PDFs can be downloaded for non-commercial information purposes only.
For questions or requests, please email velez.colab@gmail.com
* denotes authors who contributed equally. Representative papers are marked in bold.
Preprints
Vélez, N., Wu, C.M.*, Gershman, S.J., & Schulz, E.* (under review). The rise and fall of technological development in virtual communities. [preprint]
Ham, H., Zhao, B., Griffiths, T.L., & Vélez, N. (under review). Teaching and learning generalizable abstractions. [preprint]
Mieczkowski, E. A., Turner, C. R., Vélez, N., & Griffiths, T. L. (under review). People evaluate idle collaborators based on their impact on task efficiency. [preprint]
Xiang, Y., Landy, J., Cushman, F., Vélez, N., & Gershman, S. J. (under review). People reward others based on their willingness to exert effort. [preprint]
Journal Articles
2024
Xiang, Y., Vélez, N., & Gershman, S.J. (2024). Optimizing competence in the service of collaboration. Cognitive Psychology. [PDF]
Chen, A.M., Palacci, A., Vélez, N., Hawkins, R., & Gershman, S.J. (2024). A hierarchical Bayesian model of adaptive teaching. Cognitive Science. [PDF]
Allen, K.*, Brändle, F.*, ... Vélez, N., Watrous, A., Tenenbaum, J., & Schulz, E. (2024). Using games to understand the mind. Nature Human Behaviour. [PDF]
2023
Xiang, Y., Landy, J., Cushman, F., Vélez, N., & Gershman, S. J. (2023). Actual and counterfactual effort contribute to responsibility attributions in collaborative tasks. Cognition. [PDF]
Vélez, N., Chen, A. M., Burke, T., Cushman, F., & Gershman, S. J. (2023). Teachers recruit mentalizing regions to represent learners' beliefs. PNAS. [PDF] [repository]
Vélez, N., Christian, B., Hardy, M., Thompson, B. D., & Griffiths, T. L. (2023). How do humans overcome individual computational limitations by working together?. Cognitive Science. [PDF]
Torabian, S., Vélez, N., Sochat, V., Halchenko, Y. O., & Grossman, E. D. (2023). The PyMVPA BIDS-App: A Robust MultiVariate Pattern Analysis Pipeline for fMRI Data. Frontiers in Neuroscience. [PDF] [repository]
Xiang, Y., Vélez, N., & Gershman, S. J. (2023). Collaborative decision making is grounded in representations of other people’s competence and effort. Journal of Experimental Psychology: General. [PDF]
Pre-2023
Vélez, Wu, C.M., & Cushman F.A. (2022). Representational exchange in social learning: Blurring the lines between the ritual and instrumental. (*Commentary on Jagiello et al., 2022). Behavioral and Brain Sciences. [PDF]
Chuey, A., Asaba, M., Bridgers, S., Carrillo, B., Dietz, G., Garcia, T., Leonard, J. A., Liu, S., Merrick, M., Radwan, S., Stegal, J., Vélez, N., Woo, B., Wu, Y., Zhou, X. J., Frank, M. C., & Gweon, H. (2021). Moderated online data-collection for developmental research: Methods and replications. Frontiers in Psychology. [PDF]
Vélez, N., & Gweon, H. (2021). Learning from other minds: An optimistic critique of reinforcement learning models of social learning. Current Opinion in Behavioral Sciences. [PDF]
Vélez, N., Bridgers, S., & Gweon, H. (2019). The rare preference effect: Statistical information influences affiliation judgments. Cognition. [PDF] [repository]
Vélez, N., & Gweon, H. (2018). Integrating incomplete information with imperfect advice. Topics in Cognitive Science. [PDF] [repository]
Koster-Hale, J.*, Richardson, H.*, Velez-Alicea, N., Asaba, M., Young, L., & Saxe, R. (2017). Mentalizing regions represent continuous, abstract dimensions of others' beliefs. Neuroimage. [PDF]
Open Science Collaboration. (2015). Estimating the reproducibility of psychological science. Science. [PDF]
Book Chapters
Wu, C. M., Vélez, N., & Cushman, F. A. (2022). Representational exchange in human social learning: Balancing efficiency and flexibility. In I. Cogliati Dezza, E. Schulz & C. Wu (Eds.) The drive for knowledge: the science of human information-seeking. Cambridge University Press. [PDF]
Refereed Conference Proceedings
2023
Witt, A., Vasama, J., Vélez, N., & Wu, C. M. (2023). Playing to win or playing to learn? Human performance in a social card game task. In L. Hunt, C. Summerfield, T. Konkle, E. Fedorenko, & T. Naselaris (Eds.), Proceedings of the 2023 Conference on Cognitive Computational Neuroscience. Oxford, UK. [PDF]
Pre-2023
Vélez & Gweon, H. (2020). Preschoolers use minimal statistical information to infer the preferences and group membership of new individuals. Proceedings of the Annual Meeting of the Cognitive Science Society. [PDF]
Vélez, & Gweon, H. (2019). Neural mechanisms underlying the computation of socially inferred rewards. Proceedings of the 2019 Conference on Cognitive Computational Neuroscience. Berlin, DE. [PDF]
Vélez, N., Wu, Y., & Gweon, H. (2018). Consistent but not diagnostic: Preschoolers' intuitions about shared preferences within social groups. Proceedings of the Annual Meeting of the Cognitive Science Society. [PDF]
Vélez, N., & Gweon, H. (2017). Integrating incomplete information with imperfect advice. Proceedings of the 2017 Conference on Cognitive Computational Neuroscience. [related publication]
Vélez, N., Bridgers, S., & Gweon, H. (2016). Not all overlaps are equal: Social affiliation and rare overlaps of preferences. Proceedings of the Annual Meeting of the Cognitive Science Society. [related publication]
Vélez, N.*, Leong, Y. C.*, Pan, C., Zaki, J., & Gweon, H. (2016). Learning and making novel predictions about others' preferences. Proceedings of the Annual Meeting of the Cognitive Science Society. [PDF]