Rui Pei

All Publications

• Diminished valuation in the brain: how repeated exposure reduces health message engagement. Annals of behavioral medicine : a publication of the Society of Behavioral Medicine Liu, J., So, J., Pei, R. 2025; 59 (1)

  Abstract

  Public health campaigns traditionally aim to maximize message reach, assuming that more exposure leads to greater intended effects. However, recent research on message fatigue suggests that repeated exposure can lead to diminished message engagement. The goal of the current study is to understand the neuropsychological processes involved in repeated health message exposure in key brain regions known to facilitate or inhibit persuasion.This study examines how repeated exposure to health campaign messages is linked to neural activity in brain regions implicated in valuation, which is in turn linked to key processes of message engagement, including attention, elaboration, and counterarguing.Thirty-seven adolescent nonsmokers viewed 12 public service announcements (PSAs) from The Real Cost anti-tobacco campaign in a functional magnetic resonance imaging scan session. We examined the relationship between the number of PSA exposures and neural activity in the hypothesized brain regions of interest (ROIs). We also investigated whether the observed neural activity, in turn, was associated with the levels of message engagement reflected in participants' subsequent verbal descriptions of the PSAs, assessed with automated linguistic coding.Increased message exposure was negatively associated with neural activity in the valuation ROI, which was positively associated with activity in the attention, elaboration, and counterarguing ROIs. Neural activity in the attention ROI was linked to higher message engagement, while activity in the counterarguing ROI was negatively associated with message engagement. No significant link was found between neural activity in the elaboration ROI and message engagement. Mediation analysis suggested that increased exposure may indirectly reduce message engagement by diminishing positive valuation of the messages, thereby decreasing attention to and elaboration of the messages.This study elucidates the counterproductive effects of repeated message exposure on message engagement by examining the neurocognitive and psychological processes involved when target audiences are repeatedly exposed to similar anti-tobacco campaign messages. These insights are crucial for planning and designing public health campaigns that typically are repeated via various media channels.

  View details for DOI 10.1093/abm/kaaf037

  View details for PubMedID 40503982

• A neural signature of social support mitigates negative emotion. Scientific reports Pei, R., Courtney, A. L., Ferguson, I., Brennan, C., Zaki, J. 2023; 13 (1): 17293

  Abstract

  Social support can mitigate the impact of distressing events. Such stress buffering elicits activity in many brain regions, but it remains unclear (1) whether this activity constitutes a stable brain signature, and (2) whether brain activity can predict buffering across people. Here, we developed a neural signature that predicted social buffering of negative emotion in response to real life stressors. During neuroimaging, participants (n = 95) responded to stressful autobiographical memories either naturally, or by imagining a conversation with a peer. Using supervised dimensionality reduction and machine learning techniques, we identified a spatio-temporal neural signature that distinguished between these two trials. Activation of this signature was associated with less negative affect across trials, and people who most activated the signature reported more supportive social connections and lower loneliness outside the lab. Together, this work provides a behaviorally relevant neurophysiological marker for social support that underlies stress buffering.

  View details for DOI 10.1038/s41598-023-43273-w

  View details for PubMedID 37828064

  View details for PubMedCentralID 3136329

• Cultural Values Influence the Developmental Trajectory of Resistance to Social Influence Over the Course of Adolescence. Developmental psychobiology Pei, R., Kranzler, E., Falk, E. B. 2024; 66 (7): e22530

  Abstract

  The opinions of peers are among the most potent factors influencing human decision-making. Research conducted in Western societies suggests that individuals become more resistant to peer influence from late adolescence to adulthood. It is unknown whether this developmental trajectory is universal across cultures. Through two cross-national studies, we present consistent self-report and behavioral evidence for culturally distinct developmental trajectories of resistance to peer influence (RPI). Our findings from the US samples replicated prior findings that reported increasing RPI. Yet, data from the Chinese participants were better fitted using a nonlinear model, displaying a U-shaped trajectory with lowest RPI levels at around 20 years old. In contrast to the long-held belief that increasing RPI from adolescence to early adulthood is a universal developmental trait, we propose that this developmental trajectory may depend on cultural context.

