Publications of Martin N. Hebart

Contier, O., Fujimori, S., Seeliger, K., Ratan Murty, N. A., & Hebart, M. N. Revealing interpretable object dimensions from a high-throughput model of the fusiform face area. Poster presented at the 23rd Annual Meeting of the Vision Science Society (VSS), St. Pete Beach, FL, USA. Retrieved from http://hdl.handle.net/21.11116/0000-000E-7604-9

St-Laurent, M., Pinsard, B., Contier, O., Seeliger, K., Borghesani, V., Boyle, J., … Hebart, M. N. Cneuromod-things: A large-scale fMRI dataset for task-and data-driven assessment of object representation and visual memory recognition in the human brain. Poster presented at the 23rd Annual Meeting of the Vision Science Society (VSS), St. Pete Beach, FL, USA. Retrieved from http://hdl.handle.net/21.11116/0000-000E-75DE-5

Roth, J., Miyawaki, Y., & Hebart, M. N. Assessing the feasibility of high stimulus presentation rates for contrasting conditions in functional MRI studies. Poster presented at the 23rd Annual Meeting of the Vision Science Society (VSS), St. Pete Beach, FL, USA. Retrieved from http://hdl.handle.net/21.11116/0000-000E-7600-D

Mahner, F., Seeliger, K., Umut, G., & Hebart, M. N. Learning cortical magnification with brain-optimized convolutional neural networks. Poster presented at the Conference on Cognitive Computational Neuroscience, San Francisco, CA, USA. Retrieved from http://hdl.handle.net/21.11116/0000-000B-1E5A-0

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. Poster presented at the 47. Jahrestagung Psychologie und Gehirn 2022, Freiburg, Germany. Retrieved from http://hdl.handle.net/21.11116/0000-000B-1B3C-5

Kaniuth, P., & Hebart, M. N. Object similarities can be efficiently generated using human ratings and neural network predictions. Poster presented at the 11th IMPRS NeuroCom Summer School, Leipzig, Germany. Retrieved from http://hdl.handle.net/21.11116/0000-000A-E2EC-D

Kaniuth, P., Perkuhn, J., & Hebart, M. N. Object similarities can be efficiently generated using human ratings and neural network predictions. Poster presented at the 28th Annual Meeting of the Organization for Human Brain Mapping (OHBM), Glasgow, United Kingdom. Retrieved from http://hdl.handle.net/21.11116/0000-000A-E2F0-7

Hansen, H., & Hebart, M. N. Automatic generation of semantic feature norms of objects using GPT-3. Poster presented at the Annual Meeting of the Vision Science Society (VSS), St. Pete Beach, FL, USA. Retrieved from http://hdl.handle.net/21.11116/0000-000B-A7F3-6

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. Poster presented at the Vision Science Society Congress, St. Pete Beach, FL, USA. Retrieved from http://hdl.handle.net/21.11116/0000-000B-1EF1-4

Contier, O., Dickter, A. H., Teichmann , L., & Hebart, M. N. THINGS-fMRI/MEG: A large-scale multimodal neuroimaging dataset of responses to natural object images. Poster presented at the Vision Sciences Society Annual Meeting (V-VSS), Virtual. Retrieved from http://hdl.handle.net/21.11116/0000-000B-3178-7

Contier, O., & Hebart, M. N. Distributed representation of behaviorally-relevant object dimensions in the human brain. Poster presented at the Vision Sciences Society Annual Meeting (VSS), St. Pete Beach, FL, USA. Retrieved from https://www.researchgate.net/publication/335962396_Revealing_the_behaviorally-relevant_dimensions_underlying_mental_representations_of_objects

Contier, O., Hebart, M. N., Dickter, A. H., Teichmann, L., Kidder, A., Corriveau, A., … Baker, C. I. THINGS-fMRI/MEG: A densely sampled multimodal neuroimaging dataset of brain responses to a broad range of natural object images. Poster presented at the Society for Neuroscience 50th Annual Meeting, Virtual. Retrieved from http://hdl.handle.net/21.11116/0000-000B-A7CD-2

Kaniuth, P., & Hebart, M. N. Feature-reweighted RSA: A general purpose method for increasing the fit between vision models and brain data. Poster presented at the 10th IMPRS NeuroCom Summer School, Virtual. Retrieved from http://hdl.handle.net/21.11116/0000-000A-E2EA-F

Contier, O., Hebart, M. N., Dickter, A. H., Teichmann, L., Kidder, A., Corriveau, A., … Baker, C. I. THINGS-fMRI/MEG: A large-scale multimodal neuroimaging dataset of responses to natural object images. Poster presented at the Vision Sciences Society Annual Meeting (V-VSS), Virtual. Retrieved from http://hdl.handle.net/21.11116/0000-000B-A7E4-7

Roth, J., Seeliger, K., Schmid, T., & Hebart, M. N. Preferred stimuli for individual voxels in the human visual system. Poster presented at the 2021 Computational and Systems Neuroscience (Cosyne), Virtual. Retrieved from http://hdl.handle.net/21.11116/0000-000B-B680-6

Kaniuth, P., & Hebart, M. N. Feature-reweighted RSA: A general purpose method for increasing the fit between vision models and brain data? Poster presented at the Society for Neuroscience Global Connectome, Virtual. Retrieved from http://hdl.handle.net/21.11116/0000-000A-E2F4-3

Singer, J., Seeliger, K., & Hebart, M. N. The representation of object drawings and sketches in deep convolutional neural networks. Poster presented at the NeurIPS Workshop SVRHM, Virtual. Retrieved from http://hdl.handle.net/21.11116/0000-000B-3686-1

Kaniuth, P., & Hebart, M. N. Tuned representational similarity analysis: Improving the fit between computational models of vision and brain data. Poster presented at the Vision Sciences Society Annual Meeting 2020, Virtual. Retrieved from http://hdl.handle.net/21.11116/0000-000A-E2EE-B

Teichmann, L., Hebart, M. N., & Baker, C. I. (2023, September 11). Multidimensional object properties are dynamically represented in the human brain. BioRxiv. doi:10.1101/2023.09.08.556679

Contier, O., Baker, C. I., & Hebart, M. N. (2023, August 24). Distributed representations of behaviorally relevant object dimensions in the human visual system. BioRxiv. doi:10.1101/2023.08.23.553812