Uncovering the core dimensions of visual object representations

Información del proyecto

COREDIM

Identificador del acuerdo de subvención: 101039712

DOI

10.3030/101039712

Fecha de la firma de la CE 7 Junio 2022

Fecha de inicio 1 Julio 2022

Fecha de finalización 30 Junio 2027

Financiado con arreglo a

• European Research Council (ERC)

Coste total

€ 1 500 000,00

Aportación de la UE

€ 1 500 000,00

Coordinado por

JUSTUS-LIEBIG-UNIVERSITAET GIESSEN
Germany

CORDIS proporciona enlaces a los documentos públicos y las publicaciones de los proyectos de los programas marco HORIZONTE.

Los enlaces a los documentos y las publicaciones de los proyectos del Séptimo Programa Marco, así como los enlaces a algunos tipos de resultados específicos, como conjuntos de datos y «software», se obtienen dinámicamente de OpenAIRE .

Publicaciones

Other (6)

The scope and limits of fine-grained image and category information in the ventral visual pathway

Autores: Markus W. Badwal, Johanna Bergmann, Johannes Roth, Christian F. Doeller, Martin N. Hebart
Publicado en: NO JOURNAL TITLE, 2024
Editor: Cold Spring Harbor Laboratory
DOI: 10.1101/2024.08.04.606507

Dimensions underlying the representational alignment of deep neural networks with humans

Autores: Florian P. Mahner, Lukas Muttenthaler, Umut Güçlü, Martin N. Hebart
Publicado en: Arxiv, 2024
Editor: Cold Spring Harbor Library
DOI: 10.48550/arXiv.2406.19087

“Identifying and characterizing scene representations relevant for categorization behavior”

Autores: Johannes J.D. Singer, Agnessa Karapetian, Martin N. Hebart, Radoslaw M. Cichy
Publicado en: 2023
Editor: Cold Spring Harbor Laboratory
DOI: 10.1101/2023.08.17.553708

Core dimensions of human material perception

Autores: Filipp Schmidt, Martin N Hebart, Alexandra C. Schmid, Roland Fleming
Publicado en: NO JOURNAL TITLE, 2022
Editor: Center for Open Science
DOI: 10.31234/osf.io/jz8ks

A high-throughput approach for the efficient prediction of perceived similarity of natural objects

Autores: Philipp Kaniuth, Florian P. Mahner, Jonas Perkuhn, Martin N. Hebart
Publicado en: NO JOURNAL TITLE, 2024
Editor: Cold Spring Harbor Laboratory
DOI: 10.1101/2024.06.28.601184

Dynamic representation of multidimensional object properties in the human brain

Autores: Lina Teichmann, Martin N. Hebart, Chris I. Baker
Publicado en: NO JOURNAL TITLE, 2023
Editor: Cold Spring Harbor Laboratory
DOI: 10.1101/2023.09.08.556679

Peer reviewed articles (14)

What comparing deep neural networks can teach us about human vision

Autores: Katja Seeliger, Martin N. Hebart
Publicado en: Nature Machine Intelligence, Edición 6, 2024, ISSN 2522-5839
Editor: Nature Springer
DOI: 10.1038/s42256-024-00789-8

How modular are modules in visual cortex?

Autores: Martin N Hebart
Publicado en: Brain, Edición 148, 2025, ISSN 0006-8950
Editor: Oxford University Press (OUP)
DOI: 10.1093/BRAIN/AWAF100

Core dimensions of human material perception

Autores: Filipp Schmidt, Martin N. Hebart, Alexandra C. Schmid, Roland W. Fleming
Publicado en: Proceedings of the National Academy of Sciences, Edición 122, 2025, ISSN 0027-8424
Editor: Proceedings of the National Academy of Sciences
DOI: 10.1073/PNAS.2417202122

THINGS-data, a multimodal collection of large-scale datasets for investigating object representations in human brain and behavior

