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Postdoctoral Researcher
University of Tübingen
lenarddome [at] gmail [dot] com
I am a computational cognitive scientist at the University of Tübingen. My research develops and evaluates process models of learning, generalisation, and decision-making — with a central commitment to model adequacy; whether models capture the right computational mechanisms, not merely the right outcomes. I work at the intersection of formal model evaluation, theories of learning and categorisation, and computational psychiatry. One of my current focus is building generative process models that account for irrational generalisation across supervised and unsupervised task structures — probing the computational principles that persist across radically different learning conditions. I am increasingly interested in what formal models of cognition reveal about the conditions under which decision-making succeeds or fails, both as a diagnostic lens for psychiatric conditions and as a principled basis for designing systems that support rather than supplant human judgment in high-stakes environments.
Game of Life
Boids Swarm
Neural Network

Publications


    2. Schlegelmilch, R., & Dome, L. (2026). Snake oil or Panacea? How to Misuse AI in Scientific Inquiries of the Human Mind. Behavioral Sciences., 16(2). https://doi.org/10.3390/bs16020219 https://doi.org/10.3390/bs16020219
    4. Marzuki, A. A., Kosina, L. A., Dome, L., Hewitt, S. R. C., & Hauser, T. U. (2025). Metacognitive Antecedents to States of Mental Ill-Health: Drops in Confidence Precede Symptoms of OCD. Research Square. https://doi.org/10.21203/rs.3.rs-7544256/v1 https://doi.org/10.21203/rs.3.rs-7544256/v1
    6. Dome, L., Kadri, K., Wagner, B. J., Webb, A., & Hauser, T. U. (2025). cpm: A Python Library for Theory-Driven Modelling in Computational Psychiatry. OSF. https://doi.org/10.31234/osf.io/6jc3t_v1 https://doi.org/10.31234/osf.io/6jc3t_v1
    8. Dome, L., & Wills, A. J. (2025). g-Distance: On the Comparison of Model and Human Heterogeneity. Psychological Review, 132(3), 632–655. https://doi.org/https://doi.org/10.1037/rev0000550 https://doi.org/https://doi.org/10.1037/rev0000550
    10. Dome, L., & Wills, A. J. (2025). Better generalization through distraction? Concurrent load reduces the size of the inverse base-rate effect. Psychonomic Bulletin & Review. https://doi.org/https://doi.org/10.3758/s13423-025-02661-1 https://doi.org/https://doi.org/10.3758/s13423-025-02661-1
    12. Dome, L., & Wills, A. J. (2023). Errorless irrationality: removing error-driven components from the inverse base-rate effect paradigm. Proceedings of the Annual Meeting of the Cognitive Science Society., 45(45), 237–243. https://doi.org/https://doi.org/10.31234/osf.io/936bj https://doi.org/https://doi.org/10.31234/osf.io/936bj
    14. Dome, L., Edmunds, C. E. R., & Wills, A. J. (2021). SUSTAIN captures category learning, recognition, and hippocampal activation in a unidimensional vs information-integration task. Proceedings of the Annual Meeting of the Cognitive Science Society., 43, 3013–3019. https://doi.org/https://escholarship.org/uc/item/5r98q3dr https://doi.org/https://escholarship.org/uc/item/5r98q3dr
    16. Spicer, S. G., Wills, A. J., Jones, P. M., Mitchell, C. J., & Dome, L. (2021). Representing uncertainty in the Rescorla-Wagner model: blocking, the redundancy effect, and outcome base rate. Open Journal of Experimental Psychology and Neuroscience. https://doi.org/https://doi.org/10.46221/ojepn.2021.66233 https://doi.org/https://doi.org/10.46221/ojepn.2021.66233
    18. Wimmer, M. C., Dome, L., Hancock, P. J. B., & Wennekers, T. (2019). Is the Letter Cancellation Task a Suitable Index of Ego Depletion? Social Psychology, 345–354. https://doi.org/10.1027/1864-9335/a000393 https://doi.org/10.1027/1864-9335/a000393