Publications

Josephs, E. L.; Hebart, M. N.; Konkle, T.: Dimensions underlying human understanding of the reachable world. Cognition 234, 105368 (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), pp. 484 - 500 (2023)

Le, L.; Ambrogioni, L.; Seeliger, K.; Güçlütürk, Y.; van Gerven, M.; Güçlü, U.: Brain2Pix: Fully convolutional naturalistic video frame reconstruction from brain activity. Frontiers in Neuroscience 16, 940972 (2022)

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)

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)

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), pp. 1173 - 1185 (2020)

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

Hansen, H.; Hebart, M. N.: Semantic features of object concepts generated with GPT-3. In: Proceedings of the Annual Meeting of the Cognitive Science Society, Vol. 44. (2022)

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)

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, June 19, 2020 - June 24, 2020. Scholar One, Inc., Charlottesville, VA (2020)

Hebart, M. N.: Revealing the core dimensions underlying mental representations of objects. CRC Workshop on Cardinal Mechanisms of Perception, Rauischholzhausen Castle, Germany (2022)

Hansen, H.; Hebart, M. N.: Semantic features of object concepts generated with GPT-3. 44th Annual Conference of the Cognitive Science Society (CogSci), Toronto, ON, Canada (2022)

Hebart, M. N.: Core representational dimensions of visually-perceived objects. Mind Brain Annual Meeting (SAMBA), Salzburg, Austria (2022)

Hebart, M. N.: The THINGS initiative: A global initiative of researchers for representative sampling of objects in brains, behavior, and computational models. Annual Meeting of the Vision Science Society (VSS) , St. Pete Beach, FL, USA (2022)

Hebart, M. N.; Perkuhn, J.; Kaniuth, P.: Efficiently-generated object similarity scores predicted from human feature ratings and deep neural network activations. Annual Meeting of the Vision Science Society (VSS), St. Pete Beach, FL, USA (2022)