Autores: Martin N Hebart, Oliver Contier, Lina Teichmann, Adam H Rockter, Charles Y Zheng, Alexis Kidder, Anna Corriveau, Maryam Vaziri-Pashkam, Chris I Baker
Publicado en: eLife, Edición 12, 2023, ISSN 2050-084X
Editor: eLife Sciences Publications, Ltd
DOI: 10.7554/eLife.82580

THINGSplus: New Norms and Metadata for the THINGS Database of 1,854 Object Concepts and 26,107 Natural Object Images

Autores: Laura Mai Stoinski; Jonas Perkuhn; Martin N Hebart
Publicado en: Behavior Research Methods, 2023, ISSN 1554-3528
Editor: Springer
DOI: 10.31234/osf.io/exu9f

Dimensions underlying the representational alignment of deep neural networks with humans

Autores: Florian P. Mahner, Lukas Muttenthaler, Umut Güçlü, Martin N. Hebart
Publicado en: Nature Machine Intelligence, Edición 7, 2025, ISSN 2522-5839
Editor: Nature Springer
DOI: 10.1038/S42256-025-01041-7

Ten principles for reliable, efficient, and adaptable coding in psychology and cognitive neuroscience

Autores: Johannes Roth; Yunyan Duan; Florian P. Mahner; Philipp Kaniuth; Thomas S. A. Wallis; Martin N. Hebart
Publicado en: Communications Psychology, 2025, ISSN 2731-9121
Editor: Nature Springer
DOI: 10.1038/S44271-025-00236-3

The Spatiotemporal Neural Dynamics of Object Recognition for Natural Images and Line Drawings

Autores: Johannes J.D. Singer; Radoslaw M. Cichy; Martin N. Hebart
Publicado en: The Journal of Neuroscience, 2022, ISSN 1529-2401
Editor: Society for Neuroscience
DOI: 10.1101/2022.08.12.503484

The features underlying the memorability of objects

Autores: Max A. Kramer, Martin N. Hebart, Chris I. Baker, Wilma A. Bainbridge
Publicado en: Science Advances, Edición 9, 2024, ISSN 2375-2548
Editor: American Association for the Advancement of Science (AAAS)
DOI: 10.1126/sciadv.add2981

Distributed representations of behavior-derived object dimensions in the human visual system

Autores: Oliver Contier; Chris I. Baker; Martin N. Hebart
Publicado en: Nature Human Behaviour, 2023, ISSN 2397-3374
Editor: Nature Springer
DOI: 10.1038/S41562-024-01980-Y

The Scope and Limits of Fine-Grained Image and Category Information in the Ventral Visual Pathway

Autores: Markus W. Badwal, Johanna Bergmann, Johannes H.R. Roth, Christian F. Doeller, Martin N. Hebart
Publicado en: The Journal of Neuroscience, Edición 45, 2025, ISSN 0270-6474
Editor: Society for Neuroscience
DOI: 10.1523/JNEUROSCI.0936-24.2024

Identifying and characterizing scene representations relevant for categorization behavior

Autores: Johannes J.D. Singer, Agnessa Karapetian, Martin N. Hebart, Radoslaw M. Cichy
Publicado en: Imaging Neuroscience, Edición 3, 2025, ISSN 2837-6056
Editor: MIT Press
DOI: 10.1162/IMAG_A_00449

Distributed representations of behaviour-derived object dimensions in the human visual system

Autores: Oliver Contier, Chris I. Baker, Martin N. Hebart
Publicado en: Nature Human Behaviour, 2024, ISSN 2397-3374
Editor: Springer Science and Business Media LLC
DOI: 10.1038/s41562-024-01980-y

A high-throughput approach for the efficient prediction of perceived similarity of natural objects

Autores: Philipp Kaniuth; Florian P. Mahner; Jonas Perkuhn; Martin N. Hebart
Publicado en: eLife, 2025, ISSN 2050-084X
Editor: eLife Sciences Publications
DOI: 10.1101/2024.06.28.601184