Publication

Found 910 results
Author Title [ Type(Desc)] Year
Journal Article
Scott, K. M. & Schulz, L. Lookit (Part 1): a new online platform for developmental research. Open Mind 1, (2017).PDF icon UNCORRECTED PROOF (561.21 KB)
Scott, K. M., Chu, J. & Schulz, L. Lookit (Part 2): Assessing the viability of online developmental research, Results from three case studies. Open Mind 1, (2017).PDF icon lookitpart2.pdf (464.02 KB)
Gerstenberg, T. et al. Lucky or clever? From changed expectations to attributions of responsibility. Cognition (2018).
Tuckute, G., Feather, J., Boebinger, D. & McDermott, J. H. Many but not all deep neural network audio models capture brain responses and exhibit correspondence between model stages and brain regions. PLOS Biology 21, e3002366 (2023).
Jara-Ettinger, J., Piantadosi, S., Spelke, E. S., Levy, R. & Gibson, E. Mastery of the logic of natural numbers is not the result of mastery of counting: Evidence from late counters. . Developmental Science (2016). doi:10.1111/desc.12459
Dasgupta, I. & Gershman, S. J. Memory as a Computational Resource. Trends in Cognitive Sciences 25, 240 - 251 (2021).
Gershman, S. J. & Burke, T. Mental control of uncertainty. Cognitive, Affective, & Behavioral Neuroscience 23, 465 - 475 (2022).
Zhou, L., Smith, K., Tenenbaum, J. B. & Gerstenberg, T. Mental Jenga: A counterfactual simulation model of causal judgments about physical support. PsyArXiv (2022). at <https://psyarxiv.com/4a5uh>
Kool, W. & Botvinick, M. Mental labour. Nature Human Behaviour 2, 899 - 908 (2018).
Wang, J., Tao, A., Anderson, W. S., Madsen, J. R. & Kreiman, G. Mesoscopic physiological interactions in the human brain reveal small-world properties. Cell Reports 36, 109585 (2021).
Allen, K. et al. Meta-strategy learning in physical problem solving: the effect of embodied experience. bioRxiv (2021).PDF icon 2021.07.08.451333v2.full_.pdf (3.05 MB)
Ullman, T. D., Spelke, E. S., Battaglia, P. & Tenenbaum, J. B. Mind Games: Game Engines as an Architecture for Intuitive Physics. Trends in Cognitive Science 21, 649 - 665 (2017).PDF icon Preprint submitted to Trends in Cognitive Science (17.64 MB)
Misra, P., Marconi, A., Peterson, M. F. & Kreiman, G. Minimal memory for details in real life events. Scientific Reports 8, (2018).
McCoy, J. P. & Ullman, T. D. A Minimal Turing Test. Journal of Experimental Social Psychology 79, 1 - 8 (2018).
Ben-Yosef, G., Kreiman, G. & Ullman, S. Minimal videos: Trade-off between spatial and temporal information in human and machine vision. Cognition (2020). doi:10.1016/j.cognition.2020.104263
Aghajan, Z. M., Kreiman, G. & Fried, I. Minute-scale periodicity of neuronal firing in the human entorhinal cortex. Cell Reports 42, 113271 (2023).PDF icon 1-s2.0-S2211124723012834-main.pdf (5.33 MB)
Ullman, S., Dorfman, N. & Harari, D. A model for discovering ‘containment’ relations. Cognition 183, 67 - 81 (2019).
Feather, J., Leclerc, G., Mądry, A. & McDermott, J. H. Model metamers reveal divergent invariances between biological and artificial neural networks. Nature Neuroscience (2023). doi:10.1038/s41593-023-01442-0
Marciniak, K., Dicke, P. W. & Thier, P. Monkeys head-gaze following is fast, precise and not fully suppressible. Proc Biol Sci 282, 20151020 (2015).PDF icon Marciniak et al 2015 Proc R Soc B Monkeys head gaze following is fast precise and not fully suppressible.pdf (7.07 MB)
Magid, R. & Schulz, L. Moral alchemy: How love changes norms. Cognition 167, 135 -150 (2017).PDF icon Moral Alchemy_Magid&Schulz.pdf (627.46 KB)
Sosa, F. A., Ullman, T., Tenenbaum, J. B., Gershman, S. J. & Gerstenberg, T. Moral dynamics: Grounding moral judgment in intuitive physics and intuitive psychology. Cognition 217, 104890 (2021).
Marques, T., Schrimpf, M. & DiCarlo, J. J. Multi-scale hierarchical neural network models that bridge from single neurons in the primate primary visual cortex to object recognition behavior. bioRxiv (2021).PDF icon 2021.03.01.433495v2.full_.pdf (3.23 MB)
Tomov, M. S., Schulz, E. & Gershman, S. J. Multi-task reinforcement learning in humans. Nature Human Behaviour (2021). doi:10.1038/s41562-020-01035-y
The naive utility calculus: Computational principles underlying commonsense psychology. (2016).
Jara-Ettinger, J., Gweon, H., Schulz, L. & Tenenbaum, J. B. The naive utility calculus: computational principles underlying social cognition. Trends Cogn Sci. (2016). doi:10.1016/j.tics.2016.05.011

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