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DiCarlo’s research goal is to reverse engineer the brain mechanisms that underlie human visual intelligence. He and his collaborators have revealed how population image transformations carried out by a deep stack of interconnected neocortical brain areas — called the primate ventral visual stream — are effortlessly able to extract object identity from visual images. His team uses a combination of large-scale neurophysiology, brain imaging, direct neural perturbation methods, and machine learning methods to build and test neurally-mechanistic computational models of the ventral visual stream and its support of cognition and behavior. Such an engineering-based understanding is likely to lead to new artificial vision and artificial intelligence approaches, new brain-machine interfaces to restore or augment lost senses, and a new foundation to ameliorate disorders of the mind.
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论文共 188 篇作者统计合作学者相似作者
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Neuron (2024)
Benjamin Peters,James J DiCarlo, Todd Gureckis,Ralf Haefner,Leyla Isik, Joshua Tenenbaum,Talia Konkle,Thomas Naselaris, Kimberly Stachenfeld, Zenna Tavares, Doris Tsao,Ilker Yildirim,
ArXiv (2024)
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James J. DiCarlo,Daniel L. K. Yamins, Michael E. Ferguson,Evelina Fedorenko, Matthias Bethge,Tyler Bonnen,Martin Schrimpf
BEHAVIORAL AND BRAIN SCIENCES (2024)
Elizabeth Mieczkowski,Alex Abate, Willian De Faria,Kirsten Lydic,James J. DiCarlo,Nancy Kanwisher,N. Apurva Ratan Murty
Journal of Visionno. 9 (2023): 5788-5788
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Michael Kuoch, Chi-Ning Chou,Nikhil Parthasarathy,Joel Dapello,James J. DiCarlo,Haim Sompolinsky,SueYeon Chung
CoRR (2023)
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Nature communicationsno. 1 (2023): 1-7
James J. DiCarlo,Daniel L. K. Yamins, Michael E. Ferguson,Evelina Fedorenko,Matthias Bethge,Tyler Bonnen,Martin Schrimpf
BEHAVIORAL AND BRAIN SCIENCES (2023): e390-e390
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