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  • 标题:Divisive normalization unifies disparate response signatures throughout the human visual hierarchy
  • 本地全文:下载
  • 作者:Marco Aqil ; Tomas Knapen ; Serge O. Dumoulin
  • 期刊名称:Proceedings of the National Academy of Sciences
  • 印刷版ISSN:0027-8424
  • 电子版ISSN:1091-6490
  • 出版年度:2021
  • 卷号:118
  • 期号:46
  • DOI:10.1073/pnas.2108713118
  • 语种:English
  • 出版社:The National Academy of Sciences of the United States of America
  • 摘要:Significance A canonical neural computation is a mathematical operation applied by the brain in a wide variety of contexts and capable of explaining and unifying seemingly unrelated neural and perceptual phenomena. Here, we use a combination of state-of-the-art experiments (ultra-high-field functional MRI) and mathematical methods (population receptive field [pRF
  • 关键词:population receptive fields; divisive normalization; human visual cortex; information-encoding models; ultra-high-field fMRI
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