formula-based procedures. The MagicCATs videos are available upon request from the original authors (Ozono et al . 42 ; https://osf.io/ad6uc ). The results of the MagicCATs Italian normative ratings are organized into six separate Excel files in the folder named “Italian MagicCATs_Dataset”, each documenting a specific aspect of the dataset. The Italian subtitles created for this study are provided in the file titled “MagicCATs_Italian subtitles”. The file “Italian_Participants_Data” contains demographic information for each participant, including unique ID, gender, age, and MoCA scores (for participants aged 65 and older). It also includes self-reported measures of general interest in magic tricks (interest in magic) and whether participants engage in performing magic themselves (personal performance of magic). The file “Magic ID_Detailed information” describes the characteristics of each MagicCATs stimulus. It includes the trick name, the category of the magical phenomenon, a brief description of the trick, the materials used, the video duration, and the list ID in which the video appears. The table is reproduced from Ozono et al . 42 under the Creative Commons Attribution license (CC BY). The file “Lists” documents the distribution of video lists among participants. It reports the mean age, age standard deviation, and the number of male and female participants for each list. The file “Italian_Magic_Rating” contains the mean ratings and standard deviations for each video clip, as well as the number of participants who indicated that they understood the trick. The file “MagicCATs_Final sample_Data” includes data from participants. It records a unique participant ID, the list(s) assigned (List ID), and the identifier of each magic trick video (Magic ID). It also contains participant ratings on five dimensions for each clip: clarity of the trick, surprise, interest, confidence in solving the trick, and curiosity about the solution. Together, these files provide a comprehensive and transparent account of the data collected for the Italian normative ratings of the MagicCATs dataset, ensuring accessibility for replication and further analysis. Technical Validation The experimental procedure was administered using a 15.5-inch laptop running E-Prime 3.0 software 56 . The software managed the randomization of stimulus presentation and the recording of participants’ responses. The laptop screen operated at a 60 Hz refresh rate, with brightness set to 100% to ensure optimal visibility of the stimuli. Standardized instructions were provided to all participants to ensure consistent understanding of the tasks and to reduce variability in responses. Experimental sessions were conducted individually in a silent laboratory under controlled lighting conditions. The entire session lasted a maximum of 30 minutes. Each participant viewed between 34 and 39 video clips, randomly selected from two of the nine predefined stimulus lists. To avoid redundancy, participants were never assigned both Lists 1 and 2, as these contained the same magic tricks in different versions (long and short). Each trial began with a preparatory screen displaying the instruction “Please see the video and give a rating”. The video was then played in full. Immediately afterward, participants provided five ratings in the following order: clarity of the trick, surprise in response to the trick, interest in the trick, confidence in the solution, and curiosity about the solution. Clarity of the trick was evaluated using a binary scale (Yes/No), with participants pressing the corresponding button. This allowed assessment of their comprehension of the magic trick and enabled the exclusion of ambiguous responses from the analysis. Ratings for the other dimensions were evaluated using a 10-point scale, with participants selecting a value by pressing the corresponding button. This procedure ensured consistency and comparability of responses across participants and video stimuli. Table “Italian_Magic_Rating” contains the mean ratings for each video. The present dataset was collected as part of a standalone study specifically designed to provide normative ratings for the MagicCATs in an Italian sample. Usage Notes The Magic Curiosity Arousing Tricks (MagicCATs) dataset, now validated within an Italian cultural context, provides a versatile and ecologically valid tool for investigating multiple epistemic emotions simultaneously, particularly curiosity, interest, and surprise, in experimental research. Similar to other validated video-based emotion elicitation tools based on dynamic visual stimuli, such as the Chieti Affective Action Videos (CAAV) 57 , MagicCATs offers standardized and dynamic stimuli that support controlled experimental investigations into affective and cognitive processes. The Italian version of MagicCATs enables culturally sensitive research designs and cross-cultural comparisons. It is especially well-suited for experimental paradigms examining how emotional engagement fosters deeper cognitive processing, supporting prior findings that link heightened curiosity to improved memory consolidation and retrieval 19 , 21 . Additionally, the dataset’s ability to reliably elicit surprise and interest allows researchers to explore how these emotions contribute to sustained attention and motivational states 11 , 14 . In this broader context of emotional-cognitive engagement, executive functions, particularly inhibitory control, have been linked to psychological well-being and may influence how individuals engage with emotionally salient cognitive tasks 58 , further underscoring the relevance of MagicCATs in studying such dynamics. Beyond cognitive psychology, MagicCATs holds promise in the field of neuroscience. The dataset can be integrated with neuroimaging methods, such as functional magnetic resonance imaging (fMRI), electroencephalography (EEG), or pupillometry, to investigate the neural circuits and temporal dynamics underlying epistemic emotions. For instance, future studies could examine how curiosity, interest, and surprise modulate activity in reward-related brain regions (e.g., the striatum, prefrontal cortex), or how they influence memory-related structures such as the hippocampus. Due to the engaging and immersive nature of the stimuli, MagicCATs may also be of interest for research at the intersection of epistemic emotions and mental health. Prior work has linked curiosity to positive psychological outcomes, such as subjective well-being and flexibility in emotional engagement in daily life 59 . In this context, MagicCATs could serve as a tool to explore how patterns of curiosity, interest, and surprise relate to emotional engagement and motivational functioning in populations characterized by affective difficulties. Furthermore, MagicCATs facilitates the investigation of age-related differences in the experience and impact of epistemic emotions. Since curiosity and surprise may differentially affect memory and learning in younger versus older adults, the dataset provides a valuable resource for studying cognitive aging and for identifying emotion-driven strategies to mitigate age-related cognitive decline 18 , 20 . In summary, the Italian normative ratings of the MagicCATs dataset represent a significant step toward the simultaneous study of epistemic emotions in experimental contexts. Moreover, these normative data provide a valuable starting point for future cross-cultural research on curiosity, interest, and surprise. Its standardized format, rich emotional content, and flexible structure support a wide range of applications across experimental psychology, neuroscience, education, and clinical research. MagicCATs offers a robust platform for advancing our understanding of how epistemic emotions interact with cognition and behavior across the lifespan. Author contributions Data were collected by E. Marascia, P. La Malva and A. Di Crosta. Data descriptor was drafted by E. Marascia, A. Di Crosta, I. Ceccato, G. Prete and R. Palumbo. The experimental design was devised and the data collection supported by E. Marascia, A. Di Domenico, and N. Mammarella. All the authors have contributed to and reviewed the manuscript. Data availability All data described in this study are publicly available on Figshare at 10.6084/M9.FIGSHARE.29365349.V3. Code availability No code was used in this study. Competing interests The authors declare no competing interests. Footnotes Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. References 1. Deigan, M. & Piñeros Glasscock, J. S. A Fitting Definition of Epistemic Emotions. Philos. Q. 74 , 777–798 (2024). [ Google Scholar ] 2. Morton, A. Epistemic Emotions , 10.1093/oxfordhb/9780199235018.003.0018 (Oxford University Press, 2009). 3. Oudeyer, P.-Y., Gottlieb, J. & Lopes, M. Intrinsic motivation, curiosity, and learning. in Progress in Brain Research vol. 229 257–284 (Elsevier, 2016). [ DOI ] [ PubMed ] 4. Tyng, C. M., Amin, H. U., Saad, M. N. M. & Malik, A. S. The Influences of Emotion on Learning and Memory. Front. 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Data Availability Statement All data described in this study are publicly available on Figshare at 10.6084/M9.FIGSHARE.29365349.V3. No code was used in this study. 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