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Publications

Journal Articles

  • Youngblood, M. (2026). NEW INC Y12 Creative Science: Alakaʻi 1777—using immersive sound to communicate the nonhuman cultural extinction crisis. Biotechnology Design. https://doi.org/10.1017/S2977905726100109

  • Mudd, K., Youngblood, M., & Schedel, M. (2026). Dynamics of creative exploration: A study of signal space constraints in music and communication. Proceedings of the Annual Meeting of the Cognitive Science Society. https://escholarship.org/uc/item/20h9h892

  • Sobchuk, O., & Youngblood, M. (2026). Cultural evolution - of the arts. Evolutionary Human Sciences. https://doi.org/10.1017/ehs.2026.10048

  • Youngblood, M. (2026). Zebra finches transform random songs to exhibit linguistic laws. Animal Cognition, 29(35). https://doi.org/10.1007/s10071-026-02058-0

  • Youngblood, M., & Passmore, S. (2026). Simulation-based inference with deep learning shows speed climbers combine innovation and copying to improve performance. Proceedings of the Royal Society B, 293(2062), 20251433. https://doi.org/10.1098/rspb.2025.1433

  • Wascher, C., & Youngblood, M. (2025). Vocal efficiency in crows. Animal Cognition, 28(75). https://doi.org/10.1007/s10071-025-01985-8

  • Whiten, A., & Youngblood, M. (2025). Convergent evolution in whale and human vocal cultures. Science, 387(6734), 581--582. https://doi.org/10.1126/science.adv2318

  • Youngblood, M. (2025). Language-like efficiency in whale communication. Science Advances, 11(6), eads6014. https://doi.org/10.1126/sciadv.ads6014

  • Pitocchelli, J., Albina, A., Bentley, R.A., Guerra, D., & Youngblood, M. (2025). Temporal stability in songs across the breeding range of Geothlypis philadelphia (mourning warbler) may be due to learning fidelity and transmission biases. Ornithology, 142(1), ukae046. https://doi.org/10.1093/ornithology/ukae046

  • Kornreich, A., Partridge, D., Youngblood, M., & Parkins, K. (2024). Rehabilitation outcomes of bird-building collision victims in the Northeastern United States. PLoS ONE, 19(8), e0306362. https://doi.org/10.1371/journal.pone.0306362

  • Sobchuk, O., Youngblood, M., & Morin, O. (2024). First-mover advantage in music. EPJ Data Science, 13(1), 37. https://doi.org/10.1140/epjds/s13688-024-00476-z

  • Youngblood, M. (2024). Language-like efficiency and structure in house finch song. Proceedings of the Royal Society B, 291(2020), 20240250. https://doi.org/10.1098/rspb.2024.0250

  • Youngblood, M., Stubbersfield, J.M., Morin, O., Glassman, R., & Acerbi, A. (2023). Negativity bias in the spread of voter fraud conspiracy theory tweets during the 2020 US election. Humanities and Social Sciences Communications, 10(1), 1--11. https://doi.org/10.1057/s41599-023-02106-x

  • Youngblood, M., Miton, H., & Morin, O. (2023). Statistical signals of copying are robust to time-and space-averaging. Evolutionary Human Sciences, 5, e10. https://doi.org/10.1017/ehs.2023.5

  • Benjamin, F.J., Kaaronen, R.O., Moser, C., Rorot, W., Tan, J., Varma, V., Williams, T., & Youngblood, M. (2023). All intelligence is collective intelligence. Journal of Multiscale Neuroscience, 2(1), 169--191. https://doi.org/10.56280/1564736810

  • Youngblood, M., & Lahti, D.C. (2022). Content bias in the cultural evolution of house finch song. Animal Behaviour, 185, 37--48. https://doi.org/10.1016/j.anbehav.2021.12.012

  • Youngblood, M., Baraghith, K., & Savage, P.E. (2021). Phylogenetic reconstruction of the cultural evolution of electronic music via dynamic community detection (1975--1999). Evolution & Human Behavior, 42(6), 573--582. https://doi.org/10.1016/j.evolhumbehav.2021.06.002

  • Kornreich, A., Youngblood, M., Mundinger, P.C., & Lahti, D.C. (2020). Female song can be as long and complex as male song in wild house finches (Haemorhous mexicanus). The Wilson Journal of Ornithology, 132(4), 840--849. https://doi.org/10.1676/19-00126

  • Youngblood, M. (2020). Extremist ideology as a complex contagion: the spread of far-right radicalization in the United States between 2005 and 2017. Humanities & Social Sciences Communications, 7(1), 1--10. https://doi.org/10.1057/s41599-020-00546-3

