基本信息
浏览量:462

个人简介
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.
研究兴趣
论文共 144 篇作者统计合作学者相似作者
按年份排序按引用量排序主题筛选期刊级别筛选合作者筛选合作机构筛选
时间
引用量
主题
期刊级别
合作者
合作机构
Zador, Anthony,Escola, Sean,Richards, Blake,Ölveczky, Bence, Bengio, Yoshua, Boahen, Kwabena,Botvinick, Matthew,Chklovskii, Dmitri,Churchland, Anne,Clopath, Claudia,DiCarlo, James,Ganguli, Surya,
nature(2023)
Joel Dapello,Kohitij Kar,Martin Schrimpf, Robert Geary, Michael Ferguson,David D. Cox,James J. DiCarlo
ICLR 2023 (2022)
Alex abate, Elizabeth Mieczkowski, Meenakshi Khosla,James DiCarlo,Nancy Kanwisher, N Apurva Ratan Murty
Journal of Visionno. 14 (2022)
引用0浏览0引用
0
0
Aran Nayebi, Javier Sagastuy-Brena,Daniel M. Bear,Kohitij Kar,Jonas Kubilius,Surya Ganguli,David Sussillo,James J. DiCarlo,Daniel L. K. Yamins
bioRxiv (2022)
加载更多
作者统计
合作学者
合作机构
D-Core
- 合作者
- 学生
- 导师
数据免责声明
页面数据均来自互联网公开来源、合作出版商和通过AI技术自动分析结果,我们不对页面数据的有效性、准确性、正确性、可靠性、完整性和及时性做出任何承诺和保证。若有疑问,可以通过电子邮件方式联系我们:report@aminer.cn