Publikationen

Zeitschriftenartikel (6)

2022
Zeitschriftenartikel
Kaniuth, P.; Hebart, M. N.: Feature-reweighted representational similarity analysis: A method for improving the fit between computational models, brains, and behavior. NeuroImage, 119294 (2022)
Zeitschriftenartikel
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)
2021
Zeitschriftenartikel
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)
Zeitschriftenartikel
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)
2020
Zeitschriftenartikel
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)
Zeitschriftenartikel
Hebart, M. N.; Schuck, N. W.: Current topics in computational cognitive neuroscience. Neuropsychologia 147, 107621 (2020)

Meeting Abstract (1)

2020
Meeting Abstract
Kaniuth, P.; Hebart, M. N.: Tuned representational similarity analysis: Improving the fit between computational models of vision and brain data. In Journal of Vision, 20, 1076. Vision Sciences Society Annual Meeting 2020, 19. Juni 2020 - 24. Juni 2020. Scholar One, Inc., Charlottesville, VA (2020)

Vortrag (2)

2022
Vortrag
Hebart, M. N.; Hannsen, H.: Semantic features of object concepts generated with GPT-3. 44th Annual Conference of the Cognitive Science Society (CogSci), Toronto, ON, Canada (2022)
2021
Vortrag
Hebart, M. N.: Revealing the multidimensional representation of objects in behavior and language. Meeting, Department of Experimental Psychology, University of Giessen, Germany (2021)

Poster (9)

2022
Poster
Hebart, M. N.; Seeliger, K.; Umut, G.; Mahner, F.: Learning cortical magnification with brain-optimized convolutional neural networks. Conference on Cognitive Computational Neuroscience, San Francisco, CA, USA (2022)
Poster
Hebart, M. N.; Contier, O.: Distributed representation of behaviorally-relevant object dimensions in the human brain. Vision Sciences Society Annual Meeting, St. Pete Beach, FL, USA (2022)
Poster
Hebart, M. N.; Contier, O.; Baker, C.I.; Teichmann, L.: The THINGS initiative: A global large-scale effort for the representative study of objects in brains, behavior, and computational models. 47. Jahrestagung Psychologie und Gehirn 2022, Freiburg, Germany (2022)
Poster
Kaniuth, P.; Hebart, M. N.: Object similarities can be efficiently generated using human ratings and neural network predictions. 11th IMPRS NeuroCom Summer School, Leipzig, Germany (2022)
Poster
Kaniuth, P.; Perkuhn, J.; Hebart, M. N.: Object similarities can be efficiently generated using human ratings and neural network predictions. 28th Annual Meeting of the Organization for Human Brain Mapping (OHBM), Glasgow, United Kingdom (2022)
Poster
Stoinski, L.; Perkuhn, J.; Hebart, M. N.: THINGS+: New norms and metadata for the THINGS database of 1,854 object concepts and 26,107 natural object images. Vision Science Society Congress, St. Pete Beach, FL, USA (2022)
2021
Poster
Kaniuth, P.; Hebart, M. N.: Feature-reweighted RSA: A general purpose method for increasing the fit between vision models and brain data. 10th IMPRS NeuroCom Summer School, Virtual (2021)
Poster
Kaniuth, P.; Hebart, M. N.: Feature-reweighted RSA: A general purpose method for increasing the fit between vision models and brain data? Society for Neuroscience Global Connectome, Virtual (2021)
2020
Poster
Kaniuth, P.; Hebart, M. N.: Tuned representational similarity analysis: Improving the fit between computational models of vision and brain data. Vision Sciences Society Annual Meeting 2020, Virtual (2020)

Preprint (1)

2022
Preprint
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 brain and behavior. (2022)
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