Publications

Fontanesi, L. (2019). Insights into reward-based decisions using computational models and ultra-high field MRI. https://doi.org/10.5451/unibas-007108237   edoc | Open Access
Spektor, M. S., Gluth, S., Fontanesi, L., & Rieskamp, J. (2019). How similarity between choice options affects decisions from experience: the accentuation-of-differences model. Psychological Review, 126(1), 52-88. https://doi.org/10.1037/rev0000122   edoc
Fontanesi, L., Gluth, S., Spektor, M. S., & Rieskamp, J. (2019). A reinforcement learning diffusion decision model for value-based decisions. Psychonomic Bulletin & Review, 26(4), 1099-1121. https://doi.org/10.3758/s13423-018-1554-2   
Fontanesi, L., Gluth, S., Spektor, M. S., & Rieskamp, J. (2019). A reinforcement learning diffusion decision model for value-based decisions. Psychonomic Bulletin & Review, 26(4), 1099-1121. https://doi.org/10.3758/s13423-018-1554-2   
Fontanesi, L., Gluth, S., Rieskamp, J., & Forstmann, B. U. (2019). The role of dopaminergic nuclei in predicting and experiencing gains and losses: A 7T human fMRI study. BioRxiv, 1-26. https://doi.org/10.1101/732560   
Botvinik-Nezer, R., Holzmeister, F., Camerer, C. F., Dreber, A., Huber, J., Johannesson, M., Kirchler, M., Iwanir, R., Mumford, J. A., Adcock, A., Avesani, P., Baczkowski, B., Bajracharya, A., Bakst, L., Ball, S., Barilari, M., Bault, N., Beaton, D., Beitner, J., Benoit, R., Berkers, R., Bhanji, J., Biswal, B., Bobadilla-Suarez, S., Bortolini, T., Bottenhorn, K., Bowring, A., Braem, S., Brooks, H., Brudner, E., Calderon, C., Camilleri, J., Castrellon, J., Cecchetti, L., Cieslik, E., Cole, Z., Collignon, O., Cox, R., Cunningham, W., Czoschke, S., Dadi, K., Davis, C., De Luca, A., Delgado, M., Demetriou, L., Dennison, J., Di, X., Dickie, E., Dobryakova, E., Donnat, C., Dukart, J., Duncan, N. W., Durnez, J., Eed, A., Eickhoff, S., Erhart, A., Fontanesi, L., Fricke, G. M., Galvan, A., Gau, R., Genon, S., Glatard, T., Glerean, E., Goeman, J., Golowin, S., González-Garc`iaC., Gorgolewski, K., Grady, C., Green, M., Guassi Moreira, J., Guest, O., Hakimi, S., Hamilton, J. P., Hancock, R., Handjaras, G., Harry, B., Hawco, C., Herholz, P., Herman, G., Heunis, S., Hoffstaedter, F., Hogeveen, J., Holmes, S., Hu, C.-P., Huettel, S., Hughes, M., Iacovella, V., Iordan, A., Isager, P., Isik, A. I., Jahn, A., Johnson, M., Johnstone, T., Joseph, M., Juliano, A., Kable, J., Kassinopoulos, M., Koba, C., Kong, X.-Z., Koscik, T., Kucukboyaci, N. E., Kuhl, B., Kupek, S., Laird, A., Lamm, C., Langner, R., Lauharatanahirun, N., Lee, H., Lee, S., Leemans, A., Leo, A., Lesage, E., Li, F., Li, M., Lim, P. C., Lintz, E., Liphardt, S., Losecaat Vermeer, A., Love, B., Mack, M., Malpica, N., Marins, T., Maumet, C., McDonald, K., McGuire, J., Melero, H., Méndez Leal, A., Meyer, B., Meyer, K., Mihai, P., Mitsis, G., Moll, J., Nielson, D., Nilsonne, G., Notter, M., Olivetti, E., Onicas, A., Papale, P., Patil, K., Peelle, J. E., Pérez, A., Pischedda, D., Poline, J.-B., Prystauka, Y., Ray, S., Reuter-Lorenz, P., Reynolds, R., Ricciardi, E., Rieck, J., Rodriguez-Thompson, A., Romyn, A., Salo, T., Samanez-Larkin, G., Sanz-Morales, E., Schlichting, M., Schultz, D., Shen, Q., Sheridan, M., Shiguang, F., Silvers, J., Skagerlund, K., Smith, A., Smith, D., Sokol-Hessner, P., Steinkamp, S., Tashjian, S., Thirion, B., Thorp, J., Tinghög, G., Tisdall, L., Tompson, S., Toro-Serey, C., Torre, J., Tozzi, L., Truong, V., Turella, L., vantextquoterightt Veer, A. E., Verguts, T., Vettel, J., Vijayarajah, S., Vo, K., Wall, M., Weeda, W. D., Weis, S., White, D., Wisniewski, D., Xifra-Porxas, A., Yearling, E., Yoon, S., Yuan, R., Yuen, K., Zhang, L., Zhang, X., Zosky, J., Nichols, T. E., Poldrack, R. A., & Schonberg, T. (2019). Variability in the analysis of a single neuroimaging dataset by many teams. BioRxiv, 1-31. https://doi.org/10.1101/843193   
Fontanesi, L., Palminteri, S., & Lebreton, M. (2019). Decomposing the effects of context valence and feedback information on speed and accuracy during reinforcement learning: a meta-analytical approach using diffusion decision modeling. Cognitive, Affective, & Behavioral Neuroscience, 19(3), 490-502. https://doi.org/10.3758/s13415-019-00723-1   
Van Maanen, L., Fontanesi, L., Hawkins, G. E., & Forstmann, B. U. (2016). Striatal activation reflects urgency in perceptual decision making. NeuroImage, 139, 294-303. https://doi.org/10.1016/j.neuroimage.2016.06.045   edoc
Gluth, S., & Fontanesi, L. (2016). Wiring the altruistic brain. Science. American Association for the Advancement of Science. https://doi.org/10.1126/science.aaf4688   edoc