Kosciessa, J. Q. (2020). Measurement and relevance of rhythmic and aperiodic human brain dynamics [PhD Thesis, Humboldt-Universität zu Berlin]. https://doi.org/10.18452/22040

Liu, Y. (2020). Neural replay in representation, learning and planning [PhD Thesis, University College London].

Ereira, S. P. A. (2019). A neurocomputational account of self-other distinction: From cell to society [PhD Thesis, University College London].

Mooraj, Z. (2022). Metamemory judgements in aging: Differences in behavioral influences, neural activation, and connectivity patterns between younger and older adults [Master's Thesis, Humboldt Universität zu Berlin].

Schmidt, M. K. (2022). Associations of non-invasive correlates of noradrenergic neuromodulation and learning across the adult lifespan [Master's Thesis, Humboldt Universität zu Berlin / Berlin School of Mind and Brain].

Eyre, H. A., Ibáñez, A., Falcao, V. P., Winter, S. F., Berk, M., Gilbert, B. J., Erickson, K. I., Smith, E., Kühn, S., Dawson, W., Hynes, W., Lundin, R., Weatherill, H. J., Sudimac, S., Chen, S., Regazzoni, C. J., Bilder, R., Lawlor, B., Cotter, E., Occhipinti, J.-A., Jeste, D. V., Quoidbach, V., Destrebecq, F., Lavretsky, H., Jraissati, J., Edmonds, T., Lister, C., Freeman, M. A., Deif, R., Sale, V., Sarnyai, Z., Storch, E. A., Robertson, I. H., Reynolds, C. F., Ng, C. H., Chadha, A. S., Dunlop, S., Farina, F. R., Booi, L., Sweiboda, P., Hawrot, T., Simó, S., Carlo, A., Loughman, A., Butterworth, I., Jacka, F., Ayadi, R., Meidl, R., Belkin, G., & Salama, M. (2023). Brain capital is key to a sustainable future (Research paper / Rice University's Baker Institute for Public Policy No. 07.10.23). Rice University's Baker Institute for Public Policy. https://doi.org/10.25613/5yez-tc65

Hertwig, R., Liebig, S., Lindenberger, U., & Wagner, G. G. (2020). Wie gefährlich ist COVID-19? Die subjektive Risikoeinschätzung einer lebensbedrohlichen COVID-19-Erkrankung im Frühjahr und Frühsommer 2020 in Deutschland (SOEPpapers on Multidisciplinary Panel Data Research No. 1095). DIW.

Dahl, M. J., Werkle-Bergner, M., & Mather, M. (Eds.). (in press). Neuromodulatory systems in aging and disease [Special issue]. Neuroscience & Biobehavioral Reviews, .

Huys, Q. J. M., & Paulus, M. (Eds.). (2023). Reliability of neurocognitive measures for mental health [Special issue]. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 8(8).

Hartley, C. A., Fandakova, Y., Bunge, S. A., Crone, E., & Lindenberger, U. (Eds.). (2020). Special Issue on Flux 2018: Mechanisms of learning & plasticity [Special issue]. Developmental Cognitive Neuroscience, 42.

Fleming, S. M. (2024, April 8). Hacking the predictive mind [Review of the book The experience machine: How our minds predict and shape reality by Andy Clark]. Brain, 147(4), 1589–1592. https://doi.org/10.1093/brain/awad417

Huys, Q. J. M. (2022). Is there mathematics to madness? Brain. https://doi.org/10.1093/brain/awac047

Hauser, T. U., Will, G.-J., Dubois, M., & Dolan, R. J. (2019). Annual research review: Developmental computational psychiatry. Journal of Child Psychology and Psychiatry, 60(4), 412–426. https://doi.org/10.1111/jcpp.12964

Dahl, M. J., Werkle-Bergner, M., & Mather, M. (2024). Neuromodulatory systems in aging and disease. Neuroscience & Biobehavioral Reviews. Advance online publication. https://doi.org/10.1016/j.neubiorev.2024.105647

Katyal, S., Lumma, A.-L., Goldin, P. R., & Roy, S. (2023). Editorial: The varieties of contemplative experiences and practices. Frontiers in Psychology (No. 14), 1232999. https://doi.org/10.3389/fpsyg.2023.1232999

Olszewska-Guizzo, A., Russo, A., Roberts, A. C., Kühn, S., Marques, B., Tawil, N., & Ho, R. C. (2023). Editorial: Cities and mental health. Frontiers in Psychiatry (No. 14), 1263305. https://doi.org/10.3389/fpsyt.2023.1263305

Bruntsch, M., Cooper, S. E., Abend, R., Boor, M., Chalkia, A., Czeszumski, A., Ehlers, M. R., Johnson, D. C., Klingelhöfer-Jens, M., Morriss, J., Mueller, E. M., Zika, O., & Lonsdorf, T. B. (2024). Associations between anxiety-related traits and fear acquisition and extinction: An item-based content and meta-analysis [Stage 1 Registered Report]. PsyArXiv, April 26, 2024. https://doi.org/10.31234/osf.io/unx7w

Brandmaier, A. M., Lindenberger, U., & McCormick, E. M. (2024). Optimal two-time point longitudinal models for estimating individual-level change: Asymptotic insights and practical implications. PsyArXiv, March 6, 2024. https://doi.org/10.31234/osf.io/6dc8e

Habicht, J., Dina, L.-M., Stylianou, M., Harper, R., Hauser, T. U., & Rollwage, M. (2024). Generative AI-enabled therapy support tool improves clinical outcomes and patient engagement in NHS talking therapies. PsyArXiv, April 10, 2024. https://doi.org/10.31234/osf.io/mj46k

Hedrich, N. L., Schulz, E., Hall-McMaster, S., & Schuck, N. W. (2024). An inductive bias for slowly changing features in human reinforcement learning. BioRxiv, January 24, 2024. https://doi.org/10.1101/2024.01.24.576910