  • Youngblood, M. (2019). A Raspberry Pi-based, RFID-equipped birdfeeder for the remote monitoring of wild bird populations. Ringing & Migration, 34(1), 25--32. https://doi.org/10.1080/03078698.2019.1759908

  • Youngblood, M. (2019). Conformity bias in the cultural transmission of music sampling traditions. Royal Society Open Science, 6(9), 191149. https://doi.org/10.1098/rsos.191149

  • Youngblood, M. (2019). Cultural transmission modes of music sampling traditions remain stable despite delocalization in the digital age. PLoS ONE, 14(2), e0211860. https://doi.org/10.1371/journal.pone.0211860

  • Youngblood, M., & Lahti, D. (2018). A bibliometric analysis of the interdisciplinary field of cultural evolution. Palgrave Communications, 4(1), 1--9. https://doi.org/10.1057/s41599-018-0175-8

Book Chapters

Preprints

  • Youngblood, M. (2026). Simulation-based inference for cultural evolution: a tutorial with baby name data. SocArXiv. https://doi.org/10.31235/osf.io/c5q2h_v1

  • Youngblood, M., Mudd, K., Anglada-Tort, M., Jones, C., Miu, E., Omigie, D., & Schedel, M. (2026). Collective creativity in hybrid societies. arXiv. https://doi.org/10.48550/arXiv.2609.02620

  • Youngblood, M., Nusz, J., & Simon, J. (2026). Dynamics of collective creativity in AI art competitions. arXiv. https://doi.org/10.48550/arXiv.2605.17141

  • Jia, Z., Ozaki, Y., Pavlovich, D., Huang, J., Benetos, E., Khasanah, U., Calhoun, S., Chiba, G., Kitayama, Y., Fujii, S., Sadaphal, D.P., Fitch, W.T., Vaida, S., Echim, S., Popescu, T., Shi, Z., Grassi, M., Guiotto Nai Fovino, L., Hajič jr., J., Nuska, P., Štěpánková, B., Tiratanti, P., Bulbulia, J.A., He, Y., Li, Y., Liu, F., Novembre, G., Coissac, C., Arnese, F., Jadoul, Y., Ravignani, A., Nweke, F.E., Oladimeji, A.O., Olokodana-James, O., Mousavi, N., Larrouy-Maestri, P., Færøvik, U., Lenvik, A., Ruiz Loria, M., Quintero-Martínez, J., Ariza, J.F., Leongómez, J.D., Cabildo, A., Vanden Bosch der Nederlanden, C., Proutskova, P., Macholl, D., Ong, J.H., Wider, C., Tunçgenç, B., Talamini, F., Leuschner, L., Thompson, W.F., Perry, G., Wolff, L., Ross, R.M., Ampiah-Bonney, A., Gabriel, S., Pfordresher, P.Q., Parkinson, H., Honbolygó, F., Kertész, C., Pavlov, Y.G., Kosachenko, A., Tarasov, D., Krzyżanowski, W., Podlipniak, P., Dabaghi Varnosfaderani, S., Beck, A., Kim, I., Jung, T., McBride, J.M., Lomsadze, T., Ripley, S., Bilous, K., Trainor, L.J., Bamford, J.S., Thompson, M., Hartmann, M., Tarr, B., Han, K.Y., McCullough, A.K., Loui, P., Dias, R., Garcia-Arasco, A., Bellot, A., Pisanski, K., Raviv, L., van Casteren, R., Kortegaard, K.B., Hansen, N.C., Kurdova, D., Mikova, Z., Arhine, A., Okantah Jr., M.O., Labayili, K.K., Ma, Y., Sears, D., Rivera, L.A., Kolios, S., Zariquiey, R., Poblete, M., Rojas, S., Haiduk, F., Nguqu, N., Opondo, P., Parselelo, M.L., Barbosa, B.S., Varella, M.A.C., Belyk, M., Youngblood, M., Purdy, S.C., & Savage, P.E. (2026). Synchronised group singing enhances social bonding more than group conversation or recitation does: A Registered Report across 30 languages. PsyArXiv. https://doi.org/10.31234/osf.io/pv3m9_v4

  • Youngblood, M. (2025). chatter: a Python library for applying information theory and AI/ML models to animal communication. arXiv. https://doi.org/10.48550/arXiv.2512.17935

  • Youngblood, M., Marie, A., & Morin, O. (2025). Status quo conservatism: A theory and a model. SocArXiv. https://osf.io/ngb58

  • GomezdelaTorre Clavel, M.G., Youngblood, M., & Lahti, D. (2020). Relationship between personality and cognitive traits in domestic rabbits (Oryctolagus cuniculus). bioRxiv. https://doi.org/10.1101/2020.10.12.336024