  View details for DOI 10.1002/dev.22530

  View details for PubMedID 39300705

• Cultural influence on COVID-19 cognitions and growth speed: The role of collectivism SOCIAL AND PERSONALITY PSYCHOLOGY COMPASS Pei, R., Cosme, D., Andrews, M. E., Mattan, B. D., Carreras-Tartak, J., Falk, E. B. 2023

  View details for DOI 10.1111/spc3.12908

  View details for Web of Science ID 001078946200001

• Neural correlates associated with conformity in adolescent and young adult men. Developmental cognitive neuroscience Minich, M., Falk, E. B., Cooper, N., Cosme, D., Chan, H. Y., Pei, R., O'Donnell, M. B., Cascio, C. N. 2023; 60: 101215

  Abstract

  Social influence affects us throughout our lives, shaping our attitudes, behaviors, and preferences. Thus, the current study aimed to examine whether key age groups (adolescence versus young adulthood) were associated with differences in neural correlates associated with processing social feedback and conformity (i.e., conflict detection, positive valuation, and mentalizing) among young men. We recruited 153 participants across 5 studies, who completed a social influence task during an fMRI scan. Overall, participants were more likely to conform by changing their ratings when misaligned with others, and adolescents were more likely to conform when misaligned (compared to aligned) with others compared to young adults. Further, we found that adolescents showed increased activity in mentalizing (TPJ, dmPFC) and positive valuation regions (VS, vmPFC), compared to young adults, in response to misalignment with others. In contrast, young adults showed increased activity in conflict detection regions (AI, dACC) when exposed to feedback that they were misaligned with others and when conforming to that feedback. Overall, our results offer initial evidence that adolescent and young adult men engage different neural processes when they find out they are misaligned with others and when conforming to the recommendations of others, and this difference appears to track with brain responses in conflict detection, mentalizing and value regions. DATA STATEMENT: Raw data and analysis codes are available upon request.

  View details for DOI 10.1016/j.dcn.2023.101215

  View details for PubMedID 36841181

• One dimensional approximations of neuronal dynamics reveal computational strategy. PLoS computational biology Brennan, C., Aggarwal, A., Pei, R., Sussillo, D., Proekt, A. 2023; 19 (1): e1010784

  Abstract

  The relationship between neuronal activity and computations embodied by it remains an open question. We develop a novel methodology that condenses observed neuronal activity into a quantitatively accurate, simple, and interpretable model and validate it on diverse systems and scales from single neurons in C. elegans to fMRI in humans. The model treats neuronal activity as collections of interlocking 1-dimensional trajectories. Despite their simplicity, these models accurately predict future neuronal activity and future decisions made by human participants. Moreover, the structure formed by interconnected trajectories-a scaffold-is closely related to the computational strategy of the system. We use these scaffolds to compare the computational strategy of primates and artificial systems trained on the same task to identify specific conditions under which the artificial agent learns the same strategy as the primate. The computational strategy extracted using our methodology predicts specific errors on novel stimuli. These results show that our methodology is a powerful tool for studying the relationship between computation and neuronal activity across diverse systems.

