Research

Our work fundamentally concerns how youths acquire cognitive, affective, and social skills needed to navigate life in a world that is rich, complex, and often messy. This motivates us to study three broad content areas: (i) emotion and emotion regulation, (ii) risky behavior and decision-making, and (iii) person knowledge and social behavior in context. To comprehensively understand phenomena under these banners, we use data collection methods such as functional magnetic resonance imaging (fMRI), capture of naturalistic written text, and ecological momentary assessment to glean insights into the hidden structures of the human mind that are not so easily observed otherwise. Our work is inclusive to data collected by the lab, shared in collaboration with other individual labs, and large consortia studies (e.g., ABCD). To analyze these data, we use a bevy of advanced computational techniques from the fields of computer science, behavioral economics, and quantitative psychology. By doing so we aim to provide tractable explanations of why certain developmental phenomena occur the way they do, while also being able to model future events. Finally, we also dabble in the development of statistical methods in service of aiding scientists with research goals similar to our own.

Topics

Risky Behavior and Decision-Making

The lab is interested in parsing the variability that is hallmark to adolescent decision-making. Thinking on our own experiences as humans, we know that it is unlikely that we make the exact same choice all or none of the time in a given decision context. This is especially true in adolescence, when individuals are granted greater autonomy to explore their environment on their own. We want to know what drives adolescent decision behavior by examining when and why teens make certain kinds of choices. We currently focus on two categories of teen choice behavior. First, we care about evaluating and refining popular scientific models of adolescent risk-taking, especially in ecologically relevant contexts (e.g., substance use, driving behavior). Second, we are broadly curious about teens’ social decision preferences involving known others (e.g., how do they navigate choices that carry outcomes for multiple known others, sometimes in conflicting ways?).
Representative Papers:
Guassi Moreira, J. F., Méndez Leal, A. S., Waizman, Y. H., Saragosa-Harris, N. M., Ninova, E., & Silvers, J. A. (2022). Early caregiving adversity differentially shapes behavioral sensitivity to reward and risk during decision-making. Journal of Experimental Psychology: General, 151(12), 3249–3267. https://doi.org/10.1037/xge0001229
Guassi Moreira, J. F., Méndez Leal, A. S., Waizman, Y. H., Saragosa-Harris, N. M., Ninova, E., & Silvers, J. A. (2021). Revisiting the neural architecture of adolescent decision-making: Univariate and multivariate evidence for system-based models. Journal of Neuroscience, 41(28), 6006–6017. https://doi.org/10.1523/JNEUROSCI.3182-20.2021
Dr. Guassi Moreira is accepting students and trainees who are interested in this line of work.

Emotion and Emotion Regulation

Emotions are constant companions of our internal lives, blanketing every waking (and many non-waking) moments. Emotions can help us deftly navigate the world, but can also lead us astray if left unchecked. Adolescence is an important time for emotional development. Teens are in the process of acquiring novel regulatory skills and refining others. In the CDNLab, we conceptualize emotion regulation acquisition as a process of specialization. Through this lens, we seek to understand how age- and experience-related changes in emotion regulation skills are supported by individual brain regions and networks that may become increasingly tuned towards emotion regulation (albeit not exclusively). Keeping with the theme of specialization, we’re also interested in understanding how unique repertoires of various emotion regulation strategies can be optimized for developmental wellbeing outcomes.
Representative Papers:
Guassi Moreira, J. F., Sahi, R. S., Calderón Leon, M. D., Saragosa-Harris, N., Waizman, Y., Sedykin, A., Ninova, E., Peris, T. S., Gross, J. J., & Silvers, J. A. (2024). A data-driven typology of emotion regulation profiles. Emotion, 24(5), 1125–1136. https://doi.org/10.1037/emo0001306
Guassi Moreira, J. F., McLaughlin, K. A., & Silvers, J. A. (2021). Characterizing the network architecture of emotion regulation neurodevelopment. Cerebral Cortex, 31(9), 4140–4150. https://doi.org/10.1093/cercor/bhab074
Dr. Guassi Moreira is accepting students who are interested in this line of work.

Person Knowledge and Social Behavior in Context

Often, the most consequential and meaningful social behaviors that teens engage in involve specific, known others: teachers in the classroom, classmates on the school bus, parents and siblings at the dinner table, and so on. Yet, so much psychological research on social behavior remains a science of strangers. This research arc of the lab is concerned with explaining and predicting social behavior in its proper ecological context—that is, behavior regarding specific and known others relevant to daily life—by blending techniques such as experience sampling, intensive longitudinal data collection, and natural language processing. We employ these research methods to better understand how teens allocate their time between the various social partners in their lives, why they choose certain shared activities over others (e.g., going to the mall vs watching a movie), and what makes an experience with a social partner enjoyable. Currently, this work takes the form of investigating how person knowledge and mental representations of social partners influence daily social behavior. Ultimately, the goal of this arc is to help translate knowledge gained in-lab to predict and understand real-world social behavior.
Representative Papers:
Guassi Moreira, J. F., & Parkinson, C. (2024). A behavioral signature for quantifying the social value of interpersonal relationships with specific others. Communications Psychology, 2(84), 1–17. https://doi.org/10.1038/s44271-024-00132-2
Guassi Moreira, J. F., Méndez Leal, A. S., Waizman, Y., Tashjian, S. M., Galván, A., & Silvers, J. A. (2023). Value-based neural representations predict social decision preferences. Cerebral Cortex, 33(13), 8605–8619. https://doi.org/10.1093/cercor/bhad144
Dr. Guassi Moreira is accepting students who are interested in this line of work.

Methods Development

Scientific advancement is impossible without methodological advancement. A nascent line of work in the lab seeks to help develop and refine methods as they relate to the problems that we and other groups face in pursuing the research described above. For us, this means taking a methodological issue that is frequently encountered in our work (e.g., necessary sample sizes for a specific type of model) and systematically probing the issue in an independent study in a such way that generates useful knowledge that can generalize to other scientists in our field (e.g., running a simulation study to ascertain the minimum number of subjects need to fit said model). We also believe in the importance of creating practical and accessible reviews of emergent methods to help spur their adoption in research groups that are interested in using them but do not have prior experience.
Representative papers:
Guassi Moreira, J. F., & Silvers, J. A. (2025). Multi-voxel pattern analysis for developmental cognitive neuroscientists. Developmental Cognitive Neuroscience, 73, 101555. https://doi.org/10.1016/j.dcn.2025.101555
Guassi Moreira, J.F., Block, J., Cruz, A., Enders, C.K., & Montoya, A.K. (In principle acceptance). Registered replication report and extension of Maas & Hox (2005), sufficient sample sizes for multilevel models. British Journal of Mathematical and Statistical Psychology. PsyArXiv
Dr. Guassi Moreira is accepting students who are interested in this line of work.