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全球神经模式相似性作为分类和识别记忆的共同基础。

Global neural pattern similarity as a common basis for categorization and recognition memory.

机构信息

Department of Psychology, Texas Tech University, Lubbock, Texas 79409,

National Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, People's Republic of China, and.

出版信息

J Neurosci. 2014 May 28;34(22):7472-84. doi: 10.1523/JNEUROSCI.3376-13.2014.

Abstract

Familiarity, or memory strength, is a central construct in models of cognition. In previous categorization and long-term memory research, correlations have been found between psychological measures of memory strength and activation in the medial temporal lobes (MTLs), which suggests a common neural locus for memory strength. However, activation alone is insufficient for determining whether the same mechanisms underlie neural function across domains. Guided by mathematical models of categorization and long-term memory, we develop a theory and a method to test whether memory strength arises from the global similarity among neural representations. In human subjects, we find significant correlations between global similarity among activation patterns in the MTLs and both subsequent memory confidence in a recognition memory task and model-based measures of memory strength in a category learning task. Our work bridges formal cognitive theories and neuroscientific models by illustrating that the same global similarity computations underlie processing in multiple cognitive domains. Moreover, by establishing a link between neural similarity and psychological memory strength, our findings suggest that there may be an isomorphism between psychological and neural representational spaces that can be exploited to test cognitive theories at both the neural and behavioral levels.

摘要

熟悉度或记忆强度是认知模型的核心概念。在之前的分类和长期记忆研究中,已经发现心理记忆强度测量与内侧颞叶(MTL)中的激活之间存在相关性,这表明记忆强度存在共同的神经基础。然而,仅激活本身不足以确定跨领域的神经功能是否基于相同的机制。受分类和长期记忆的数学模型的指导,我们提出了一种理论和方法来检验记忆强度是否源于神经表示之间的全局相似性。在人类受试者中,我们发现 MTL 中激活模式之间的全局相似性与识别记忆任务中的后续记忆信心以及类别学习任务中的基于模型的记忆强度测量之间存在显著相关性。我们的工作通过说明相同的全局相似性计算在多个认知领域的处理中都起着基础作用,从而将形式认知理论和神经科学模型联系起来。此外,通过在神经相似性和心理记忆强度之间建立联系,我们的发现表明,心理和神经表示空间之间可能存在同构性,可以利用它在神经和行为层面上同时检验认知理论。

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本文引用的文献

1
2
Global matching models of recognition memory: How the models match the data.
Psychon Bull Rev. 1996 Mar;3(1):37-60. doi: 10.3758/BF03210740.
3
Measuring neural representations with fMRI: practices and pitfalls.
Ann N Y Acad Sci. 2013 Aug;1296:108-34. doi: 10.1111/nyas.12156. Epub 2013 Jun 5.
4
Confounds in multivariate pattern analysis: Theory and rule representation case study.
Neuroimage. 2013 Aug 15;77:157-65. doi: 10.1016/j.neuroimage.2013.03.039. Epub 2013 Apr 2.
5
Global similarity and pattern separation in the human medial temporal lobe predict subsequent memory.
J Neurosci. 2013 Mar 27;33(13):5466-74. doi: 10.1523/JNEUROSCI.4293-12.2013.
6
Quantifying the internal structure of categories using a neural typicality measure.
Cereb Cortex. 2014 Jul;24(7):1720-37. doi: 10.1093/cercor/bht014. Epub 2013 Feb 26.
8
Ten ironic rules for non-statistical reviewers.
Neuroimage. 2012 Jul 16;61(4):1300-10. doi: 10.1016/j.neuroimage.2012.04.018. Epub 2012 Apr 13.
9
Activation in the neural network responsible for categorization and recognition reflects parameter changes.
Proc Natl Acad Sci U S A. 2012 Jan 3;109(1):333-8. doi: 10.1073/pnas.1111304109. Epub 2011 Dec 19.
10
Multi-voxel patterns of visual category representation during episodic encoding are predictive of subsequent memory.
Neuropsychologia. 2012 Mar;50(4):458-69. doi: 10.1016/j.neuropsychologia.2011.09.002. Epub 2011 Sep 8.

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