Cargando…
Unsupervised deep learning identifies semantic disentanglement in single inferotemporal face patch neurons
In order to better understand how the brain perceives faces, it is important to know what objective drives learning in the ventral visual stream. To answer this question, we model neural responses to faces in the macaque inferotemporal (IT) cortex with a deep self-supervised generative model, β-VAE,...
Autores principales: | Higgins, Irina, Chang, Le, Langston, Victoria, Hassabis, Demis, Summerfield, Christopher, Tsao, Doris, Botvinick, Matthew |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8578601/ https://www.ncbi.nlm.nih.gov/pubmed/34753913 http://dx.doi.org/10.1038/s41467-021-26751-5 |
Ejemplares similares
-
Anatomical correlates of face patches in macaque inferotemporal cortex
por: Arcaro, Michael J., et al.
Publicado: (2020) -
Disentangling the latent space of GANs for semantic face editing
por: Niu, Yongjie, et al.
Publicado: (2023) -
Shape Similarity, Better than Semantic Membership, Accounts for the Structure of Visual Object Representations in a Population of Monkey Inferotemporal Neurons
por: Baldassi, Carlo, et al.
Publicado: (2013) -
Cortical midline involvement in autobiographical memory
por: Summerfield, Jennifer J., et al.
Publicado: (2009) -
Differential engagement of brain regions within a ‘core’ network during scene construction
por: Summerfield, Jennifer J., et al.
Publicado: (2010)