Publications of Martin N. Hebart

Journal Article (39)

2018
Journal Article
Hebart, M. N., Bankson, B. B., Harel, A., Baker, C. I., & Cichy, R. M. (2018). The representational dynamics of task and object processing in humans. ELife, 7. doi:10.7554/eLife.32816
2017
Journal Article
Görgen, K., Hebart, M. N., Allefeld, C., & Haynes, J.-D. (2017). The same analysis approach: Practical protection against the pitfalls of novel neuroimaging analysis methods. NeuroImage, 180, 19–30.
2016
Journal Article
Guo, R., Böhmer, W., Hebart, M. N., Chien, S., Sommer, T., Obermayer, K., & Gläscher, J. (2016). Interaction of instrumental and goal-directed learning modulates prediction error representations in the ventral striatum. The Journal of Neuroscience, 36, 12650–12660.
Journal Article
Korjus, K., Hebart, M. N., & Vicente, R. (2016). An efficient data partitioning to improve classification performance while keeping parameters interpretable. PLoS One, 11. doi:10.1371/journal.pone.0161788
Journal Article
Hebart, M. N., & Baker, C. I. (2016). Facing up to stereotypes. Nature Neuroscience, 19, 763–764.
Journal Article
Guggenmos, M., Wilbertz, G., Hebart, M. N., & Sterzer, P. (2016). Mesolimbic confidence signals guide perceptual learning in the absence of external feedback. ELife, 5. doi:10.7554/eLife.13388
Journal Article
Hebart, M. N., Schriever, Y., Donner, T. H., & Haynes, J.-D. (2016). The relationship between perceptual decision variables and confidence in the human brain. Cerebral Cortex, 26, 118–130.
2015
Journal Article
Höhne, J., Bartz, D., Hebart, M. N., Müller, K.-R., & Blankertz, B. (2015). Analyzing neuroimaging data with subclasses: A shrinkage approach. NeuroImage, 124, 740–751.
Journal Article
Peth, J., Sommer, T., Hebart, M. N., Vossel, G., Büchel, C., & Gamer, M. (2015). Memory detection using fMRI: Does the encoding context matter? NeuroImage, 113, 164–174.
Journal Article
Christophel, T. B., Cichy, R. M., Hebart, M. N., & Haynes, J.-D. (2015). Parietal and early visual cortices encode working memory content across mental transformations. NeuroImage, 106, 198–206.
Journal Article
Hebart, M. N., Görgen, K., & Haynes, J.-D. (2015). The Decoding Toolbox (TDT): A versatile software package for multivariate analyses of functional imaging data. Frontiers in Neuroinformatics, 8. doi:10.3389/fninf.2014.00088
Journal Article
Hebart, M. N., & Gläscher, J. (2015). Serotonin and dopamine differentially affect appetitive and aversive general Pavlovian-to-instrumental transfer. Psychopharmacology, 232, 437–451 .
2014
Journal Article
Ritter, C., Hebart, M. N., Wolbers, T., & Bingel, U. (2014). Representation of spatial information in key areas of the descending pain modulatory system. The Journal of Neuroscience, 34, 4634–4639.
Journal Article
Stein, T., Seymour, K., Hebart, M. N., & Sterzer, P. (2014). Rapid fear detection relies on high spatial frequencies. Psychological Science, 25, 566–574 .
2012
Journal Article
Hebart, M. N., Donner, T. H., & Haynes, J.-D. (2012). Human visual and parietal cortex encode visual choices independent of motor plans. NeuroImage, 63, 1393–1403.
Journal Article
Christophel, T. B., Hebart, M. N., & Haynes, J.-D. (2012). Decoding the contents of visual short-term memory from human visual and parietal cortex. The Journal of Neuroscience, 32, 12983–12989.
Journal Article
Hebart, M. N., & Hesselmann, G. (2012). What visual information is processed in the human dorsal stream? The Journal of Neuroscience, 32, 8107–8109.
2011
Journal Article
Stein, T., Hebart, M. N., & Sterzer, P. (2011). Breaking continuous flash suppression: A new measure of unconscious processing during interocular suppression? Frontiers in Human Neuroscience, 5. doi:10.3389/fnhum.2011.00167
Journal Article
Hesselmann, G., Hebart, M. N., & Malach, R. (2011). Differential BOLD activity associated with subjective and objective reports during “Blindsight” in normal observers. The Journal of Neuroscience, 31, 12936–12944.

Conference Paper (2)

2023
Conference Paper
Hebart, M. N. (2023). Revealing interpretable object representations from human visual cortex and artificial neural networks. In Proceedings of the 11th International Winter Conference on Brain-Computer Interface (BCI). IEEE. doi:10.1109/BCI57258.2023.10078606
Go to Editor View