Publications

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)

Seeliger, K.; Ambrogioni, L.; Güçlütürk, Y.; van den Bulk, L. M.; Güçlü, U.; van Gerven, M. A. J.: End-to-end neural system identification with neural information flow. PLoS Computational Biology 17 (2), e1008558 (2021)

Schmidt, F.; Hebart, M. N.; Schmid, A.; Fleming, R. W.: The mental representation of materials distilled from >1.5 million similarity judgements. In Journal of Vision, 21, 1981. Scholar One, Inc., Charlottesville, VA (2021)

Seeliger, K.; Roth, J.; Schmid, T.; Hebart, M. N.: Synthesizing preferred stimuli for individual voxels in the human visual system. In Journal of Vision, 21, 2311. Scholar One, Inc., Charlottesville, VA (2021)

Muttenthaler, L.: Interpretable object dimensions in humans and deep convolutional neural networks. Meeting, TU Berlin, Germany (2021)

Seeliger, K.: Convolutional neural networks and visual information processing. Osnabrück Search Symposium Computational Neuroscience , Virtual (2021)

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)

Hebart, M. N.: Revealing interpretable representations in artificial and biological vision. Japanese Meeting for Human Brain Imaging, National Institute for Physiological Sciences, Okazaki, Japan (2021)

Seeliger, K.: A large single-participant fMRI dataset for probing brain responses to naturalistic stimuli in space and time. Symposium on Naturalistic Stimuli in Cognitive Neuroscience, Virtual (2021)

Hebart, M. N.: Revealing the similarities and differences between object representations in humans and DNNs. Tagung experimentell arbeitender Psychologen (TeaP), Ulm, Germany (2021)

Contier, O.; Hebart, M. N.; Dickter, A. H.; Teichmann, L.; Kidder, A.; Corriveau, A.; Zheng, C.; Vaziri-Pashkam, M.; Baker, C. I.: THINGS-fMRI/MEG: A densely sampled multimodal neuroimaging dataset of brain responses to a broad range of natural object images. Society for Neuroscience 50th Annual Meeting, Virtual (2021)

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)

Contier, O.; Hebart, M. N.; Dickter, A. H.; Teichmann, L.; Kidder, A.; Corriveau, A.; Zheng, C.; Vaziri-Pashkam, M.; Baker, C. I.: THINGS-fMRI/MEG: A large-scale multimodal neuroimaging dataset of responses to natural object images. Vision Sciences Society Annual Meeting (V-VSS), Virtual (2021)

Seeliger, K.: Synthesizing preferred stimuli for individual voxels in the human visual system. Vision Sciences Society (V-VSS), Virtual (2021)

Roth, J.; Seeliger, K.; Schmid, T.; Hebart, M. N.: Preferred stimuli for individual voxels in the human visual system. 2021 Computational and Systems Neuroscience (Cosyne), Virtual (2021)

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)

Josephs, E. L.; Hebart, M. N.; Konkle, T.: Emergent dimensions underlying human understanding of the reachable world. (2021)

Seeliger, K.; Güçlü, U.; Le, L.; Güçlütürk, Y.; van Gerven, M.: Brain2Pix: Fully convolutional naturalistic video reconstruction from brain activity. (2021)