Zobrazeno 1 - 10
of 406
pro vyhledávání: '"J DiCarlo"'
Autor:
Michael J Lee, James J DiCarlo
Publikováno v:
PLoS Computational Biology, Vol 19, Iss 12, p e1011713 (2023)
A core problem in visual object learning is using a finite number of images of a new object to accurately identify that object in future, novel images. One longstanding, conceptual hypothesis asserts that this core problem is solved by adult brains t
Externí odkaz:
https://doaj.org/article/52d81f82071e4fdaa1f0e3c77f882b08
Computational models of category-selective brain regions enable high-throughput tests of selectivity
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-14 (2021)
Distinct brain regions are claimed to respond selectively to faces, places and bodies, but what counts as a face, place or body is less well defined. Here we build computational models that accurately predict the response of these regions to novel im
Externí odkaz:
https://doaj.org/article/d9c8cf3114034a60be95c24ad337054d
Publikováno v:
Nature Communications, Vol 11, Iss 1, Pp 1-13 (2020)
The neuronal mechanisms underlying recognition of written letters remain unknown. Here, the authors show that populations of neurons in the ventral visual pathway of macaque monkeys encode orthographic stimuli, indicating that this pathway might be a
Externí odkaz:
https://doaj.org/article/8098ed3c4ead4645b8eeb6e4a7c4cf27
Publikováno v:
eLife, Vol 10 (2021)
Temporal continuity of object identity is a feature of natural visual input and is potentially exploited – in an unsupervised manner – by the ventral visual stream to build the neural representation in inferior temporal (IT) cortex. Here, we inve
Externí odkaz:
https://doaj.org/article/e16d6ccbf52f457ea330f26f7c2190f4
Autor:
Eshed Margalit, Hyodong Lee, Dawn Finzi, James J. DiCarlo, Kalanit Grill-Spector, Daniel L. K. Yamins
Publikováno v:
bioRxiv
A key feature of many cortical systems is functional organization: the arrangement of neurons with specific functional properties in characteristic spatial patterns across the cortical surface. However, the principles underlying the emergence and uti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::578405db44f209ce5f7577a262205e5a
https://europepmc.org/articles/PMC10245753/
https://europepmc.org/articles/PMC10245753/
Autor:
Michael J. Lee, James J. DiCarlo
How humans learn new visual objects is a longstanding scientific problem. Previous work has led to a diverse collection of models for how object learning may be accomplished, but a current limitation in the field is a lack of empirical benchmarks tha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d7bf2aca3136fb81f783abde7a970a16
https://doi.org/10.1101/2022.12.31.522402
https://doi.org/10.1101/2022.12.31.522402
Publikováno v:
eLife, Vol 7 (2018)
Ventral visual stream neural responses are dynamic, even for static image presentations. However, dynamical neural models of visual cortex are lacking as most progress has been made modeling static, time-averaged responses. Here, we studied populatio
Externí odkaz:
https://doaj.org/article/cbf9415b7ce7413b9a6b2e8e330013f2
Publikováno v:
Nature Methods. 18:1112-1116
Optogenetic methods have been widely used in rodent brains, but remain relatively under-developed for nonhuman primates such as rhesus macaques, an animal model with a large brain expressing sophisticated sensory, motor and cognitive behaviors. To ad
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::868ba4179827bbeac7b783fb836403d6
https://doi.org/10.1038/s41592-021-01238-9
https://doi.org/10.1038/s41592-021-01238-9
Autor:
Joel Dapello, Kohitij Kar, Martin Schrimpf, Robert Geary, Michael Ferguson, David D. Cox, James J. DiCarlo
While some state-of-the-art artificial neural network systems in computer vision are strikingly accurate models of the corresponding primate visual processing, there are still many discrepancies between these models and the behavior of primates on ob
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cc0440778e03951abe1952ac9fb9f30f
https://doi.org/10.1101/2022.07.01.498495
https://doi.org/10.1101/2022.07.01.498495
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