Publikationen von Quentin J. M. Huys

Malamud, J., Guloksuz, S., van Winkel, R., Delespaul, P., De Hert, M. A. F., Derom, C., Thiery, E., Jacobs, N., Rutten, B. P. F., & Huys, Q. J. M. (2024). Characterizing the dynamics, reactivity and controllability of moods in depression with a Kalman filter. PLoS Computational Biology, 20(9), Article e1012457. https://doi.org/10.1371/journal.pcbi.1012457

Malamud, J., Lewis, G., Moutoussis, M., Duffy, L., Bone, J., Srinivasan, R., Lewis, G., & Huys, Q. J. M. (2024). The selective serotonin reuptake inhibitor sertraline alters learning from aversive reinforcements in patients with depression: Evidence from a randomized controlled trial. Psychological Medicine, 54(10), 2719–2731. https://doi.org/10.1017/S0033291724000837

Mishchanchuk, K., Gregoriou, G., Qü, A., Kastler, A., Huys, Q. J. M., Wilbrecht, L., & MacAskill, A. F. (2024). Hidden state inference requires abstract contextual representations in the ventral hippocampus. Science, 386(6724), 926–932. https://doi.org/10.1126/science.adq5874

Montemitro, C., Ossola, P., Ross, T. J., Huys, Q. J. M., Fedota, J. R., Salmeron, B. J., di Giannantonio, M., & Stein, E. A. (2024). Longitudinal changes in reinforcement learning during smoking cessation: A computational analysis using a probabilistic reward task. Scientific Reports, 14, Article 32171. https://doi.org/10.1038/s41598-024-84091-y

Norbury, A., Hauser, T. U., Fleming, S. M., Dolan, R. J., & Huys, Q. J. M. (2024). Different components of cognitive-behavioral therapy affect specific cognitive mechanisms. Science Advances, 10(13), Article eadk3222. https://doi.org/10.1126/sciadv.adk3222

Russek, E. M., Moran, R., Liu, Y., Dolan, R. J., & Huys, Q. J. M. (2024). Heuristics in risky decision-making relate to preferential representation of information. Nature Communications, 15, Article 4269. https://doi.org/10.1038/s41467-024-48547-z

Talwar, A., Cormack, F., Huys, Q. J. M., & Roiser, J. P. (2024). A hierarchical reinforcement learning model explains individual differences in attentional set shifting. Cognitive, Affective, & Behavioral Neuroscience, 24, 1008–1022. https://doi.org/10.3758/s13415-024-01223-7

Browning, M., Paulus, M., & Huys, Q. J. M. (2023). What is computational psychiatry good for? Biological Psychiatry, 93(8), 658–660. https://doi.org/10.1016/j.biopsych.2022.08.030

Chen, H., Belanger, M. J., Garbusow, M., Kuitunen-Paul, S., Huys, Q. J. M., Heinz, A., Rapp, M. A., & Smolka, M. N. (2023). Susceptibility to interference between Pavlovian and instrumental control predisposes risky alcohol use developmental trajectory from ages 18 to 24. Addiction Biology, 28(2), Article e13263. https://doi.org/10.1111/adb.13263

Chen, K., Garbusow, M., Sebold, M., Kuitunen-Paul, S., Smolka, M. N., Huys, Q. J. M., Zimmermann, U. S., Schlagenhauf, F., & Heinz, A. (2023). Alcohol approach bias is associated with both behavioral and neural Pavlovian-to-instrumental transfer effects in alcohol-dependent patients. Biological Psychiatry Global Open Science, 3(3), 443–450. https://doi.org/10.1016/j.bpsgos.2022.03.014