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Super-resolution fluorescence microscopy (SRFM) provides a better resolution than conventional fluorescence microscopy by reducing the point spread function (PSF). PSF is the light intensity distribution from a point that causes it to appear blurred. Due to PSF, each fluorescing point appears bigger than its actual size, and it is the PSF interference of nearby fluorophores that causes the blurred image. Various approaches to achieving higher resolution through SRFM have recently been...
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在不连续的闪光抑制下,解码动态的面孔和场景而无意识.

Yen-Ju Feng1, Shao-Min Hung2,3, Po-Jang Hsieh4

  • 1Department of Psychology, National Taiwan University, Taipei, Taiwan, ROC. yenju0115@gmail.com.

Communications biology
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概括
此摘要是机器生成的。

即使面孔对有意识的意识是不可见的,大脑也会深入地处理它们. 先进的方法揭示了脑后部和部区域的无意识面部识别,特别是状面部区域 (FFA) 和脑后面部区域 (OFA).

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科学领域:

  • 感知科学 感知科学
  • 认知神经科学是一种认知神经科学.
  • 神经成像是一种神经成像.

背景情况:

  • 无意识处理的程度仍然是感知科学中的一个关键辩论.
  • 了解无意识感知的神经相关性对于认知理论至关重要.

研究的目的:

  • 为了研究无意识的面部处理的神经基础.
  • 完善用于检测微妙无意识信号的实验范式.
  • 探索视觉处理的深度,以寻找看不见的刺激.

主要方法:

  • 利用改进的范式,刺激和分析来探索无意识的面部处理.
  • 采用单变量和多变量分析,包括全脑分类和兴趣区域 (ROI) 分析.
  • 使用整眼抑制来使面孔对有意识的意识无形 (n=43).

主要成果:

  • 有意识的面孔显示出比有意识的场景更广泛的单变量激活.
  • 对于看不见的面孔/场景,没有统一的结果.
  • 多变量分类成功地将看不见的面孔与部部区域的场景区分开来.
  • 双边的FFA和OFA从场景中区分了动态的隐形面孔.

结论:

  • 隐形面孔在腹部视觉流中经历深度处理.
  • 优化实验设计和分析对于揭示无意识的神经信号至关重要.
  • 这些发现有助于理解意识感知的边界.