Sommer Verena R, Sander Myriam C
Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany.
Neuropsychol Dev Cogn B Aging Neuropsychol Cogn. 2022 May;29(3):443-462. doi: 10.1080/13825585.2021.2019184. Epub 2021 Dec 23.
Long-standing theories of cognitive aging suggest that memory decline is associated with age-related differences in the way information is neurally represented. Multivariate pattern similarity analyses enabled researchers to take a representational perspective on brain and cognition, and allowed them to study the properties of neural representations that support successful episodic memory. Two representational properties have been identified as crucial for memory performance, namely the and the of neural representations. Here, we review studies that used multivariate analysis tools for different neuroimaging techniques to clarify how these representational properties relate to memory performance across adulthood. While most evidence on age differences in neural representations involved stimulus category information , recent studies demonstrated that particularly item-level stability and specificity of activity patterns are linked to memory success and decline during aging. Overall, multivariate methods offer a versatile tool for our understanding of age differences in the neural representations underlying memory.
长期以来的认知衰老理论表明，记忆衰退与信息在神经表征方式上的年龄相关差异有关。多变量模式相似性分析使研究人员能够从表征的角度研究大脑与认知，并让他们研究支持成功情景记忆的神经表征特性。已确定两种表征特性对记忆表现至关重要，即神经表征的 和 。在此，我们回顾了使用多变量分析工具对不同神经成像技术进行研究的相关文献，以阐明这些表征特性在整个成年期如何与记忆表现相关联。虽然关于神经表征年龄差异的大多数证据都涉及刺激类别信息 ，但最近的研究表明，特别是活动模式的项目级稳定性和特异性与衰老过程中的记忆成功和衰退有关。总体而言，多变量方法为我们理解记忆背后神经表征的年龄差异提供了一种通用工具。
