Journal publications:

  • Jozwik, K.M.*, O'Keeffe*, J., Storrs*, K., Guo, W., Golan, T., Kriegeskorte, N. (2022) (*contributed equally)
    "Face dissimilarity judgements are predicted by representational distance in morphable and image-computable models"
    Proceedings of the National Academy of Sciences 119(27)e2115047119

  • Jozwik, K.M., Najarro, E., van den Bosch, JJF., Charest, I., Cichy*, RM., Kriegeskorte*, N. (2022) (*contributed equally)
    "Disentangling five dimensions of animacy in human brain and behaviour"
    Communications Biology 5, 1247

  • Jozwik, K.M. (2021)
    "What AI can learn from the biological brain"
    Science 372 (6544), 798-798

  • Adhya, D., Swarup, V., Nagy, R., Dutan, L., Shum, C., Valencia-Alarcón, E.P., Jozwik, K.M., Mendez, M.A., Horder, J., Loth, E., Nowosiad, P., Lee, I., Skuse, D., Flinter, F.A., Murphy, D., McAlonan, G., Geschwind, D.H., Price, J., Carroll, J., Srivastava, D.P., Baron-Cohen, S. (2021)
    "Atypical neurogenesis in induced pluripotent stem cell (iPSC) from autistic individuals"
    Biological Psychiatry 89 (5), 486-496

  • Cichy, R. M., Kriegeskorte, N., Jozwik, K.M., van den Bosch, J.J.F. , Charest, I. (2019)
    "The spatiotemporal neural dynamics underlying perceived similarity for real-world objects"
    Neuroimage, 194, 12-24

  • Jozwik, K.M., Kriegeskorte, N., Storrs, K. R., Mur, M. (2017)
    “Deep convolutional neural networks outperform feature-based but not categorical models in explaining object similarity judgments” 
    Frontiers in Psychology 8(10):1726

  • Jozwik, K.M., Kriegeskorte N, Mur M (2016)
    “Visual features as stepping stones toward semantics: Explaining object similarity in IT and perception with non-negative least squares” 
    Neuropsychologia 83:201-26

  • Jozwik, K.M., Chernukhin I, Serandour AA, Nagarajan S, Carroll JS (2016)
    “FOXA1 directs H3K4 monomethylation at enhancers via recruitment of the methyltransferase MLL3” 
    Cell Reports 17(10):2715-2723

  • Jozwik, K.M., Carroll JS (2012)
    “Pioneer factors in hormone dependent cancers” 
    Nature Reviews Cancer 12(6):381-5

Peer-reviewed conference publications:

  • Jozwik, K.M., Lee, H., Kanwisher, N. and DiCarlo, J.J. (2019)
    "Are topographic deep convolutional neural networks better models of the ventral visual stream?"
    Conference on Cognitive Computational Neuroscience

  • Jozwik, K.M., Kriegeskorte, N., Cichy, R. M., Mur, M. (2018)
    “Deep convolutional neural networks, features, and categories perform similarly at explaining primate high-level visual representations”
    Conference on Cognitive Computational Neuroscience

  • Jozwik, K.M., Charest I., Kriegeskorte, N. Cichy, R. M., (2017)
    “Animacy dimensions ratings andapproach for decorrelating stimuli dimensions” 
    Conference on Cognitive Computational Neuroscience


  • Jozwik, K.M., Elias Najarro, E., Bosch, JJF., Charest, I., Kriegeskorte, N., and Cichy, R.M. (2021)
    "Disentangling dimensions of animacy in human brain and behaviour"

  • Jozwik, K.M., Kietzmann, T.C., Cichy, R.M., Kriegeskorte, N., Mur, M. (2021)
    "Deep neural networks and visuo-semantic models explain complementary components of human ventral-stream representational dynamics"

  • Jozwik, K.M., Schrimpf, M., Kanwisher, N. and DiCarlo, J.J. (2019)
    "To find better neural network models of human vision, find better neural network models of primate vision"

  • Jozwik, K.M., Lee, M., Marques, T., Schrimpf, M., Bashivan, P. (2019)
    "Large-scale hyperparameter search for predicting human brain responses in the Algonauts challenge"