Publikationen von Martin N. Hebart

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)

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 (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)

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)

Singer, J. J. D.; Cichy, R. M.; Hebart, M. N.: The spatiotemporal neural dynamics of object recognition for natural images and line drawings. The Journal of Neuroscience 43 (3), S. 484 - 500 (2023)

Kaniuth, P.; Hebart, M. N.: Feature-reweighted representational similarity analysis: A method for improving the fit between computational models, brains, and behavior. NeuroImage 257, 119294 (2022)

Singer, J.; Seeliger, K.; Kietzmann, T. C.; Hebart, M. N.: From photos to sketches-how humans and deep neural networks process objects across different levels of visual abstraction. Journal of Vision 22 (2), 4 (2022)

Grootswagers, T.; Zhou, I.; Robinson, A. K.; Hebart, M. N.; Carlson, T. A.: Human EEG recordings for 1,854 concepts presented in rapid serial visual presentation streams. Scientific Data 9 (1), 3 (2022)

Muttenthaler, L.; Hebart, M. N.: THINGSvision: A Python toolbox for streamlining the extraction of activations from deep neural networks. Frontiers in Neuroinformatics 15, 679838 (2021)

Liu, P.; Chrysidou, A.; Doehler, J.; Hebart, M. N.; Wolbers, T.; Kuehn, E.: The organizational principles of de-differentiated topographic maps in somatosensory cortex. eLife 10, e60090 (2021)

Hebart, M. N.; Zheng, C. Y.; Pereira, F.; Baker, C. I.: Revealing the multidimensional mental representations of natural objects underlying human similarity judgements. Nature Human Behaviour 4 (11), S. 1173 - 1185 (2020)

Hebart, M. N.; Schuck, N. W.: Current topics in computational cognitive neuroscience. Neuropsychologia 147, 107621 (2020)

Bönstrup, M.; Iturrate, I.; Hebart, M. N.; Censor, N.; Cohen, L. G.: Mechanisms of offline motor learning at a microscale of seconds in large-scale crowdsourced data. npj Science of Learning 5, 7 (2020)

Hebart, M. N.; Dickter, A. H.; Kidder, A.; Kwok, W. Y.; Corriveau, A.; Van Wicklin, C.; Baker, C. I.: THINGS: A database of 1,854 object concepts and more than 26,000 naturalistic object images. PLoS One 14 (10), e0223792 (2019)

Hebart, M. N.; Baker, C. I.: Deconstructing multivariate decoding for the study of brain function. NeuroImage 180 (Part A), S. 4 - 18 (2018)

Bankson, B. B.; Hebart, M. N.; Groen, I. I. A.; Baker, C. I.: The temporal evolution of conceptual object representations revealed through models of behavior, semantics and deep neural networks. NeuroImage 178, S. 172 - 182 (2018)

Hebart, M. N.; Bankson, B. B.; Harel, A.; Baker, C. I.; Cichy, R. M.: The representational dynamics of task and object processing in humans. eLife 7, e32816 (2018)

Görgen, K.; Hebart, M. N.; Allefeld, C.; Haynes, J.-D.: The same analysis approach: Practical protection against the pitfalls of novel neuroimaging analysis methods. NeuroImage 180 (Part A), S. 19 - 30 (2017)