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将多维内容表示映射到情节性记忆的神经和行为表达的神经和行为表达
Yingying Wang1, Hongmi Lee2, Brice A Kuhl3
1Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou 310028, China; Department of Psychology, University of Oregon, Eugene, OR 97403, USA.
NeuroImage
|June 16, 2023
概括
研究人员使用语义编码模型和fMRI解码了丰富的内存内容. 从视觉和皮层的多维信息在观看和回忆过程中被重建,显示大脑活动反映了详细的情节性记忆.
科学领域:
- 神经科学是一个神经科学.
- 认知科学 认知科学
- 神经成像是一种神经成像.
背景情况:
- 情节性记忆是由分布式的神经活动模式所代表的.
- 以前的神经成像研究解码了简单的刺激特性,而不是丰富的记忆内容.
- 语义编码模型可以描述情节性记忆中的多维信息.
研究的目的:
- 构建和应用语义编码模型来重建情节性记忆内容.
- 研究多维记忆信息的神经表征.
- 为了比较视觉感知与记忆回忆期间的重建.
主要方法:
- 在四个人体中进行功能磁共振成像 (fMRI).
- 从fMRI数据开发语义编码模型的开发.
- 从观看和回忆期间的大脑活动中重建自然场景图像内容.
- 自然语言处理对口头回忆数据的应用.
主要成果:
- 多维语义信息在观看和回忆过程中从视觉和侧面皮层重建.
- 视觉皮层重建对于观看的图像更准确;侧面重建对于观看和回忆的图像是相似的.
- fMRI重建与受试者的口头描述相匹配,腹腔时皮层重建与自己的口头回忆更好地对齐.
- 编码跨主体传输的模型,使得使用独立主体数据重建记忆.
结论:
- 可以成功地重建多维和特异性记忆表示.
- 视觉皮层和侧面形区域对外部视觉信息和内部记忆生成具有不同的敏感性.
- 语义编码模型为解码复杂的内存内容提供了强大的工具.
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