Publications

Roth, J.; Duan, Y.; Mahner, F.; Kaniuth, P.; Wallis, T. S. A.; Hebart, M. N.: Ten principles for reliable, efficient, and adaptable coding in psychology and cognitive neuroscience. Communications Psychology 3 (1), 62 (2025)

Hebart, M. N.: How modular are modules in visual cortex? Brain (2025)

Schmidt, F.; Hebart, M. N.; Schmid, A. C.; Fleming, R. W.: Core dimensions of human material perception. Proceedings of the National Academy of Sciences of the United States of America 122 (10), e2417202122 (2025)

Badwal, M. W.; Bergmann, J.; Roth, J.; Doeller, C. F.; Hebart, M. N.: The scope and limits of fine-grained image and category information in the ventral visual pathway. The Journal of Neuroscience 45 (3), e0936242024 (2025)

van Bree, S.; Levenstein, D.; Krause, M. R.; Voytek, B.; Gao, R.: Processes and measurements: A framework for understanding neural oscillations in field potentials. Trends in Cognitive Sciences (2025)

Singer, J.; Karapetian, A.; Hebart, M. N.; Cichy, R. M.: Identifying and characterizing scene representations relevant for categorization behavior. Imaging Neuroscience 3, imag_a_00449 (2025)

Contier, O.; Baker, C. I.; Hebart, M. N.: Distributed representations of behaviour-derived object dimensions in the human visual system. Nature Human Behaviour 8 (11), pp. 2179 - 2193 (2024)

van Dyck, L.; Bremmer, F.; Dobs, K.: Artificial intelligence meets body sense: Task-driven neural networks reveal computational principles of the proprioceptive pathway. Signal Transduction and Targeted Therapy 9 (1), 171 (2024)

van Bree, S.: Why the neural ingredients for a language of thought are not like spatial cells (commentary on Kazanina & Poeppel, 2023). European Journal of Neuroscience 59 (10), pp. 2552 - 2555 (2024)

Stoinski, L. M.; Perkuhn, J.; Hebart, M. N.: THINGSplus: New norms and metadata for the THINGS database of 1854 object concepts and 26,107 natural object images. Behavior Research Methods 56 (3), pp. 1583 - 1603 (2024)

Seeliger, K.; Hebart, M. N.: What comparing deep neural networks can teach us about human vision. Nature Machine Intelligence 6, pp. 122 - 123 (2024)

Zheng, X. Y.; Hebart, M. N.; Grill, F.; Dolan, R. J.; Doeller, C. F.; Cools, R.; Garvert, M.: Parallel cognitive maps for multiple knowledge structures in the hippocampal formation. Cerebral Cortex 34 (2), bhad485 (2024)

Golan, T.; Taylor, J.; Schütt, H.; Peters, B.; Sommers, R. P.; Seeliger, K.; Doerig, A.; Linton, P.; Konkle, T.; van Gerven, M. et al.; Kording, K.; Richards, B.; Kietzmann, T. C.; Lindsay, G. W.; Kriegeskorte, N.: Deep neural networks are not a single hypothesis but a language for expressing computational hypotheses. Behavioral and Brain Sciences 46, e392 (2023)

Kalyani, A.; Contier, O.; Klemm, L.; Azañon, E.; Schreiber, S.; Speck, O.; Reichert, C.; Kuehn, E.: Reduced dimension stimulus decoding and column-based modeling reveal architectural differences of primary somatosensory finger maps between younger and older adults. NeuroImage 283, 120430 (2023)

Doerig, A.; Sommers, R. P.; Seeliger, K.; Richards, B.; Ismael, J.; Lindsay, G. W.; Kording, K. P.; Konkle, T.; van Gerven, M. A. J.; Kriegeskorte, N. et al.; Kietzmann, T. C.: The neuroconnectionist research programme. Nature Reviews Neuroscience 24 (7), pp. 431 - 450 (2023)

Josephs, E. L.; Hebart, M. N.; Konkle, T.: Dimensions underlying human understanding of the reachable world. Cognition 234, 105368 (2023)

Kramer, M. A.; Hebart, M. N.; Baker, C. I.; Bainbridge, W. A.: The features underlying the memorability of objects. Science Advances 9 (17), eadd2981 (2023)

Hebart, M. N.; Contier, O.; Teichmann, L.; Rockter, A. H.; Zheng, C. Y.; Kidder, A.; Corriveau, A.; Vaziri-Pashkam, M.; Baker, C. I.: THINGS-data, a multimodal collection of large-scale datasets for investigating object representations in human brain and behavior. eLife 12, e82580 (2023)

Dima, D. C.; Hebart, M. N.; Isik, L.: A data-driven investigation of human action representations. Scientific Reports 13 (1), 5171 (2023)

Borghesani, V.; Armoza, J.; Hebart, M. N.; Bellec, P.; Brambati, S. M.: The Three Terms Task - An open benchmark to compare human and artificial semantic representations. Scientific Data 10 (1), 117 (2023)