  View details for DOI 10.1371/journal.pcbi.1010784

  View details for PubMedID 36607933

• Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States. Proceedings of the National Academy of Sciences of the United States of America Cramer, E. Y., Ray, E. L., Lopez, V. K., Bracher, J., Brennen, A., Castro Rivadeneira, A. J., Gerding, A., Gneiting, T., House, K. H., Huang, Y., Jayawardena, D., Kanji, A. H., Khandelwal, A., Le, K., Mühlemann, A., Niemi, J., Shah, A., Stark, A., Wang, Y., Wattanachit, N., Zorn, M. W., Gu, Y., Jain, S., Bannur, N., Deva, A., Kulkarni, M., Merugu, S., Raval, A., Shingi, S., Tiwari, A., White, J., Abernethy, N. F., Woody, S., Dahan, M., Fox, S., Gaither, K., Lachmann, M., Meyers, L. A., Scott, J. G., Tec, M., Srivastava, A., George, G. E., Cegan, J. C., Dettwiller, I. D., England, W. P., Farthing, M. W., Hunter, R. H., Lafferty, B., Linkov, I., Mayo, M. L., Parno, M. D., Rowland, M. A., Trump, B. D., Zhang-James, Y., Chen, S., Faraone, S. V., Hess, J., Morley, C. P., Salekin, A., Wang, D., Corsetti, S. M., Baer, T. M., Eisenberg, M. C., Falb, K., Huang, Y., Martin, E. T., McCauley, E., Myers, R. L., Schwarz, T., Sheldon, D., Gibson, G. C., Yu, R., Gao, L., Ma, Y., Wu, D., Yan, X., Jin, X., Wang, Y. X., Chen, Y., Guo, L., Zhao, Y., Gu, Q., Chen, J., Wang, L., Xu, P., Zhang, W., Zou, D., Biegel, H., Lega, J., McConnell, S., Nagraj, V. P., Guertin, S. L., Hulme-Lowe, C., Turner, S. D., Shi, Y., Ban, X., Walraven, R., Hong, Q. J., Kong, S., van de Walle, A., Turtle, J. A., Ben-Nun, M., Riley, S., Riley, P., Koyluoglu, U., DesRoches, D., Forli, P., Hamory, B., Kyriakides, C., Leis, H., Milliken, J., Moloney, M., Morgan, J., Nirgudkar, N., Ozcan, G., Piwonka, N., Ravi, M., Schrader, C., Shakhnovich, E., Siegel, D., Spatz, R., Stiefeling, C., Wilkinson, B., Wong, A., Cavany, S., España, G., Moore, S., Oidtman, R., Perkins, A., Kraus, D., Kraus, A., Gao, Z., Bian, J., Cao, W., Lavista Ferres, J., Li, C., Liu, T. Y., Xie, X., Zhang, S., Zheng, S., Vespignani, A., Chinazzi, M., Davis, J. T., Mu, K., Pastore Y Piontti, A., Xiong, X., Zheng, A., Baek, J., Farias, V., Georgescu, A., Levi, R., Sinha, D., Wilde, J., Perakis, G., Bennouna, M. A., Nze-Ndong, D., Singhvi, D., Spantidakis, I., Thayaparan, L., Tsiourvas, A., Sarker, A., Jadbabaie, A., Shah, D., Della Penna, N., Celi, L. A., Sundar, S., Wolfinger, R., Osthus, D., Castro, L., Fairchild, G., Michaud, I., Karlen, D., Kinsey, M., Mullany, L. C., Rainwater-Lovett, K., Shin, L., Tallaksen, K., Wilson, S., Lee, E. C., Dent, J., Grantz, K. H., Hill, A. L., Kaminsky, J., Kaminsky, K., Keegan, L. T., Lauer, S. A., Lemaitre, J. C., Lessler, J., Meredith, H. R., Perez-Saez, J., Shah, S., Smith, C. P., Truelove, S. A., Wills, J., Marshall, M., Gardner, L., Nixon, K., Burant, J. C., Wang, L., Gao, L., Gu, Z., Kim, M., Li, X., Wang, G., Wang, Y., Yu, S., Reiner, R. C., Barber, R., Gakidou, E., Hay, S. I., Lim, S., Murray, C., Pigott, D., Gurung, H. L., Baccam, P., Stage, S. A., Suchoski, B. T., Prakash, B. A., Adhikari, B., Cui, J., Rodríguez, A., Tabassum, A., Xie, J., Keskinocak, P., Asplund, J., Baxter, A., Oruc, B. E., Serban, N., Arik, S. O., Dusenberry, M., Epshteyn, A., Kanal, E., Le, L. T., Li, C. L., Pfister, T., Sava, D., Sinha, R., Tsai, T., Yoder, N., Yoon, J., Zhang, L., Abbott, S., Bosse, N. I., Funk, S., Hellewell, J., Meakin, S. R., Sherratt, K., Zhou, M., Kalantari, R., Yamana, T. K., Pei, S., Shaman, J., Li, M. L., Bertsimas, D., Skali Lami, O., Soni, S., Tazi Bouardi, H., Ayer, T., Adee, M., Chhatwal, J., Dalgic, O. O., Ladd, M. A., Linas, B. P., Mueller, P., Xiao, J., Wang, Y., Wang, Q., Xie, S., Zeng, D., Green, A., Bien, J., Brooks, L., Hu, A. J., Jahja, M., McDonald, D., Narasimhan, B., Politsch, C., Rajanala, S., Rumack, A., Simon, N., Tibshirani, R. J., Tibshirani, R., Ventura, V., Wasserman, L., O'Dea, E. B., Drake, J. M., Pagano, R., Tran, Q. T., Ho, L. S., Huynh, H., Walker, J. W., Slayton, R. B., Johansson, M. A., Biggerstaff, M., Reich, N. G. 2022; 119 (15): e2113561119

  Abstract

  SignificanceThis paper compares the probabilistic accuracy of short-term forecasts of reported deaths due to COVID-19 during the first year and a half of the pandemic in the United States. Results show high variation in accuracy between and within stand-alone models and more consistent accuracy from an ensemble model that combined forecasts from all eligible models. This demonstrates that an ensemble model provided a reliable and comparatively accurate means of forecasting deaths during the COVID-19 pandemic that exceeded the performance of all of the models that contributed to it. This work strengthens the evidence base for synthesizing multiple models to support public-health action.

  View details for DOI 10.1073/pnas.2113561119

  View details for PubMedID 35394862