muton
(2022-11-30 23:19):
#paper https://science.org/doi/10.1126/ sciadv.abm3829 Science Advances,2022,Higher-dimensional neural representations predict better episodic memory
情景记忆使人类能够编码并随后生动地检索有关我们丰富经历的信息,但怎样的神经表征可以支持这一心理能力?作者让被试学习人脸图片和词语的配对,使用表征维度的分析方法,对由脑成像得到的神经相似性矩阵进行PCA分析,得到每个主成分的eigenvalue,通过对eigenvalue的处理得到RD(representational dimensionality)值,来分析面孔选择区和其他相关脑区的差异,结果发现,面孔选择区保留了高维表征,重要的是,RD值越大,记忆效应就越好。本文提供了新的神经表征分析方法。
Higher-dimensional neural representations predict better episodic memory
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Abstract:
Episodic memory enables humans to encode and later vividly retrieve information about our rich experiences, yet the neural representations that support this mental capacity are poorly understood. Using a large fMRI dataset ( = 468) of face-name associative memory tasks and principal component analysis to examine neural representational dimensionality (RD), we found that the human brain maintained a high-dimensional representation of faces through hierarchical representation within and beyond the face-selective regions. Critically, greater RD was associated with better subsequent memory performance both within and across participants, and this association was specific to episodic memory but not general cognitive abilities. Furthermore, the frontoparietal activities could suppress the shared low-dimensional fluctuations and reduce the correlations of local neural responses, resulting in greater RD. RD was not associated with the degree of item-specific pattern similarity, and it made complementary contributions to episodic memory. These results provide a mechanistic understanding of the role of RD in supporting accurate episodic memory.
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